CARBONENGINEERING CONFIDENCE Command report
Jay, AI personaAIJayAI test manager · CARBON

Meet Jay. Modeled on Jason Arbon’s approach to testing: start with the customer’s intent, follow the consequential risks, challenge the evidence, and make the next useful action clear.

Jay is an AI persona inspired by Jason Arbon, not Jason himself. His visual identity is a distinctive J-shaped character, not a human portrait.

Jason’s background spans embedded systems, operating systems, search, enterprise servers, crowdsourced testing, and manual and automated testing at scale. Jay draws on the methods curated into CARBON; he did not personally hold those roles.

Coordinates specialists, presents recorded evidence, and helps the coding agent verify authorized fixes. Human judgment and existing permissions stay in control.

partial2026-10-23T20:56:44Z
DecisionRESULT

CARBON X — independent public Xbox UI evaluation

25 of 31 bounded checks executed: 22 passed, one failed focus-return check, one partial mobile-dialog check and one access-wording observation. Three blocked, two planned, one conditional control check not offered. Seven route identities, three viewports. Not a full product assessment.

Basis: One in-app browser session, 23 October 2026. Browser engine version unavailable. 32 public capture pairs. No real AT, full contrast/zoom, second engine, physical mobile or measured performance. Persona opinions are AI interpretations, not user research. Native run initialization was partial; this command report summarizes separate evidence.

IntentPublic signed-out https://www.xbox.com/en-US/play; no authentication, age verification, purchases, gameplay or service mutation.
Risk0 finding(s) recorded
Evidence7 artifact(s) linked
DecisionRESULT
Next evidencecarbon-accessibility
Run context · /carbon

Public signed-out https://www.xbox.com/en-US/play; no authentication, age verification, purchases, gameplay or service mutation. · partial · 2026-10-23T20:56:44Z

Testing perspectivesUser Interface
Usability sub-agent icon AI
Usability sub-agent

Usability sub-agent

User-centered design and usability specialist focused on discoverability, task clarity, responsive behavior, interaction friction, visual hierarchy, and inclusive UX.

AI sub-agents identify the applied testing perspective. Findings and pass states still require the evidence shown in this report.

Evidence needed for a stronger decision
01
Real assistive technology and continuous keyboard journey

Targeted keyboard checks do not establish conformance

02
Ownership/subscription intent

Access wording may be ambiguous

03
Physical mobile and another engine

Viewport resizing does not cover device behavior

Executed bounded checks
25 / 31
Passed narrow oracles
22
Capture pairs
32
Route identities
7
A

Optional questions that could change this assessment

The assessment is complete. Answer now or later with /carbon-human; these questions do not block the run.

Testers

HUM-A911C8F2

Which domain invariants, exceptional cases, or reconciliation rules would an experienced operator spot immediately but are not written in the code or tests?

Why it matters: Data and API behavior often have business rules that look valid syntactically while being wrong operationally.

Quick choices: No additional rules; I can provide rules; Ask a domain expert; Need discovery. You can also give your own answer.

PM (Project Manager)

HUM-55F74463

If authentication, payment, privacy, or a currently severe finding fails in the real workflow, who absorbs the harm, what is the worst credible outcome, and which failures are unacceptable even once?

Why it matters: The code cannot determine business consequence, compensating controls, or the organization’s risk appetite.

Quick choices: Hold on failure; Canary with safeguards; Recoverable incident; Need risk owner. You can also give your own answer.

HUM-9E83644B

What decision should CARBON help make for Public signed-out https://www.xbox.com/en-US/play; no authentication, age verification, purchases, gameplay or service mutation.: a demo readiness call, an internal trial, a staged rollout, or production release—and when?

Why it matters: The project evidence does not reliably establish the release stage, deadline, or decision owner.

Quick choices: Demo; Internal trial; Staged rollout; Production release. You can also give your own answer.

Product Manager

HUM-6ED04AC0

What evidence would convince the accountable product owner that the intended user achieved the promised outcome with acceptable effort?

Why it matters: A stated feature or workflow is not yet a decision-quality value oracle.

Quick choices: Observe a real user; Pilot outcome; Product metric; Not defined yet. You can also give your own answer.

HUM-09B1D403

For the intended user, what would make this experience feel credible, clear, and worth trusting—and what confusion or surprise would make it unacceptable?

Why it matters: Visual and interaction checks can detect defects, but product taste, trust, and workflow fit need accountable human judgment.

Quick choices: Clear enough; Reduce friction; Validate with users; Not judged yet. You can also give your own answer.

Human decision context is pending; confidence covers observed technical evidence but not unrecorded intent, risk appetite, taste, consequence, or accountability.

Evidence boundary

One in-app browser session, 23 October 2026. Browser engine version unavailable. 32 public capture pairs. No real AT, full contrast/zoom, second engine, physical mobile or measured performance. Persona opinions are AI interpretations, not user research. Native run initialization was partial; this command report summarizes separate evidence.