Writing

How to scaffold a project for agentic AI driven development

Jun 2026 · 8 min

Agentic development lives or dies on how legible your repository is. An agent that can't find the seams of your codebase will thrash: reading whole files, guessing at conventions, and quietly reintroducing bugs you already fixed. Most of the work of "being good at AI development" is really the work of making a project easy to reason about — for the agent and for you.

Start with a map

The single highest-leverage file is the one that tells the agent how the project is organised. Where do routes live? Where do shared utilities go? What's generated and must never be hand-edited? Write it down once, explicitly.

Keep files single-purpose

One file, one job. When a file does three things, an agent editing the first thing has to load the context for all three — and it will happily "improve" the other two.

  • Split large modules along their natural seams.
  • Name files after what they contain, not how they're used.
  • Co-locate tests with the code they exercise.

Encode the guardrails

Conventions that live only in your head are invisible to an agent. Put them in the repo:

# Never do
- Commit secrets or .env files
- Use `as any` type casting
- Modify generated files directly

An agent treats these as hard constraints. A human treats them as good advice. Both of you benefit.

The payoff

A well-scaffolded project turns the agent from an eager intern into a competent collaborator. You stop babysitting edits and start reviewing outcomes.