Human-Centered AI / Engineering-Handoff Profile

Looks finished.
What has been demonstrated?

Six questions before you invest in building an AI-created or AI-enabled workflow.

See what works, what is still assumed, and who owns the next step. For designers, builders, business owners and advisors—not just AI specialists.

0.1-rc.4-candidate.2 · September 24, 2026 · What changed?

01 / Start small

Bring one real case, not a perfect presentation.

You do not need to read the whole protocol or edit technical records. An advisor can ask the questions aloud and record the answers.

Owner or advisor?

Bring a recent example of today's work and someone who knows where it gets stuck. Start with time, people and rework.

Designer or builder?

Bring the proposed artifact and its requirements. Show the failure path, the test, and the exact revision tested.

Studying human review?

Keep experimental judgments separate from this guided review. Hints and answer keys can change the task.

Read the research boundary

Begin here: “Walk me through one recent case.”

Where does it start? Who touches it? Where does someone check, fix or chase it? If there is no measurable current-state baseline, stop and observe the work. ROI stays indeterminate.

Read the one-page starting guide
02 / The conversation

Six questions. One useful next action.

Check risk first. Low risk with records available can use QUICK-6. Moderate, high or unknown risk goes to FULL before the short review.

  1. What happens today? Show the current steps, people, time, touches, failures, review and volume.
  2. What needs to improve, for whom? Connect an actual end-user need to an owned, testable requirement.
  3. What happens when things go wrong? Explain edge cases, recovery, data preservation, escalation and human/agent authority.
  4. What demonstrates the important behavior? Link the requirement, exact artifact revision and executed check. Label simulated behavior.
  5. What work remains for people? Subtract review, correction, escalation and rework before claiming net savings.
  6. Is that enough to fund the next step? Apply the risk threshold, resolve critical findings, and name the scope, owner and resource limit.

“We do not know yet” is a useful answer.

Stop at the first failed or missing gate. Later gates are not evaluated. Preserve the record, identify the next action, and continue in a linked FULL review after remediation.

The ≤15-minute target is untested. Count capture and explanation; disclose preparation separately. Take breaks or use an accessible format. Needing longer is not a participant failure.

Constructed example · not a pilot

Beautiful prototype.
No measured baseline.

Pause: insufficient evidence.
ROI is indeterminate.

Next: observe a current case.
Owner: the workflow owner.

Open QUICK-6 · Open the full risk-tiered profile

03 / Potential situations

Useful when a convincing artifact hides an unanswered question.

These examples illustrate intended use—not observed benefits, pilot results, or proof that AI causes these defects.

The booking screen loses details after payment fails

A normal-path demo is not a recovery test. Define who notices the failure, what is preserved and how the user resumes. Revise the recovery path before commitment.

The tests passed—before the coding agent's latest edit

Compare the tested artifact digest with the current revision. A mismatch blocks the traceability gate; rerun the affected checks. A green report for old code is not current evidence.

The agent can send, but nobody defined approval

Document what it may read, change or send; who can approve or stop it; and how to recover. Higher consequences require deeper review, not a longer happy-path demo.

Checking the AI output consumes the expected savings

In a fictional case, 15 gross minutes saved minus 15 minutes of review/correction/escalation leaves zero net labor savings. Show that result and any recurring cost. Do not retain inflated ROI.

Read all seven scenarios · Inspect a synthetic decision report

04 / The detail underneath

Four principles. Fourteen inspectable criteria.

Open only the principle you need. Each criterion explains the requirement, how to check it and what failure looks like. These support human review; they do not replace it.

Understand the work before judging the solution
HCAI-1.1 · Bound the task

Requirement: Name the workflow, one unit of work, start and end boundaries, context, AI role, exclusions and a current/manual/non-AI alternative.

How to check: Ask a second person what is inside and outside this review; compare their answer with the scope record.

Meets the intent: Review one intake request from receipt to advisor confirmation; exclude live sending.

Common failure: Make our business AI-ready without naming a task.

Verification boundary: Required fields plus accountable human scope review

Decision gate: G2_NEED_REQUIREMENTS. No separate certification is issued.

HCAI-1.2 · Observe the current workflow

Requirement: Retain an observed baseline and a connected current-state map with actors, normal work, exceptions, recovery, time, volume and an endpoint. Mark reported paths separately.

How to check: Follow a recent case through every step; reconcile elapsed time, labor and the sampling window. Inspect where work changes hands or returns for correction.

Meets the intent: A work log supports measured labor; a separate operator account describes an exception not observed in that sample.

Common failure: The owner guesses hours saved without knowing today's steps or work volume.

Verification boundary: Graph and numeric checks plus direct observation review

Decision gate: G1_BASELINE. No separate certification is issued.

HCAI-1.3 · Connect requirements to an actual need

Requirement: Connect each need to an owned, checkable requirement. Use distinct original work or end-user sources at the required risk depth.

How to check: Ask whose difficulty the requirement resolves, what would count as success, and whether two sources share the same origin.

Meets the intent: An operator discussion and a work record independently support preserving data after cancellation.

Common failure: Two summaries of one conversation are presented as two independent customers.

Verification boundary: Reference, origin and source-kind checks plus human relevance judgment

Decision gate: G2_NEED_REQUIREMENTS. No separate certification is issued.

Make intended behavior and evidence inspectable
HCAI-2.1 · Explain form fit and function

Requirement: Every requirement names what is represented, how it fits the surrounding workflow, what it must do and the reference material used to judge it.

How to check: Inspect the reference before judging whether the visible artifact belongs and behaves as intended.

Meets the intent: A review form is linked to required intake fields, advisor responsibilities and cancellation rules.

Common failure: A finished-looking screen is accepted without knowing its purpose or reference requirements.

Verification boundary: Structured references plus human interpretation

Decision gate: G4_TRACEABILITY. No separate certification is issued.

HCAI-2.2 · Trace the exact artifact to a check

Requirement: Each important artifact and each requirement-artifact pair has an executed walkthrough or test. The check identifies the exact tested artifact digest.

How to check: Open the chain from requirement to artifact to result; compare the recorded tested digest with the reviewed artifact. Repeat the check after a change.

Meets the intent: A cancellation walkthrough records the exact screen revision and the field-preservation result.

Common failure: An agent edits error handling after tests ran, but the old test pass is reused.

Verification boundary: Deterministic chain and revision checks plus inspection of execution evidence

Decision gate: G4_TRACEABILITY. No separate certification is issued.

HCAI-2.3 · Distinguish simulated from implemented behavior

Requirement: Label each requirement's behavior as specified only, simulated or implemented. Do not label a walkthrough of a simulation as an implementation test.

How to check: Ask what is actually connected and what is mocked. Keep visual polish separate from functional evidence.

Meets the intent: The export button is simulated; the review checks the intended recovery behavior and funds only implementation of that behavior.

Common failure: A mock success screen is presented as proof that a payment or export completed.

Verification boundary: Behavior-status and test-level consistency plus human inspection

Decision gate: G4_TRACEABILITY. No separate certification is issued.

Keep people able to understand and recover
HCAI-3.1 · Cover normal edge and recovery states

Requirement: Represent normal, edge and recovery paths with triggers, behavior, resulting state, data treatment, owner and requirement links; review dependencies.

How to check: Try missing input, empty results, delay, unavailable dependency, cancellation and resumption where relevant. Document which cases apply.

Meets the intent: A failed save keeps entered data and explains how to retry or return to manual work.

Common failure: The happy path works but a failed save silently discards the user's input.

Verification boundary: State/reference checks plus context-specific human walkthrough

Decision gate: G3_STATES_RECOVERY. No separate certification is issued.

HCAI-3.2 · Make human and automated authority explicit

Requirement: Record what people and automated components may access, change or send. Review approval, interruption, escalation and recovery boundaries. If AI only created the artifact, say so.

How to check: For an agent action, ask who authorizes it, how to stop it, what happens after partial completion and who resolves exceptions.

Meets the intent: A draft-only agent cannot send; an advisor approves changes and can return to a saved record.

Common failure: An agent may delete or message externally without a stated owner, approval boundary or recovery path.

Verification boundary: Required boundary review plus specialist verification when risk demands it

Decision gate: G3_STATES_RECOVERY. No separate certification is issued.

HCAI-3.3 · Count human oversight work

Requirement: Estimate disjoint review, correction, escalation, rework and residual manual minutes with an owner and basis. Distinguish gross from net benefit.

How to check: Subtract every oversight component from gross labor savings. Keep waiting time and labor time separate. Leave missing baseline ROI indeterminate.

Meets the intent: Fifteen minutes of gross savings and fifteen minutes of oversight are reported as zero net time savings.

Common failure: Only generation speed is counted while a person must check and rewrite every output.

Verification boundary: Required fields and arithmetic plus human estimate review

Decision gate: G5_OVERSIGHT. No separate certification is issued.

Make the commitment accountable
HCAI-4.1 · Scale depth before starting

Requirement: Classify all six risk dimensions with rationale. Use the highest dimension; moderate, high or unknown risk cannot qualify through QUICK6.

How to check: Review consequence, reversibility, complexity, importance, impact and mission before choosing the path. Do not lower risk to fit the meeting.

Meets the intent: A consequential allocation workflow goes to FULL even when its interface has only one screen.

Common failure: A simple-looking UI is treated as low risk despite an irreversible outcome.

Verification boundary: Deterministic routing plus competent human risk classification

Decision gate: G6_COMMITMENT. No separate certification is issued.

HCAI-4.2 · Resolve findings at the required depth

Requirement: Review reference defects, findings and unresolved risks. Unresolved critical findings cannot be waived. Add independent review and deeper plans when the risk tier requires them.

How to check: Inspect unresolved findings rather than averaging gate passes. Verify reviewer independence for moderate/high risk.

Meets the intent: A critical data-loss defect stays visible even when the baseline is also missing.

Common failure: A critical finding is marked accepted to obtain a favorable readiness result.

Verification boundary: Finding status and evidence checks plus reviewer judgment

Decision gate: G6_COMMITMENT. No separate certification is issued.

HCAI-4.3 · Limit the engineering commitment

Requirement: Record an owner, bounded engineering step, resource limit and next review trigger. Explain any investment despite a nonpositive net estimate; obtain separate owner authorization.

How to check: Ask what the team may build next and what it may not do yet. Retain a separate dated owner decision.

Meets the intent: One engineer-day for a disposable prototype, with no live sending and a review before further work.

Common failure: A gate pass is treated as permission for unrestricted building or deployment.

Verification boundary: Recorded bounds and rationale; authorization remains a separate human act

Decision gate: G6_COMMITMENT. No separate certification is issued.

HCAI-4.4 · Separate effort from performance

Requirement: Record preparation, timed-session and reporting burden. Keep protocol cost, projected operating oversight, reviewer judgments and actual system performance separate.

How to check: Check units and which activity each number measures. Do not infer operational accuracy, safety or readiness from document completeness.

Meets the intent: An expensive evaluation is reported separately from the workflow's projected operating cost.

Common failure: A high checklist score is reported as evidence that the implemented system works.

Verification boundary: Separate contract fields and arithmetic; no combined score

Decision gate: G6_COMMITMENT. No separate certification is issued.

HCAI-4.5 · Preserve evidence and disclosure boundaries

Requirement: Retain exact versions, source origins, digests and previous-run links. Preserve missing and stopped records. Keep private identities/comments out of public materials without permission.

How to check: Can the run be reconstructed, and is each proposed disclosure permitted? Do not alter an old record into a new pass.

Meets the intent: A new FULL record links to the stopped QUICK6 record; private notes remain outside the public package.

Common failure: A synthetic example is relabeled as an actual pilot or private feedback is published as an endorsement.

Verification boundary: Structural provenance checks plus human permission review; hashes alone do not prove truth

Decision gate: G6_COMMITMENT. No separate certification is issued.

Inspired by WCAG 2.0's layered guidance, not its conformance levels. This author-defined candidate is not a W3C standard, accessibility certification or universal AI-quality standard.

How risk changes the required evidence

Highest of complexity, importance, impact, mission, failure consequence and irreversibility sets depth. Low: at least 1 observed case and 1 need origin. Moderate: at least 3 cases, 2 origins, actual end-user discussion, independent review and validation planning. High: at least 5 cases plus hazard, mission and operational-evaluation planning. Moderate/high require FULL.

These are provisional completeness floors, not representative sample sizes or validated safety thresholds.

What stays separate in the result

Current-state baseline; proposed workflow; protocol evaluation cost and separately operational oversight burden; engineering-handoff evidence; actual post-implementation performance. No combined readiness score. Preparation and session effort are visible. Gross savings, net operating benefit and one-time cost remain distinct.

05 / Optional tools

Use the same method with an assistant.

MCP 0.2.0rc2 and ai-ready Skill 0.2.0-rc.2 share the same deterministic gates. The new guided path asks one question at a time and produces a readable, private report—not only a technical data object.

Set up MCP

Requires uv. The first run downloads the versioned wheel and dependencies. It runs locally without a model key; your assistant host can see supplied records. Do not submit confidential data without permission.

{
  "mcpServers": {
    "hcai-readiness-candidate": {
      "command": "uvx",
      "args": ["--from", "https://www.takyejun.com/static/research/ai-readiness/rc4-candidate-2/hcai_readiness_mcp-0.2.0rc2-py3-none-any.whl", "hcai-readiness-mcp"]
    }
  }
}

Start with new_review_record, continue with review_next_step, then assessment_report. Get one criterion with get_review_criterion. No evidence or authorization is invented.

Set up the ai-ready Skill

The Skill guides the conversation and includes a portable Python engine. Requires Python 3.11+ and Pydantic 2 for deterministic assessment. Without the runtime, it prepares evidence and reports assessment pending.

Download ai-ready Skill

Extract the ai-ready folder into your assistant's Skill directory. Follow its included instructions. This does not authorize contacting people or publishing private records.

Full setup and tool reference
06 / Read, print or try

Take only what you need.

Start a short review

Six questions and a visible stop.

QUICK-6 PDF

Read the complete method

Scope, principles and boundaries.

Read in your browser

Protocol PDF

Try one bounded external use

A short voluntary packet. No endorsement expected.

Pilot packet PDF
Full profile, package and verification records

Full-profile PDF · Complete candidate package · Software test results · Change-to-test mapping · Download checksums

What has—and has not—been established.

Practitioner correspondence informed refinement. It is not controlled empirical validation. Hillel Glazer approved attribution for his traceability feedback; other themes are summarized without publishing private identities or comments. No endorsement is implied.

The proposed research studies visual fidelity and reviewers' defect detection while AI authorship stays constant. Perceived readiness and confidence are separate judgments. It does not yet establish that AI coding causes these problems or that this protocol prevents them.

No actual external pilot is recorded. Usability, the time target, risk thresholds and effectiveness remain unvalidated. Final rc.4 requires regression checks and recorded bounded end-user/advisor use. The owner separately authorizes engineering; deployment requires separate evaluation.

Read the update log

Frozen history, citation and reuse

rc.3 and the first rc.4 candidate remain available, unchanged. Historical rc.3 PDF · First-candidate package · Migration notes.

Tak, Y. (2026). Human-Centered AI Deployment Readiness Protocol: Engineering-Handoff Profile, 0.1-rc.4-candidate.2. MCP 0.2.0rc2; Skill 0.2.0-rc.2. No candidate DOI is assigned. 10.5281/zenodo.22667623 identifies rc.3 only.

Original text and synthetic data: CC BY 4.0; software: MIT. AI-assisted development. Research Harness v3 is a separate project, not validation evidence for this protocol. Source repository.