AI agents expose architecture debt quickly. They search by names, follow imports, copy nearby patterns, and use tests as feedback. If those signals disagree, the agent can make a locally sensible change that violates the system.

The same repository is difficult for a new engineer. Designing for agents is mostly designing for inspectability.

Make change boundaries visible

A module should have a narrow reason to change and an explicit public surface. Internal details can move without forcing callers to know.

Package by capability when that matches the domain. Keep the invoice policy, persistence adapter, API handler, and tests near enough that a search for “invoice” reveals the path through the system.

Avoid utility folders that become shared dependencies for unrelated behavior. A small helper used everywhere can create a larger blast radius than a substantial feature module.

You can test the boundary with one question: which files should change when this behavior changes? If the answer is “it depends on who notices,” the architecture is hiding coupling.

Turn boundaries into executable checks

Directory names communicate intent, but they do not enforce it. Add checks for the constraints that matter:

  • unit tests for local behavior;
  • contract tests for module or service interfaces;
  • integration tests at database and network boundaries;
  • architecture tests or lint rules for forbidden dependencies;
  • type checks for data passed between layers.

An agent can run these checks after each slice. The repository tells it when a change crossed a boundary instead of waiting for a reviewer to reconstruct the rule.

Keep commands predictable. A focused test should be easy to run without knowing the entire CI system.

Prefer local reasoning

Code is easier to change when the relevant behavior fits in a small reading set. A handler that relies on distant hooks, runtime patching, and implicit global state requires a model to hold more assumptions at once.

Pass dependencies explicitly. Keep side effects behind named interfaces. Use data structures whose invariants are visible in types and constructors.

Local reasoning does not require tiny files. Splitting one coherent operation across twelve wrappers can make navigation worse. The goal is a small conceptual surface, not a line-count target.

Make the correct pattern easy to find

Agents often copy the nearest example. Give canonical examples clear names and remove obsolete alternatives.

Document the commands, package boundaries, generated files, and areas that require human approval. Put package-specific rules inside that package instead of one enormous root document.

If a constraint matters during review, try to encode it in a test or tool. Prose is still useful for the reason behind the constraint and for decisions that cannot be checked mechanically.

Remove ambiguous success states

A repository is agent-friendly when “done” has evidence. The build passes, focused tests cover the new behavior, generated files are current, and the diff has no unrelated edits.

Avoid scripts that swallow failures or print success before asynchronous work ends. Stable exit codes and useful error messages shorten the correction loop for people and tools.

Audit one change path

Pick a routine change, such as adding a field to an API response. Follow it from request to persistence and back.

Count the modules involved. Find the tests that prove compatibility. Note every rule you had to remember but could not discover. Those notes are your architecture backlog.

Good structure does not make an agent trustworthy. It makes the agent’s work easier to inspect, constrain, and reject when it is wrong. That is also what a maintainable codebase should do for people.