Cross-AI Collaboration System

The question

When several AI tools share one task, how do you stop context, ownership and acceptance criteria from disappearing between handoffs?

Approach

1. Give each role an explicit scope and output contract.
2. Keep evidence and unresolved items in the handoff instead of relying on chat memory.
3. Require the receiving role to verify the previous output independently.
4. Revise the protocol from observed failures.

Result

The handoff method completed two content-production rounds and was revised using the failures found during real use.

Evidence

Version history, handoff records and review outputs.

The failure happens between the tools

When one AI plans and another executes, the hard part is not opening two tools. The receiving agent must know the task, boundaries and acceptance criteria. This project uses versioned, file-based handoffs so each result can be reviewed later.

Design responsibility before connectivity

The protocol limits context, fixes output locations, treats asking for missing information as a valid stop condition and prevents the planning role from declaring its own work complete.

A task crosses systems through a bounded handoff

The planning role reduces the background into a bounded, testable assignment. The execution role receives only the required material and returns a versioned output for independent review.

1. Define the task
2. Write the handoff
3. Isolate execution
4. Review against acceptance criteria

Two production rounds changed the protocol

The first round produced 12 images for six articles and exposed one repeatable style failure. A later four-article round completed on the first pass after the handoff rules were revised.

Evidence behind the case

Three Chinese articles explain role separation, context isolation and cross-session handoffs. English editions remain pending editorial and SEO review.