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Why ait

AI coding agents are useful, but their work is easy to lose track of.

ait exists for engineers who already use Claude Code, Codex, Aider, Gemini CLI, Cursor CLI, or similar tools and want every run to leave a local, reviewable record in the repo.

The short version

Without ait, an agent run is usually just a chat transcript plus whatever changed in your working tree.

With ait, an agent run becomes an attempt:

  • what you asked
  • what the agent changed
  • what another agent found during review
  • what decision should be remembered later
  • whether you explicitly applied it

The attempt lives under .ait/ in the repo. It is local. No telemetry. No SaaS.

Problem 1: the next agent starts from zero

Yesterday Claude investigated a bug and found a constraint. Today Codex opens the same repo and repeats the investigation because the useful context lived in a closed chat.

With ait, the next wrapped agent can receive a compact handoff from prior attempts, accepted facts, notes, and live repo memory files such as CLAUDE.md, AGENTS.md, .claude/memory.md, .codex/memory.md, and .cursor/rules.

Try the demo:

ait demo

See also: Pain-point demos.

Problem 2: the implementer reviews its own work

An agent finishes and says the tests pass. That is useful, but it is not the same as an independent review. The same model, in the same context, often misses the same blind spots.

With ait, you can ask a different agent to review the attempt before apply:

ait review attempt latest-reviewable --mode adversarial --review-adapter claude-code
ait review finding list --severity high

This is not proof of correctness. It is a separate review pass with recorded findings.

Problem 3: failed runs leave debris

An agent is interrupted, times out, or makes a risky edit. Without isolation, you may be left with a confusing working tree.

With ait, the wrapped run lands in an isolated workspace. Your root checkout should not change until you decide to apply:

ait apply latest

If the result needs inspection:

ait recover latest
ait resume latest

Problem 4: useful decisions disappear

You decided the retry budget should be three. Three weeks later, a new agent proposes five because it never saw the earlier reasoning.

With ait, you can search prior attempts and repo memory:

ait memory recall "retry budget"

You still decide which recalled context matters. ait gives you the record; it does not outsource judgment.

What ait is not

ait is intentionally narrow.

It is not:

  • an IDE plugin
  • an autocomplete engine
  • a hosted dashboard
  • a cross-machine sync service
  • a replacement for Claude Code, Codex, Aider, Cursor, Cline, or Git
  • proof that an AI reviewer will find all defects

When it is worth using

Use ait when the cost of losing agent context is higher than the cost of one extra workflow layer.

It is most useful when you:

  • use more than one agent CLI
  • want explicit apply/recover instead of direct working-tree mutation
  • want a separate reviewer agent for risky changes
  • need old prompts, diffs, findings, and decisions to be searchable
  • prefer local-first metadata over SaaS provenance tools

Ready to try it: Getting started.