AGENTS.md: Guardrails for AI Coding Agents

The most useful way to think about an AI coding agent is as an extremely fast contributor who has never read your codebase and forgets everything between sessions. It can write a lot of correct-looking code quickly, but it does not know your conventions, your folder structure, or the rules you would tell a new hire on day one.

AGENTS.md is where you write those rules down once so the agent reads them every time. It is the difference between an agent that fits your project and one that fights it.

A good guardrail file is specific and enforceable, not a vague style guide:

• Where things live: folder structure and what belongs in each layer
• Naming and component conventions the project actually uses
• Which tools and patterns are required, and which are banned
• How to validate, handle errors, and structure data access
• The package manager, the framework version, and other easy-to-get-wrong defaults

The goal is that an agent reading the file produces code that looks like the rest of the codebase, not a different project bolted on.

Without guardrails, AI-assisted building tends to optimize for visible output over operational correctness, which is the root cause behind why vibe-coded SaaS apps break at launch. The agent happily produces another screen while quietly skipping the validation, isolation, and error handling that a real product needs.

Guardrails do not slow the agent down. They point its speed at the right target, which is the whole argument behind moving from vibe code to production.

An AGENTS.md only works if the conventions it describes actually exist in the code. A guardrail file that points at a messy, inconsistent codebase has nothing to enforce. That is why agent guardrails and a clean structure go together, and why a strong starter treats both as features rather than afterthoughts. The comparison in SaaS boilerplate vs vibe coding gets at the same point from the founder's side.

You can see how this is set up in practice in the agent instructions recipe and the AI feature docs.

aSaaSin ships with AI-agent guardrails built in, backed by conventions that actually hold across the codebase. When you point an agent at the project, it has a clear map of where things go and how they should be written, so generated code stays consistent instead of drifting.

If you build with AI tools, see pricing or explore the docs to see the guardrails in place.