Agent experience — how well the environment is set up for an agent to do good work in a codebase. The agent-facing counterpart to DX. When the same agent performs well in one repo and badly in another — same model, same harness — the difference is usually AX. The instinct is to blame the model or rewrite the prompt; the fix is more often in the repo.
Good AX has three main dimensions:
| Dimension | What good AX looks like |
|---|---|
| Automated checks | Fast, deterministic automated checks — types, tests, lints — that the agent can self-correct from without a human |
| Architecture | A codebase the agent can navigate without reading everything: predictable structure, a lot of behaviour behind small interfaces, names that say what things do |
| Free context | AGENTS.md, skills, and tools kept lean, so most of the context window is available for the task and the agent stays in the smart zone instead of drowning |
AX and DX overlap — good checks and clean architecture help both audiences — but they diverge. Humans tolerate tribal knowledge, slow CI, and "ask Sarah about the billing module"; agents can't. Agents don't benefit from IDE tooltips or pretty dashboards; they need failures as text in a tool result. A codebase can have good DX and poor AX.
Avoid: treating AX as a synonym for DX — the audiences need different investments.
Usage:
"The agent writes great code in the API repo and garbage in the frontend."
"The API repo has strict types and a fast test suite; the frontend has neither and forty always-loaded skills. That's an AX gap, not a model problem."