Checking Access...

Verifying your enrolment.

Claude, Claude Code & Claude Co-work

10-Module Training Course 42 Sections 120 Questions Estimated: 10 modules (1–2 hours per module)
Designed for property professionals
🎧 This course includes professional audio narration, available in-browser or via the Hillway Training iOS app.
1

Module 1: Understanding AI Assistants

What AI is, how it works, and why Claude is a powerful tool for property professionals ~90 minutes

1

What is AI? A Practical Introduction

Learning Objectives

  • Understand what artificial intelligence means in a practical business context
  • Identify AI tools you already use in daily life
  • Explain why AI matters specifically for property professionals
  • Distinguish between general AI hype and practical AI utility

Forget the science fiction

When people hear "artificial intelligence", they often think of robots or sentient computers from films. The reality is far more practical. AI, as used in modern property practice, is software that can understand and generate human language, analyse documents, and help with tasks that would normally require significant human time and effort.

Think of it this way: a calculator helps you do maths faster. AI helps you do thinking tasks faster — reading, writing, summarising, analysing, and communicating.

The term "Artificial Intelligence" was coined in 1956 at a conference at Dartmouth College. Since then, AI has gone through several waves of excitement and disappointment (known as "AI winters"). What makes the current wave different is the breakthrough of Large Language Models (LLMs) — a type of AI that is genuinely useful for everyday professional work.

Types of AI you already use

You interact with AI every day without realising it:

  • Predictive text on your phone — suggests the next word as you type
  • Spam filters in your email — learn what is junk and what is important
  • Sat nav routing — analyses traffic patterns to find the best route
  • Netflix/Spotify recommendations — learns what you like and suggests more
  • Voice assistants (Siri, Alexa) — understand spoken language
  • Photo tagging on social media — recognises faces in images
  • Fraud detection on your bank account — spots unusual transactions
  • Grammar checkers (Grammarly, Word) — suggest corrections to your writing

The type of AI covered in this course is a more advanced version of these ideas, specifically a Large Language Model (LLM). It specialises in understanding and generating text.

Why this matters for property

As a surveyor, a huge part of your job involves text: reading leases, writing reports, drafting emails, analysing comparable evidence, preparing fee proposals, and communicating with clients. AI is exceptionally good at all of these tasks. It does not replace your professional judgement — it amplifies it.

Consider these numbers: a typical rent review file might include a 200-page lease, 50 pages of comparable evidence, correspondence, and financial schedules. Reading and extracting key information from these documents manually might take 3-4 hours. With AI assistance, the initial data extraction and summarisation can be done in minutes, freeing you to focus on the analysis and professional judgement that only a qualified surveyor can provide.

The RICS Future of the Profession report identified technology adoption as one of the key drivers of change in surveying. Firms that embrace AI tools effectively will deliver faster, more thorough work — and that is exactly where forward-thinking firms are positioning themselves.

Key Concept: Narrow AI vs General AI

Narrow AI (also called "weak AI") is designed to perform specific tasks well. Every AI system you interact with today is narrow AI — including Claude. It excels at language tasks but cannot drive a car or perform surgery.

General AI (also called "strong AI" or AGI) would be a system that can perform any intellectual task a human can. This does not exist yet and is a topic of active research and debate. When you hear headlines about AI "taking over", they are usually conflating narrow AI with general AI.

In property practice, narrow AI is used for what it is good at: language processing, document analysis, and information structuring. It is paired with what humans are good at: professional judgement, relationship management, and physical observation.

Try This Now

Open your phone and start typing a text message. Notice how it predicts the next word? That is a tiny language model at work. Now think about how much more useful a model that has read millions of documents, legal texts, and property reports could be for your work. That is the leap from predictive text to Claude.

2

How Large Language Models Work

The autocomplete analogy

Start with something you already know. When you type a message on your phone and it suggests the next word, that is a simple language model. It has learned from billions of text messages that after "See you" the next word is often "later" or "tomorrow".

A Large Language Model like Claude works on exactly the same principle, but at an enormously larger scale. Instead of predicting one word from a short message, it has been trained on a vast amount of text (books, articles, websites, code) and can generate entire paragraphs, analyses, and documents — all by predicting what comes next, one piece at a time.

Key Concept: Tokens

What are tokens?

AI models do not read words the way you do. They break text into smaller pieces called tokens. A token is roughly three-quarters of a word. So "property management" is about 3 tokens, and a full page of text is roughly 400 tokens.

Why does this matter? Because there is a limit to how many tokens the model can process at once — this is called the context window. Think of it as the model's "working memory". Claude can handle up to 1 million tokens at extended tiers, with 200,000 tokens at standard pricing — roughly 500 pages of text at minimum. That is enough to read an entire lease and all supporting documents in one go.

Here are some examples of token counts for common property documents:

  • A short email: ~100 tokens (less than a paragraph)
  • A one-page letter: ~400 tokens
  • A 10-page report: ~4,000 tokens
  • A 50-page lease: ~20,000 tokens
  • A 200-page full repairing lease with schedules: ~80,000 tokens

Even with a large lease, Claude still has over half its context window available for your instructions and its response.

Key Concept: Training

How was Claude trained?

Training an LLM is a massive, expensive process. It involves feeding the model enormous amounts of text and teaching it to predict the next token. Through this process, the model learns grammar, facts, reasoning patterns, and even writing styles.

Think of it like an apprentice who has read the entire library. They have not experienced anything directly, but they have read about almost everything. They can produce impressive work based on patterns they have absorbed, but they lack the practical wisdom that comes from real-world experience. That is why your professional experience and judgement remain essential.

The training process has several stages:

  1. Pre-training — The model reads vast amounts of text and learns patterns in language
  2. Fine-tuning — The model is refined on curated examples to improve quality and helpfulness
  3. RLHF / Constitutional AI — The model is further aligned with human values and safety principles

Key Concept: Inference

What happens when you ask Claude a question?

When you send a message to Claude, a process called inference takes place. The model takes your input (the prompt), processes it against everything it learned during training, and generates a response token by token. This is why responses appear to stream in word by word — the model is literally generating each piece sequentially.

This is not a search engine looking up answers in a database. Claude is generating its response fresh each time based on the patterns it learned during training. This is both its strength (it can be creative and flexible) and its weakness (it can sometimes generate plausible-sounding but incorrect information).

Important limitation: the knowledge cutoff

Claude's training data has a cutoff date. It does not know about events, legislation changes, or market data after that date unless you provide the information in your prompt. For property work, this means you should always provide current market evidence, recent case law, or updated regulations rather than asking Claude to recall them from memory.

For example, if there was a significant court ruling on service charge disputes last month, Claude will not know about it. But if you paste the ruling into the conversation, Claude can analyse it brilliantly. Always supply current data for current analysis.

Key Concept: Hallucination

A hallucination is when an AI model generates information that sounds plausible and confident but is actually incorrect or entirely fabricated. This happens because the model is predicting what text "should" come next based on patterns, not consulting a verified database of facts.

Common hallucination examples in property work include: fabricated case law citations (e.g., "Smith v Jones [2024] EWHC 1234" that does not exist), invented statistics ("the Sheffield industrial market vacancy rate is 4.2%" when this figure was made up), and incorrect legislative references.

This is why verification is not optional — it is a professional requirement.

Try This Now

Go to claude.ai and ask: "What is the current market rent for a 5,000 sq ft industrial unit in Sheffield S9?" Notice how Claude will either give a general range based on training data or explain that it does not have current market data. This demonstrates the knowledge cutoff in action. Now try pasting in some actual comparable evidence and asking the same question — the response will be much more useful.

3

Claude by Anthropic

Who makes Claude?

Anthropic is an AI safety company founded in 2021 by former members of OpenAI, including Dario and Daniela Amodei. Their core mission is to build AI systems that are safe, beneficial, and understandable. This safety-first approach is what sets Claude apart from competitors.

Anthropic has raised substantial venture capital funding from investors including Amazon and Google. The company employs some of the world's leading AI researchers and is based in San Francisco. Unlike some AI companies that prioritise speed-to-market, Anthropic takes a measured approach to releasing capabilities, which is why Claude tends to be more careful and less likely to produce harmful content.

Constitutional AI: why Claude behaves differently

Claude is trained using a method called Constitutional AI. Rather than relying solely on human reviewers to judge every response, Claude is given a set of principles (a "constitution") that guide its behaviour. These principles include:

  • Be helpful, harmless, and honest
  • Do not assist with illegal or harmful activities
  • Acknowledge uncertainty rather than guess
  • Respect privacy and confidentiality
  • Be transparent about being an AI

In practice, this means Claude is less likely to make up information, more willing to say "I do not know", and more careful about sensitive topics. For professional work, this reliability is essential. When Claude is unsure, it will tell you — rather than confidently making something up.

Claude vs ChatGPT vs Gemini — honest comparison

Feature Claude (Anthropic) ChatGPT (OpenAI) Gemini (Google)
Strengths Long documents, careful reasoning, safety, coding, professional writing General knowledge, plugins ecosystem, image generation (DALL-E) Google integration, multimodal (images, video), real-time search
Weaknesses No built-in image generation, no real-time internet access without tools Can be overly confident, shorter context window on some tiers Can be verbose, less precise on professional and technical writing
Context window 200K–1M tokens Up to 400K tokens (GPT-5.2) 1M+ tokens (~2,500 pages)
Best for Professional documents, analysis, coding, careful reasoning General tasks, creative content, quick answers Research with real-time search, Google Workspace users
Why it suits property work Best at professional writing, lease analysis, careful reasoning — critical for RICS-standard work

Common Pitfall

Assuming all AI tools are the same. A common mistake is thinking "I tried ChatGPT and it was not very good, so AI is not useful for property work." Different models have different strengths. Claude's ability to handle long documents and produce careful, nuanced analysis makes it particularly well-suited to surveying work. Always evaluate the right tool for the task.

4

Claude Model Tiers & How to Access Claude

Three tiers, three use cases

Anthropic offers Claude in three tiers. Think of them like car models — a city car, a family saloon, and a performance car. Each has its place.

Haiku
Fast & affordable
  • Fastest response times
  • Lowest cost per token
  • Good for simple tasks
  • Email classification, quick summaries
  • Like a city car — quick for short trips
Opus
Most capable
  • Highest quality reasoning
  • Best at complex analysis
  • Most expensive per token
  • Strategic decisions, complex code
  • Like a performance car — for when it matters most

How to access Claude

There are four main ways to interact with Claude:

  • claude.ai — The web interface. Open a browser, go to claude.ai, and start chatting. This is the simplest way and good for one-off tasks.
  • Claude mobile app — Available on iOS and Android. Useful when you are on site or travelling.
  • Claude API — For developers building applications that use Claude. Not something you will use directly.
  • Claude Code — A command-line tool that lets Claude read and write files, run commands, and connect to other services. This is what we will focus on from Module 2 onwards.

Your first conversation with Claude

Go to claude.ai and try these starter prompts:

Try this
"I am a graduate surveyor at a commercial property consultancy. Explain what a rent review is as if you were training me on my first day."
Try this
"Summarise the key differences between a full repairing and insuring lease and an internal repairing lease. Present this as a comparison table."
Try this
"Draft a professional email to a client confirming the date and time of an inspection at their property next Tuesday at 10am. Keep it concise and friendly."

Notice how Claude adapts to your request. It can be formal or informal, detailed or concise, depending on what you ask for.

Understanding context windows and conversation memory

Within a single conversation, Claude remembers everything you have said. You can reference earlier messages, build on previous answers, and refine outputs iteratively. However:

  • Each conversation is separate — Claude does not remember your last chat when you start a new one (on claude.ai).
  • The context window is finite — Very long conversations may lose early context. For critical work, keep conversations focused on one topic.
  • You can paste documents — Copy and paste lease clauses, reports, or data directly into the chat. Claude processes them immediately.

Try This Now

  1. Go to claude.ai and start a conversation
  2. Ask Claude to explain what "yield" means in property investment
  3. Then in the same conversation, ask "Now explain that to someone who has never invested in property"
  4. Notice how Claude adapts its language because it remembers your earlier message
  5. Start a NEW conversation and ask "Can you give me a simpler version?" — Claude will not know what you are referring to, because each conversation starts fresh
5

Safety, Ethics & Responsible AI Use

The golden rule of AI in professional practice

AI is a tool, not a colleague. It produces drafts, not final products. Every piece of AI-generated content must be reviewed by a qualified human before it is sent to anyone. This is not optional — it is a professional and regulatory requirement.

What AI does well

  • Drafting text that you then review and refine
  • Analysing large documents quickly (finding key clauses in a 200-page lease)
  • Summarising complex information into plain English
  • Generating first drafts of emails, reports, and proposals
  • Structuring your thoughts and organising research
  • Converting rough notes into professional formats
  • Comparing documents and identifying differences
  • Processing spreadsheet data and performing calculations

What AI does NOT do well

  • Professional judgement — it cannot value a property or give a professional opinion
  • Guaranteeing accuracy of facts, figures, or legal citations
  • Understanding nuance that requires local market knowledge
  • Replacing the need for site inspections and physical observation
  • Confidential reasoning that accounts for relationships and politics
  • Making decisions that require a RICS qualification to sign off
  • Knowing about events after its training data cutoff
  • Understanding client relationships and the history behind a negotiation

AI will not replace surveyors. But surveyors who use AI will replace those who do not.

— A useful way to think about it

Ethical use in practice

  • Transparency — If a client asks whether AI was used in preparing work, always be honest
  • Verification — Never send AI output directly to a client without human review
  • Confidentiality — We will cover data security in detail on Module 10, but for now: never paste sensitive client data into public AI tools
  • Fairness — Be aware that AI can reflect biases from its training data. Question assumptions in its output
  • Accountability — You are responsible for the work, not the AI. Your name goes on the report, not Claude's
  • Proportionality — Use the right level of AI assistance for the task. Not everything needs AI, and not everything should bypass it

The human-AI partnership model

The most effective way to think about AI in your practice is as a partnership:

AI does the... Human does the...
First draftReview and refinement
Data extractionData verification
Research compilationProfessional analysis
Document formattingQuality assurance
Calculation processingMethodology validation
Pattern identificationContextual interpretation

Module 1 Summary

  • AI is software that processes language — not science fiction, not magic
  • LLMs like Claude work by predicting the next token based on learned patterns
  • Claude is made by Anthropic and uses Constitutional AI for safety
  • Three model tiers: Haiku (fast), Sonnet (balanced, the default), Opus (most capable)
  • Context windows allow Claude to process ~500 pages at once
  • Hallucinations are a real risk — always verify AI output
  • AI is a tool, not a colleague — you remain professionally responsible

Video: Generative AI in a Nutshell

Henrik Kniberg · 18 minutes

Watch this excellent visual overview of generative AI before tackling the quiz. It reinforces the key concepts from this module's reading.

Module 1 Knowledge Check

Test your understanding of AI fundamentals. You get up to 3 attempts per question — hints will guide you if you get it wrong.

Question 1 of 12
Who created Claude?
Claude is made by Anthropic, a company founded in 2021 by former members of OpenAI, including Dario and Daniela Amodei. Their focus is on building safe, reliable AI systems.
Question 2 of 12
What is a "token" in the context of AI language models?
Tokens are the small pieces of text that AI models break language into for processing. One token is roughly three-quarters of a word. Claude's context window of ~200,000 tokens means it can process about 500 pages of text at once.
Question 3 of 12
What is a "hallucination" in AI?
A hallucination is when an AI model generates information that sounds plausible and confident but is actually incorrect or entirely made up. This is why human review of all AI output is essential, especially in professional work.
Question 4 of 12
Approximately how many pages of text can Claude process at once in its context window?
Claude's context window of approximately 200,000 tokens translates to roughly 500 pages of text. This is what makes it excellent for analysing long leases, reports, and other property documents.
Question 5 of 12
Which Claude model tier is recommended as the default for most everyday tasks?
Sonnet is the recommended default model — the best balance of speed, quality, and cost. Haiku is used for quick, simple tasks, and Opus is reserved for complex analysis and strategic decisions.
Question 6 of 12
What training approach does Anthropic use that sets Claude apart from competitors?
Constitutional AI is Anthropic's approach where Claude is given a set of principles (a "constitution") that guide its behaviour — including being helpful, harmless, and honest. This makes Claude more reliable and less likely to produce harmful content.
Question 7 of 12
Which of the following should you NOT rely on AI to do?
A formal property valuation requires professional judgement, local market knowledge, site inspection, and a qualified surveyor's signature. AI can help with research and drafting, but the professional opinion must always come from a qualified human.
Question 8 of 12
What is the name of the process when Claude generates a response to your prompt?
Inference is the process of generating a response. The model takes your input, processes it against its trained knowledge, and generates output token by token. This is different from searching a database — the response is generated fresh each time.
Question 9 of 12
What type of AI is Claude classified as?
Claude is narrow AI — it excels at language tasks (reading, writing, analysing, summarising) but cannot perform physical tasks, drive a car, or do anything outside its language capabilities. General AI (AGI) does not exist yet.
Question 10 of 12
What is the golden rule of AI use in professional practice?
The golden rule: AI is a tool, not a colleague. It produces drafts, not final products. Every piece of AI-generated content must be reviewed by a qualified human before it is sent to clients or third parties.
Question 11 of 12
Why might Claude give outdated information about current market rents?
Claude has a knowledge cutoff date. Its training data only extends to a certain point in time, so it may not know about recent market transactions, new legislation, or current events. Always provide current data for accurate analysis.
Question 12 of 12
What is the first stage of training a Large Language Model?
The first stage is pre-training, where the model reads enormous amounts of text and learns patterns in language. This is followed by fine-tuning (improving quality on curated examples) and then alignment with safety principles (Constitutional AI / RLHF).

Module 1 Complete

0/12

2

Module 2: Claude Code — Getting Started

The AI coding assistant that runs in your terminal ~90 minutes

6

What is Claude Code?

Learning Objectives

  • Understand the difference between claude.ai and Claude Code
  • Navigate the terminal with basic commands
  • Understand the tool and permission model in Claude Code
  • Know what MCP servers are and which ones are commonly used in property practice

More than a chatbot

On Module 1 you used claude.ai — a web chat interface. Claude Code takes things much further. It is a command-line tool that runs in your terminal (the black screen with text that developers use). Unlike the web chat, Claude Code can:

  • Read files on your computer — leases, spreadsheets, reports, code
  • Write and edit files — create documents, modify spreadsheets, generate reports
  • Run commands — execute programs, process data, automate repetitive tasks
  • Connect to external services — Google Workspace, Xero, GitHub, Slack, and more

Think of it this way: claude.ai is like having a knowledgeable colleague on the phone. Claude Code is like having that colleague sitting at your desk, able to open files, send emails, and operate your computer directly — with your permission, of course.

Claude Code vs claude.ai — key differences

Feature claude.ai (Web Chat) Claude Code (Terminal)
InterfaceBrowser-based chat windowTerminal / command line
File accessUpload files manually (drag and drop)Reads files directly from your computer
File creationCannot create or save filesCreates, edits, and saves files directly
External toolsLimited integrationsConnects to 15+ services via MCP
Multi-step tasksOne response at a timeCan chain multiple steps automatically
Best forQuick questions, one-off tasksComplex projects, file processing, automation
Learning curveVery easy — just type and chatModerate — need basic terminal comfort

Why Claude Code suits property work

Claude Code is the primary tool for property professionals to interact with AI because it can do things the web chat cannot:

  • Read a lease PDF, extract key terms, and create a summary document — all in one command
  • Query your Xero accounting system for outstanding invoices and create a report
  • Draft a fee proposal in Google Docs using your template and client data
  • Search your entire document library for relevant comparable evidence
  • Process a spreadsheet of property data and generate formatted tables
  • Send an email to a client with a covering letter and attachment
  • Schedule a calendar event for a site inspection

The key advantage is automation of multi-step workflows. Instead of copying data between applications, Claude Code handles the entire workflow end-to-end.

Key Concept: Agentic AI

Claude Code is what is known as an agentic AI system. This means it can take actions autonomously (with your permission) rather than just generating text. It can plan a sequence of steps, execute them, handle errors, and adjust its approach if something does not work. This is fundamentally different from a chatbot that just responds to messages.

7

The Terminal: A Gentle Introduction

What is a terminal?

A terminal (also called the "command line" or "shell") is a text-based interface for your computer. Instead of clicking icons and menus, you type commands. It looks like this:

Terminal $ _

That $ symbol is called the prompt — it is waiting for you to type a command. Do not be intimidated by it. You only need a handful of commands to use Claude Code effectively.

On a Mac, the terminal application is called "Terminal" and you can find it in Applications > Utilities, or by pressing Cmd+Space and typing "Terminal". On Windows, it is called "Command Prompt" or "PowerShell".

Essential terminal commands (just 8 to start)

Command What it does Example
pwd"Print working directory" — shows where you arepwd → /Users/yourname/Projects
ls"List" — shows files in the current folderls → lease.pdf report.docx
cd"Change directory" — moves to a different foldercd Documents
cd ..Go up one folder levelcd ..
cd ~Go to your home foldercd ~
clearClears the screen (cosmetic only)clear
mkdir"Make directory" — creates a new foldermkdir new-project
claudeStarts Claude Code!claude

Your first Claude Code session

Here is what a typical first session looks like:

Terminal Session # Open your terminal (Cmd+Space, type "Terminal", press Enter) # Navigate to your project folder $ cd ~/Projects/my-training # Start Claude Code $ claude Claude Code v1.0 Type your message or use /help for commands. > What files are in this directory? I can see the following files: - courses/ - js/ - admin.html - induction.html ...

Once Claude Code is running, you simply type in natural English. No special syntax required. Ask it to read a file, summarise a document, or create a new file — just as you would ask a colleague.

Installation

If Claude Code is not already installed, the recommended command is:

# Recommended (macOS / Linux) $ curl -fsSL https://claude.ai/install.sh | bash # Alternative (via npm) $ npm install -g @anthropic-ai/claude-code

The native installer is recommended for most users. The npm command is an alternative, particularly useful for teams that manage packages via npm.

Try This Now

  1. Open Terminal on your Mac (Cmd+Space, type "Terminal")
  2. Type pwd and press Enter — note your current location
  3. Type ls — see what files are in this folder
  4. Type cd ~/Projects — navigate to the Projects folder
  5. Type claude to start Claude Code
  6. Type "Hello, I am [your name] and I am learning to use Claude Code" — see how Claude responds
  7. Type /help to see available commands
8

Tools, Permissions & How Claude Code Works

The permission model

Claude Code needs your permission before it does certain things. This is a safety feature. When Claude wants to read a file, write a file, or run a command, it will ask you first. You will see something like:

Claude wants to read the file: leases/tenant-abc-lease.pdf Allow? (y/n)

You can approve or deny each action. Over time, you can set up automatic approvals for common, safe actions. The permission system exists to ensure you always know what Claude is doing with your files and data.

There are three permission levels:

  • Ask every time — Claude prompts you before every action (most secure, default for new users)
  • Allow for session — Approve a type of action once and Claude can repeat it during this session
  • Always allow — Permanently approve certain safe actions (like reading files in your project folder)

Understanding tool use

Claude Code interacts with your computer using tools. Each tool does something specific:

Tool What it does Example use
ReadReads a file from your computerReading a lease, a spreadsheet, or a report
WriteCreates a new fileCreating a summary document or a new report
EditModifies an existing fileUpdating figures in a report, fixing a typo
BashRuns a terminal commandProcessing data, running a script, checking file sizes
GrepSearches for text across filesFinding every mention of "rent review" in a folder of leases
GlobFinds files by name patternFinding all PDF files in a directory
WebSearchSearches the internetFinding current market data or property listings
WebFetchReads a webpageExtracting data from a property listing

You do not need to know these tool names. Just ask Claude what you want in plain English, and it will choose the right tools automatically.

What Claude Code can and cannot access

Can access

  • Files in your current project folder
  • Connected MCP services (Google, Xero, etc.)
  • The internet (for web searches, API calls)
  • Terminal commands on your machine

Cannot access

  • Files you have not given permission for
  • Other people's computers
  • Encrypted or password-protected files (without keys)
  • Actions blocked by your organisation's IT policy

Common Pitfall

Denying all permissions out of caution. New users sometimes deny every permission request, which makes Claude Code essentially useless. The whole point of Claude Code is that it can interact with your files and services. If you are uncomfortable, start by allowing read-only access to files and work up from there.

9

MCP: How Claude Connects to External Services

What is MCP?

MCP stands for Model Context Protocol. It is the system that allows Claude Code to connect to external services like Google Workspace, Xero, Slack, and GitHub. Think of MCP as a set of power adapters — each one lets Claude plug into a different service.

Without MCP, Claude could only read files on your computer and chat with you. With MCP, Claude becomes a hub that can coordinate across all the tools your business uses.

MCP is an open standard developed by Anthropic. It works like a universal translator between Claude and external services. Each service has an MCP "server" that understands the service's API and translates Claude's requests into the right format.

MCP servers in practice

Here are the services Claude Code can connect to:

GitHub — Code repositories, issues
Supabase — Database, authentication
Google Workspace — Docs, Sheets, Gmail, Calendar
Slack — Team messaging
Xero — Accounting, invoices
Playwright — Browser automation
Memory — Persistent knowledge
Sentry — Error monitoring
Gemini/Imagen — Image generation
Filesystem — File management

MCP in action: a real example

Imagine you need to check outstanding invoices. Without MCP, you would open Xero in your browser, navigate to invoices, filter, and export. With Claude Code and MCP:

You type
"Show me all outstanding invoices in Xero over 30 days old."
Claude uses the Xero MCP server to query your invoices, filters for those over 30 days outstanding, and presents a formatted table with client names, amounts, and dates — all without you leaving the terminal.

You do not need to configure MCP

Once MCP servers are configured, you simply use Claude Code in natural English, and it will automatically use the right MCP server when needed. For example:

  • "Send an email to john@acme.com" → Uses Google Workspace MCP
  • "Create a new invoice for ABC Ltd" → Uses Xero MCP
  • "Search our Drive for the Smith property report" → Uses Google Workspace MCP
  • "Post an update in the #general Slack channel" → Uses Slack MCP
  • "Remember that Client X prefers bullet-point reports" → Uses Memory MCP

Module 2 Summary

  • Claude Code is a terminal-based AI tool that can read/write files and connect to services
  • The terminal is a text-based interface — you only need ~8 basic commands
  • Claude Code uses a permission model to keep you in control
  • Tools (Read, Write, Edit, Bash, Grep, Glob) let Claude interact with your computer
  • MCP (Model Context Protocol) connects Claude to external services like Xero, Google, and Slack
  • Once configured, MCP servers work seamlessly
  • You interact with Claude Code in natural English — it chooses the right tools automatically

Module 2 Knowledge Check

Test your understanding of Claude Code basics. Remember: up to 3 attempts per question with hints.

Question 1 of 12
Where does Claude Code run?
Claude Code runs in the terminal (command line). This gives it the ability to read and write files, run commands, and connect to external services — things the web chat interface cannot do.
Question 2 of 12
What does MCP stand for?
Model Context Protocol (MCP) is the system that allows Claude Code to connect to external services. Each MCP server acts like a bridge between Claude and a specific service such as Xero, Google Workspace, or Slack.
Question 3 of 12
What does the terminal command pwd do?
pwd stands for "Print Working Directory". It shows the full path of the folder you are currently in.
Question 4 of 12
What happens when Claude Code wants to read or write a file on your computer?
Claude Code uses a permission model. Before reading a file, writing a file, or running a command, it asks for your approval.
Question 5 of 12
Which Claude Code tool would search for every mention of "rent review" across a folder of documents?
Grep is the tool that searches for text content across multiple files. Glob finds files by name pattern rather than content.
Question 6 of 12
Which MCP server would Claude Code use to check outstanding invoices?
Xero is the MCP server for accounting and financial data.
Question 7 of 12
What is the main advantage of Claude Code over the claude.ai web interface?
The main advantage of Claude Code is that it can directly read and write files, run commands, and connect to external services via MCP.
Question 8 of 12
What does the terminal command ls do?
ls stands for "list". It displays all the files and folders in your current directory.
Question 9 of 12
What type of AI system is Claude Code described as?
Claude Code is an agentic AI system — it can plan sequences of steps, execute them, handle errors, and adjust its approach. This is different from a simple chatbot.
Question 10 of 12
Which Claude Code tool would you use to find all PDF files in a folder?
Glob finds files by name pattern (e.g., *.pdf). Grep searches for text content within files, which is a different purpose.
Question 11 of 12
You want Claude Code to send an email. Which MCP server handles this?
Google Workspace MCP handles email (Gmail), documents (Docs), spreadsheets (Sheets), calendar, and Drive.
Question 12 of 12
What command do you type in the terminal to start Claude Code?
Simply type claude at the terminal prompt to start Claude Code.

Module 2 Complete

0/12

Module 3

Practical Property Tasks with Claude Code

Put your new skills to work on real property tasks — emails, research, reports, and prompt patterns.

Estimated time: 90–120 minutes

Module 3 Learning Objectives

  • Draft professional property emails using Claude Code and Google Workspace MCP
  • Conduct market research and comparable analysis with real data sources
  • Generate structured reports and workspace documents
  • Apply effective prompt patterns for repeatable, high-quality results
10

Emails & Documents

One of the most immediate ways Claude Code saves time is drafting professional emails and documents. Rather than starting from a blank page, you describe what you need, Claude produces a polished draft, and you review and send. Over a week, this can save hours of writing time.

The Draft-Review-Send Workflow

Claude Code never sends anything without your approval. The workflow is always: (1) You describe what you need(2) Claude drafts it(3) You review and edit(4) You approve sending. This keeps you in full control of every communication you send.

Drafting Property Emails

When asking Claude Code to draft an email, always provide:

  • Recipient and context — who are they, what is the relationship?
  • Purpose — what do you need to communicate?
  • Tone — formal/informal, urgent/routine?
  • Key facts — dates, figures, property addresses, reference numbers
  • Any attachments to mention — documents you will attach manually
Example Prompt
Draft an email to Sarah Chen at Knight Frank regarding the rent review at Unit 4, Riverside Business Park, Sheffield S2 4SL. The current passing rent is £45,000 pa and the review date is 25 March 2026. We are acting for the landlord. Tone should be professional but collaborative. Mention that we have prepared comparable evidence and would welcome a meeting to discuss.

Claude will produce a complete, properly formatted email. Before sending, always check:

Email Review Checklist

  • Are all names, addresses, and figures correct?
  • Is the tone appropriate for this recipient?
  • Have any facts been fabricated (hallucinated)?
  • Does it accurately represent your firm's position?
  • Is it compliant with RICS professional standards?

Sending Emails via Google Workspace MCP

Claude Code can send emails directly through Gmail using the Google Workspace MCP server. This means you can draft and send without leaving the terminal.

Example Prompt
Send an email to sarah.chen@knightfrank.co.uk with the subject "Rent Review - Unit 4, Riverside Business Park, S2 4SL" and the body we just drafted.

Claude will ask for your confirmation before actually sending. You will see a permission request like:

Claude wants to use: Google Workspace > Send Gmail Message
To: sarah.chen@knightfrank.co.uk
Subject: Rent Review - Unit 4, Riverside Business Park, S2 4SL

Allow? (y/n)

Only type y when you have verified everything is correct.

Creating Google Docs and Sheets

Beyond email, Claude Code can create documents directly in Google Drive:

Task MCP Tool Example Prompt
Create a document Google Workspace > Create Doc "Create a Google Doc called 'Q1 2026 Property Report' with the analysis we discussed"
Create a spreadsheet Google Workspace > Create Spreadsheet "Create a Google Sheet with columns for property address, tenant, rent, review date, and notes"
Edit an existing doc Google Workspace > Modify Doc Text "Open the Riverside report and add a section on market comparables"
Read spreadsheet data Google Workspace > Read Sheet Values "Read all data from the tenant schedule spreadsheet"

Try This Now

Ask Claude Code to draft a professional email to a fictional tenant, confirming a lease renewal meeting. Include:

  • The property address: 15 High Street, Sheffield S1 2GE
  • Meeting date: Thursday 20 March 2026 at 2:00pm
  • Location: [Your office address]
  • Ask them to bring their current lease and any relevant correspondence

Review what Claude produces. Would you send it as-is, or would you make changes?

Managing Slack Messages

Claude Code can also send messages to Slack channels, which is useful for internal team updates:

Example Prompt
Post a message to the #property-updates Slack channel: "Rent review at Unit 4 Riverside Business Park now scheduled for meeting on 20 March. Comparable evidence pack ready for review in the shared drive."

Common Pitfall: Sending Without Review

Never rush through permission prompts. Claude Code will always ask before sending any email or message, but it is easy to type "y" out of habit. Take the time to read the full content before approving. One incorrect figure or wrong recipient can cause real professional embarrassment.

Section Summary

Claude Code can draft emails, create Google Docs and Sheets, and post Slack messages — all from the terminal. The critical rule is: always review before approving. AI drafts are starting points, not final products.

11

Research & Data

Property work relies on accurate, current data. Claude Code can help you gather, structure, and analyse information from multiple sources — but you must understand where the data comes from and how to verify it.

Web Research with Claude Code

Claude Code has two tools for accessing the web:

Tool What It Does Best For
WebSearch Searches the internet and returns results Finding current market data, news, company information
WebFetch Fetches and reads a specific web page Reading articles, extracting data from known URLs
Example: Market Research
Search for recent office rental transactions in Sheffield city centre from the last 6 months. I need comparable evidence for a rent review of Grade A office space. Look at EGi, CoStar news, and local property press.

Claude will search the web and compile findings. However, remember these limitations:

Web Research Limitations

  • Paywalled content — Claude cannot access EGi, CoStar, or other subscription databases directly
  • Accuracy — Web data may be outdated, incomplete, or incorrect. Always verify against primary sources
  • Confidential data — Claude cannot access your firm's internal databases or files unless you point it to them
  • Not RICS-compliant evidence — Web research is a starting point for comparable evidence, not a substitute for properly sourced and verified comparables

Working with Property Data Files

Much of the most valuable research involves analysing files already on your computer or in shared drives. Claude Code excels at this:

1
Point Claude to the data

"Read the tenant schedule at /Users/yourname/Documents/riverside-tenants.xlsx"

2
Ask for analysis

"Which tenants have lease expiries in the next 12 months? What is the total rent at risk?"

3
Request a structured output

"Create a table showing tenant name, unit, current rent, lease expiry, and break date, sorted by expiry date."

Comparable Evidence Analysis

A core property skill is gathering and analysing comparable evidence for rent reviews and valuations. Claude Code can help structure this work:

Example: Comparable Analysis
I have the following comparable transactions for Grade A office space in Sheffield city centre. Analyse them and suggest an ERV range: 1. 25 Church Street, S1 - 3,500 sq ft let at £22.50 psf, Jan 2026, 10-year term, 6-month rent-free 2. Victoria House, S1 - 5,000 sq ft let at £21.00 psf, Oct 2025, 5-year term, 3-month rent-free 3. Steel Works, S1 - 2,800 sq ft let at £24.00 psf, Nov 2025, 10-year term, 12-month rent-free Adjust to headline and effective rents. Our subject property is 4,200 sq ft.

Headline Rent vs Effective Rent

Headline rent is the stated rent in the lease. Effective rent accounts for incentives like rent-free periods, stepped rents, and capital contributions. When comparing evidence, you must adjust to a consistent basis. Claude can calculate this, but you must verify the methodology.

Xero Financial Data

Claude Code connects to Xero via MCP to access your firm's financial data. This is useful for checking invoices, tracking payments, and financial reporting:

Example: Financial Query
Check Xero for any outstanding invoices from our company. Show the invoice number, client name, amount, and due date for anything overdue.

Common Pitfall: Trusting AI Numbers Without Verification

When Claude Code calculates figures — whether rental values, yields, or financial summaries — always check the arithmetic manually or with a calculator. AI is excellent at structuring calculations but can make errors, especially with complex multi-step arithmetic. A wrong figure in a rent review report can damage your firm's professional reputation.

Try This Now

Give Claude Code three fictional comparable transactions and ask it to:

  • Calculate the headline rent per square foot for each
  • Adjust for rent-free periods to show effective rents
  • Suggest an ERV range for a 5,000 sq ft subject property

Check its arithmetic with a calculator. Did it get everything right?

Section Summary

Claude Code can search the web, analyse local files, work with comparable evidence, and query Xero financial data. The key discipline is always verifying data and arithmetic against primary sources. AI research is a starting point, not a final answer.

12

Reports & Workspace

Property consultants spend a significant amount of time producing reports — from brief client letters to full valuation reports. Claude Code can dramatically speed up this process by generating structured first drafts that you then refine with your professional expertise.

Common Report Types in Property Practice

Report Type Typical Length How Claude Helps
Client letter 1–2 pages Full draft from brief instructions
Head of Terms 2–3 pages Structured from key deal points
Market update 3–5 pages Research gathering + first draft
Rent review report 5–15 pages Comparable analysis + first draft sections
Valuation report 15–40 pages Section drafts, but requires significant human review
Fee proposal 3–5 pages Full draft from brief and fee schedule

Structuring Report Prompts

For longer reports, break the work into sections rather than asking for everything at once. This gives better results because:

  • Each section gets focused attention
  • You can provide section-specific data and instructions
  • You can review as you go, catching errors early
  • Claude's context stays focused and relevant
Example: Section-by-Section Report
I am writing a rent review report for Unit 4, Riverside Business Park, S2 4SL. Let's start with the Property Description section. Here are the key facts: - Industrial/warehouse unit with ancillary offices - GIA: 8,500 sq ft (warehouse 7,200 sq ft, offices 1,300 sq ft) - Built 2005, refurbished 2019 - Eaves height 6m - 4 loading doors - 15 car parking spaces - EPC rating: B Write the property description in a professional surveyor's tone, suitable for a rent review report.

Working with Google Drive

Claude Code can interact with your Google Drive to find, read, and create documents:

Example: Finding Documents
Search Google Drive for any documents related to "Riverside Business Park" from the last year. Show me the file names, types, and last modified dates.

This is particularly useful when you need to find a previous report, check what has been sent to a client, or locate comparable evidence files.

Template-Based Documents

Your firm may have standard templates for common documents. Claude Code can use these as starting points:

1
Read the template

"Read the fee proposal template from your templates folder"

2
Provide specific details

"Fill in this template for a rent review instruction from ABC Property Fund for their portfolio of 12 industrial units in Sheffield"

3
Create the document

"Save this as a Google Doc in the client folder"

Try This Now

Ask Claude Code to write a Heads of Terms document for a fictional lease:

  • Property: Ground Floor, 22 West Street, Sheffield S1 4EQ
  • Tenant: Fresh Grind Coffee Ltd
  • Landlord: Sheffield Properties Ltd
  • Term: 10 years
  • Rent: £35,000 per annum
  • Rent reviews: 5-yearly, upward only
  • Break clause: tenant only at year 5 with 6 months notice
  • Rent-free period: 3 months for fitting out

Review the output. Does it include all the standard HoT sections a chartered surveyor would expect?

Section Summary

Claude Code accelerates report writing by generating structured first drafts. For best results, work section-by-section on longer reports, provide specific data, and always apply your professional judgement to the output before it is delivered to clients.

13

Prompt Patterns

By now you have used Claude Code for several practical tasks. This section introduces prompt patterns — reusable structures that consistently produce high-quality results. Learning these patterns is like learning keyboard shortcuts: a small upfront investment that saves time every day.

The CONTEXT-TASK-FORMAT Pattern

The single most useful prompt pattern. Every good prompt contains three elements:

CTF: Context → Task → Format

  • Context — Background information Claude needs (who you are, what the situation is, relevant facts)
  • Task — What you want Claude to do (the specific instruction)
  • Format — How you want the output structured (bullet points, table, formal letter, etc.)
CTF Example
[Context] I am a chartered surveyor preparing for a rent review meeting tomorrow. The property is a 5,000 sq ft retail unit on Division Street, Sheffield. Current passing rent is £65,000 pa. The lease has upward-only rent reviews every 5 years. The tenant is a national coffee chain. [Task] Prepare a briefing note summarising the key negotiation points I should raise, potential arguments for increasing the rent, and risks to be aware of. [Format] Structure as: (1) Key Facts, (2) Arguments for Increase, (3) Tenant Counter-Arguments to Anticipate, (4) Recommended Strategy. Keep each section to 3–5 bullet points.

The ROLE Pattern

Telling Claude to adopt a specific role changes the style and depth of its response:

Role Pattern Example
You are an experienced RICS-qualified commercial property surveyor with 20 years of experience in the Sheffield market. A junior colleague has asked you to explain the difference between a Section 25 notice and a Section 26 request under the Landlord and Tenant Act 1954. Explain it clearly, with practical examples relevant to retail and office properties.

By assigning a role, Claude draws on more relevant knowledge and uses appropriate professional language.

The CONSTRAINTS Pattern

Adding constraints focuses Claude's output and prevents common problems:

Constraint Type Example Why It Helps
Length "Keep this under 200 words" Prevents rambling, keeps output focused
Tone "Write formally, suitable for a RICS report" Ensures professional language
Exclusion "Do not include legal advice or recommendations" Keeps within professional boundaries
Audience "Write for a client with no property background" Adjusts complexity and jargon level
Jurisdiction "Focus on English and Welsh law only" Prevents irrelevant Scottish/international references

The ITERATION Pattern

Complex outputs rarely come out perfect first time. The iteration pattern uses follow-up prompts to refine:

1
First draft

"Draft a market update for Sheffield industrial property"

2
Refine content

"Good start. Add more detail on supply pipeline and development activity in the Lower Don Valley"

3
Adjust tone

"Make it slightly less formal — this is for a quarterly client newsletter, not a formal report"

4
Final polish

"Shorten to 500 words and add a brief outlook section at the end"

Context Carries Forward

Within a single Claude Code session, Claude remembers everything you have discussed. You do not need to repeat context in follow-up messages. Simply say "Make it shorter" or "Add a section on..." and Claude understands what you mean. This is what makes the iteration pattern so powerful.

The EXAMPLE Pattern

Showing Claude an example of what you want is often more effective than describing it:

Example Pattern
Here is an example of how I write property descriptions in reports: "The subject property comprises a modern, detached industrial/warehouse unit of steel portal frame construction with insulated metal cladding under a pitched roof. The unit provides clear span accommodation with an eaves height of approximately 8 metres, served by two roller shutter loading doors to the front elevation." Now write a similar description for: a 1960s mid-terrace retail unit, ground floor only, brick construction, flat roof, single-glazed timber shopfront, approximately 1,200 sq ft sales area with 400 sq ft stockroom at the rear.

Try This Now

Practice the CTF pattern. Pick one of these tasks and write a prompt using Context, Task, Format:

  • A client briefing note for a dilapidations claim
  • A market commentary for a property management report
  • An internal memo summarising a site inspection

Compare the output you get with a basic prompt ("Write a briefing note about dilapidations") versus a well-structured CTF prompt. Notice the difference in quality and relevance.

Common Pitfall: Vague Prompts

The most common mistake is giving Claude too little context. "Write a report about the property" will give a generic, unhelpful response. "Write the property description section of a rent review report for a 5,000 sq ft retail unit at 22 Division Street, Sheffield, built 1985, refurbished 2020, with a Class E (formerly A1) use" will give you something genuinely useful. Specificity is the key to quality.

Module 3 Summary

In this module you learned to use Claude Code for practical property tasks: drafting emails, conducting research, generating reports, and applying reusable prompt patterns. The four key patterns — CTF (Context-Task-Format), ROLE, CONSTRAINTS, and ITERATION — will serve you well across every type of property work. Remember: Claude produces drafts, you produce the finished product.

Video: The Perfect Prompt Formula

Jeff Su · 8 minutes

Learn the 6-component prompt formula (Task, Context, Exemplars, Persona, Format, Tone) — then practise it in the interactive playground below.

Module 3 Knowledge Check

Test your understanding of practical property tasks with Claude Code. Remember: up to 3 attempts per question with hints.

Question 1 of 12
What is the correct workflow when using Claude Code to send an email?
The correct workflow is: describe → draft → review → approve. Claude always asks for your permission before sending anything. You maintain full control.
Question 2 of 12
Which MCP server does Claude Code use to send emails via Gmail?
Google Workspace MCP handles Gmail, Google Docs, Sheets, Calendar, and Drive — all Google services in one connection.
Question 3 of 12
Why might Claude Code be unable to find recent comparable evidence from EGi or CoStar?
EGi and CoStar are subscription databases behind paywalls. Claude Code cannot log into paid services. You need to extract data from these sources yourself and provide it to Claude for analysis.
Question 4 of 12
What is the difference between headline rent and effective rent?
Headline rent is the stated rent in the lease. Effective rent accounts for incentives (rent-free periods, stepped rents, capital contributions) and reflects what the tenant actually pays over the lease term. When comparing evidence, you must adjust to a consistent basis.
Question 5 of 12
What does the CTF prompt pattern stand for?
Context, Task, Format — the three essential elements of an effective prompt. Context provides background, Task is the instruction, and Format specifies how you want the output structured.
Question 6 of 12
When Claude Code calculates an effective rent from comparable evidence, what should you always do?
Always verify arithmetic manually. AI can make errors in multi-step calculations. A wrong figure in a rent review report can damage professional reputation and client outcomes.
Question 7 of 12
What is the recommended approach when using Claude Code to draft a lengthy report?
Section-by-section is the recommended approach. It gives each section focused attention, lets you provide section-specific data, and allows you to catch errors early rather than reviewing a massive document at the end.
Question 8 of 12
What is the purpose of the ROLE prompt pattern?
The ROLE pattern tells Claude to adopt a specific professional perspective (e.g., "You are an experienced RICS-qualified surveyor"). This changes the style, depth, and vocabulary of the response to match that professional context.
Question 9 of 12
Which Claude Code tool would you use to search for recent property market news?
WebSearch searches the internet for current information. Grep and Glob work on local files, while Read opens a specific file. Only WebSearch can access live internet content.
Question 10 of 12
In the ITERATION prompt pattern, why can you say "Make it shorter" without repeating context?
Context carries forward within a Claude Code session. Claude remembers everything you have discussed, so follow-up instructions like "Make it shorter" are understood in the context of the previous exchange. This is what makes iterative refinement so efficient.
Question 11 of 12
Which of these prompts would produce the best property description?
Specificity is the key to quality. The more detail you provide (size, location, age, use class, features), the more relevant and usable Claude's output will be. Vague prompts produce vague results.
Question 12 of 12
Before sending a Claude-drafted email to a client, which of these checks is NOT part of the email review checklist?
The email review checklist covers: accuracy of facts, appropriate tone, checking for hallucinations, representing your firm's position correctly, and RICS compliance. Matching competitors' formatting is not a review criterion — your firm has its own professional standards.

Module 3 Complete

0/12

Module 4

Co-work Mode & Agent Teams

Learn how to work alongside Claude in real time, use agent teams for complex tasks, and leverage custom workflows.

Estimated time: 90–120 minutes

Module 4 Learning Objectives

  • Understand co-work mode and how to collaborate with Claude Code in real time
  • Explain what agent teams are and when to use them
  • Know how to find and use custom agents and skills
  • Use Memory MCP and workflows to maintain context across sessions
14

Co-work Basics

Up until now, you have been working with Claude Code in a request-response pattern: you ask something, Claude does it, you ask the next thing. Co-work mode changes this dynamic. Instead of sequential requests, you and Claude work on the same task simultaneously — like having a colleague sitting next to you.

What is Co-work Mode?

Co-work mode is a way of using Claude Code where you maintain an ongoing conversation while Claude works on tasks in the background. You can continue giving instructions, ask questions, and refine direction while Claude is actively working. Think of it as pair-working with an AI colleague.

When to Use Co-work Mode

Use Co-work Mode Use Standard Mode
Complex, multi-step tasks (e.g., writing a full report) Quick, one-off questions
Tasks where you want to guide direction as you go Tasks with clear, complete instructions upfront
Exploratory work (researching a topic, exploring options) Repetitive tasks with fixed patterns
Learning/training (working through a problem together) Simple file operations or calculations

Effective Co-work Techniques

To get the most from co-work mode:

1
Start with the big picture

Explain the overall goal before diving into details. "I need to prepare for a rent review meeting tomorrow. The property is..."

2
Guide as Claude works

If Claude starts down a path you don't want, redirect immediately. "Actually, focus on the industrial comparables, not office."

3
Ask clarifying questions

"Why did you choose that comparable? Is there anything more recent?" Treat Claude as a colleague you are checking in with.

4
Use checkpoints

For long tasks, periodically confirm you are on the right track. "Good so far. Before we continue to the valuation section, let me review what we have."

Co-work Session Example
You: I need to put together a fee proposal for ABC Property Fund. They want us to manage 8 industrial units across Sheffield and Rotherham. Let's start by listing what services we'd typically include. Claude: [Lists property management services] You: Good. Add building surveying services too — they mentioned some units need condition surveys. Now let's work on pricing. Our standard PM fee is 8% of rent collected for portfolios under 10 units. Claude: [Calculates fees based on rent schedule] You: That total looks right but round the building surveying fees to the nearest £50. Also, add a 10% discount for the first year as we discussed. Claude: [Refines the proposal]

Try This Now

Start a co-work session with Claude Code. Tell it you need to prepare for a site inspection of a fictional commercial property. Work through:

  • What items should be on the inspection checklist?
  • What equipment do you need?
  • What photographs should you take?
  • What measurements are needed?

Guide Claude as it works, adding your own property knowledge to refine the output.

Section Summary

Co-work mode transforms Claude from a request-response tool into a collaborative working partner. Use it for complex, multi-step tasks where you want to guide direction as you go. Start with the big picture, guide as Claude works, and use checkpoints to stay on track.

15

Agent Teams

One of Claude Code's most powerful features is agent teams — the ability to spin up multiple AI agents that work together on a task. Instead of one Claude doing everything sequentially, several specialised agents can work in parallel, each focusing on their area of expertise.

What is an Agent Team?

An agent team is a group of specialised AI agents coordinated by a lead agent. Each team member has a specific role (researcher, analyst, writer, reviewer) and they communicate with each other to complete complex tasks faster and more thoroughly than a single agent could. Think of it like delegating work to a team of specialists.

How Agent Teams Work

1
You give a command

You invoke a team skill (like /team or /audit)

2
The lead agent plans the work

A team lead agent breaks the task into sub-tasks and assigns them to specialist agents

3
Agents work in parallel

Multiple agents work simultaneously — one researching, one analysing, one drafting

4
Results are combined

The lead agent compiles the results into a coherent output and presents it to you

When Agent Teams Add Value

Agent teams are most valuable for tasks that benefit from multiple perspectives or parallel processing:

  • Property research — One agent checks VOA data, another searches the web, another analyses local files
  • Project audits — Multiple agents examine different aspects (code quality, security, documentation, performance)
  • Fee proposals — Research agent gathers market rates, writer agent drafts the proposal, reviewer checks quality
  • Board discussions — Multiple AI “directors” debate a strategic question from different perspectives

Agent Team Considerations

  • Cost — Each agent in a team uses API tokens, so teams cost more than single-agent tasks
  • Complexity — For simple tasks, a single agent is faster and more efficient
  • Coordination — Agents may occasionally produce conflicting outputs that the lead must reconcile
  • Review still required — More agents does not mean less human review. You must still verify everything

Example Team Commands

Command Team Size Purpose
/team or /surveyor Variable Property work — research, proposals, reports, letters
/board-v2 6 directors Strategic decisions — board debate from multiple perspectives
/audit 8 specialists Project audit — comprehensive quality review
/pitch 7 + Devil’s Advocate Product evaluation — assess a business idea
/growth-swarm 6 specialists Marketing strategy — campaigns and growth planning
/security-swarm 8 specialists Security assessment — vulnerability and compliance audit

Note: These are examples of custom skills that firms can configure. They are not built-in Claude Code commands.

Example: Using the Property Team
/team Prepare a comprehensive rent review report for Unit 4, Riverside Business Park, S2 4SL. The current passing rent is £45,000 pa and the review is effective 25 March 2026. We act for the landlord. Include comparable evidence analysis, ERV assessment, and negotiation strategy.

Section Summary

Agent teams multiply Claude's capabilities by assigning specialised agents to work in parallel. Use them for complex, multi-faceted tasks. For simple tasks, stick with a single agent. Always review the combined output — more agents does not replace human judgement.

16

Custom Agents & Skills

You can configure a library of custom skills (also called slash commands) tailored to your firm's specific business needs. These are pre-built prompt patterns and workflows that you can invoke with a single command.

Property Skills

These are the skills commonly useful for property professionals:

Skill What It Does Example Use
/rent-review-analysis Calculates rent review positions using comparables Preparing for a rent review negotiation
/comparables Fetches VOA comparable evidence Finding comparable rents by postcode
/lease-advisory Lease analysis (reviews, renewals, breaks) Advising on a tenant's break clause options
/property-lookup Full property intelligence from 10 UK data sources Quick property research for a new instruction
/investment-yield Calculates NIY, EY, reversionary yield Pricing an investment property
/dcf-property Discounted cash flow analysis Investment appraisal for a client
/epc EPC rating lookup for any UK property Checking energy performance before a letting
/flood-check Environment Agency flood risk assessment Due diligence on a property acquisition
/voa VOA data — floor area, rateable value, market rent Checking rateable values for business rates advice

Business & Communication Skills

Skill What It Does
/proposal Generates fee proposals for clients
/letter Drafts formal client letters
/email Drafts professional emails
/report Drafts formal property reports
/brief Generates client briefing notes
/linkedin Creates LinkedIn content for your firm

Using Skills in Practice

Example: Property Lookup
/property-lookup 22 Division Street, Sheffield S1 4GF

This single command triggers a comprehensive property intelligence report that checks up to 10 data sources: VOA ratings, EPC certificates, Land Registry ownership, flood risk, planning applications, and more. What would take you 30 minutes of manual research happens in seconds.

Example: Rent Review Analysis
/rent-review-analysis Property: Unit 7, Meadowhall Business Park, S9 1EP Current rent: £55,000 pa Review date: 29 September 2026 Lease terms: upward only, 5-yearly reviews We act for: Landlord

Try This Now

Try the /voa skill with a Sheffield postcode you know well (perhaps the postcode of a property you have visited on a site inspection). See what data comes back. Then try /epc with the same postcode. Compare what each skill provides.

Common Pitfall: Using Skills Without Understanding Them

Skills are powerful shortcuts, but you should understand what they do before relying on their output. A /rent-review-analysis output is a starting point for professional analysis, not a finished product. Always apply your surveying knowledge and judgement to the results.

Section Summary

You can build a library of custom skills that automate common property and business tasks. Learn which skills are available and what they produce. Use them as starting points and time-savers, but always apply your professional judgement to the output.

17

Memory & Workflows

A significant limitation of AI chat is that each new session starts from scratch — Claude does not remember what you discussed yesterday. This is solved with Memory MCP and CLAUDE.md files, which give Claude persistent context across sessions.

How Memory Works

Memory MCP

The Memory MCP server stores important information as “entities” — structured pieces of knowledge that Claude can query at the start of any session. This means Claude can remember client preferences, project decisions, and important context without you having to repeat it every time.

Types of information stored in Memory:

  • Client information — preferences, history, contact details
  • Project decisions — architecture choices, approach decisions with rationale
  • Milestones — what has been completed, what is next
  • Risk registers — identified risks and mitigations

CLAUDE.md Files

Projects typically have a CLAUDE.md file that gives Claude essential context about the project. When you start Claude Code in a project directory, it automatically reads this file.

Example CLAUDE.md Structure
# Project: Riverside Business Park Rent Reviews ## Status In progress — 3 of 8 units reviewed ## Client ABC Property Fund (main contact: James Wright) ## Key Decisions - Using 5-year average growth for industrial rents (decided 12 Jan 2026) - Excluding Unit 3 from review (tenant exercised break clause) ## Last Working State Comparable evidence pack complete for Units 1, 2, and 4. Next: analyse comparables for Units 5-8.

Session Workflows

Structured workflows help maintain continuity across sessions:

1
Start of session

Claude reads CLAUDE.md and queries Memory MCP for relevant context. You pick up where you left off.

2
During the session

Important decisions are stored in Memory. Files are saved regularly. Progress is tracked.

3
End of session

CLAUDE.md is updated with current status. Work is committed to Git. Memory is updated with any new decisions.

Checkpoints and Handoffs

For long tasks that might span multiple sessions, Checkpoints help you pick up where you left off:

Command What It Does
/checkpoint Saves current task state to a checkpoint file + Memory. Safe to clear context after this.
/resume Reads the checkpoint and continues where you left off after a context clear.
/compact Compresses the current conversation to free up context space without losing important information.

Context Window Management

Claude has a limited context window (how much information it can hold in “working memory”). For long sessions with many files and extensive conversation, the context can fill up. Using /checkpoint before clearing context ensures nothing is lost. Think of it like saving your work before closing a document.

Try This Now

Ask Claude Code what it knows about you by saying: "What context do you have about me and my projects?" Notice how Claude can access information from Memory MCP and CLAUDE.md files without you providing it. This is persistent context in action.

Module 4 Summary

In this module you learned about co-work mode for collaborative working, agent teams for complex parallel tasks, your library of custom skills, and how Memory MCP provides persistent context across sessions. These tools transform Claude Code from a simple Q&A tool into an integrated working environment for property professionals.

Module 4 Knowledge Check

Test your understanding of co-work mode, agent teams, and custom workflows. Remember: up to 3 attempts per question with hints.

Question 1 of 12
What is the key difference between co-work mode and standard Claude Code usage?
Co-work mode transforms the interaction from sequential request-response into ongoing collaboration. You can guide, redirect, and refine as Claude works, like having a colleague working alongside you.
Question 2 of 12
What is an agent team in Claude Code?
An agent team is a group of specialised AI agents, each with a specific role (researcher, analyst, writer, reviewer), coordinated by a lead agent. They work in parallel to complete complex tasks faster and more thoroughly than a single agent.
Question 3 of 12
When should you use an agent team instead of a single Claude agent?
Agent teams are best for complex, multi-faceted tasks that benefit from parallel processing or multiple perspectives. Simple tasks are more efficiently handled by a single agent — teams add cost and complexity that is not justified for straightforward work.
Question 4 of 12
Which skill provides a comprehensive property intelligence report from multiple data sources?
/property-lookup triggers a comprehensive property intelligence report that checks up to 10 data sources: VOA ratings, EPC certificates, Land Registry ownership, flood risk, planning applications, and more.
Question 5 of 12
What is the purpose of Memory MCP?
Memory MCP stores important information as entities (client details, project decisions, milestones) that persist across sessions. This means Claude can remember context without you repeating it every time you start a new conversation.
Question 6 of 12
What is the purpose of a CLAUDE.md file in a project directory?
A CLAUDE.md file provides essential project context — current status, key decisions, team information, and last working state. Claude reads it automatically when you start a session in that directory, so it immediately understands the project context.
Question 7 of 12
What should you do before clearing context in a long Claude Code session?
/checkpoint saves your current task state to both a checkpoint file and Memory MCP. After checkpointing, you can safely clear context and later use /resume to pick up exactly where you left off.
Question 8 of 12
Why do agent teams cost more than using a single Claude agent?
Each agent uses API tokens independently. If you have 6 agents in a team, that is 6 times the token usage of a single agent. This is why teams should be reserved for complex tasks where the parallel processing genuinely adds value.
Question 9 of 12
Which skill would you use to calculate the yield on a commercial investment property?
/investment-yield calculates investment yields including NIY (Net Initial Yield), EY (Equivalent Yield), and Reversionary Yield for commercial property. It is designed for pricing investment properties.
Question 10 of 12
What is the recommended first step when starting a co-work session with Claude Code?
Start with the big picture. Explain the overall goal before diving into details. This gives Claude the context to make better decisions as the session progresses, and helps it understand how individual tasks fit together.
Question 11 of 12
What does the /board-v2 command do?
/board-v2 creates a virtual board meeting with 6 AI directors covering operations, technology, growth, commercial, people, and legal perspectives. They debate the question from different angles before reaching a consensus recommendation.
Question 12 of 12
What is the key rule when using custom skills like /rent-review-analysis?
Skills are powerful shortcuts, not replacements for professional expertise. A /rent-review-analysis output is a starting point. You must apply your surveying knowledge, check the data, verify calculations, and ensure the output meets RICS standards before using it professionally.

Module 4 Complete

0/12

Module 5

Best Practices & Professional Use

Master prompt principles, RICS compliance, security practices, and advanced Claude Code features.

Estimated time: 90–120 minutes

Module 5 Learning Objectives

  • Apply advanced prompt engineering principles for consistent, high-quality output
  • Build and use reusable prompt templates for common property tasks
  • Understand RICS implications of AI-assisted professional work
  • Implement security best practices and handle AI failures gracefully
18

Prompt Principles

You have already learned the basic prompt patterns (CTF, ROLE, CONSTRAINTS, ITERATION). Now we go deeper into the principles that separate average prompts from excellent ones. These principles apply to every interaction with Claude Code.

Principle 1: Be Explicit, Not Implicit

Claude cannot read your mind. Information that seems obvious to you may not be obvious to an AI. Always state assumptions explicitly.

Implicit (Poor) Explicit (Good)
"Write about the rent review" "Write the landlord's opening position for a rent review at Unit 4, Riverside BP, S2 4SL. Current rent £45,000 pa, review date 25/03/2026, upward only, 5-yearly."
"Analyse the comparables" "Analyse these 5 comparable transactions, adjusting headline rents to effective rents over a 10-year term. Present as a table with columns for address, size, headline rent psf, incentives, and effective rent psf."
"Make it professional" "Rewrite in a formal tone suitable for a RICS-compliant rent review report. Use third person. Avoid colloquialisms."

Principle 2: Provide Reference Material

When you want Claude to match a specific style or standard, show it an example rather than describing it abstractly:

Providing Reference Material
Read the fee proposal template at /Users/yourname/Projects/templates/fee-proposal.docx. Now draft a fee proposal for ABC Property Fund using the same structure, tone, and formatting. The instruction is for rent review advice on 8 industrial units across Sheffield.

Principle 3: Decompose Complex Tasks

Large tasks should be broken into smaller, manageable steps. This reduces errors and gives you checkpoints for review:

1
Outline first

"Create an outline for a market update report covering Sheffield industrial property"

2
Review the outline

"Good outline. Move the supply pipeline section before the demand analysis. Remove the retail section — this is industrial only."

3
Write section by section

"Now write the Executive Summary section. Keep it under 200 words."

4
Review and iterate each section

"Tighten the language in paragraph 2. Add a specific statistic about vacancy rates."

Principle 4: Define the Negative Space

Telling Claude what NOT to do is often as important as telling it what to do:

Defining Negative Space
Write a market commentary on Sheffield office property. Do NOT: - Include any specific rental figures unless I provide them - Give legal advice or opinions on legislation - Make predictions about future market movements - Use American English spellings or terminology - Include any information about residential property

Principle 5: Request Reasoning

When you want Claude to show its working (not just give an answer), ask it to explain its reasoning:

Requesting Reasoning
Based on these 6 comparable transactions, what ERV would you recommend for the subject property? Show your reasoning step by step: explain which comparables you weighted most heavily and why, what adjustments you made, and how you arrived at your final figure.

Try This Now

Take a task you have already done with Claude Code this week and rewrite your original prompt using all five principles. Compare the output quality. You should see a noticeable improvement in relevance, accuracy, and usefulness.

Section Summary

Five advanced prompt principles: be explicit, provide reference material, decompose complex tasks, define negative space, and request reasoning. Applying these consistently will dramatically improve the quality of Claude's output.

19

Templates

Reusable prompt templates save time and ensure consistency across similar tasks. Many firms maintain a library of templates for common property work.

Building a Prompt Template

A good template has fixed structure with variable fields that change per use:

TEMPLATE: Rent Review Opening Letter

CONTEXT:
- Property: [ADDRESS]
- Tenant: [TENANT NAME]
- Landlord: [LANDLORD NAME]
- Current rent: [AMOUNT] per annum
- Review date: [DATE]
- Review basis: [UPWARD ONLY / OPEN MARKET]
- We act for: [LANDLORD / TENANT]

TASK:
Draft a formal opening letter for the rent review.
Include reference to the lease review clause.
State our initial position on ERV.
Propose a meeting to discuss.

FORMAT:
- Formal letter format (your firm's letterhead style)
- Maximum 1 page
- Professional but collaborative tone

Common Property Templates

Template Variables to Fill In Typical Output
Rent review opening letter Property, parties, rent, date, basis 1-page formal letter
Fee proposal Client, service, property, fees, timeline 3–5 page proposal document
Site inspection notes Property, date, attendees, observations Structured inspection record
Comparable evidence schedule Subject property, comparables data Formatted comparison table
Client update email Client name, project, progress, next steps Professional email draft
Lease summary Full lease document or key terms Structured summary of key provisions

Using Templates Effectively

Templates work best when you:

  • Fill in all variables — empty fields lead to hallucinated content
  • Customise for the situation — templates are starting points, not rigid forms
  • Review the output critically — template-generated content still needs human review
  • Update templates over time — improve them based on what works and what does not

Try This Now

Create your own prompt template for a task you do regularly. Think about:

  • What context does Claude always need for this task?
  • What variables change each time?
  • What format should the output take?
  • What constraints or exclusions are important?

Test the template with fictional data. Refine it until the output consistently meets your standards.

Section Summary

Prompt templates provide reusable structures for common tasks. Build them with fixed structure and variable fields. Always fill in all variables, customise for the situation, and review the output critically.

20

RICS & Professional Judgement

For RICS-regulated firms, there are specific obligations around how AI is used in professional work. This section covers the intersection of AI tools and professional standards.

RICS and AI: The Core Principle

RICS members remain personally responsible for all professional advice and work product, regardless of whether AI tools were used to assist. AI can help with research, drafting, and analysis, but the professional judgement, opinion, and signature must come from a qualified human.

What AI Can and Cannot Do Under RICS Standards

AI Can Assist With AI Must NOT Provide
Research and data gathering Formal valuations or professional opinions
Drafting reports and letters Legal advice
Analysing comparable evidence Expert witness opinions
Calculating yields and rent adjustments Final figures without human verification
Summarising lease documents Interpretation of lease terms for clients
Preparing meeting notes and agendas Negotiation strategy without professional review

Disclosure and Transparency

Mandatory position on AI disclosure under the RICS AI standard:

  • Internal work — no client disclosure required, but maintain internal records of AI use
  • Client-facing work — notify clients in writing that AI tools are used, specifying which parts of the process, and offer opt-out where practicable
  • Formal reports — the signing surveyor is responsible for all content; document the AI review process
  • General — be transparent and proactive about AI use; do not wait to be asked

The Human Oversight Framework

Every piece of AI-generated work should go through a human oversight process:

1
Generation

Claude Code produces a draft or analysis

2
Fact-check

Verify all facts, figures, dates, and names against primary sources

3
Professional review

Apply professional judgement — is the analysis sound? Are conclusions reasonable?

4
RICS compliance check

Does the output meet relevant RICS standards and guidance?

5
Approval

A qualified professional approves the final output before it is sent to clients

Common Pitfall: Over-Reliance on AI Analysis

It is tempting to accept Claude's analysis at face value, especially when it looks thorough and well-structured. But AI can miss nuances that an experienced surveyor would catch — unusual lease provisions, local market factors, or physical property issues that affect value. Your professional training and experience are irreplaceable.

Section Summary

RICS members remain personally responsible for all professional advice, regardless of AI involvement. AI assists with research and drafting; humans provide judgement and sign-off. Follow the human oversight framework for every piece of work.

21

Security & Handling Failures

Using AI tools involves data security responsibilities and the need to handle situations when AI gets things wrong. This section covers both.

Data Security with Claude Code

What Data is Safe to Use with Claude Code?

Claude Code processes data through Anthropic's API. Your firm's arrangement may mean that data sent to Claude is not used for training. However, you should still exercise caution with highly sensitive information and follow your firm's data handling policies.

Safe to Use Use with Caution Do Not Use
Property addresses and descriptions Client financial information (for analysis only) Personal passwords or API keys
Publicly available market data Lease terms and rental figures Bank account details
Internal procedures Client contact details (for drafting communications) National Insurance or passport numbers
Professional standards references Draft reports (before client approval) Credit card numbers

When Claude Gets It Wrong

AI failures happen. Knowing how to identify and handle them is an essential skill:

Types of AI Failure

  • Hallucination — Claude confidently states something incorrect. Example: inventing a comparable transaction that never happened
  • Outdated information — Claude's training data has a cutoff. It may not know about recent legislation or market changes
  • Misunderstanding context — Claude may apply the wrong jurisdiction (Scottish law instead of English) or wrong property type (residential instead of commercial)
  • Arithmetic errors — Multi-step calculations can go wrong, especially with complex adjustments
  • Tone misjudgement — An email may be too casual or too formal for the recipient

Handling Failures

1
Identify the error

Check facts against primary sources. Verify arithmetic. Read critically, not passively.

2
Correct Claude directly

"That comparable at 25 Church Street — the rent was £22.50 psf, not £25.00. Please recalculate."

3
Provide correct information

Give Claude the right data and ask it to redo the work.

4
Learn the pattern

If Claude consistently makes the same type of error, adjust your prompts to prevent it.

Try This Now

Deliberately test Claude Code's accuracy. Ask it a question about a specific property transaction you know the details of, or a specific RICS standard you have studied. Does it get everything right? Where does it go wrong? Understanding Claude's failure modes makes you a more effective user.

Section Summary

Security means knowing what data is safe to use with Claude and what is not. Handling failures means actively checking AI output, correcting errors, and learning from patterns. Both skills are essential for professional AI use.

22

Advanced Tools

This section introduces advanced Claude Code features that will become more useful as your confidence grows.

Playwright: Browser Automation

Claude Code can control a web browser via the Playwright MCP server. This enables automation of tasks that normally require manual web interaction:

  • Navigating to a website and extracting data
  • Filling in forms and submitting applications
  • Taking screenshots of web pages for reports
  • Checking the status of online planning applications
Example: Browser Automation
Use Playwright to navigate to the Sheffield City Council planning portal. Search for planning applications within 500m of S1 4GF submitted in the last 3 months. Take a screenshot of the results.

Bash: Running Commands

The Bash tool lets Claude run command-line operations. For property work, this is useful for:

  • Processing multiple files at once (e.g., renaming, converting)
  • Running scripts that connect to external APIs
  • Managing Git repositories for version control of documents
  • Installing or updating tools

Git: Version Control for Documents

Git is a system for tracking changes to files over time. It is commonly used for code projects, but it can also track changes to important documents:

Why Git Matters

Git records every change ever made to a file, who made it, and when. This means you can always go back to a previous version. For property work, this provides an audit trail of how reports and analyses evolved — useful for professional accountability.

Thinking Triggers

For complex analytical tasks, you can tell Claude to think more deeply by using specific triggers:

Trigger Thinking Depth Best For
think Standard Single-file changes, simple analysis
think hard Deeper Multi-document coordination, complex reports
think harder Extended Strategic analysis, complex valuation methodology
ultrathink Maximum Critical decisions, complex financial models, security analysis
Example: Using Thinking Triggers
Ultrathink about this: We have been instructed to advise on the rent review for a 50,000 sq ft distribution warehouse in Rotherham. The lease was granted in 2010 with 5-yearly upward-only reviews. The tenant is a national retailer. The current passing rent is £275,000 pa. Comparable evidence is limited. What methodology should we adopt, and what risks should we flag to the client?

Module 5 Summary

This module covered advanced prompt principles, reusable templates, RICS professional standards with AI, data security, handling AI failures, and advanced tools including browser automation, Git, and thinking triggers. You now have a comprehensive understanding of Claude Code for professional property work. The remaining modules will deepen specific areas.

Video: Prompt Engineering Deep Dive

Anthropic · Selected segment

Direct from Anthropic's prompt engineering team — the definitive guide to getting the best results from Claude. Focus on the first 20 minutes for the most relevant techniques.

Module 5 Knowledge Check

Test your understanding of best practices, RICS compliance, and advanced features. Remember: up to 3 attempts per question with hints.

Question 1 of 12
What does "defining the negative space" mean in prompt engineering?
Defining the negative space means explicitly telling Claude what to exclude — what not to include, what topics to avoid, what format not to use. This prevents common AI tendencies like including irrelevant information or overstepping professional boundaries.
Question 2 of 12
Under RICS standards, who is responsible for professional advice produced with AI assistance?
The RICS member remains personally responsible for all professional advice, regardless of whether AI tools were used. AI assists with research and drafting, but the professional judgement, opinion, and signature must come from a qualified human.
Question 3 of 12
Which of the following should you NEVER input into Claude Code?
Never input personal passwords, bank account details, National Insurance numbers, or credit card numbers into Claude Code or any AI tool. Property addresses, market data, and professional standards are safe to use.
Question 4 of 12
What is the "decompose complex tasks" principle?
Decomposing complex tasks means breaking them into smaller steps — outline first, then section by section, with review at each stage. This reduces errors, gives you checkpoints, and keeps Claude's output focused.
Question 5 of 12
What is the key characteristic of a good prompt template?
A good template has fixed structure (the prompt pattern, format requirements, constraints) with variable fields (property address, client name, figures) that change each time. This gives consistency while allowing customisation.
Question 6 of 12
Claude Code cites a comparable transaction at "14 Market Street, let at £18 psf in March 2025" but you cannot find any record of this. What type of AI failure is this?
This is a hallucination — Claude has confidently presented a transaction that never happened. This is one of the most dangerous AI failures in property work because fabricated comparables could lead to incorrect valuations. Always verify comparables against primary sources.
Question 7 of 12
When should you use the "ultrathink" thinking trigger?
Ultrathink triggers the deepest level of reasoning. Use it for critical decisions, complex financial modelling, and situations requiring maximum analytical depth. For simple tasks, standard thinking is sufficient — ultrathink uses more tokens and takes longer.
Question 8 of 12
In the human oversight framework, what comes after "fact-check"?
The framework is: Generation → Fact-check → Professional review → RICS compliance check → Approval. Professional review is where you apply your judgement to assess whether the analysis is sound and conclusions are reasonable.
Question 9 of 12
Which MCP tool would you use to automatically check a planning portal website?
Playwright is the browser automation MCP tool. It can navigate to websites, fill in forms, click buttons, and take screenshots — perfect for checking planning portals, extracting data from websites, or automating any web-based task.
Question 10 of 12
Why is Git useful for property document management?
Git provides a complete audit trail — every change, who made it, and when. You can always go back to a previous version. For property work, this supports professional accountability and provides evidence of how reports and analyses evolved.
Question 11 of 12
According to the "be explicit, not implicit" principle, which prompt is better?
The explicit prompt provides specific data, clear methodology, and exact format requirements. Claude cannot read your mind — stating assumptions, data, and desired output format explicitly always produces better results than vague instructions.
Question 12 of 12
If a client directly asks whether your firm uses AI in its work, what is the correct response?
The recommended policy is honesty and transparency. If asked directly: "We use AI tools to assist with research and drafting, but all professional advice is reviewed and approved by a qualified surveyor." This builds trust while reassuring clients that human expertise underpins all advice.

Module 5 Complete

0/12

Module 6

Advanced Prompting Techniques

Master chain-of-thought reasoning, few-shot learning, persona engineering, and build a property prompt library.

Estimated time: 90–120 minutes

Module 6 Learning Objectives

  • Use chain-of-thought prompting to improve analytical accuracy
  • Apply few-shot learning by providing examples in prompts
  • Create effective personas for different property contexts
  • Build and maintain a personal prompt library for common tasks
23

Chain-of-Thought Prompting

Chain-of-thought (CoT) prompting is a technique that dramatically improves Claude's accuracy on analytical tasks by asking it to show its reasoning step by step, rather than jumping directly to an answer.

Why Chain-of-Thought Works

When Claude "thinks out loud," it breaks complex problems into smaller steps, catches its own errors, and produces more accurate results. This mirrors how professionals work — a surveyor does not jump from raw data to a final valuation. They work through comparables, adjustments, weighting, and methodology step by step.

Basic Chain-of-Thought

The simplest way to invoke chain-of-thought is to add "Think step by step" or "Show your working" to your prompt:

Without CoT (Less Accurate)
What ERV would you recommend for a 5,000 sq ft office at 22 Division Street, Sheffield, based on these comparables? [data]
With CoT (More Accurate)
Based on these comparables, what ERV would you recommend for a 5,000 sq ft office at 22 Division Street, Sheffield? Think step by step: 1. First, assess each comparable for relevance (location, size, quality, timing) 2. Adjust each to an effective rent basis 3. Weight the comparables based on relevance 4. Apply any necessary adjustments for the subject property 5. State your recommended ERV range with justification [data]

Structured Chain-of-Thought for Property Analysis

For property-specific analysis, structure the chain of thought to match professional methodology:

Rent Review CoT
Analyse this rent review position step by step: Step 1: LEASE TERMS - Summarise the relevant lease provisions (review clause, basis, assumptions) Step 2: MARKET CONTEXT - Assess the current market for this property type and location Step 3: COMPARABLE EVIDENCE - Analyse each comparable, noting strengths and weaknesses Step 4: ADJUSTMENTS - Apply time, size, quality, and location adjustments Step 5: WEIGHTING - Weight the adjusted comparables and explain your reasoning Step 6: ERV RECOMMENDATION - State a recommended range and preferred figure Step 7: RISKS - Identify risks to this position and potential counter-arguments Property: [details] Comparables: [data]

When to Use Chain-of-Thought

Good for CoT Not Needed for CoT
Comparative analysis (rent reviews, valuations) Simple email drafting
Financial calculations (yields, DCF) Formatting or restructuring text
Strategic decisions (negotiation approach) Summarising a document
Risk assessment Translating between formats (table to list)
Legal clause interpretation Creating meeting agendas

Try This Now

Take a comparable evidence analysis task. First, ask Claude for a straight answer without chain-of-thought. Then ask the same question with structured CoT steps. Compare the two outputs — the CoT version should be more thorough, better reasoned, and more useful for professional work.

Section Summary

Chain-of-thought prompting improves accuracy by making Claude show its reasoning. Use it for analytical tasks, calculations, and strategic analysis. Structure the steps to match professional methodology for the best results.

24

Few-Shot Learning & Personas

Two powerful techniques that work together: few-shot learning (showing Claude examples of what you want) and persona engineering (defining who Claude should be for a specific task).

Few-Shot Learning

What is Few-Shot Learning?

Instead of describing what you want, you show Claude by providing examples. Claude learns the pattern from your examples and applies it to new inputs. "Few-shot" means providing a small number (1–5) of examples.

Zero-Shot vs One-Shot vs Few-Shot

Approach Examples Given Best For
Zero-shot None — just describe what you want Simple, well-understood tasks
One-shot One example Style matching, format consistency
Few-shot 2–5 examples Complex patterns, professional tone matching, specialised formats
Few-Shot Example: Property Descriptions
Here are three examples of how I write property descriptions for your client reports: Example 1: "The property comprises a modern, detached industrial unit of steel portal frame construction with profiled metal cladding to walls and roof. The unit provides clear span warehouse accommodation with an eaves height of 8 metres." Example 2: "The premises consist of a ground floor retail unit within a Victorian mid-terrace building of traditional brick construction under a pitched slate roof. The unit provides open-plan sales accommodation with an ancillary storage area to the rear." Example 3: "The subject property is a self-contained first floor office suite within a 1990s purpose-built office building. The accommodation provides open-plan workspace with perimeter cellular offices and a central meeting room." Now write a property description for: a 1970s semi-detached light industrial unit, single-storey, with blockwork walls, corrugated roof, one roller shutter door, small office at the front, approximately 3,000 sq ft total.

Persona Engineering

A persona goes beyond a simple role assignment. It defines Claude's expertise, communication style, knowledge focus, and even personality traits:

Basic Role vs Detailed Persona
Basic role: "You are a surveyor." Detailed persona: "You are a senior RICS-chartered commercial property surveyor with 25 years of experience in the South Yorkshire industrial and logistics market. You specialise in rent reviews and lease renewals for institutional landlord clients. Your communication style is precise, data-driven, and confident. You always qualify opinions with reference to evidence. You are aware of current market trends including the growth of last-mile logistics and the impact of ESG requirements on industrial rents."

Combining Techniques

The most effective prompts often combine multiple techniques. Here is an example combining persona, few-shot, and chain-of-thought:

Combined Technique
[Persona] You are a senior RICS-qualified investment surveyor advising institutional clients on commercial property acquisitions in Sheffield. [Few-shot] Here is how I typically structure investment analysis for my clients: "Property: [address]. The subject property is currently let to [tenant] at a passing rent of £X pa, reflecting a capital value of £Y at a NIY of Z%. The reversionary position, based on an ERV of £A pa, suggests upside/downside of B%..." [Chain-of-thought] Now analyse this investment opportunity step by step: 1. Summarise the investment characteristics 2. Calculate the NIY and reversionary yield 3. Assess tenant covenant strength 4. Identify risks and opportunities 5. Provide an investment recommendation Property data: [details]

Try This Now

Create a detailed persona for Claude that matches your own professional context. Include your level of experience, your focus areas, the types of clients you work with, and the market you operate in. Then use this persona to generate a market commentary on Sheffield industrial property. Compare the output with a generic "you are a surveyor" prompt.

Section Summary

Few-shot learning teaches Claude by example — show it what you want rather than describing it. Persona engineering defines Claude's expertise, style, and focus for a specific task. Combining these with chain-of-thought produces the highest quality output.

25

Property-Specific Prompts

This section provides tested prompt structures for common property tasks. Each has been refined through real use and produces consistently good results.

Rent Review Analysis Prompt

PERSONA: Senior RICS commercial surveyor, 20+ years experience,
specialising in [office/industrial/retail] rent reviews.

CONTEXT:
- Property: [address], [size] sq ft, [property type]
- Current rent: £[amount] pa (£[psf] psf)
- Review date: [date]
- Review basis: [upward only / open market]
- We act for: [landlord / tenant]

COMPARABLE EVIDENCE:
1. [address], [size] sq ft, [rent] psf, [date], [term], [incentives]
2. [repeat for each comparable]

TASK: Analyse these comparables and recommend an ERV position.

METHOD:
1. Assess relevance of each comparable
2. Adjust to effective rents
3. Weight by relevance
4. Apply adjustments for subject property
5. Recommend ERV range and preferred figure
6. Identify risks to our position

FORMAT: Structured report section with clear headings.
Do not include legal advice.

Lease Summary Prompt

Read the lease document at [file path].

Produce a structured summary covering:
1. PARTIES - Landlord, tenant, guarantor (if any)
2. PROPERTY - Description and demise
3. TERM - Commencement, expiry, any options to extend
4. RENT - Current rent, payment frequency, VAT position
5. RENT REVIEWS - Frequency, basis, assumptions/disregards
6. BREAK CLAUSES - Who can break, when, conditions, notice period
7. REPAIR - Landlord vs tenant obligations (FRI or internal only?)
8. ALTERATIONS - What requires consent?
9. ALIENATION - Assignment and subletting restrictions
10. USER CLAUSE - Permitted use, any restrictions
11. SERVICE CHARGE - Applicable? Cap? Sinking fund?
12. INSURANCE - Who insures? How are premiums recovered?

Flag any unusual or particularly important clauses.
Use plain English suitable for a non-lawyer client.

Fee Proposal Prompt

Draft a fee proposal for [client name].

SERVICE: [rent review advice / property management / valuation / etc.]
PROPERTY: [details]
SCOPE: [what is included and excluded]
FEES: [fee structure - fixed / percentage / hourly]
TIMELINE: [expected duration]
TEAM: [who will be involved]

Follow your firm's standard fee proposal format:
1. Introduction and understanding of instruction
2. Scope of services
3. Our approach and methodology
4. Team and qualifications
5. Fee schedule and payment terms
6. Terms and conditions
7. Contact details

Tone: Professional, confident, but not arrogant.
Emphasise your firm's local market knowledge and RICS credentials.

Market Commentary Prompt

Write a market commentary on [property type] property in [location].

PERIOD: [quarter/year]
AUDIENCE: [institutional client / private investor / general]
LENGTH: [word count]

Cover:
1. Market overview and key trends
2. Supply and demand dynamics
3. Rental growth/movement
4. Investment yields
5. Development pipeline
6. Outlook and risks

Do NOT include specific rental or yield figures unless I provide them.
Do NOT make specific predictions about future values.
Use British English throughout.

Try This Now

Choose one of the prompt templates above and use it with fictional data. Assess the output: is it the quality you would expect from a first draft in a professional practice? What would you change? Adapt the template to better suit your specific needs.

Section Summary

Property-specific prompt structures produce consistently high-quality output because they mirror professional methodology. Use these as starting points and adapt them to your specific situations. Over time, build your own library of tested prompts.

26

Building Your Prompt Library

Professional efficiency with AI comes from having a curated library of prompts that you refine over time. This section guides you through creating and maintaining your personal prompt library.

What to Include in Your Library

Start with the tasks you do most frequently:

  • Daily tasks — email drafts, meeting notes, quick calculations
  • Weekly tasks — client reports, market updates, comparable analysis
  • Monthly tasks — management reports, fee proposals, portfolio reviews
  • Occasional tasks — valuation reports, expert witness prep, lease negotiations

Organising Your Library

Store prompts as text files in a dedicated folder. Claude Code can read these files directly:

/Users/yourname/prompts/
  /emails/
    client-update.txt
    rent-review-opening.txt
    meeting-confirmation.txt
  /reports/
    rent-review-analysis.txt
    lease-summary.txt
    market-commentary.txt
  /proposals/
    fee-proposal.txt
    terms-of-engagement.txt
  /analysis/
    comparable-analysis.txt
    yield-calculation.txt
    dcf-template.txt
Using a Library Prompt
Read my rent review analysis template at /Users/yourname/prompts/reports/rent-review-analysis.txt and use it for the following: Property: Unit 12, Parkway Business Park, S9 4WA Current rent: £38,000 pa Review date: 24 June 2026 We act for: Landlord Comparables: 1. Unit 8, Parkway BP - 4,500 sq ft, £9.50 psf, Feb 2026, 10yr, 6m RF 2. Unit 3, Valley Business Park - 5,200 sq ft, £8.75 psf, Nov 2025, 5yr, 3m RF 3. Unit 22, Riverside - 3,800 sq ft, £10.00 psf, Jan 2026, 10yr, 9m RF

Refining Prompts Over Time

1
Track what works

When a prompt produces great output, note why. Was it the structure, the persona, the examples?

2
Track what fails

When output is poor, identify whether the prompt or the data was the problem. Adjust accordingly.

3
Version your prompts

Keep previous versions so you can compare performance. Use a simple v1, v2, v3 naming convention.

4
Share with colleagues

Prompts that work well should be shared across the team. This builds firm-wide consistency.

Common Pitfall: Prompt Hoarding

Some people save dozens of prompts but never use them because they cannot find the right one. Keep your library focused — 10–15 well-refined prompts that cover your most common tasks are more valuable than 100 untested ones. Quality over quantity.

Module 6 Summary

In this module you learned four advanced techniques: chain-of-thought reasoning for analytical accuracy, few-shot learning for style and format matching, persona engineering for context-appropriate output, and building a prompt library for consistent, efficient professional work. These techniques compound over time — the more you use and refine them, the better your results become.

Module 6 Knowledge Check

Test your understanding of advanced prompting techniques. Remember: up to 3 attempts per question with hints.

Question 1 of 12
What is the main benefit of chain-of-thought prompting?
Chain-of-thought prompting improves accuracy because when Claude "thinks out loud," it breaks complex problems into smaller steps and can catch its own errors. This is especially valuable for analytical tasks like comparable analysis and financial calculations.
Question 2 of 12
What is few-shot learning in prompt engineering?
Few-shot learning means providing a small number of examples (typically 1–5) in your prompt. Claude learns the pattern from your examples and applies it to new inputs. This is especially effective for matching specific writing styles or output formats.
Question 3 of 12
What distinguishes a "persona" from a simple "role" in prompting?
A persona goes beyond a job title to define specific expertise (25 years in South Yorkshire industrial), communication style (precise, data-driven), knowledge focus (rent reviews, lease renewals), and context awareness (ESG trends, logistics growth). This produces much richer, more relevant output.
Question 4 of 12
Which task would benefit MOST from chain-of-thought prompting?
Comparable analysis involves multiple steps: assessing relevance, adjusting rents, weighting evidence, and forming a recommendation. Chain-of-thought prompting ensures each step is handled carefully. Simple tasks like reformatting or summarising don't need step-by-step reasoning.
Question 5 of 12
What is a "zero-shot" prompt?
Zero-shot means providing no examples — you describe what you want and Claude figures it out. This works well for simple, well-understood tasks. For complex or specialised tasks, one-shot or few-shot prompts (with examples) produce better results.
Question 6 of 12
What is the recommended approach to building a prompt library?
Quality over quantity. Focus on 10–15 well-refined prompts covering your most common tasks. These are more valuable than 100 untested prompts because you know they produce good results and you can find them quickly.
Question 7 of 12
How can you use a saved prompt template with Claude Code?
Claude Code can read files directly from your filesystem. Tell it to read your template file, then provide the specific data for this particular use. Claude will apply the template structure to your data and produce the output.
Question 8 of 12
In the lease summary prompt template, which section covers who can end the lease early?
BREAK CLAUSES cover who can end the lease early (landlord, tenant, or mutual), when they can exercise the break, what conditions must be met, and the required notice period. This is one of the most commercially important provisions in a lease.
Question 9 of 12
When a prompt consistently produces poor output, what should you do?
Diagnose before changing. Poor output may be caused by insufficient context (prompt problem) or incorrect/incomplete data (data problem). Identify the root cause, make targeted adjustments, and compare the new output with the old. This systematic approach builds better prompts over time.
Question 10 of 12
Which combination of techniques produces the highest quality analytical output?
Combining persona (for expertise and tone), few-shot examples (for style and format), and chain-of-thought (for methodical reasoning) produces the highest quality output. Each technique addresses a different dimension of quality.
Question 11 of 12
In the rent review analysis prompt template, what is the first step in the method?
The first step is to assess the relevance of each comparable — considering location, size, quality, and timing. Not all comparables are equally relevant, and this initial assessment determines how much weight each should carry in the analysis.
Question 12 of 12
Why should effective prompts be shared with colleagues?
Sharing effective prompts builds firm-wide consistency. When everyone uses tested templates, the overall quality of AI-assisted work improves, clients get a consistent experience, and the firm develops institutional knowledge about what works.

Module 6 Complete

0/12

Module 7

Document Processing & Analysis

Read, analyse, extract, and generate professional property documents at scale.

Estimated time: 90–120 minutes

Module 7 Learning Objectives

  • Use Claude Code to read and analyse PDFs, leases, and multi-page documents
  • Extract structured data from lease documents
  • Generate professional reports and client letters from templates
  • Process multiple documents in batch operations
27

Reading Documents

Property consultancy involves vast amounts of document work — leases, licences, reports, correspondence, schedules, and plans. Claude Code can read and analyse these documents directly, saving hours of manual review.

What Claude Code Can Read

Format How Claude Reads It Typical Property Use
PDF Read tool with page ranges Leases, reports, title documents
Word (.docx) Read tool (extracts text) Draft reports, letters, memos
Excel (.xlsx) Read tool (extracts data) Rent rolls, tenant schedules, budgets
Text (.txt, .csv) Read tool (direct text) Data exports, logs, notes
Images (.png, .jpg) Read tool (visual analysis) Site photos, plans, maps
Google Docs/Sheets Google Workspace MCP Shared documents, collaborative files

Reading Large Documents

Large documents like leases can be hundreds of pages. Claude Code handles these efficiently by reading in sections:

Reading a Lease PDF
Read the lease at /Users/yourname/Documents/leases/riverside-unit4-lease.pdf, pages 1–10. Give me a summary of the key terms on these pages.

Page-Range Reading

For large PDFs, always specify page ranges (e.g., pages 1–5, pages 10–20). Reading the entire document at once can exceed Claude's context window. Work through the document in sections, building up your analysis as you go.

Reading Strategies for Different Document Types

1
Leases: Start with the cover page and contents

Read pages 1–3 first to understand the structure, parties, and key dates. Then target specific clauses.

2
Reports: Read the executive summary first

Most professional reports front-load key findings. Read the summary, then dive into specific sections.

3
Spreadsheets: Ask for an overview first

"Read this spreadsheet and tell me what tabs it has, what data is in each, and how many rows."

4
Correspondence: Read chronologically

For chains of letters or emails, read in date order to understand how a matter has progressed.

Try This Now

Find a PDF document on your computer (it could be a property report, a lease, or any professional document). Ask Claude Code to read the first 5 pages and provide a structured summary. Assess how accurate the summary is compared to your own reading of the document.

Section Summary

Claude Code can read PDFs, Word documents, spreadsheets, and images. For large documents, use page-range reading and work through sections. Always verify Claude's interpretation of important documents against your own professional reading.

28

Lease Data Extraction

Extracting structured data from leases is one of the highest-value applications of Claude Code in property. A task that might take 30–60 minutes manually can be done in 2–3 minutes, with you reviewing the output for accuracy.

Standard Lease Extraction Fields

The core data points to extract from any commercial lease:

Category Fields
Parties Landlord, tenant, guarantor, original parties (if assigned)
Dates Lease date, term commencement, term expiry, rent commencement
Term Length, contractual term, any option to extend
Rent Initial rent, current rent, payment frequency, VAT
Reviews Frequency, basis (upward only/open market), review dates, assumptions and disregards
Breaks Who can exercise, break date(s), notice period, conditions (vacant possession, no arrears, etc.)
Repair FRI or internal only, schedule of condition, dilapidations provisions
Use Permitted use class, any specific restrictions, keep-open obligations

Structured Extraction Prompt

Lease Extraction
Read the lease at [file path]. Extract the following data into a structured format: PARTIES: - Landlord: [name and registered address] - Tenant: [name and registered address] - Guarantor: [if any] TERM: - Lease date: [date] - Term: [years] - Commencement: [date] - Expiry: [date] RENT: - Initial rent: £[amount] per annum - Current rent: £[amount] per annum (if different) - Payment: [quarterly/monthly] in [advance/arrear] - VAT: [applicable/exempt] RENT REVIEWS: - Frequency: [every X years] - Next review: [date] - Basis: [upward only / open market] BREAKS: - Type: [tenant only / landlord only / mutual] - Date(s): [date] - Notice: [period] - Conditions: [list] REPAIR: - Obligation: [FRI / internal repairing / other] - Schedule of condition: [yes/no] USE: - Permitted: [use class and description] - Restrictions: [any] For any field where the information is ambiguous or not found, write "NOT FOUND - manual check required" rather than guessing.

Critical: Never Trust AI Lease Interpretation Without Verification

Lease extraction is where AI errors can have the most serious consequences. A misread break date could mean missing a deadline. A wrong rent figure could affect a valuation. Always verify extracted data against the original document, especially for dates, figures, and conditions. If Claude flags something as "NOT FOUND," check manually — the clause may exist in a different section than expected.

Comparing Multiple Leases

When working with a portfolio, Claude Code can extract data from multiple leases and compile it into a comparison table:

Multi-Lease Comparison
I have 5 lease PDFs in /Users/yourname/Documents/portfolio/. Read each one and create a comparison table with columns: - Property address - Tenant - Term (start – end) - Current rent - Next rent review - Next break date - Repair basis Sort by next rent review date (earliest first).

Try This Now

If you have access to a lease document (even a sample or template), ask Claude Code to extract the key terms using the structured extraction prompt above. Compare Claude's extraction with your own reading. Note any discrepancies — these tell you where to focus your verification effort.

Section Summary

Lease data extraction is one of Claude Code's most valuable property applications. Use structured extraction prompts to ensure consistency. Always verify extracted data against the original document, especially dates, figures, and conditions. Instruct Claude to flag uncertainty rather than guess.

29

Generating Reports & Letters

Building on the document skills from Module 3, this section covers more advanced report and letter generation, including multi-section reports, formatted output, and integration with Google Docs.

Multi-Section Report Generation

For full-length property reports, use a staged approach:

1
Define the report structure

"Create an outline for a rent review report following RICS guidance. Include sections for: executive summary, property description, lease analysis, comparable evidence, ERV analysis, and recommendation."

2
Generate each section with specific data

Provide section-specific data and instructions for each part.

3
Review and refine

Check each section for accuracy, tone, and compliance before moving to the next.

4
Compile into final document

"Create a Google Doc called 'Rent Review Report - Unit 4, Riverside BP' with all sections combined. Add your firm's standard header and footer."

Professional Letter Generation

Professional letters should follow a standard format. Claude Code can produce them quickly with the right template:

Client Letter
Draft a formal letter from [Your Firm Name] to Mr James Wright, Director, ABC Property Fund Ltd, 45 Park Lane, London W1K 1PN. Subject: Rent Review Advice – Riverside Business Park, Sheffield S2 4SL Purpose: Confirming our instruction to act on the landlord's behalf for rent reviews across 8 industrial units. Outline our approach, proposed timeline, and fee basis (as agreed, 15% of any increase achieved, subject to a minimum fee of £2,500 per unit). Include: - Reference to our meeting on 12 February 2026 - Confirmation of the portfolio (8 units, addresses to follow) - Proposed timeline (comp evidence gathering in March, initial recommendations by end of April) - Request for access to current lease documents and recent service charge accounts - Standard terms of engagement reference Sign off with your name, qualifications, and title.

Document Formatting and Output

Claude Code can output documents in several formats:

  • Google Docs — created directly via Google Workspace MCP
  • Local text files — saved to your computer using the Write tool
  • Markdown — useful for structured content that can be converted to other formats
  • HTML — for web-based reports or email content

Section Summary

Advanced report generation uses a staged approach: define structure, generate sections with specific data, review and refine, then compile into the final document. Professional letters follow standard templates with specific details. Always review thoroughly before sending.

30

Batch Processing

One of Claude Code's most powerful capabilities is processing multiple documents or data items in a single operation. This is especially valuable for portfolio management, where the same analysis needs to be applied across many properties.

When to Use Batch Processing

  • Portfolio rent reviews — extracting key dates from 20+ leases
  • EPC checks — looking up energy ratings for all properties in a portfolio
  • Tenant covenant checks — researching multiple tenants' financial health
  • Comparable analysis — processing multiple sources of comparable data
  • Correspondence review — summarising a chain of letters on a dispute

Batch Processing Examples

Batch: Portfolio Lease Summary
In the folder /Users/yourname/Documents/abc-portfolio/, there are 8 lease PDFs. For each one, extract: - Property address - Tenant name - Lease expiry date - Next rent review date - Current rent - Break dates (if any) Compile all results into a single table, sorted by next rent review date. Flag any leases with reviews in the next 6 months as URGENT.
Batch: EPC Lookups
Here are 12 property postcodes from our management portfolio. Look up the EPC rating for each using the /epc skill: 1. S1 4GF 2. S2 4SL 3. S9 1EP 4. S9 4WA [... etc.] Create a table showing address, current EPC rating, and expiry date. Flag any with ratings below C (which may need improvement under MEES regulations).

Best Practices for Batch Operations

Batch Processing Tips

  • Start with a test — run the operation on 1–2 items first to verify the output format before processing the full batch
  • Set clear output format — define exactly what columns, structure, or format you want before starting
  • Include error handling — tell Claude what to do when data is missing: "If any field cannot be found, write 'N/A' and flag for manual review"
  • Review a sample — for large batches, manually verify 20–30% of the results against source documents
  • Save intermediate results — for long-running batches, ask Claude to save progress after each item in case of interruption

Try This Now

Create a batch task for Claude Code. Even with fictional data, practice the workflow:

  1. Define the batch operation (what data, what analysis, what output)
  2. Test on one item
  3. Verify the output
  4. Run the full batch
  5. Sample-check the results

Module 7 Summary

This module covered the full document processing workflow: reading documents (PDFs, Word, Excel, images), extracting structured data from leases, generating professional reports and letters, and batch processing multiple documents. The consistent theme: Claude Code does the heavy lifting, but you verify the output. For lease data especially, always check extracted dates, figures, and conditions against the original document.

Module 7 Knowledge Check

Test your understanding of document processing and analysis. Remember: up to 3 attempts per question with hints.

Question 1 of 12
What is the recommended approach for reading a 200-page lease PDF with Claude Code?
Read in page-range sections (e.g., pages 1–5, then pages 6–15). Start with the cover page and contents to understand the structure, then target specific clauses. Reading the entire document at once can exceed Claude's context window.
Question 2 of 12
When extracting lease data, what should Claude do if it cannot find a specific field?
Claude should flag missing data rather than guess. Writing "NOT FOUND — manual check required" alerts you to check the original document. A guessed lease term or break date could lead to serious professional errors.
Question 3 of 12
Why is it particularly important to verify break clause data extracted by Claude Code?
Break clauses are commercially critical. Missing a break deadline means the tenant is locked in for the remainder of the term. Misunderstanding conditions (vacant possession, no arrears, decoration requirements) can invalidate a break notice. Always verify break clause details manually.
Question 4 of 12
What should you do before running a batch operation on 20 lease documents?
Always test on 1–2 items first. This lets you verify the output format is correct, catch any issues with the prompt, and adjust before investing time in the full batch. It is much easier to fix a problem with 2 results than 20.
Question 5 of 12
In lease extraction, what does "FRI" mean under the Repair category?
Full Repairing and Insuring (FRI) means the tenant is responsible for all repairs to the property and pays the insurance costs. This is the most common basis for single-let commercial properties. The alternative (internal repairing only) is more common in multi-let buildings.
Question 6 of 12
For a batch operation processing 20 documents, what percentage of results should you manually verify?
The recommended sample check is 20–30% of results. This balances thoroughness with efficiency. If you find errors in the sample, check more results and consider adjusting the prompt.
Question 7 of 12
What is the first step in the multi-section report generation approach?
The first step is to define the report structure — create an outline with section headings before generating any content. This ensures logical flow, prevents duplication, and gives you a framework to review before investing time in detailed writing.
Question 8 of 12
Which of these can Claude Code NOT read directly?
Claude Code can read digital files (PDFs, Word, Excel, text, images) but cannot read physical paper documents. You would need to scan or photograph a paper document to make it readable by Claude Code.
Question 9 of 12
In the batch EPC lookup example, why are properties with EPC ratings below C flagged?
MEES regulations set minimum energy efficiency standards for commercial lettings. Properties below the minimum rating may be unlawful to let, so identifying them in a portfolio review is essential for compliance and risk management.
Question 10 of 12
What is the recommended first step when Claude Code reads a complex spreadsheet?
Start with an overview — ask what tabs exist, what data is in each, and how many rows. This helps you understand the structure before asking for specific analysis, and prevents Claude from processing more data than necessary.
Question 11 of 12
How can you save a completed report directly to Google Drive using Claude Code?
The Google Workspace MCP can create Google Docs directly in Drive. Ask Claude to "Create a Google Doc called [name] with this content" and it will be saved to your Google Drive, accessible from any device.
Question 12 of 12
In a lease extraction, what are "assumptions and disregards" under rent reviews?
Assumptions and disregards are lease clauses that define the terms of the hypothetical letting at rent review. Assumptions might include that the property is in good repair; disregards typically include tenant's improvements and goodwill. These fundamentally affect the reviewed rent.

Module 7 Complete

0/12

Module 8

Research & Analysis

Conduct thorough market research, analyse data from multiple sources, and verify AI-generated findings.

Estimated time: 90–120 minutes

Module 8 Learning Objectives

  • Conduct structured web research for property market intelligence
  • Analyse market data and identify trends using Claude Code
  • Integrate multiple data sources into coherent analysis
  • Fact-check AI-generated research and recognise unreliable sources
31

Web Research

Effective property research combines multiple sources: web searches, local files, databases, and professional knowledge. Claude Code brings these together in a structured way, but you need to guide the research strategy.

Research Strategy Framework

1
Define the research question

Be specific about what you need to know and why. "What is the current ERV for Grade A office space in Sheffield city centre?" is better than "Research Sheffield offices."

2
Identify the best sources

Consider which sources are most reliable for your question: VOA data, EPC registers, planning portals, market reports, news articles, company filings.

3
Gather data systematically

Use Claude Code's web search, file reading, and MCP tools to gather data from each source.

4
Cross-reference and verify

Check findings against multiple sources. If only one source reports something, treat it with caution.

5
Synthesise into conclusions

Ask Claude to compile verified findings into a structured analysis with clear conclusions.

Types of Property Research

Research Type Key Sources Claude Code Approach
Market rents VOA, recent lettings, market reports /voa + WebSearch + local comparable files
Tenant covenant Companies House, credit reports WebSearch + /company-financial-health
Planning status Local authority planning portals /planning + Playwright for portal searches
Ownership Land Registry, CCOD /ownership + Land Registry price paid data
Environmental EA flood maps, contamination registers /flood-check + WebSearch
Market intelligence Trade press, agent reports, RICS data WebSearch + WebFetch for specific articles
Structured Research Prompt
I need to prepare a property briefing note for a potential acquisition at 45 Meadowhall Road, Sheffield S9 1HD. Research the following: 1. PROPERTY DATA: Use /voa for rateable value and floor area. Use /epc for energy rating. 2. OWNERSHIP: Use /ownership to find the current owner. 3. FLOOD RISK: Use /flood-check for Environment Agency flood risk data. 4. PLANNING: Use /planning to check for recent or pending applications nearby. 5. MARKET CONTEXT: Search the web for recent industrial transactions in Sheffield S9. Compile all findings into a briefing note with clear headings. Flag any data you could not find or are uncertain about.

Try This Now

Choose a property you know (perhaps one you have visited on a site inspection) and run a structured research exercise using the framework above. Compare what Claude finds with what you already know about the property. Where are the gaps?

Section Summary

Effective research follows a structured framework: define the question, identify sources, gather data, cross-reference, and synthesise. Claude Code combines web search, file analysis, and specialist skills to gather data from multiple sources efficiently.

32

Market Analysis

Market analysis goes beyond data gathering. It requires interpreting trends, understanding context, and forming professional opinions. Claude Code is excellent at structuring analysis; you provide the professional interpretation.

Rental Market Analysis

Market Trend Analysis
I have the following data on Sheffield industrial rents over the past 3 years: Q1 2024: Average £7.50 psf, 12 transactions Q2 2024: Average £7.75 psf, 15 transactions Q3 2024: Average £8.00 psf, 10 transactions Q4 2024: Average £8.25 psf, 14 transactions Q1 2025: Average £8.50 psf, 11 transactions Q2 2025: Average £8.75 psf, 16 transactions Q3 2025: Average £9.00 psf, 13 transactions Q4 2025: Average £9.25 psf, 18 transactions Q1 2026: Average £9.50 psf, 9 transactions Analyse this data: 1. Calculate the quarterly and annual growth rate 2. Identify the trend (accelerating, steady, decelerating) 3. Compare transaction volumes to assess market depth 4. Note any seasonal patterns 5. Provide a professional market commentary suitable for a client report

Investment Yield Analysis

Claude Code can calculate and compare investment yields, but the interpretation requires professional judgement:

Yield Comparison
Compare these investment transactions: 1. Meadowhall Road warehouse, £1.2m at NIY 6.5%, let to national occupier 2. Parkway retail unit, £450k at NIY 8.0%, let to local independent 3. City centre office, £2.8m at NIY 5.25%, multi-let to professional services For each, calculate the passing rent. Then analyse: what does the yield spread tell us about investor risk perception for different property types and tenant covenants in Sheffield?

Yield Reflects Risk

Lower yields indicate lower perceived risk (and higher prices). The yield spread between property types, locations, and tenant qualities reveals market sentiment. Claude can calculate the numbers, but interpreting why yields are what they are requires market knowledge that comes from professional experience.

Comparative Analysis

One of the most powerful uses of Claude Code is comparing data across multiple dimensions:

Multi-Dimensional Comparison
Here are 10 comparable industrial lettings. Create a comprehensive comparison matrix: [data for 10 comparables] For each comparable, show: - Location quality score (1–5, with 5 being prime) - Size adjustment vs subject (% larger/smaller) - Age/quality adjustment (newer = premium, older = discount) - Time adjustment (annualised growth to bring to current date) - Final adjusted rent psf Then weight the comparables: give me your recommended weights based on relevance, and calculate a weighted average ERV for the subject property (6,000 sq ft modern industrial unit in S9).

Common Pitfall: Confusing Correlation with Causation

When Claude identifies trends or correlations in data, remember that correlation does not imply causation. "Industrial rents rose 25% while new construction increased" does not mean construction caused rent increases — both might be driven by strong occupier demand. Apply your market knowledge to interpret the "why" behind the numbers.

Section Summary

Market analysis requires both data (which Claude Code can structure) and professional interpretation (which you provide). Use Claude for calculations, trend identification, and comparison matrices. Apply your market knowledge to explain why trends exist and what they mean for clients.

33

Data Sources & Integration

Claude Code can access a wide range of data sources. Understanding what each provides and how reliable it is helps you build comprehensive, accurate analysis.

The Property Data Toolkit

Source Accessed Via What It Provides Reliability
VOA /voa skill Rateable values, floor areas, property descriptions High (official data)
EPC Register /epc skill Energy ratings, floor area estimates, recommendations High (regulated assessors)
Land Registry /land-registry, /ownership Ownership, transaction prices, title details High (official register)
Environment Agency /flood-check Flood zones, flood risk assessment High (government data)
Planning Portals /planning, Playwright Applications, decisions, enforcement High (public records)
Companies House /company-financial-health Company accounts, directors, filings High (statutory filings)
Web Search WebSearch tool News, market reports, agent commentary Variable (check source)
Xero Xero MCP Your firm's financial data, invoices, accounts High (your firm's data)

Integrating Multiple Sources

The real power comes from combining data sources into a single, comprehensive view:

Integrated Property Report
Create a comprehensive due diligence report for 45 Meadowhall Road, S9 1HD by combining data from multiple sources: 1. /voa — get floor area and rateable value 2. /epc — get energy rating and certificate details 3. /ownership — identify current owner 4. /flood-check — assess flood risk 5. /planning — check for relevant planning applications 6. WebSearch — find any market intelligence about this area Present as a professional due diligence summary with a RAG (Red/Amber/Green) status for each category.

RAG Status for Due Diligence

Red = significant issue requiring further investigation. Amber = moderate concern, manageable with appropriate action. Green = no issues identified. This simple framework helps clients and colleagues quickly understand the risk profile of a property.

Try This Now

Run the integrated property report prompt for a Sheffield postcode you are familiar with. Review the RAG status assessments Claude produces. Do they match your professional assessment? Where might you disagree?

Section Summary

Claude Code integrates data from 8+ sources into comprehensive analysis. Understand the reliability of each source and always cross-reference important findings. The RAG status framework provides a clear, professional way to communicate risk assessments.

34

Fact-Checking & Verification

The ability to fact-check AI-generated research is the skill that separates effective AI users from dangerous ones. This section provides a systematic approach to verification.

The Verification Framework

1
Check the source

Where did Claude get this information? Official databases (VOA, Land Registry) are more reliable than web articles. If no source is cited, be suspicious.

2
Verify key facts

Check the most important facts (figures, dates, names) against primary sources. Even one wrong date can invalidate an analysis.

3
Check arithmetic

Recalculate any key figures manually or with a calculator. Pay special attention to multi-step calculations.

4
Apply the smell test

Does the conclusion make sense given your knowledge of the market? If Claude says Sheffield prime industrial rents are £50 psf, your experience should tell you that is implausible.

5
Check for freshness

Is the data current? Claude may cite older information. For market analysis, check that transaction dates and statistics are recent.

Red Flags in AI-Generated Research

Watch For These Warning Signs

  • Suspiciously precise numbers — "The vacancy rate is exactly 4.27%" without a cited source
  • Fabricated transactions — comparable evidence you cannot verify through any known source
  • Outdated market commentary — analysis that does not reflect recent events you know about
  • Wrong jurisdiction — references to laws or regulations that apply in Scotland, the US, or other jurisdictions
  • Implausible figures — yields, rents, or values that are clearly outside market parameters
  • Circular reasoning — using AI-generated data to validate other AI-generated conclusions

Asking Claude to Self-Check

You can ask Claude to review its own output for potential errors:

Self-Check Prompt
Review the analysis you just produced and flag: 1. Any facts you are less than 90% confident about 2. Any figures that might be outdated (from your training data rather than current sources) 3. Any conclusions that depend on assumptions I should verify 4. Any areas where you might be wrong or uncertain Be honest about your confidence levels.

The Trust Gradient

Not all AI output deserves the same level of trust. High trust: data extracted directly from official APIs (VOA, Land Registry). Medium trust: analysis and calculations based on data you provided. Low trust: general market commentary, statistics without sources, and any claim about specific transactions. Adjust your verification effort accordingly.

Try This Now

Ask Claude Code to produce a market analysis of Sheffield industrial property. Then use the self-check prompt above. Notice how Claude identifies its own uncertainties. Now fact-check three specific claims from the analysis against other sources. How accurate was Claude's self-assessment?

Module 8 Summary

This module covered the complete research lifecycle: structured web research, market analysis and trend interpretation, integrating multiple data sources, and systematic fact-checking. The critical skill is verification — knowing what to trust, what to check, and how to spot AI-generated errors. Apply the trust gradient: official API data gets high trust; unsourced market commentary gets low trust.

Module 8 Knowledge Check

Test your understanding of research, analysis, and fact-checking. Remember: up to 3 attempts per question with hints.

Question 1 of 12
What is the first step in a structured research approach with Claude Code?
The first step is to define the specific research question. A clear, specific question like "What is the current ERV for Grade A office space in Sheffield city centre?" guides the research far more effectively than a vague request to "research Sheffield offices."
Question 2 of 12
According to the trust gradient, which data source deserves the HIGHEST level of trust?
Official API data from VOA, Land Registry, EPC Register, and similar sources is the most reliable because it comes directly from official databases. Web articles and general AI knowledge should be treated with lower confidence and verified against primary sources.
Question 3 of 12
In a RAG-status due diligence report, what does an "Amber" rating indicate?
Amber indicates moderate concern that is manageable with appropriate action. Red means significant issues requiring further investigation. Green means no issues identified. This framework gives clients a quick visual summary of risk.
Question 4 of 12
Claude Code cites a "vacancy rate of exactly 4.27% for Sheffield industrial" without a source. What should this tell you?
Suspiciously precise numbers without cited sources are a red flag for AI hallucination. Real market statistics come from specific reports with known methodologies. If Claude presents a precise figure without saying where it came from, treat it as unreliable until verified.
Question 5 of 12
In investment analysis, what does a LOWER yield generally indicate?
Lower yields indicate lower perceived risk and higher investor demand. Investors accept lower returns (yields) for properties they consider safer — typically prime locations, strong tenants, and long unexpired lease terms. Higher yields suggest higher risk.
Question 6 of 12
What is the "smell test" in fact-checking AI research?
The smell test is applying your professional knowledge to check whether AI output is plausible. If Claude claims Sheffield prime industrial rents are £50 psf, your market experience should tell you this is implausible. Professional knowledge is your most important verification tool.
Question 7 of 12
Which data source provides the most reliable floor area measurements for commercial property?
The VOA provides official floor area measurements used for business rates assessments. While not always perfectly accurate, they are measured by qualified valuers and provide the most consistent, official data source for commercial floor areas.
Question 8 of 12
What is the purpose of the "self-check" prompt?
The self-check prompt asks Claude to honestly assess its own confidence levels, flag potentially outdated information, and identify assumptions that need verification. This helps you focus your manual fact-checking on the areas where Claude is least confident.
Question 9 of 12
Why is "circular reasoning" a red flag in AI-generated research?
Circular reasoning occurs when AI-generated data validates other AI-generated conclusions, creating a closed loop where errors compound. Always verify AI claims against independent, primary sources rather than other AI outputs.
Question 10 of 12
Claude notes that "as new development increased, industrial rents rose by 25%." What should you consider?
Correlation does not imply causation. New development and rent increases might both be caused by a third factor (strong occupier demand). Your market knowledge is essential for interpreting the "why" behind statistical trends. AI identifies patterns; you provide the professional explanation.
Question 11 of 12
Why should you cross-reference findings from multiple data sources?
Cross-referencing increases confidence in your findings. If multiple independent sources report the same data, it is more likely to be accurate. If only one source reports something (especially an AI-generated finding), treat it with caution until verified.
Question 12 of 12
In the verification framework, what does "check freshness" mean?
Check freshness means verifying that data is current. Claude may cite older statistics from its training data. For market analysis, ensure transaction dates, vacancy rates, and other statistics reflect the current market, not data from a year ago.

Module 8 Complete

0/12

Module 9

Automation & Workflows

Build repeatable workflows, integrate APIs and services, use version control, and troubleshoot common issues.

Estimated time: 90–120 minutes

Module 9 Learning Objectives

  • Design and implement repeatable workflows for common property tasks
  • Understand how APIs and integrations extend Claude Code's capabilities
  • Use Git for version control and professional accountability
  • Troubleshoot common Claude Code issues and work around limitations
35

Repeatable Workflows

A workflow is a sequence of steps that you follow regularly for a specific type of task. By designing workflows around Claude Code, you can dramatically reduce the time and effort required for routine property work while maintaining consistency and quality.

Workflow Design Principles

Good Workflow Design

  • Consistent inputs — define exactly what data is needed at the start
  • Clear steps — each step should have a specific purpose and expected output
  • Review checkpoints — build in points where a human reviews before proceeding
  • Defined output — specify what the final deliverable looks like
  • Error handling — plan for what happens when data is missing or steps fail

Workflow Example: New Instruction Setup

When your firm receives a new client instruction, a standardised workflow ensures nothing is missed:

1
Property intelligence gathering

"Run /property-lookup for [address]. Save the results to [client folder]."

2
Client and tenant research

"Search for [client/tenant name] on Companies House. Check financial health."

3
Document setup

"Create a Google Doc called '[Client] - [Property] - Instruction Notes' with the property data we gathered."

4
Fee proposal draft

"Using the /proposal skill, draft a fee proposal for [service type]."

5
Client confirmation

"Draft an email to [client] confirming the instruction and enclosing the fee proposal."

6
Internal notification

"Post to your team's Slack channel: 'New instruction from [client] for [service] at [property].'"

Workflow Example: Monthly Rent Collection Review

Rent Collection Workflow
Run the monthly rent collection review: 1. Query Xero for all invoices due in the current month 2. Identify any that are overdue by more than 14 days 3. For each overdue invoice, draft a polite reminder email to the tenant 4. Create a summary table showing: tenant name, property, amount due, days overdue, action taken 5. Post a summary to your accounts channel Present the summary before sending any emails — I want to review first.

Building Your Own Workflows

Identify tasks you do repeatedly and design a workflow:

  1. Map the current process — write down every step you currently take
  2. Identify AI-automatable steps — which steps can Claude handle?
  3. Design review checkpoints — where should humans review before proceeding?
  4. Write the workflow prompt — create a reusable prompt that executes the workflow
  5. Test and refine — run the workflow with real data and improve it

Try This Now

Think about a task you do at least once a month. Map out the current process (even if informal). Then design a Claude Code workflow for it, including at least one human review checkpoint. Save the workflow prompt as a template.

Section Summary

Workflows transform ad-hoc AI use into systematic, repeatable processes. Design them with consistent inputs, clear steps, review checkpoints, and defined outputs. Start with your most frequent tasks and build a library of tested workflows.

36

APIs & Integrations

Claude Code's power comes partly from its ability to connect to external services through MCP servers and APIs. Understanding how these connections work helps you use them more effectively.

What is an API?

An API (Application Programming Interface) is a way for software systems to talk to each other. When Claude Code queries the VOA for a rateable value, it is making an API call to the VOA's system. Think of it like a waiter in a restaurant: you (Claude) give an order (the request), the waiter (the API) takes it to the kitchen (the external system), and brings back your food (the data).

How MCP Servers Work

MCP servers act as bridges between Claude Code and external services:

Layer What It Does Example
Claude Code Understands your request and decides which tool to use "Check outstanding invoices" → uses Xero MCP
MCP Server Translates Claude's request into the format the service expects Formats a Xero API call with correct authentication
External Service Processes the request and returns data Xero returns a list of outstanding invoices
MCP Server Translates the response back for Claude Formats invoice data for Claude to read
Claude Code Interprets the data and presents it to you Shows a formatted table of overdue invoices

Common Active Integrations

Service What It's Used For
Google Workspace Email (Gmail), documents (Docs), spreadsheets (Sheets), calendar, file storage (Drive)
Xero Accounting, invoicing, financial reporting
Slack Internal team communication and notifications
GitHub Code and document version control
Playwright Browser automation for web portals and data extraction
Supabase Database hosting for SaaS products
Memory Persistent context storage across sessions
Sentry Error monitoring for software products

Multi-Service Workflows

The most powerful workflows combine multiple services in a single operation:

Multi-Service Example
Run the quarterly client report workflow for ABC Property Fund: 1. Read the tenant schedule from Google Sheets ("ABC Fund - Tenant Schedule") 2. Check Xero for any outstanding service charge invoices for the portfolio 3. Use /voa to verify rateable values for all 8 units 4. Search the web for any relevant planning applications near the portfolio properties 5. Create a Google Doc report combining all findings 6. Draft an email to James Wright at ABC Fund with the report attached 7. Post a summary to #client-reports on Slack Present the draft report for my review before sending the email.

Section Summary

APIs and MCP servers connect Claude Code to external services. Understanding this architecture helps you design more effective workflows. Common integrations span accounting, communications, file management, and data sources — enabling comprehensive, multi-service workflows.

37

Scripts & Version Control

While you may not write code as part of your surveying role, understanding scripts and version control helps you work more effectively with Claude Code and maintain professional accountability.

Understanding Scripts

What is a Script?

A script is a file containing a sequence of commands that the computer executes automatically. Think of it like a recipe: instead of doing each step manually, you run the script and it follows the recipe for you. Claude Code can create and run scripts to automate repetitive tasks.

You do not need to write scripts yourself — Claude Code can create them for you. But understanding what they do helps you verify that Claude is doing the right thing:

Asking Claude to Automate a Task
I have a folder of 50 PDF documents at /Users/yourname/Documents/portfolio-leases/. I want to: 1. Read each PDF 2. Extract the tenant name and lease expiry date 3. Save the results as a CSV file called "lease-expiry-schedule.csv" Create a script to do this automatically, then run it. Show me the results.

Git Basics for Non-Developers

Git is the version control system that tracks all changes to files over time. Claude Code uses Git to manage projects. You should understand the basics:

Git Concept Plain English Property Analogy
Repository A project folder tracked by Git Like a client file on the shared drive
Commit A saved snapshot of all changes Like dating and initialling a report draft
Branch A separate copy to work on without affecting the main version Like creating a "working draft" folder while the final version stays safe
Push Upload changes to a shared location Like saving your file back to the shared drive
Pull Download the latest version from the shared location Like checking the shared drive for updated files
History The complete record of all changes Like a file note showing every version and who changed what

You do not need to run Git commands yourself. Claude Code handles version control automatically. But understanding the concepts helps you appreciate the audit trail that Git provides — which is valuable for professional accountability.

Section Summary

Scripts automate repetitive tasks — Claude Code can create and run them for you. Git provides version control and an audit trail of all changes. Both tools support professional efficiency and accountability.

38

Troubleshooting

Things do not always go smoothly with AI tools. This section covers the most common issues and how to resolve them.

Common Issues and Solutions

Issue Likely Cause Solution
Claude gives a generic, unhelpful response Prompt is too vague Add more context, specifics, and format requirements
Claude says it cannot access a file Wrong file path or permissions issue Check the file path is correct and the file exists
MCP tool returns an error Service connection issue Try again in a few minutes. If persistent, escalate to a senior colleague
Claude's response gets cut off Context window is full Use /checkpoint, then /compact or start a new session
Claude repeats information you already told it Context may be confused Start a fresh session with a clear, concise prompt
Calculations seem wrong AI arithmetic error or misunderstood inputs Provide data more clearly and ask Claude to show working
Claude applies Scottish or US law Context confusion Explicitly state "English and Welsh law only" in your prompt

When to Escalate

Most issues can be resolved by adjusting your prompt or restarting the session. Escalate to a senior colleague when:

  • An MCP server consistently fails to connect (may need authentication refresh)
  • Claude Code itself will not start or crashes
  • You discover a security concern (data appearing where it should not)
  • You need access to a new service or tool that is not currently configured

Maximising Performance

Tips for Getting the Best from Claude Code

  • Start fresh for new topics — a clean context avoids confusion from previous conversations
  • Be specific about outputs — "Create a table with these columns..." beats "Analyse this data"
  • Use checkpoints for long sessions — save progress before the context window fills up
  • Correct errors immediately — do not let wrong assumptions carry forward through the conversation
  • Use the right thinking level — ultrathink for complex analysis, standard for simple tasks
  • Break big tasks into steps — five focused prompts beat one enormous prompt

Try This Now

Deliberately cause a common issue: give Claude a vague prompt like "Tell me about the property" (with no context). See the generic response. Then rewrite the prompt with full context, specific requirements, and format instructions. Compare the two responses to understand the impact of prompt quality on output quality.

Module 9 Summary

This module covered workflow design, API integrations, version control basics, and troubleshooting. The key takeaway: systematic workflows with built-in review checkpoints produce the most reliable results. When things go wrong, most issues can be resolved by improving your prompt, restarting the session, or asking Claude to show its working.

Module 9 Knowledge Check

Test your understanding of automation, workflows, and troubleshooting. Remember: up to 3 attempts per question with hints.

Question 1 of 12
What is a critical component of any AI workflow in property practice?
Human review checkpoints are essential in any AI workflow. These are built-in points where a professional reviews the output before the workflow proceeds. This catches errors early and maintains professional accountability.
Question 2 of 12
In simple terms, what is an API?
An API (Application Programming Interface) is a way for software systems to talk to each other. When Claude Code queries the VOA for a rateable value, it makes an API call — like a waiter (API) taking your order to the kitchen (external service) and bringing back the result.
Question 3 of 12
What is the role of an MCP server in Claude Code's architecture?
An MCP server acts as a bridge between Claude Code and external services. It translates Claude's request into the format the service expects, sends it, receives the response, and translates it back for Claude. Each service (Xero, Google, Slack) has its own MCP server.
Question 4 of 12
In Git version control, what is a "commit"?
A Git commit is a saved snapshot of all changes at a specific point in time, like dating and initialling a report draft. The complete history of commits provides an audit trail showing every version and who changed what.
Question 5 of 12
What is the first step in building a Claude Code workflow for a task?
The first step is to map the current manual process. Write down every step you currently take. Then identify which steps can be automated, where review checkpoints should go, and design the workflow prompt. You cannot automate what you do not understand.
Question 6 of 12
Claude Code gives a generic, unhelpful response. What is the most likely cause?
A vague prompt is the most common cause of poor output. Adding context, specific details, and clear format requirements almost always improves the response. The quality of the output is directly proportional to the quality of the input.
Question 7 of 12
Claude Code's response gets cut off mid-sentence. What should you do?
When responses get cut off, the context window is likely full. Use /checkpoint to save your progress, then /compact to free up space, or start a new session. Use /resume to pick up where you left off. This is normal for long sessions with many file reads.
Question 8 of 12
What is a script in the context of Claude Code?
A script is a file containing a sequence of commands that the computer executes automatically. Claude Code can create and run scripts to automate repetitive tasks like processing multiple files, extracting data, or generating reports. You do not need to write them yourself.
Question 9 of 12
What makes multi-service workflows particularly powerful?
Multi-service workflows combine data from multiple sources (accounting, documents, databases, communications) into comprehensive outputs. A single workflow can gather data from Xero, Google Sheets, and the VOA, compile a report in Google Docs, draft an email, and notify Slack — all in one operation.
Question 10 of 12
What is a Git "branch"?
A Git branch is a separate copy of the project where you can make changes without affecting the main version. It is like creating a "working draft" folder while the final version stays safe. When changes are ready, the branch can be merged back into the main version.
Question 11 of 12
Which situation should you escalate rather than trying to fix yourself?
Consistent MCP server failures may need authentication refresh or technical configuration changes that require admin access. Vague responses, wrong calculations, and jurisdiction errors can all be fixed by improving your prompt or restarting the session.
Question 12 of 12
What is the quickest fix when Claude Code seems confused by previous conversation context?
Starting a fresh session clears all previous context, giving Claude a clean slate. Write a clear, concise prompt that includes all necessary context. This is often faster and more effective than trying to untangle a confused conversation thread.

Module 9 Complete

0/12

Module 10

AI Ethics, Security & Professional Practice

Data protection, RICS standards with AI, bias awareness, professional liability, and your AI-enhanced future in property practice.

Estimated time: 90–120 minutes

Module 10 Learning Objectives

  • Understand data protection obligations when using AI tools
  • Apply RICS professional standards to AI-assisted work
  • Recognise and mitigate AI bias in property analysis
  • Plan your ongoing development as an AI-enhanced property professional
39

Data Protection & AI

Using AI tools with client data brings data protection responsibilities under UK GDPR and the Data Protection Act 2018. As a property professional, you must understand these obligations.

UK GDPR and AI: The Basics

Key Principle: Data Minimisation

Only share the minimum personal data necessary for the task. If Claude does not need a client's home address or personal phone number to draft a market report, do not include it. Less data = less risk.

Personal Data Categories

Data Type Examples AI Use Guidance
Business contact data Work email, office phone, job title Generally safe — needed for drafting correspondence
Property data Addresses, rents, lease terms, valuations Generally safe — this is commercial data, not personal
Personal contact data Home address, personal mobile, personal email Use only when necessary — prefer business contacts
Financial personal data Personal bank details, salary, NI number Do not use with AI tools
Special category data Health data, religious beliefs, political opinions Never use with AI tools

AI Data Policy Best Practice

Rules for Using Client Data with Claude Code

  1. Commercial property data is generally fine — addresses, rents, lease terms, valuations
  2. Business contact details are acceptable — for drafting emails and letters
  3. Personal financial data must not be input — NI numbers, bank details, salary information
  4. Minimise personal data — only include what is needed for the specific task
  5. Client confidentiality applies — do not input data from one client's file when working for a different client
  6. Do not input third-party confidential data — without appropriate authority

Data Processing Agreement

Your firm should have a data processing arrangement with Anthropic (Claude's maker) that means:

  • Data sent to Claude is not used for AI training
  • Data is encrypted in transit and at rest
  • Data is not shared with third parties
  • Your firm can request data deletion if needed

This arrangement provides a level of protection, but it does not eliminate your responsibility to handle data carefully.

Common Pitfall: Accidental Data Mixing

When working on multiple client matters in the same Claude session, be careful not to mix client data. Start a new session when switching between clients, or clearly separate the work. Accidentally including Client A's data in Client B's analysis would be a data protection breach and a potential conflict of interest.

Section Summary

Data minimisation is the key principle: only share what is needed. Commercial property data is generally safe; personal financial data is not. Start new sessions when switching clients. Your firm's data processing agreement provides protection, but professional care is still essential.

40

RICS & AI in Practice

Building on the RICS principles from Module 5, this section examines how specific RICS standards apply to AI-assisted property work in practice.

Mandatory RICS Professional Standard (Effective 9 March 2026)

RICS published “Responsible use of artificial intelligence in surveying practice” (1st edition, September 2025). This is now mandatory for all RICS members and regulated firms.

Key mandatory requirements when using Claude Code or any AI tool:

  • Knowledge & Competence — understand AI limitations, failure modes, bias, and data risks
  • Client Notification — notify clients in writing where AI is used in service delivery, with opt-out options
  • Data Protection — safeguard confidential data; only use in AI systems with consent and after risk assessment
  • Professional Oversight — ensure sufficient human review of AI outputs; document the review in writing
  • Risk Management — maintain an AI risk register and governance policies, reviewed periodically
  • Record Keeping — document that AI was used, what review was performed, and the professional judgement applied

RICS Global Professional and Ethical Standards

Five key RICS principles and how they apply to AI use:

RICS Principle AI Implication
Act with integrity Be honest about AI use. Do not present AI output as original analysis without review
Provide a high standard of service AI should enhance service quality, not reduce it. Review all AI output thoroughly
Act in a way that promotes trust Clients must be able to trust that advice is professionally sound, whether AI-assisted or not
Treat others with respect AI should not be used to produce content that could be discriminatory or disrespectful
Take responsibility You are responsible for AI-generated output that you approve and send

AI in Valuations

Valuations are the most regulated area of surveying practice. AI use requires particular care:

Valuation Rules

  • AI can assist with data gathering, comparable analysis, and report drafting
  • The valuation opinion must be formed by a qualified valuer
  • The signing surveyor must be able to justify every figure in the report
  • AI-generated comparables must be independently verified before inclusion
  • Reliance on AI does not reduce the duty of care owed to the client
  • The Red Book (RICS Valuation Standards) requirements apply regardless of methodology

AI in Client Advice

When Claude Code helps produce client advice (rent review recommendations, lease advisory, investment analysis), remember:

1
The advice is yours, not the AI's

Once you review and approve, it carries your professional name and your firm's reputation

2
You must understand the reasoning

If a client questions your advice, "Claude said so" is not a professional answer. You must be able to explain the analysis

3
Limitations must be disclosed

If your analysis relies on limited data or unverified sources, say so in the report

Try This Now

Ask Claude Code to produce a brief rent review recommendation. Then ask yourself: could you explain every element of this recommendation to a client? Could you defend it at an independent expert determination? If not, what additional work would you need to do?

Section Summary

RICS standards apply fully to AI-assisted work. The five professional principles guide how you should use AI. For valuations and formal advice, the qualified professional must form the opinion, understand the reasoning, and take full responsibility for the output.

41

Bias, Liability & Risk

AI systems can reflect and amplify biases present in their training data. Understanding these risks helps you use AI responsibly in property practice.

Types of AI Bias in Property

Bias Type How It Appears Property Example
Geographic bias More data on some areas than others AI may have extensive data on London but limited knowledge of Sheffield submarkets
Recency bias Overweighting recent trends Assuming current rental growth will continue indefinitely
Selection bias Training data is not representative AI may know more about transactions that were publicly reported than off-market deals
Confirmation bias AI reinforces the framing of your prompt Asking "Why is this property undervalued?" assumes it IS undervalued
Cultural bias Assumptions based on dominant cultural norms Defaulting to US property conventions (triple net leases) instead of UK (FRI)

Mitigating Bias

Strategies for Reducing AI Bias

  • Frame questions neutrally — "Assess whether this property is over or undervalued" not "Explain why this is undervalued"
  • Provide local context — "Focus on the Sheffield S9 industrial submarket" prevents London-centric analysis
  • Ask for counter-arguments — "What are the arguments against our position?" reveals one-sided thinking
  • Check for balance — does the analysis consider both risks and opportunities?
  • Apply your local knowledge — you know Sheffield better than any AI model

Professional Liability

AI use does not change your firm's professional liability. Key points:

  • Professional indemnity insurance covers AI-assisted work, provided normal professional standards are followed
  • "AI error" is not a defence — you are responsible for output you approve and send
  • Duty of care is the same whether you used AI or not
  • Record keeping must document that AI was used and what human review was performed. This is a mandatory requirement under the RICS AI standard
  • If in doubt, escalate — discuss with a senior colleague before issuing advice you are uncertain about

The Responsibility Chain

The responsibility chain is clear: Claude produces a draftYou review and refineA senior professional approvesThe firm stands behind the output. AI assists at step 1; professional judgement governs steps 2–4.

Section Summary

AI bias exists in geographic, temporal, selection, confirmation, and cultural forms. Mitigate it by framing questions neutrally, providing local context, and asking for counter-arguments. Professional liability is unchanged by AI use — you remain responsible for every piece of work that carries your firm's name.

42

Your Future & Skills Portfolio

Completing this course marks the beginning, not the end, of your AI journey. The property professionals who thrive in the coming years will be those who combine strong traditional skills with confident AI use. You are now one of them.

What You Have Learned

Module Topic Key Skill Gained
1 AI Fundamentals Understanding how AI works and its limitations
2 Claude Code Basics Terminal use, tools, permissions, MCP servers
3 Practical Tasks Emails, research, reports, prompt patterns
4 Co-work & Teams Collaborative working, agent teams, custom skills
5 Best Practices Advanced prompting, RICS compliance, security
6 Advanced Prompting Chain-of-thought, few-shot, personas, prompt library
7 Document Processing Reading, extracting, generating, batch processing
8 Research & Analysis Market research, data integration, fact-checking
9 Automation Workflows, APIs, version control, troubleshooting
10 Ethics & Practice Data protection, RICS standards, bias, liability

Your Ongoing Development Plan

1
Week 1–2: Build confidence

Use Claude Code daily for at least one real task. Focus on email drafting, meeting prep, and simple research. Build the habit.

2
Month 1: Expand your toolkit

Try each of the available skills at least once. Start building your prompt library. Begin using co-work mode for complex tasks.

3
Month 2–3: Develop workflows

Design 3–5 personal workflows for your most common tasks. Test and refine them. Share effective prompts with colleagues.

4
Month 3+: Advanced applications

Start using batch processing, multi-service workflows, and agent teams for complex projects. Mentor others on AI use.

The AI-Enhanced Surveyor

Your value as a property professional is not diminished by AI — it is amplified. The market needs people who can:

  • Ask the right questions — AI answers questions; you decide which questions to ask
  • Apply professional judgement — AI processes data; you interpret what it means for the client
  • Build client relationships — AI drafts communications; you build trust and rapport
  • Inspect properties — AI analyses documents; you see the building in person
  • Take responsibility — AI assists; you sign your name and stand behind the advice

“The surveyors who will succeed are not those who resist AI, nor those who rely on it blindly, but those who use it as a tool to amplify their professional expertise.”

Resources for Continued Learning

  • Anthropic documentation — docs.anthropic.com for the latest Claude features
  • Claude Code release notes — new features are added regularly
  • RICS (2025) Responsible use of artificial intelligence in surveying practice, 1st edition — mandatory from 9 March 2026. Available at rics.org
  • Your team — ask colleagues for help and share what you learn
  • This course — come back to refresh specific skills. The quizzes can be reset and retaken

Final Exercise

Write a personal commitment statement for how you will use AI in your practice. Include:

  • Three tasks you will start using Claude Code for this week
  • One workflow you will build in the first month
  • Your approach to verification and quality control
  • How you will balance AI efficiency with professional development

Share this with a senior colleague during your next catch-up.

Module 10 Summary & Course Conclusion

You have completed the Claude Code Training Course. Over 10 modules, you have learned AI fundamentals, mastered Claude Code's tools and integrations, developed advanced prompting skills, understood document processing and research methodology, and grounded everything in RICS professional standards and ethical practice. The key message throughout: AI is a powerful tool that amplifies your professional capabilities. Use it confidently, verify everything, and never stop learning.

Module 10 Knowledge Check

Final quiz — test your understanding of AI ethics, data protection, and professional practice. Remember: up to 3 attempts per question with hints.

Question 1 of 12
What is the key UK GDPR principle that applies to using client data with Claude Code?
Data minimisation means only sharing the minimum personal data necessary for the specific task. If Claude does not need a client's home address to draft a market report, do not include it. Less data means less risk.
Question 2 of 12
Which type of data must NEVER be input into Claude Code?
Personal financial identifiers like National Insurance numbers, bank account details, and credit card numbers must never be input into AI tools. Property data, business contacts, and lease terms are generally acceptable for professional use.
Question 3 of 12
How does confirmation bias appear in AI-assisted property analysis?
Confirmation bias occurs when your prompt assumes a conclusion. "Why is this property undervalued?" tells Claude to find evidence for undervaluation. A neutral prompt like "Assess whether this property is fairly valued, overvalued, or undervalued" produces more balanced analysis.
Question 4 of 12
Which RICS principle is most relevant when Claude Code produces an error that reaches a client?
Take responsibility. You are responsible for output that you approve and send. "AI error" is not a professional defence. The duty of care is the same whether you used AI or not. This is why thorough review of all AI output is non-negotiable.
Question 5 of 12
What does a data processing arrangement with Anthropic mean in practice?
The arrangement means data is not used for training, is encrypted, and is not shared with third parties. However, this does not eliminate your responsibility to handle data carefully. Data minimisation, client confidentiality, and professional care still apply.
Question 6 of 12
In RICS-compliant valuations, what role can AI play?
AI can assist with data gathering, comparable analysis, and report drafting, but the valuation opinion must be formed by a qualified valuer. The signing surveyor must be able to justify every figure. Red Book requirements apply regardless of the tools used.
Question 7 of 12
How can you mitigate geographic bias when asking Claude about the Sheffield property market?
Specify the local submarket and provide local data. AI may default to London-centric analysis or national averages. By saying "Focus on the Sheffield S9 industrial submarket" and providing local comparables, you steer the analysis toward your actual market.
Question 8 of 12
What should you do when switching from Client A's work to Client B's work in Claude Code?
Start a new session when switching clients. This prevents accidental data mixing (a data protection issue) and potential conflicts of interest. Claude Code sessions carry forward all context, so Client A's data would still be visible when working on Client B's matter.
Question 9 of 12
In a firm's responsibility chain for AI-assisted work, what is your role as the reviewer?
As the reviewer, you verify facts, apply professional judgement, and ensure quality before work goes for senior approval. This is where your professional skills are most valuable — catching errors, improving analysis, and ensuring the output meets RICS standards.
Question 10 of 12
Why should you ask Claude Code for counter-arguments to your analysis?
Asking for counter-arguments reveals one-sided thinking and weaknesses in your position. This is valuable for rent reviews (anticipating the other side's arguments), investment analysis (identifying risks), and any professional advice where balance and thoroughness are important.
Question 11 of 12
According to the development plan, what should you focus on in your first two weeks after completing this course?
The first two weeks should focus on building confidence through daily use. Start with familiar tasks (email drafting, meeting prep, simple research) and build the habit of incorporating Claude Code into your daily workflow. Complexity comes later.
Question 12 of 12
What is the single most important principle from this entire course?
The core principle: AI is a powerful tool that amplifies your professional capabilities. Use it confidently, verify everything, and never stop learning. AI does not replace professional judgement — it enhances it. Your value comes from the combination of AI efficiency and human expertise.

Module 10 Complete

0/12

Final Assessment

Course Progress

0 of 120 questions

Your Results by Module

Complete all quizzes to see your results here. Each module has 12 questions.

Module Topic Questions
1AI Fundamentals12
2Claude Code Basics12
3Practical Property Tasks12
4Co-work & Agent Teams12
5Best Practices12
6Advanced Prompting12
7Document Processing12
8Research & Analysis12
9Automation & Workflows12
10AI Ethics & Professional Practice12

This will clear all quiz progress. This action cannot be undone.

Key Takeaways

The 10 Essential Principles

  1. AI is a tool, not a colleague — every output must be reviewed by a qualified human
  2. Specificity drives quality — detailed prompts produce useful output; vague prompts produce vague results
  3. Verify everything — check facts, arithmetic, dates, and names against primary sources
  4. RICS standards apply fully — AI does not change your professional obligations
  5. Data minimisation matters — only share what is needed for the specific task
  6. Use the right tool for the job — simple tasks need simple prompts; complex tasks need structured approaches
  7. Build workflows, not one-off prompts — systematic processes produce consistent results
  8. Combine AI efficiency with human expertise — your professional judgement is irreplaceable
  9. Learn from errors — when AI gets it wrong, understand why and adjust your approach
  10. Never stop learning — AI tools evolve rapidly; stay curious and keep experimenting

References & Further Reading

References & Further Reading

  • RICS (2025) Responsible use of artificial intelligence in surveying practice, 1st edition. Available at: rics.org
  • Anthropic — Claude documentation: docs.anthropic.com
  • Anthropic — Claude Code documentation: docs.anthropic.com/claude-code
  • UK General Data Protection Regulation (UK GDPR) and Data Protection Act 2018
  • RICS Valuation — Global Standards (the “Red Book”)
  • Town and Country Planning (Use Classes) (Amendment) (England) Regulations 2020 — Class E reclassification
  • ICO guidance on AI and data protection

AI Disclosure — In accordance with the RICS professional standard on responsible use of AI, we confirm that AI tools were used in the creation of this course content. All material has been reviewed, verified, and approved by qualified RICS professionals at Hillway. Last reviewed: March 2026.

© 2026 Hillway Holdings Limited. All rights reserved.

Built with Claude Code — the tool you just learned to use.