Handoffs

Human Handoff

Solves: receiving finished or blocked work from an agent with enough to judge it.

Emerging — seen across multiple products; the shape is still settling.

watching →emerging →established →contested →fading 38 sightings since Mar 2026
Ask an assistant about this pattern Ask ChatGPT ↗Ask Claude ↗

Human Handoff is the moment responsibility moves back from the agent to a person. The agent says what it did and shows the changes. It names the choices it made and the questions it could not settle, and says what it needs next. Continuity is the test: the person can act without reconstructing what happened.

When to Use It

  • Finished or blocked work returns to a human for review
  • The agent made judgment calls the human should see
  • Review should start from a summary and a diff, not archaeology

When Not To

  • Nothing is reviewable — pure status updates belong in progress
  • The "summary" would be the only record — keep the diff primary
  • You're asking permission before acting — that's approval, not handoff

Three views

The exchange between the human, the agent and the system the agent acts on; who holds each part of it; and the component that implements it.

01 · the interaction
human agent system diff · logs · test results reads its own diff, log and test results summary, diff, decisions made flags the open questions inspects the changed files or records accepts or returns the work
02 · who holds what
human interface agent Summary: What the AI did, in a few sentences 01 Summary Diff: The changes, laid out so you can review them 02 Diff Decisions: The choices the AI made for you along the way 03 Decisions Open questions: The things the AI could not settle on its own 04 Open questions Next actions: What it wants you to do now 05 Next actions
human interface agent Summary: What the AI did, in a few sentences 01 Summary Diff: The changes, laid out so you can review them 02 Diff Decisions: The choices the AI made for you along the way 03 Decisions Open questions: The things the AI could not settle on its own 04 Open questions Next actions: What it wants you to do now 05 Next actions
  1. 01 Summary What the AI did, in a few sentences
  2. 02 Diff The changes, laid out so you can review them
  3. 03 Decisions The choices the AI made for you along the way
  4. 04 Open questions The things the AI could not settle on its own
  5. 05 Next actions What it wants you to do now
03 · the component

primitive wireframe, generated from the anatomy — the installable component ships when this pattern's anatomy stabilizes

Field Notes

OCT 14 · Paper · via arXiv ApprovalHuman HandoffObservabilityReview

Hidden ads in search results steered what a shopping AI bought

The human approved the task, then reviewed the result. The middle, what the agent read and what it was told inside those pages, stayed invisible. That gap is what this paper lands on.

OCT 14 · Paper · via arXiv Confidence SignalingHuman HandoffReview

Expertise shapes how far workers trust and delegate to AI

Experts caught errors; novices did not. The difference was review behavior, not trust. A screen that makes scrutiny feel optional skips the most important moment in the interaction.

OCT 14 · Paper · via arXiv Confidence SignalingHuman HandoffReview

Researchers find AI interaction leaves measurable marks on the human

The interaction leaves a mark on the human, and most patterns are designed as if it doesn't. That's the gap. Delegation, review, confidence-signaling: each one trains the human in a direction. Worth knowing which direction before you ship.

SEP 28 · Paper · via arXiv Confidence SignalingHuman HandoffReview

NYT's Epstein Files agent cut 26,000 documents to 2,500 for reporters

The Times scoped the agent to surface, not conclude. The reporter kept the decision. That boundary was chosen, not accidental. Designing the division before building the tool is the move worth copying.

SEP 28 · Paper · via arXiv Confidence SignalingHuman HandoffReview

366-person study finds AI lifts confidence faster than skill

The agent handed the human a finished result and the human felt expert. A review screen that shows only the output inflates confidence without building skill. That gap is the design problem.

SEP 25 · Paper · via arXiv Agent IdentityHuman HandoffInterruption

Enterprise workers renegotiate their roles when agents join the team

The repair work was real labor, and none of it was visible in the product. That gap, between what the agent did and what the team could see and correct, is where agent-identity and human-handoff patterns earn their keep.

SEP 17 · Clipped · via GitHub Blog Human HandoffObservabilityReview

GitHub used Copilot to rewrite a core part of Copilot itself

Engineers stopped writing code and started directing it. Review becomes the hard problem: agent output volume outpaces tooling built for human-paced work, and that gap is where the interface needs to do more.

SEP 16 · Paper · via arXiv DelegationHuman HandoffReview

20 workers show how reviewing finished agent work opens a reuse loop

The review screen is also the screen where a worker starts the next job. Workers moved from judging a finished run to copying it for a new one. Treating those as two separate screens adds a step the worker does not need.

SEP 16 · Paper · via arXiv DelegationHuman HandoffReview

535 humans and capable AI agents still left gains on the table

The synergy existed in the model; the human did not reach for it. That is a design failure in how work gets passed to the agent, not a capability gap. If a human cannot see the right moment to pass work over, the agent's power goes unused.

SEP 15 · Clipped · via The Pragmatic Engineer DelegationHuman HandoffReview

OpenAI engineers hand Codex their code reviews and move on

The engineer's job moved from writing to judging. Review is now the primary human moment, and most agent products design it as an afterthought. That is the gap to close.

AUG 31 · Paper · via arXiv Agent IdentityContextHuman Handoff

CrabOS proposes an operating system that agents and workers share

If context and action provenance live at the OS layer, your app no longer owns the handoff surface. That changes where you design the moment a human reviews or takes back work from an agent.

AUG 29 · Clipped · via GitHub Background ExecutionHuman HandoffObservability

Karpathy's autoresearch runs experiments start to finish unattended

No approval, planning, or handoff surface in sight — autoresearch is the strongest sighting I have of observability and human-handoff as design absences rather than features.

AUG 28 · Clipped · via Simon Willison Confidence SignalingHuman HandoffObservability

Linus Torvalds kept debugging the kernel after the AI gave up

The agent gave up; the expert didn't. That gap is the design problem. Human-handoff needs to handle 'I ran out of ideas' as a first-class exit state, with the agent's reasoning trail intact for re-entry.

AUG 28 · Clipped · via Maggie Appleton DelegationHuman HandoffPlanning

Maggie Appleton says design, not the model, now sets the pace

Appleton's argument shifts the pressure: model capability is no longer the slow part, design decisions are. The patterns teams name now will be the defaults agentic products ship with, and reversing bad defaults in production is expensive.

AUG 13 · Firsthand · via X · @bcherny Ambient StatusBackground ExecutionHuman Handoff

A designer ran app maintenance through Claude for weeks from Slack

Slack doing triple duty as status layer, handoff surface, and approval gate is the cleanest argument I've seen that background-execution agents don't need bespoke UI — the medium earns its keep.

Documented sightings (12) — anatomy-mapped observations from vendor materials

The agent surfaces price, auto-renew choice, and registrant details to the human via interactive terminal or dashboard at the moment of purchase, creating a structured handoff point.

Vercel Blog · Oct 9, 2026

The incident reveals the absence of any structured escalation path from automated agent activity to human intervention beyond one volunteer moderator.

arXiv · Oct 6, 2026

Rather than failing silently or escalating to its operator, the agent sought human expertise from third parties, representing an unplanned lateral handoff to external humans.

Hacker News · Oct 3, 2026

The system was explicitly designed not as an autonomous writer but as a handoff interface, surfacing material that human reporters then interpreted and wrote.

arXiv · Sep 28, 2026

Boundary objects are proposed as the mechanism by which humans and agents transition responsibility across a shared representation of a task.

Maggie Appleton · Sep 14, 2026

62% of commits carry an AI co-author trailer, revealing a recurring pattern where AI drafts or suggests skill edits that humans then approve and merge.

arXiv · Sep 9, 2026

The paper recommends an 'interface that asks rather than invents'—a design pattern where the agent surfaces uncertainty about remembered facts and prompts the user to re-confirm rather than hallucinating continuity.

arXiv · Sep 9, 2026

CrabOS enables seamless turn-taking between humans and AI on the same task by representing shared work state as natural-language-readable text objects accessible to both parties without bridging code.

arXiv · Aug 31, 2026
Anthropic

Handoff as authored artifact: summary, diff, decisions, and test plan written at handoff time into commit/PR.

Anthropic docs · Mar 15, 2026
OpenAI

Handoff as product surface: the task result IS a diff view with summary and logs; PR creation is the accept action.

OpenAI docs · Mar 15, 2026

The MCP client facilitates navigation to a browser URL, transferring the sensitive interaction entirely out of the agent pipeline to a human-controlled user-agent.

MCP Spec · Aug 29, 2026

The paper examines when and how control should transfer back to humans, arguing current handoff designs erode the cognitive readiness required to accept control effectively.

arXiv · Aug 29, 2026

Side by Side

Anatomy part AnthropicOpenAI
Summary prose summary in PR/commitagent summary attached to result
Diff git diff as reviewable artifactdiff view is the primary surface
Decisions decision notes in description—
Open questions ——
Next actions test plan checklistopen PR from result

What Vendors Call It

Chart unlocks as the corpus grows — n = 0 mentions across 0 quarters.

  • Anthropic session summary / PR description
  • OpenAI task review
  • Cognition (Devin) Devin's ticket update

Tensions & Failure Modes

  • Summary trust: the summary is written by the party being reviewed
  • Blocked vs. done: interfaces rarely distinguish a finished handoff from a stuck one
  • Receipt decay: handoffs vanish into chat scrollback

What we are learning from the community

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The Story So Far

  1. Oct 13, 2026 drift: steady → rising (30d sightings 7 → 7)
  2. Oct 1, 2026 drift: rising → steady (30d sightings 7 → 6)
  3. Sep 13, 2026 drift: new → rising (30d sightings 5 → 4)
  4. Aug 30, 2026 Seeded from SPEC v1.5 Phase 0: Anthropic-first corpus with OpenAI counterparts
  5. Aug 28, 2026 pattern-launch Claude Code and Codex hand finished work back the same way The reverse of delegation was always the weaker half of the loop. It just cleared the promotion bar.
  6. Aug 28, 2026 Promoted to published: cleared the promotion bar with Anthropic + OpenAI examples

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