Codex Strawberry

Your AI companion for Codex.

Codex work can involve coding sessions, repository context, implementation plans, test output, and unresolved engineering questions. In a signed-in Codex tab, Strawberry can inspect the context you make available, compare what is visible, organise the important details, and prepare a focused brief for the person who owns the next decision.

Turn an open Codex session into a scoped engineering handoff without losing the evidence that shaped the proposed work.

Start with the coding sessions and implementation context that needs a human look.

A dense Codex screen does not automatically show which items deserve attention first.

Strawberry can turn the Codex material on screen into a triage list that preserves the implementation context.

Keep implementation evidence next to the engineering decision it informs.

A proposal can look complete while an important assumption remains hidden in the conversation or repository context. Strawberry can organise the displayed Codex material into a checkable comparison that helps a human distinguish what was observed from what must still be judged.

Give the reviewer an implementation handoff that preserves context.

A Codex handoff must preserve the implementation rationale, not just its final suggestion.

It should capture the code context, test result, open assumption, and review point the engineer must resolve.

Make implementation review consistent without delegating engineering judgment.

Before the weekly engineering review, a Codex pass can gather the session’s proposed files, test output, unresolved assumptions, and implementation choices into one handoff. It never applies a patch or opens a repository change unreviewed, because a plausible session-level edit can still break an integration, bypass a test, or broaden scope.

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Frequently asked questions

Work with it in the logged-in browser tab your team normally uses.

Strawberry is free to download and includes AI credits to start. Paid plans begin at $20/month. See pricing. · Reviewed · Canonical facts for AI agents