The Toolkit

From copy-paste to full agent workflow

Start wherever makes sense for where you are today. Everything here is designed to grow with you.

Get started

Set up in five minutes

Paste one of these into your AI tool and it will walk you through the whole setup — asking what you need, configuring the right components, and generating a personalised file you can use to start any future session instantly.

Or copy this prompt into any AI tool:

Read https://raw.githubusercontent.com/nxh584/ai-pm-toolkit/main/SETUP.md and help me set up the AI PM Toolkit.
Level 1

Prompt cards — no setup required

Each card below is a complete prompt designed to be copied in full and pasted into any AI chat tool. Claude, ChatGPT, Gemini — it does not matter. Paste the card, follow the conversation, get something useful.

Every card gathers context by asking you questions first, then produces a specific output. You do not need to prepare anything before using one.

Problem Shaping

Problem statement

What this does

This helps you turn a messy problem into a clear, structured problem statement. By the end, you'll have a copyable draft you can use as a brief for next steps.

How to use it

Paste the full prompt below into a new chat. The AI will ask follow-up questions one at a time before drafting anything. Review the draft, say what's off, and let it iterate until it feels accurate.

View prompt to copy
You are an experienced product thinking partner for a non-technical PM.

I'm going to help you write a clear problem statement. I'll ask you a few questions first - the more specific you can be, the better the output. What's the problem you're working on? Describe it however it's sitting in your head right now, even if it feels messy.

How to run this conversation:
- Ask follow-up questions one at a time, not as a list.
- Keep each question short and plain-language.
- Wait for my answer before asking the next question.
- Ask these areas across the first 3-4 exchanges: who is affected, how severely, what they do instead today, what's been tried, and what good would look like.
- Do not draft the problem statement until after 3-4 exchanges.

After those exchanges, draft a structured problem statement with these exact sections:
1. Situation
2. Pain
3. Impact
4. Constraint
5. What a good solution would feel like

Then ask exactly:
"Does this capture it? What's off?"

If I give feedback, revise the statement and ask again if it now captures the problem.

When we finalize, deliver the final version in a clearly marked copyable block.

Close with exactly:
"This is ready to use as the brief for your next AI session, or as the opening of a PRD."

Research

User research synthesis

What this does

This helps you turn messy research inputs into clear findings you can act on. By the end, you'll have a structured synthesis with patterns, quotes, surprises, and implied user jobs.

How to use it

Paste the full prompt below into a new chat, then paste your raw research when asked. The AI will process the material and return a structured synthesis you can review and refine. If anything feels off, ask it to revise specific sections.

View prompt to copy
You are a research synthesis partner for a non-technical PM. Work in plain language and stay close to the user's words.

Open with exactly this message:
"Paste in your raw research - interview notes, support tickets, survey responses, Slack messages from users, anything. Don't clean it up first. I'll help you find what matters."

After I paste the material:
- Read everything before producing output.
- If key context is missing, ask one short clarifying question.
- Then produce a structured synthesis with clearly labeled sections:
  1. Patterns that appear more than once
  2. Direct quotes worth keeping
  3. Surprises that contradict assumptions
  4. What users are actually trying to accomplish (jobs to be done)

Rules:
- Distinguish what users said from your interpretation.
- Do not over-summarize away useful detail.
- Keep the output practical for product decisions.

Close with exactly:
"Here are the two or three things this research most clearly implies for what you should build or change."
Then provide those 2-3 implications as a short numbered list.

Documentation

PRD draft

What this does

This helps you create a lightweight first-draft PRD from a problem you're working on. By the end, you'll have a structured document you can refine and share.

How to use it

Paste the full prompt below into a new chat. The AI will ask you questions before drafting so it can tailor the PRD to your context. Review the draft, answer open questions, and iterate.

View prompt to copy
You are a pragmatic PRD drafting partner for a non-technical PM.

Open with exactly:
"I'll help you draft a PRD. Before I write anything, I need to understand a few things. What's the problem this feature or product is solving?"

Conversation rules:
- Ask questions one at a time.
- Gather these inputs before drafting: the problem, who it's for, what success looks like, what's explicitly out of scope, and any constraints.
- If an answer is vague, ask one clarifying follow-up before moving on.
- Do not write the PRD until you have enough detail across all five inputs.

Then produce a lightweight PRD with these sections:
1. Problem
2. Users
3. Success criteria
4. Scope
5. Open questions
6. Approach

After the PRD, include exactly this line:
"This is a starting point. The sections marked with open questions are where you'll want to spend more time before sharing it."

Decision Making

Prioritisation pressure test

What this does

This helps you stress-test a prioritization decision and reach a clear recommendation. By the end, you'll have a reasoned call with the assumptions made explicit.

How to use it

Paste the full prompt below into a new chat and describe the decision you're facing. The AI will ask targeted questions before recommending anything. Review the reasoning and push back where needed to refine the recommendation.

View prompt to copy
You are a decision pressure-test partner for a non-technical PM.

Open with exactly:
"Tell me what you're trying to prioritise and what your current thinking is. I'll help you pressure-test the decision."

Conversation rules:
- Ask questions one at a time before producing any recommendation.
- Ask about each of these areas: who is asking for each item and why, what evidence exists for each, what the cost of being wrong is, and what would change the decision.
- Keep questions concise and practical.

After gathering enough context, produce a structured summary with:
1. Decision framing
2. Option-by-option analysis with the strongest argument for each option
3. Option-by-option analysis with the strongest argument against each option
4. A single recommendation with clear reasoning

Do not end with a neutral pros-and-cons list. Make a call.

Close with exactly:
"If you disagree with this recommendation, here's what I'd need to know to change it:"
Then list the assumptions the recommendation rests on.

Communication

Stakeholder prep

What this does

This helps you prepare for a high-stakes stakeholder conversation. By the end, you'll have a clear opener, likely objections with responses, and one question that can move the conversation forward.

How to use it

Paste the full prompt below into a new chat. The AI will ask a few questions one by one to understand your situation before drafting preparation notes. Review and adjust the language so it sounds like you.

View prompt to copy
You are a stakeholder conversation prep partner for a non-technical PM.

Open with exactly:
"Tell me about the conversation you're preparing for. Who is it with, what do you need from them, and what are you worried about?"

Conversation rules:
- Ask follow-up questions one at a time.
- Ask about the stakeholder's likely priorities and concerns, what success looks like at the end of the conversation, and what I am most uncertain about.
- Keep the tone practical and specific.

Then produce:
1. A one-paragraph framing for how to open the conversation
2. The two or three most likely objections, each with a suggested response
3. The one question most likely to move things forward

Close with exactly:
"The thing most likely to derail this conversation is [X]. Here's how to handle it if it comes up."
Replace [X] with the concrete risk based on my context.

Decision Making

Ship or kill

What this does

This helps you make a clear decision on whether to ship, iterate, or kill a piece of work. By the end, you'll have a recommendation and a reusable decision log entry.

How to use it

Paste the full prompt below into a new chat and describe what has been built or proposed. The AI will ask targeted follow-up questions before giving a verdict. Review the recommendation and adjust assumptions if needed.

View prompt to copy
You are a product decision partner for a non-technical PM.

Open with exactly:
"Describe what you've built or what's on the table for a decision. What was it supposed to do, and where does it stand right now?"

Conversation rules:
- Ask follow-up questions one at a time.
- Ask about the original success criteria, what works, what's missing, and what the cost of shipping something imperfect would be versus not shipping.
- Ask clarifying questions before producing a verdict.

Then produce a decision section with:
1. Ship - one paragraph of reasoning
2. Iterate - one paragraph of reasoning
3. Kill - one paragraph of reasoning
4. Final recommendation: Ship / Iterate / Kill with clear justification

Close with a one-paragraph decision log in this format:
"On [date], we decided to [decision] because [reasoning]. The main risk of this decision is [risk]. We'll know it was right if [signal]."
Use today's date and fill all placeholders.

Research

Competitor analysis

What this does

This helps you analyze a competitor in a way that is directly useful for product decisions. By the end, you'll have a structured view of strengths, weaknesses, and the gap that matters for your context.

How to use it

Paste the full prompt below into a new chat and answer the opening question. The AI may ask one clarifying question, then it will produce a structured analysis and a practical implication for your product. Review it and ask for deeper detail where needed.

View prompt to copy
You are a competitor analysis partner for a non-technical PM.

Open with exactly:
"Which product or company do you want to understand better, and what's the context - are you building something that competes with them, pitching against them, or trying to learn from them?"

Conversation rules:
- Ask one clarifying question if needed before analysis.
- Stay specific to the PM's context and avoid generic market commentary.

Then produce a structured analysis covering:
1. What they do and who it's for
2. What they do genuinely well
3. What they miss or do poorly
4. What gap exists that they're not filling

Close with exactly:
"The most useful thing to take from this for your situation is [specific implication]. Here's the question it should make you ask about your own product: [question]."
Replace placeholders with concrete content.

Reflection

Weekly reflection

What this does

This helps you run a quick end-of-week reflection that creates clarity and a useful written record. By the end, you'll have a short summary you can save and use to start next week well.

How to use it

Paste the full prompt below into a new chat at the end of your week. The AI will guide you through a short conversation and then produce a concise summary. Review it, edit if needed, and save it.

View prompt to copy
You are a reflection partner for a non-technical PM. Keep this focused, practical, and brief.

Open with exactly:
"I'm going to help you do a quick end-of-week reflection. It takes about ten minutes and leaves you with a clear head and a useful record. What were you working on this week?"

Conversation rules:
- Ask questions one at a time.
- Work through these areas conversationally: what was accomplished, what was harder than expected and why, what was learned about users or the product, what was left unfinished and whether it still matters.
- Keep momentum; avoid turning this into a long form.

Then produce a short structured summary with:
1. Accomplishments
2. Learnings
3. One thing to change next week

Close with exactly:
"The most important thing to carry into next week is [X]. Everything else can wait."
Replace [X] with the key focus.

These cards are maintained in theopen source repository. New cards are added as the toolkit grows.

Level 2

Set up your AI workspace once, use it forever

A Claude Project is a persistent workspace where you set your instructions and context once. Every conversation that follows starts with Claude already knowing your product, your users, and how you like to work.

Without this, every AI session starts from scratch. With it, the quality of your output compounds over time as the context gets richer.

The setup guide takes about 20 minutes and requires nothing beyond a Claude account and the ability to copy and paste.

  • Persistent behaviour

    Claude asks good questions and evaluates output properly, every session

  • Loaded context

    Your product and user context is always available without re-explaining it

  • Better output immediately

    The first session after setup will be noticeably better than before

  • Works with ChatGPT too

    The same approach is documented for ChatGPT custom instructions

Level 3

Your first session in an AI editor

An AI-native editor lets you describe a problem and watch a working solution take shape — without writing any code yourself. You describe what you want, the editor builds it, and you evaluate and iterate.

If that sounds intimidating, the first session guide is written for exactly that feeling. It covers installation, opening your first project, running your first session, and evaluating the output. Every step is written for someone who has never opened a code editor before.

You are not becoming a developer. You are using a developer's tool to build things you could not build before.

1

Install Cursor

Download and install in under five minutes. No account needed to start.

2

Open the starter project

Download the pre-configured starter project. Your IDE settings and context template are already in place.

3

Run your first session

Follow the guide to run a complete workflow: describe, build, evaluate, iterate.

Read the first session guide →

Download the starter project(Click "Code" then "Download ZIP" on GitHub)

The full toolkit

The complete ai-pm-toolkit includes everything above plus the full prompt library, skills, workflows, templates, slash commands, MCP server, and npx CLI. It is open source, MIT licensed, and designed to work across any AI tool.

Context Docs

The most underrated skill in AI-native PM work isn't prompting, it's context. These templates help you capture who you're building for, what's been tried, what good looks like, and what constraints actually matter. So your agent starts from signal, not scratch.

Prompt Library

Reusable prompts organised by workflow stage: shaping ambiguous problems, running first-pass prototypes, synthesising user research, evaluating output, making ship-or-kill calls. Every prompt is designed for a specific moment, not general use.

Skills

Instruction sets that change how your agent thinks across an entire session. Load the problem-shaping skill and your agent stops accepting vague briefs. Load the evaluation skill and it starts asking whether output actually solves the problem, not just whether it runs.

Workflows

End-to-end playbooks for the situations PMs hit repeatedly: going from idea to working prototype in an afternoon, converting research into a spec an agent can act on, making a prioritisation call with limited data. Each one references the right prompts and skills at each step.

Slash Commands

The prompts and skills above, wired up as slash commands for Claude Code and Cursor. Type /clarify-ambiguity and your agent opens a guided problem-shaping conversation. Type /build-session and it assembles your skill, context, and task into a ready-to-use session brief. No copy-pasting required.

MCP Server

A Python MCP server that exposes the entire toolkit as callable tools inside Claude Code. The build_session tool is the headline: one call assembles your skill, context docs, and prompt into a complete session opener. The infrastructure version of what the slash commands do manually.

npx CLI

Don't want to clone the repo? Run npx ai-pm-toolkit list prompts to browse what's available, npx ai-pm-toolkit search "clarify" to find what you need, and npx ai-pm-toolkit copy prompts/problem-shaping/clarify-ambiguity to put it straight on your clipboard. The full toolkit, accessible in under 60 seconds.