When AI Assistants Work on the Same Task

You work through a problem with ChatGPT. You decide on an approach, rule out a few alternatives, and work out what to do next. Later, you open Cursor to implement it.

The work continues. The conversation doesn't come with it.

You can paste a summary, link the chat, or explain the decisions again. Each helps, but someone still has to decide what matters and keep that account current as the work changes.

At Taskaid, we use our own backlog this way. An idea starts in a conversation, becomes a task, gets investigated in another assistant, and comes back with findings or a narrower next step. The task is where we leave enough context for the next conversation to start from where the work actually stands.

We wrote earlier about tasks becoming handoff objects. Building and using that idea has made a few requirements clearer.

The task outlives the conversation. What it remembers, and how assistants change it, determines whether that continuity is useful.

What a handoff note keeps

A name such as "Fix the login redirect" is enough to remind you of something. For an assistant joining the work later, it leaves several questions open. Which redirect? What went wrong? Has anyone investigated it? Is there an agreed approach?

Here is an illustrative note for that task:

Outcome: After signing in, someone who opened a task link should return to that task.

Finding: The redirect to login currently drops the destination. Signing in then sends the person to Home.

Decision: Preserve the destination through sign-in. Start with the existing callback mechanism.

Current state: Investigated; implementation still open.

Next step: Trace where the destination is lost, make the change, and check both a direct task link and an ordinary sign-in.

The next assistant has a place to begin. It can verify the finding against the code, work within the decision, and update the note with what it learns. The person returning next week has the same benefit.

This is a writing pattern you can use in any shared task or document. Keep the outcome, the decisions that still matter, the current state, and the next action close together. Link to supporting material where it helps. After a substantial conversation, ask the assistant to leave that context with the work.

The assistant should write the first version of the handoff and keep it useful as it goes. If you have to reconstruct every conversation yourself, continuity becomes another task on your list.

As work progresses, the note needs to distinguish what was considered from what was chosen, and what was planned from what was completed. "We could use an event" and "the event is live" lead the next assistant to very different actions. A finding can become outdated; keeping its date or the version it was checked against gives the next reader something to verify.

A stable address

The handoff also needs a stable address. "Continue the login task" can refer to several things. In Taskaid, a reference such as TASKAID-45 names one task within your account, even after its title, date or list changes.

You can ask a connected assistant:

Read TASKAID-45 and help me continue from its current state.

A task's Open menu starts that conversation in your assistant. The prompt carries the reference, and the assistant reads the task through its Taskaid connection. That gives it the saved state at the time it reads, including changes made since the previous conversation.

You can also copy the task as a prompt for an assistant without a connection. That copy is a snapshot you will need to bring back up to date.

Editing without erasing

Reading the current note is only half of sharing the work. An assistant also has to leave other people's writing intact when it adds its own.

Suppose you wrote a constraint about keeping the change small. One assistant adds its investigation. A second discovers a better approach. A useful update changes the relevant passage and preserves the constraint. Rewriting the whole note creates opportunities to lose qualifications or turn an unresolved question into a confident decision.

Taskaid lets assistants edit or append a specific part of a note. An exact replacement that no longer matches is refused, so the assistant can read the note again and reconsider its edit. This gives us a way to preserve untouched text; choosing the right passage to change still requires care.

Sharing a task also means sharing an account of progress. An assistant that drafted a fix should record in the task that the fix is drafted. A task marked complete should reflect the outcome the person asked for. The next assistant relies on those words to decide what remains to be done.

Knowing what changed

The way people combine assistants brought another requirement into focus. A pattern we see is one assistant making changes to tasks while another checks on a schedule for progress, reading the same tasks far more often than they change.

The two assistants work through shared records, and the checking assistant keeps reading them to discover whether anything has changed.

That behaviour is useful feedback for us: a shared workspace needs to help assistants discover changes as well as read the current state.

On 30 September, we tested a first step in production. ChatGPT watched a Taskaid list for new tasks. We created a task through Claude, and ChatGPT responded with a summary. The event carried enough information to identify the task; its note stayed in Taskaid, where the assistant could read it when needed.

That test ran in ChatGPT Work mode. The feature currently covers task creation. Notifications for edits, and a durable record that supports replay after a missed delivery, are work ahead. Setups like the scheduled check exposed the need; the task-created test demonstrates one part of the connection.

As more assistants contribute, the workspace also needs to answer who changed what. Taskaid currently records where a task was created. That fact stays with it, but it cannot explain later edits. Knowing which assistant created a task tells you little about a later change made through another. We are designing a change log to make that distinction visible.

Moving between assistants

These details shape how comfortably someone can move between assistants. Can the next conversation find the right task? Does the note explain what is true now? Can an assistant contribute without losing the person's thinking? Can another assistant discover that contribution?

Our aim is for someone to choose an assistant for the work in front of them and keep their tasks available across those choices. A conversation may produce a useful decision today, an implementation tomorrow, and a review next week. Leaving the outcome of each stage with the task gives the next person or assistant somewhere useful to start.