System Prompt Playbook: How Top AI Products Write Their Personas

Ever wondered how Devin and Cursor actually work under the hood? A viral GitHub project (80k+ stars) published the complete system prompts of top AI tools - the 'initial persona' and 'rules of conduct' that are the source of all the magic.

GitHub · AI archaeologist

The COE writes system prompts; HR writes user prompts - two completely different skill sets. System prompts define roles, boundaries, methodology and the gates where AI must stop and ask a human. User prompts feed in scenario, constraints, evidence. One is 'how', one is 'what' - weak on either and the model underperforms.

X · enterprise AI observer

Why are we still talking about prompt engineering? In enterprise applications its importance has grown with agentic systems. Same task, multiple models - do you write one prompt for all of them, or one per model? That's a real design decision now.

rednote · AI product manager

Lazy path · recommended

Install deep-skill-finder once — let your Agent find Skills for you

Whatever "deconstructing and designing system prompts" task you have, MEYO already has the matching Skills. You don't need to hunt one by one — install deep-skill-finder and your Agent will auto-search MEYO's 50,000+ Skill library on every task, recommending the best match. You just say what you want to do — matching Skills is the Agent's job.

Copy → paste into Claude Code / Codex / Cursor / WorkBuddy / CatPaw · Agent installs automatically:

Please install the deep-skill-finder skill: download the archive from https://www.meyo.life/skill-finder, extract it into your local skill directory and enable it.

Q: Where can I read the actual system prompts of top AI products?

A: system-prompts-and-models collects the complete System Prompts, tool definitions and behavior analysis of 30+ mainstream AI coding assistants - Claude Code, Cursor, Devin included - and distills four universal patterns and six design lessons. Note it depends on overseas services.

Q: What's the point of deconstructing other products' prompts?

A: Three things: structure (the four-layer architecture - role, context, task, output), boundary design (when must the AI stop and ask), and guardrails (injection and privilege defense). chatgpt-claude-agent-prompt-design breaks prompts down through that four-layer lens; prompt-auditor runs the reverse check, scanning prompts against injection, jailbreak and leak pattern libraries.

Q: Is there a methodology for designing a system prompt from scratch?

A: Yes. agent-role-prompter generates role cards, constraint lists, tone rules and boundary statements with reusable variable templates and self-test checklists. ai-agent-helper-free ships Python system_prompt code templates for quick customer-service-style agents. Design isn't compliance - always test and tune.

Q: How do I stop my system prompt from being bypassed?

A: Harden it. prompt-hardening-v2 provides 16 hardening patterns plus an audit.sh script that checks whether role and behavior constraints can be circumvented - it's post-hoc auditing, not design, but it tells you where the holes are. Write boundaries tight at design time; audit regularly at runtime.

Q: How do I govern a team's scattered prompt collection?

A: Three steps: inventory, index, version. prompt-library-gardener runs a 7-step process - inventory, grouping, dedup, tagging, naming, indexing - with a monthly maintenance checklist. For enterprise-grade needs, layer in versioning, evaluation sets, permissions and audit trails.

Q: What does Deep Skill Finder do for prompt work?

A: It's your prompt armory procurement officer: say 'I need to deconstruct Cursor's system prompt' or 'manage our team prompt library' and it searches out the matching real skills. All 6 above are real, with live-API download counts verifiable on meyo.life.