How it actually works
- You describe the outcome — 'migrate the auth module to the new token format, keep the API stable, cover it with tests.'
- The agent plans — a step list appears before any code changes: read, plan, edit, test, report. You can edit the plan or veto it.
- Per-step model routing — architecture reasoning goes to Claude Opus or GPT-5; mechanical edits and test scaffolding go to DeepSeek; the final self-review goes to a different model than the one that wrote the code, because models catch each other's mistakes better than their own.
- Sandboxed execution — edits land in an isolated clone with dependencies pre-installed. Tests run there. Your working tree is untouched until you accept.
- Receipt — every step logs model, tokens, credits and wall-clock time. Total cost of the task is printed at the end.
Plan: 7 steps · est. 34 creditsawaiting approval
Architecture pass — Claude Opus✓ 8.2 cr
Mechanical edits ×23 — DeepSeek✓ 1.4 cr
Test generation — GPT-5✓ 3.1 cr
Adversarial self-review — Claude✓ 6.0 cr
Diff ready · 4 files · tests greenreview →
A real Code Agent run — every step metered
What it's for — and what it isn't
Strong: migrations, refactors, dependency upgrades, test backfills, bug fixes with reproduction cases, API surface changes across many files. Not for: ambiguous product decisions, UI taste, anything where 'what should this even do' is the hard question. Give it work with a definition of done.
Guardrails: spend caps per task, branch allowlists, and a hard rule that the agent never force-pushes. Pro plans run up to 3 concurrent agents; Ultra runs 10.
Delegate your next refactor
Pro plan includes the Code Agent. Trial it free for 3 days on a real repo.
No card, no email, no signup · 3 days free · Windows 10/11