If You Build With AI, You Need This File. And The System That Generates It.
AI Rules File Generator: A Beginner-Friendly System for Replit, Cursor, Gemini & Claude Builders.
While their post focused on writing, it hits builders just as hard. Without the systems I built, I’d collapse under my own workload.
My standard for this Substack: quality or nothing.
Never AI slop. Never anything I haven’t researched deeply. Nothing I haven’t crawled through myself first.My standard for my builds: ethical, solid, anti-cookie-cutter, and maintainable.
My problem: Time.
Without my obsessively refined workflows, built at the kitchen table while someone asks where their shoes are, I’d have burned out ages ago.
So I build reusable systems as I go. Stubbornly. For writing, for building, for anything that matters.
And one of them sits at the foundation of every vibecoding project I ship: the flow that generates the rules for my AI agents.
Today, I’m sharing that one with you, tuned specifically for beginners who are just starting with coding agents.
Hey, I’m Karo 🤗
AI product manager, builder of StackShelf.app, and chronic optimizer of workflows. If you’re new here - welcome! Here’s what you might have missed:
Vibecoding Tips: The Ultimate Collection
Claude Skills Are Taking the AI Community by Storm
Perplexity Comet: 11 Use Cases from “Nice” to “Wow!”
The Problem With Every AI Rules File I’ve Seen
AI Rules Files are instruction manuals for your coding agent.
They’re just markdown files that sit in your repo and tell the AI what conventions to follow, what technologies to use, what patterns to avoid.
You’ll see them under different names: replit.md, agents.md, cursor.md, claude.md, constitution.md - but they all serve one purpose: to give your coding agent a playbook.
Without them, agents improvise. With them, they follow your rules.
Since starting with AI-assisted coding, I’ve analyzed a small mountain of repos. Studied how skilled engineers structure their AI files. Read all the guides. Built my own. Buried most of them.
Here’s what I found:
Most respectable AI Rules Files are technically brilliant.
Almost all of them are missing something critical: beginner-friendly product thinking.
Why This Matters Now More Than Before
2025 transformed the industry’s attitude toward AI autonomy: we opened the year warning against autonomous agents, and ended it embracing them because the productivity upside was too big to deny.
The entire tools ecosystem is racing in the same direction:
Replit’s Agent 3, announced two months ago gives builders real, usable autonomy. Duolingo, Zillow, and Coinbase implement it at scale.
(Side note: Replit’s progress this year has been wild. I wouldn’t be surprised if it becomes the viral hit of 2026).Devin is a real autonomous AI software engineer that can plan, code, debug, and deploy in sandboxed environments. Goldman Sachs began deploying hundreds of Devin instances in mid-2025.
Google’s new Antigravity IDE empowers agents to plan, code, and validate software autonomously. Figma, Shopify and Thomson Reuters are among the early adopters.
Whatever tool you’re using, chances are it’s already nudging you toward autonomy, whether you’re ready for it or not.
Why Clear Instructions and Rules Are Critical
Prompt engineering + proper specs + human expertise = AI agent performance
When you use this formula, AI performance jumps dramatically:
68% fewer hallucinations (because the agent isn't guessing)
87% higher compliance (because it knows what not to do)
Why I Add Product Thinking to the Rules For AI
Many vibecoders don’t know the formal conventions or terminology yet, and that’s perfectly fine.
None of us were born knowing what a migration is, let alone an idempotent one. We all start somewhere.
That’s exactly why I tuned this system the way I did: it doesn’t just spit out a file, it walks you through the thinking.
⚡️ The Agent Rules Generator Prompt ⚡️
Before running the prompt, make sure you’ve read this👇.
How And Why This System Works
Best practices: It preserves the best of the existing ‘rules for AI’ best practices, with a few additions tailored for beginner-friendly product thinking.
Environment-aware: it generates the right file for your actual setup -
replit.md,cursor.mdc, whatever you’re using.Teaching built in: every rule explains why it exists in simple language. You learn conventions in context, not from a textbook.
Ripple-effect awareness: it shows the downstream consequences beginners without product management experience usually miss:
If you add a trial period ➜ your billing logic + onboarding flow change
If you add notifications ➜ you’ll need scheduling + retries + preferences
If you add user-generated content ➜ you’ll need moderation flows + abuse checks
It also forces a clean Build Now vs. Build Later split so you don’t ship products that look like my Substack drafts folder: 37 features started, none finished.
For Agents And For Humans: You’ll notice the prompt is written in plain language, not JSON.
That’s intentional - it outputs a critical project file so I want to keep it bilingual, readable by both humans and agents.
How To Use The Agent Rules Builder Prompt
This prompt is a full system on its own, so I’m giving it a dedicated page.
You can grab it here.
Use the prompt in your ChatGPT/Claude/Gemini.
Be prepared to answer questions from the agent - it takes 10 minutes now, saves you hours afterwards.
What To Do With The Generated Rules File
How you set up and manage your rules file depends on which tool you use:
The Habit That Keeps Your AI Rules File From Rotting
Agent files aren’t static, they grow with your project.
This workflow gives you a rock-solid starting framework,
but the real power comes from how you evolve it.
As your projects get deeper, you’ll find yourself adding new instructions, commands, and shortcuts so you don’t have to retype the same prompts over and over.
If you’re using things like a deep-error-fixing prompt, debugging rituals, or design files, bake them right into the file.
None of this needs to be perfect on day one, the file will mature alongside your projects.
💡 Pro Tip
Whenever your agent breaks something, don’t just fix it - ask it this:
Based on our session and the fixes we made, what are the key things that should be added to my replit.md to prevent these issues in the future.Here’s a real response from Replit to that exact question, from yesterday’s session:
That gives me a clear to‑do list for updating my project’s replit.md. And, more importantly, I walk away smarter than before.
Prompt Versioning
The version you see today is v9, and I’ll be updating it in real-time on the prompt page so you always have access to the latest iteration.
Key Takeways
Rules files are how you “raise” well‑behaved AI agents: they encode conventions, guardrails, and product context instead of letting agents improvise.
Most public rules files miss beginner‑friendly product thinking, so agents ship changes that ignore flows like billing, onboarding, and moderation.
The Agent Rules Generator is a single prompt that outputs platform‑specific rules files (Replit, Cursor, Gemini, Lovable, Antigravity) with explanations in plain language.
You use it as a living system: generate an initial rules file, then update it every time an agent breaks something so each failure hardens the rules.
As autonomous coding agents go mainstream, builders who invest in strong rules, specs, and governance prompts will get the upside without letting agents quietly wreck their product.
Conclusion
Everything I’ve managed to build this year -every workflow, post, and bug fix squeezed between “Moooom!” and a Teams meeting only happened because I had systems to hold the weight.
I hope this one helps you too!
Additional Resources
👉 The Self-Improving Prompt System That Gets Smarter With Every Use
👉 Vibecoding vs Spec-driven: A Definitive Guide for Product Builders
👉 Is Your Agent Looping? This Will Help
From The Community
- become a Substack Bestseller! 🎉
We’re trying something new! You likely follow some of these writers already and trust them for both their prompts and their habit of digging past the obvious:
, , ‚ , , , , , , ,On Tuesday, each of them shared one of their favourite prompts, and you can now find them all in attitudevault.dev.
They’re all free, and a few have never been shared anywhere before: from quick two-liners to the deep context-engineering systems.
One tiny favour: if any of these prompts make your life easier, let the author know, it means a lot 🤗If you want to share your own prompts, join us for the next Skills Swap Tuesday
in the community chat.
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Great resource! I know from personal experience how important it is to do the product thinking up front and give coding agents well-documented standards…and what happens when you don’t! 😆
I did this for my most recent project and have experienced so much less chaos…
same approach I started. a command file that clearly guide the llm, only upload the custom input for each new work. so value your post, I will adjust and improve my strategy with it. thanks again @Karo