Capital One R249772 — Dohan Buys Implementation, Jorge Buys Accountability

Phase 1: The Moment

The search is 115 days old. R249772 first posted May 28 and resurfaced with an August 21 date under the same requisition number — same req, renewed listing. Patrick Dohan, VP of Design for Capital One's Premium group (travel, rewards, dining, entertainment, platform; 100M+ cardholders), posted the hiring call himself. VPs at Capital One rarely post individual reqs. Treat him as the hiring manager. That is inference from one strong signal rather than confirmation, and it is strong enough to route on.

The role defines how Capital One's hundreds-person experience design org integrates AI into design practice: methodology, tooling, standards, adoption. That is an org transformation mandate, not product design leadership for customers. The search reset moved the job from visionary authority toward operational enablement.

Two buyers, two anxieties. Dohan's post language — "deep technical expertise," "experimentation bias at scale," "architect how designers work in the future" — tells you what he is filtering for: will designers actually work differently after this hire. Jorge's March interview gives the institutional filter, "keep people at the center while considering both the value and the consequences." Her question is whether the org can change without design judgment getting less accountable.

Window. At 115 days of total search with a mid-August reset, the pipeline is either stalled or deep, and public signal cannot tell you which. Either way Dohan wants it filled; he put his own name on the posting. If the search is stalled, the committee has already learned it needs operational depth over vision — the revised language says as much — so lead with Carrier IQ and the TinyFish production experience, which prove you build. If it is deep, the slate probably holds enterprise design directors and DesignOps leads, and neither archetype tends to arrive with published methodology backed by production AI work. Then the Trust essay carries more weight, not less.

Verdict: Act. Dohan by Tuesday. Jorge within 48 hours of Dohan.

Phase 2: Portfolio Mapping

Lead with the Trust essay plus Carrier IQ. The five handoffs (Intent-Setting, In-Progress, Output Review, Decision Gate, Loop Feedback) and the trust ladder (Watch → Verify → Delegate) are the operating protocol this Director would install. They answer Dohan directly: here is how designers evaluate AI-assisted work at each stage, with explicit criteria for advancing and for intervening. Carrier IQ shows all five running in a regulated context — staged execution, evidence surfacing, operator intervention, re-verification, approval gate.

The methodology layer is missing from junochen.com. The forward-looking visual artifacts — interaction models, user flows, state diagrams showing how a designer evaluates AI-assisted work at each handoff — would give Dohan something inspectable. For a buyer whose whole anxiety is adoption at the team level, a deliverable that shows the working method beats an essay that argues for one. Those artifacts sit in the Build Queue, unpublished. Building the Human-Agent System Design artifact first would materially strengthen the pitch to him. At 115 days, the posting may not wait that long. Move now with the essay and Carrier IQ. If the artifact ships before the first conversation, send it as the follow-up; it is the strongest second touch available to you.

Enterprise credibility, secondary. Alibaba.com ($50B+ GMV, +20% daily transactions, +2.2pt NPS): as Head of Design and Research, North America, you named a structural gap the org had not named, built the mandate, and executed three cross-functional sprints. Thermo Fisher mySupply ($20M+ margin recovered annually, 6/6 partner adoption): as Product Design Director at BCG Digital Ventures, you shipped inside a compliance-constrained environment with measurable outcomes.

TinyFish, past tense, always. Most recently as Head of Product at TinyFish, you shipped an enterprise web agent platform from 0 to 1 in three months and worked daily with agent traces, auditability, and governance. That production history is what makes the Trust framework credible to a technical evaluator. It is not portfolio proof and should never be described as such.

The objection Dohan will raise. You have never installed an AI methodology across a hundreds-person design org. What makes the objection hard is that nobody has; the practice is three years old at most. The answer is that Watch → Verify → Delegate governs how a designer relates to an AI-assisted output the same way it governs how a user relates to an agent, Carrier IQ is inspectable proof you have built staged evaluation architecture, and Alibaba is proof you have run org-scale change to numbers. None of the three answers him alone. Presented together they do.

Competitive landscape. An AI-native design leader (moderate confidence) brings brand credibility and is unlikely to have published a framework for how AI changes design practice at org scale. An enterprise design director (high confidence) brings org-politics fluency and is unlikely to have AI-native production experience. A DesignOps or process leader (moderate confidence) brings tooling expertise and will struggle to earn craft credibility with the designers. You sit in the overlap of published methodology, production AI depth, and enterprise execution proof.

Mandate laundering test — whether the posting describes authority this role will not actually hold. It assigns adoption, tooling, and measurable value. It does not assign budget, release gates, evaluation standards, or incident review. Five questions for the first conversation:

1. If I evaluate an AI design tool and decide it is not ready for the team, do I make that call or recommend it to someone who does?
2. When AI-assisted design work ships and the outcome is poor, who owns the post-mortem?
3. Does this Director set the quality bar for AI-assisted output, or does each product team set its own?
4. What budget does the role control directly?
5. What does this Director stop someone from doing in the first 90 days?

Ask question 3 of both Dohan and Jorge. Divergent answers mean the mandate is still being negotiated internally and you would be hired into an unresolved argument.

Phase 3: The Outreach Package

Warm path: no mutual connections identified for either buyer. Both messages are cold.

Message to Patrick Dohan

Subject: Experimentation bias at scale — when the methodology is the product

Patrick — "architect how designers work in the future" is a specific mandate, and most companies soften it into tooling adoption. You paired it with "experimentation bias at scale," which reads as wanting someone who has already built the evaluation framework rather than someone who will survey the team on which AI tools they like.

I published that framework. Trust Is the New Interface maps five handoffs where human judgment stays in the loop as AI takes over more of the workflow, and I built a live demo in InsurTech quote automation that runs all five stages in a regulated context. As Head of Product at TinyFish, I shipped an enterprise agent platform from zero to production and worked through the adoption problems your XD org is about to meet: when does AI-assisted work need human review, and how do you scale that judgment across a large team.

Would 20 minutes make sense to talk about what the methodology looks like for a hundreds-person org?

Message to Daniela Jorge

Subject: Design judgment at scale when AI enters the workflow

Daniela — your Graded interview named the tension most design orgs skip: "keeping people at the center while considering both the value and the consequences." That is an accountability problem before it is a tooling one.

At Alibaba.com I led a platform redesign across $50B+ GMV, which meant diagnosing a structural gap the org had not named, building the mandate, and executing three cross-functional sprints to measurable outcomes (+20% daily transactions, +2.2pt NPS). Moving that fast at that scale carries the same institutional risk AI adoption does: judgment standards degrade a little at a time unless someone builds the accountability structure that protects them.

I have since published that structure. Trust Is the New Interface maps the stages where human judgment stays in the loop as AI takes on more of the work, and the trust ladder — Watch, Verify, Delegate — is a way to scale accountability alongside capability.

Would 20 minutes make sense to discuss how design judgment scales across a hundreds-person org adopting AI?

Resume Framing Note

Lead with TinyFish as the most recent role: Head of Product, enterprise web agent platform, Series A, 0→1 in three months, agent traces, auditability, governance. Frame it as the bridge back into design. Follow with the Trust essay and Carrier IQ as the methodology layer, which is what you would install here. Alibaba second, for org-scale change. Thermo Fisher third, attributed as Product Design Director at BCG Digital Ventures, for regulated-environment credibility. Trim Equinox+ and Allē to one line each. In the summary, borrow Dohan's vocabulary — architecting how designers work with AI, experimentation at scale. Avoid design systems framing; this role is about judgment standards, not component libraries.

Cover Letter Hook

Capital One's XD org is about to answer a question most design organizations avoid: when AI is in the design workflow, who decides what is ready to ship, and by what standard. I built the framework for that decision, published it, and deployed it in production, and the five-stage trust model maps onto the evaluation methodology a hundreds-person design org needs in order to adopt AI without weakening accountability for design judgment.

After sending (enterprise archetype). Five to seven business days for a response is normal. Past ten days, follow up; again at day 20. A recruiter screen and a hiring manager screen in the same week is a hot signal, so prioritize prep immediately. A request for work samples means high intent: prepare the Carrier IQ walkthrough at carrier-iq.junochen.com, framed as the methodology in action. Three unanswered messages across both routes and you redirect the energy.

Phase 4: Window Summary

September 22, 2026.