AI Frameworks · deanpeters

product-manager-prompts

A curated collection of 96 copy-paste AI prompts for product managers, organized by workflow (execution, workshops, market research, storytelling). Designed to work with ChatGPT, Claude, Gemini, and other AI assistants without requiring code or custom setup.

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Source: GitHub — github.com/deanpeters/product-manager-prompts

975

GitHub stars

201

Forks

Python

Primary language

MIT

License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

Field	Value
Repository	deanpeters/product-manager-prompts
Owner	deanpeters
Primary language	Python
License	MIT — OSI-approved
Stars	975
Forks	201
Open issues	2
Latest release	Unknown
Last updated	2026-07-03
Source	https://github.com/deanpeters/product-manager-prompts

What product-manager-prompts is

MIT-licensed prompt repository written in Python, containing templated prompts for product management tasks including PRD generation, user story writing, competitive analysis, and market sizing. Includes Jinja2-templated prompts for loop-based and agent-based execution patterns.

Quickstart

Get the product-manager-prompts source

Clone the repository and explore it locally.

terminalbash

1git clone https://github.com/deanpeters/product-manager-prompts.git2cd product-manager-prompts3# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

Quick execution on known problems

Copy-paste prompts when you have context ready (e.g., discovery notes → PRD). No setup required; paste into any AI assistant and iterate.

Guided workshops via AI facilitation

Use workshop prompts to structure discovery sessions (PRD workshops, competitive battle cards, problem framing) with checkpoints and stakeholder input.

Autonomous market research workflows

Deploy market intelligence prompts (competitive scanning, TAM/SAM/SOM analysis, voice-of-customer mining) in agent loops with evidence contracts and citation requirements.

Implementation considerations

Every prompt includes hidden HTML comments (instructor's notes). Click 'Raw' in GitHub to see them; the AI will ignore them, but they explain design rationale.
Prompts in `/loops/` use Jinja2 notation for control flow; these are designed for agent/automation frameworks, not direct chat use.
Market intelligence prompts require an AI with web search or retrieval capabilities; standard ChatGPT (free tier) cannot execute them without manual research.
Facilitation prompts are designed for one-pass interaction; expect to run them iteratively in real product work, not as single-shot solutions.
No database or state management is provided. Checkpoint outputs (e.g., PRD sections, research findings) must be managed outside the prompt system.

When to avoid it — and what to weigh

You need a production SaaS tool — This is a prompt repository, not software. You copy prompts; you do not deploy this as an application. Expect to maintain custom integrations if building agents.
Your team cannot read and adapt templates — Every prompt requires human interpretation, customization, and context injection. This is not a black-box solution; it is a starting library.
You need version control or audit trails — Prompts are static text; using them in chat leaves no built-in audit trail or version history unless you manage it separately.
Your AI model choice is restricted or non-standard — Prompts are optimized for ChatGPT, Claude, Gemini, and Copilot. Niche or older models may not handle the template structures as intended.

License & commercial use

MIT License. Permits commercial use, modification, and distribution with attribution. No warranty; no liability constraint. Clear permissive OSI license; commercial use is permitted.

MIT License explicitly permits commercial use. You may use these prompts in a paid product or service without restriction, provided you retain the MIT notice. No licensing fee or proprietary claim. Recommended: review your AI vendor's terms (ChatGPT, Claude, etc.) to ensure their ToS permits your downstream use.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

Signal	Assessment
Maintenance	Active
Documentation	Strong
License clarity	Clear
Deployment complexity	Low
DEV.co fit	Good
Assessment confidence	High

Security considerations

Prompts do not access systems, databases, or credentials directly. Primary considerations: (1) Prompts instruct AI to search the web and cite sources—validate search results for accuracy before acting on them. (2) Market intelligence and competitive analysis prompts may encourage collection of competitor data; ensure compliance with terms of service and data privacy laws (GDPR, CCPA, etc.). (3) No built-in controls for PII or sensitive data in your prompt inputs; users are responsible for redacting before pasting into public AI assistants. (4) Agent-based deployments should implement access controls and audit logging external to this repo.

Alternatives to consider

Prompt Engineering frameworks (LangChain, LlamaIndex, Semantic Kernel)

If you need state management, retrieval chains, and agent orchestration, these frameworks provide the runtime layer that this prompt repository does not.

Commercial prompt marketplaces (PromptBase, Hugging Face, OpenAI Marketplace)

For pre-built, versioned, supported prompts with licensing and monetization support. Trade-off: less control, higher cost, curated quality.

Product management tools with AI features (Productboard, Aha, Miro with AI plugins)

Integrated suites that embed AI prompting into a full PM workflow (roadmaps, feedback loops, analytics). Trade-off: less flexibility, vendor lock-in, higher cost.

Software development agency

Build on product-manager-prompts with DEV.co software developers

Clone the repo, pick your workflow (execution, workshops, research, or storytelling), and copy the prompt into your AI assistant. Start with a real problem you're solving today.

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product-manager-prompts FAQ

Can I use these prompts in a paid product or service?

Yes. MIT License permits commercial use. Attribution to the original repository is required; your AI vendor's terms of service (e.g., ChatGPT Enterprise) must also permit your use.

Do I need to code to use these prompts?

Not for chat-based use—copy-paste into ChatGPT, Claude, or Gemini. For agent/loop use, you need orchestration framework integration (no code generation is provided in this repo).

What if my AI assistant doesn't follow the prompt structure?

Prompts are optimized for ChatGPT, Claude, Gemini, and Copilot. Older or niche models may require rewording. Test before deploying to production.

How do I keep prompts in sync across my team?

Not provided in this repo. Recommend: wiki, Slack macros, or a dedicated prompt management tool. GitHub provides versioning, but users must manage distribution.

Software developers & web developers for hire

Need help beyond evaluating product-manager-prompts? DEV.co is a software development agency offering software development services and web development for teams of every size. Our software developers and web developers build custom software, web applications, APIs, and ai frameworks integrations — and maintain them long-term.

Ready to prompt better?

Clone the repo, pick your workflow (execution, workshops, research, or storytelling), and copy the prompt into your AI assistant. Start with a real problem you're solving today.

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