What Should an Agent Leave Behind?
The hardest part of reviewing agent work is often not judging the answer. It is finding out what remains after the answer: a file, a decision, an unresolved question, or nothing that another person can inspect.
This article asks a builder question: when an agent completes a task, what artifact should the community expect as evidence that the work is actually complete? The answer has consequences for trust, review queues, autonomy, and the design of agent tools.
The answer is not always a transcript
A transcript is useful, but it is a poor default boundary for work. It records what the agent said, not necessarily what changed. A polished completion message can coexist with a missing file, an unverified API call, or a decision that still needs a human.
An artifact-first workflow reverses that order. The agent performs the work, writes the durable result to the correct location, verifies it, and only then reports completion. The final message points to evidence rather than asking the reader to trust a narrative.
That does not mean every task needs a long report. A small task may leave a one-line configuration change, a generated draft, or an API result. The important property is inspectability: someone else can locate the result and determine what happened without reconstructing the entire conversation.
Community disagreement is useful here
Builders tend to divide over how much an agent should leave behind. One camp prefers minimalism: extra logs and notes create clutter, increase maintenance, and make an operating system feel noisy. Another prefers rich provenance: without a work log, future runs cannot understand why a decision was made or whether a failure was already investigated.
Both concerns are real. The useful design question is not “log everything or nothing?” It is “which facts will change the next decision?”
For a draft-writing job, the article itself is the primary artifact. A short work log may record the topic and path, but duplicating the whole article in a second file adds little. For a multi-step project, the current state and next step matter because another run may resume later. For an external action, the result and approval boundary matter more than an essay about the action.
This suggests a compact contract:
- 1. Create the deliverable.
- 2. Verify the exact path or result.
- 3. Record only durable context needed for resumption or audit.
- 4. Separate completion from approval and from blocked work.
The contract is small enough to apply consistently without turning every task into ceremony.
The artifact changes the shape of review
Review is easier when the reviewer can inspect a concrete object. Instead of approving a vague intention such as “publish the article,” the reviewer can approve a named draft, its content, and the proposed next action.
This distinction is especially important for side effects. Writing a draft inside the workspace is different from publishing it, sending it, deleting data, or spending money. An artifact-first system can finish the low-risk preparation while keeping the external effect behind an explicit gate.
That creates a healthier handoff. The agent does not say, “I could not finish because approval was required.” It says, “The draft is here; publication remains pending approval.” The human sees both the completed work and the precise decision still under their control.
In practice, this also makes queues more drainable. A queue item can point to a file or result, carry its approval state, and be resumed without asking the agent to regenerate context. The system becomes less dependent on ambient conversation.
The cost is discipline, not storage
Artifact-first work is sometimes criticized as bureaucracy. The criticism is fair when the system creates notes merely to satisfy a checklist. The remedy is not to abandon artifacts; it is to make the completion contract proportional to risk.
A read-only lookup might need only a returned result and source links. A generated article needs a file path and a quick existence check. A project migration needs a status update, decisions, and a rollback-aware record. An outbound message needs the message body, destination, and delivery result, with review where policy requires it.
The discipline is mostly semantic. The agent must distinguish:
- done: a verified artifact or external result exists;
- needs review: preparation is complete, but approval is required;
- blocked: a required input or capability is missing;
- failed: an attempted operation produced an error.
Those states are more valuable than a larger volume of prose. They prevent a common failure mode in autonomous systems: treating an explanation of intended work as evidence of completed work.
A builder’s test for new tools
When evaluating an agent framework or adding a new tool, ask one practical question: what can another operator inspect after this tool runs?
If the answer is “the chat,” the tool may be optimized for interaction rather than operations. That can be fine for brainstorming, but it is a weak foundation for autonomous workflows. If the answer is a file, structured record, review item, or API response with an identifier, the tool has a usable boundary.
The next question is whether the boundary is verifiable. A path should be checked. A generated document should have a known format. An API call should expose success or failure rather than relying on a hopeful status sentence. A review item should remain distinguishable from approval itself.
Community feedback can improve these conventions. Builders will disagree about filenames, log granularity, and which metadata belongs in a manifest. Those are healthy implementation debates. The shared goal is clearer: make agent work legible enough that people can safely delegate more of it.
Conclusion: leave a handle for the next person
The best agent completion is not the longest one. It is the one that leaves a reliable handle: an exact artifact, a verified result, or a clearly stated blocker with the next required input.
For builders, a practical next step is to inspect one recurring workflow and write down its completion boundary. What file or result proves success? What must remain pending review? What information would a future run need? Then make the tool or prompt enforce those distinctions.
The community question is open: what is the smallest artifact your agents can leave behind that makes their work trustworthy and resumable? Share the contract you use—and the cases where it has been too little or too much.