Handoff Reader

The problem

AI coding assistants are getting better at writing code, but they are still surprisingly bad at inheriting project context.

When starting a new coding session, developers often have to manually explain:

  • what has already been implemented
  • what is still in progress
  • which files matter
  • what should not be changed
  • whether previous summaries are still accurate

As projects grow, chat history becomes an unreliable source of truth.

Our solution

Handoff Reader creates reliable, evidence-grounded handoffs between AI coding sessions.

Instead of relying on chat history, it collects repository evidence such as:

  • Git status
  • recent commits
  • project checkpoints
  • repository metadata

It then generates a structured handoff that can be validated against the repository before being used by another AI session.

What makes it different

The handoff is designed to be:

  • evidence-grounded
  • provider-neutral
  • portable
  • freshness validated

Instead of being tied to one AI model, Handoff Reader focuses on transferring repository state between AI coding sessions.

Built during OpenAI Build Week

For Build Week we focused on making handoffs trustworthy.

Recent work includes:

  • immutable repository snapshots
  • freshness validation
  • guide validation
  • fail-closed repository collection
  • consistency checking
  • extensive automated tests

What's next

We plan to continue improving AI-to-AI developer workflows by making context transfer more reliable across coding sessions, model tiers, and development tools.

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