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Vibe Coding Hub for Product Builders

The most complete collection of battle-tested AI-assisted development resources — for Product Managers, Designers, and Developers who want to ship real products with AI.

What's inside: 75 ready-to-use Cursor & Claude Code skills · 123 Jupyter notebooks · 31 research papers (PDFs in papers/) · 14 industry reports · 21 n8n workflow templates (JSON) · 14 system prompts from leading agents · 36 OpenClaw derivatives catalogued.

Whether you're a PM who wants to prototype faster, a Designer who wants to understand the code your AI is generating, or a Developer looking for the sharpest rules to ship with — this repo is built to be copied, forked, and used the same day.

Quick start

Pick your path and start in under 5 minutes:

For Product Managers

1. Read cursor-and-claude/product-management/no-vibe-coding.md — Spec-Driven Development
2. Use cursor-and-claude/product-management/create-prd.md to turn an idea into a PRD with AI
3. Generate tasks with cursor-and-claude/product-management/generate-tasks.md
4. Ship with cursor-and-claude/skills/writing-plans/ + cursor-and-claude/skills/executing-plans/

For Designers

1. Drop cursor-and-claude/skills/frontend-design/ into your Claude Code project
2. Follow cursor-and-claude/skills/web-design-guidelines/ (Vercel) for distinctive UI
3. Read cursor-and-claude/best-practices/accessibility.md before shipping

For Developers

1. Install the core skills: brainstorming, test-driven-development, systematic-debugging
2. Grab the slash commands: cursor-and-claude/commands/ (code-review, final-review, git-commit, security-audit)
3. Pick your stack rules from cursor-and-claude/coding/ (Python, TypeScript, FastAPI, Next.js, …)
4. Lock down security with cursor-and-claude/security/anthropic-security-audit.md

For Learners

1. Start with the notebooks in research/nn-zero-to-hero/ (Karpathy's Zero to Hero)
2. Read learning/README.md to pick a textbook
3. Follow research/understanding-deep-learning/ chapter-by-chapter

Project structure

awesome-vibe-coding/
├── openclaw/                 # OpenClaw ecosystem — see openclaw/README.md
│   ├── README.md
│   └── skills/               # Skills index — openclaw/skills/README.md, categories/
├── cursor-and-claude/                   # Cursor & Claude Code — see cursor-and-claude/README.md
│   ├── skills/               # cursor-and-claude/skills/README.md
│   ├── commands/             # cursor-and-claude/commands/README.md
│   ├── best-practices/
│   ├── coding/
│   ├── product-management/   # cursor-and-claude/product-management/README.md
│   ├── security/
│   └── references/           # cursor-and-claude/references/README.md
├── prompt-engineering/         # prompt-engineering/README.md, prompts/
├── learning/                   # learning/README.md — books and textbooks
├── reports/                    # reports/README.md — industry reports (McKinsey, OpenAI, …)
├── n8n-templates/              # Workflow templates
├── papers/                     # papers/README.md — PDFs and paper notes
├── research/                   # research/README.md — notebooks & experiments
└── CONTRIBUTING.md

Quick links

What's inside

Cursor & Claude (cursor-and-claude/)

Prompts library (prompt-engineering/)

Battle-tested prompts for Cursor, Claude, Grok, Kimi, n8n, Lovable, v0, and more — see prompt-engineering/README.md and prompt-engineering/prompts/.

Learning (learning/)

Three freely-available textbooks that ground the notebooks and skills in this repo: Understanding Deep Learning (Prince), Mathematics for Computer Science (MIT 6.042J), and Algorithms for Decision Making (Stanford). See learning/README.md for what each is best for.

Reports (reports/)

14 industry reports from McKinsey, Deloitte, KPMG, OpenAI, Anthropic, Air Street Capital, and others — useful for pitch decks, business cases, and agent metrics. See reports/README.md for a themed index.

OpenClaw (openclaw/)

Derivative agents and a skills index (VoltAgent, official OpenClaw archive). Details: openclaw/README.md, openclaw/skills/README.md.

n8n templates (n8n-templates/)

Workflow templates (AI assistants, messaging, sheets, scraping, etc.).

Research & experiments (research/)

Educational notebooks and autonomous research setups. Full catalog and source links: research/README.md.

Other items (e.g. DeepSeek OCR) are documented in research/README.md when present.

Papers (papers/)

PDFs and reading notes — papers/README.md.

About

This repository is maintained by Adrianno, a Staff Product Manager at Pipefy, diving into the magic behind LLMs.

You can find more about me on GitHub and LinkedIn. Feel free to connect with me, I'm always open to discussing AI, product management and building cool things together!

Who this is for

• Product Managers who want to prototype ideas without waiting for engineering
• Product Designers who want to understand the code their AI generates
• Product Builders who want to go from idea to product faster
• Developers looking for optimized Cursor and Claude rules
• Anyone curious about how AI-assisted development actually works.

What makes this different

This isn't just another collection of AI tools. We focus on:

• Understanding the fundamentals — You'll learn why things work, not just how to use them
• Real-world applications — Every example is something you'd actually build
• Product thinking — We connect technical concepts to business outcomes
• Reproducible results — Everything is tested and documented

Inspired by

AI & development

• awesome-copilot — Custom agents, instructions, skills, and plugins for GitHub Copilot
• awesome-llm-apps — LLM applications with AI Agents
• awesome-cursorrules — Configuration files that enhance Cursor AI editor experience
• awesome-deepseek-integration — Integrate the DeepSeek API into popular softwares
• awesome-datascience — Data science resources

Programming languages

• awesome-python — Python resources
• awesome-typescript — TypeScript resources

Architecture & design patterns

• awesome-design-patterns — Software and architecture related design patterns
• awesome-system-design-resources — Learn System Design concepts and prepare for interviews
• awesome-scalability — The Patterns of Scalable, Reliable, and Performant Large-Scale Systems

Design & product

• Awesome-Design-Tools — The best design tools and plugins for everything
• awesome-for-beginners — A list of awesome beginners-friendly projects
• awesome-cto — Resources for Chief Technology Officers, with emphasis on startups

Contributing

1. Fork the repo
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (see CONTRIBUTING.md for Conventional Commits)
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

Full guidelines: CONTRIBUTING.md.

License

This project is licensed under the MIT License — see LICENSE.

Ready to level up? Start with cursor-and-claude/README.md, openclaw/README.md, or prompt-engineering/README.md. The best way to learn is by doing.