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Wagglet

AI work handoff

Can one person prepare an exact AI task for someone else to run?

An AI work handoff is the transfer of a prepared task and its working context from one person to another so the recipient can run it in their own AI agent session, supervise the work, and return evidence for review.

Worked example

One prepared task, two instruction fields, one runner

Suppose a team wants a teammate to add CSV export to an invoice screen without changing calculations or permissions. The work becomes transferable only when the handoff removes the need to guess.
LLM instructions
Name the outcome, repository and branch, in-scope files, unchanged authorization boundary, required CSV cases, test commands, evidence, and stop conditions.
Human instructions
Tell the runner to use synthetic invoices, open the result in a text editor and spreadsheet, inspect the active filter, stop on any tax-rounding change, and keep real customer data out of the run.
Recorded outcome and delivery evidence
Return the branch, files changed, tests and results, requested screenshots or checks, warnings, and any limitation that remains.

The workflow

Prepare, claim, supervise, deliver, review

Each stage has exactly one human owner. The agent can perform work, but it does not inherit ownership or authority.
  1. 01

    Prepare

    Owner: task author. Write the outcome, LLM instructions, Human instructions, scope, constraints, permitted context, evidence, and stop conditions before offering the task to the team.

  2. 02

    Claim

    Owner: runner. Choose work you may access, can supervise, and are qualified to judge. Claiming assigns the work; it does not transfer the author's provider relationship.

  3. 03

    Supervise

    Owner: runner. Copy the bounded task into a fresh agent session, supply only authorized access, observe the real environment, perform the Human instructions, and stop when authority or evidence is missing.

  4. 04

    Deliver

    Owner: runner. Use the separate delivery prompt in the same session to record the outcome, branch, changes, checks, warnings, and useful failure information. Delivery reports what happened; it does not approve it.

  5. 05

    Review

    Owner: authorized reviewer. Compare the evidence with the task, then accept it, send it back to the runner, or reopen it. Delivery, acceptance, merge, and deployment are separate facts.

Read the exact runner procedure in the Task Handoff guide, see why the two readers get different instructions in the Dual Prompt field note, or return to the Wagglet home page.

Limits

Only the task context moves

The task context moves; provider identity, accounts, keys, subscriptions, credits, and token balances stay with their owner.
  • Not multi-agent orchestration. The category coordinates a human handoff; it does not assign autonomous agents to one another.
  • Not an agent runtime. Each runner starts and supervises work in their own Claude Code, Codex, Cursor, or other agent environment.
  • Not autonomous delegation. No agent is the accountable assignee. A person claims the work, supervises the run, and answers for the result; the agent carries the brief.
  • Not AI subscription sharing or a quota workaround. No account, provider identity, key, subscription, credit, or token balance is shared or transferred.

Who it is not for

A solo developer across sequential sessions needs a file, not a handoff system

If you are a solo developer working alone across sequential agent sessions, you do not need an AI work handoff. A file in the repository is the right answer.

Record the current state, decisions, commands, checks, and next step in that file. The extra claim, ownership, delivery, and independent-review lifecycle is useful only when work is crossing between people.

Related questions

Choose the question you need answered next

The category splits into four practical decisions for a team adopting AI task handoff.
Team capacityShared AI execution capacityHow can a qualified teammate use available Claude Code or Codex capacity without moving accounts or credentials?Answer the capacity question →Cross-tool contextClaude Code, Codex, and Cursor handoffWhat context must move when a prepared task passes among Claude Code, Codex, and Cursor?See what has to move →Neutral comparisonWagglet and LinearWhere does a general task tracker stop, and where does an AI work handoff begin?Compare the workflows →Ongoing accessMCP Workspace integrationWhen does an agent need ongoing scoped workspace access instead of one bounded handoff?Choose the access model →