Why sharing a file
isn’t sharing context.

Our working premise: a useful AI handoff should preserve the relevant decisions, reasons and sources—not simply transfer the latest file.

The output and the context

Imagine a teammate spends an afternoon developing a proposal with an AI assistant. They compare approaches, reject an option, agree on a constraint and produce a document. Another teammate opens that document in a different assistant to continue the work.

The document may contain the chosen proposal. It may not contain why the other option was rejected, which assumptions are still uncertain, or what the team promised to check next. Those details can determine whether the next step is useful.

The useful handoff is not always the entire conversation. It is the context needed to continue.

A different handoff question

“Which file should I send?” is a practical question. We also want to ask: “What does the next person need to understand?”

For a project decision, that can mean the current choice, the reason behind it, its source, and the remaining work. If the choice changes later, the recipient should be able to distinguish the updated direction from the historical one.

This is the experience we are designing toward with Lashley’s Context Handoff. It builds on personal and shared memory, with a deliberately scoped transfer of useful context.

A boundary, not a copy

Personal context is not automatically team context. Sharing what a colleague needs for a project should not require sharing unrelated conversations, preferences or private history.

A handoff therefore needs a boundary: what is included, who can access it, where it came from, and which context is still personal. More information is not automatically a better handoff.

Nor does shared context make different AI models identical. They may still reason differently or have different capabilities. The aim is to reduce avoidable reconstruction of the relevant background—not to promise identical answers.

What we need to evaluate

The value of this approach needs to be tested in real workflows. Useful measures include the time needed to resume a task, the number of clarifications required, mistakes caused by superseded decisions, and whether sharing respects the intended access boundary.

This note describes a design direction, not benchmark findings. We will publish measured results with their evaluation method and limitations when that work is ready to examine.