Site check, June 30, 2026
junochen.com homepage is live. Agentic Labs portal shows four named systems in the carousel (Carrier IQ, UAT Sentinel, Retail Velocity, Brand Pulse); portal copy still reads "three live agents." Trust Is the New Interface is live with the five-handoff framework and watch-verify-delegate ladder intact. Alibaba, Thermo Fisher, Red Cross, Equinox+, and Allē case studies remain published. Everything below references only what's live on the site right now.
Update the portal copy to "four" before sending any message. If you can't push that change today, lead outreach with system names rather than a count. A recipient who clicks through and sees "three" when you wrote "four" will notice, and at this level, small credibility cracks compound.
The principle both of these companies share
Capital One and Suno have almost nothing in common. One is a regulated financial institution with a mature design org. The other is a venture-backed creative-AI startup valued at $2.45B. But the buyer at each company is solving the same category of problem: how should humans interact with agentic AI systems in ways that produce trust, and not just output?
For that buyer, standard portfolio logic works against you. Leading with your strongest case study tells them you've shipped good product design. They already assume that. Every candidate at this level has shipped good product design. They need to know whether the person they hire has already lived inside the design-AI integration problem and come out with a working model. A resume scan can't tell them that. At Capital One, the fear is transformation risk: installing AI workflows across a large design org that designers resist or that produce worse outcomes than the processes they replace. At Suno, the fear is trust miscalibration: building creative tools where the AI's capability feels extractive rather than empowering. The Trust essay directly addresses both fears. Case studies address capability, which the buyer answered by scanning your background before you entered the conversation.
Juno, internalize this as a reusable heuristic. Any time the buyer is hiring someone to change how their org or product relates to AI, your published framework and live systems outrank your case studies as lead credentials. Case studies prove you can operate at this level. The framework proves you've already thought through the specific problem they're trying to solve, and at this level, that thinking is what's scarce.
Capital One R243245, Director of Product Design, AI in Experience Design
Priority: Act this week. Role is confirmed live.
What the posting tells you
The R243245 role posted May 28. It has been live for roughly a month. It sits in the XD "top of house" team and partners directly with the SVP and Chief Design Officer and their senior leadership team. The scope: AI tooling roadmaps, design process evolution, AI-centric talent upskilling across the design organization.
Read that scope again. This is an organizational transformation role wearing a design director title. The buyer wants someone who can change how designers work.
Confidence flags: The posting names the CDO partnership but does not name the individual. Capital One's leadership pages returned 404 during this research pass. I cannot confirm who holds the CDO title. Treat the CDO as the primary buyer and expect product and engineering leaders on the panel. Do not cite a specific designer headcount in outreach; if scale surfaces in conversation, reference the scope implied by the role rather than anchoring to an unverifiable number.
Why the Trust essay is your operating model here
The five-handoff framework (Intent-Setting, In-Progress, Output Review, Decision Gate, Loop Feedback) maps directly onto every Agentic Labs system you've built. Make this connection explicit.
Carrier IQ uses structured intake and canonical interpretation before agents execute. Intent-Setting. UAT Sentinel shows parallel browser agents running in real time with visible progress — In-Progress transparency designed to build confidence before results arrive. Retail Velocity surfaces displacement scores, confidence levels, and opportunity framing so a field team can act without redoing the agent's analysis. Decision Gate. Brand Pulse exposes source counts, sentiment direction, and platform coverage rather than collapsing everything into a single number. Output Review with traceable provenance.
The watch-verify-delegate ladder from the essay describes how users build trust through repeated interaction loops. Every one of these systems is designed to make that ladder climbable.
Capital One needs to hear this stated plainly: you have a design operating model for agentic systems, you published it, and then you built four live products that implement it. The theory and the artifacts are one body of work.
The solo-to-scale bridge
The predictable objection. You built these systems alone. Capital One needs someone who can install this thinking across an organization at scale.
Your framing: Solo-building four agentic products from concept through live deployment means you encountered every handoff failure mode firsthand. You designed the intake patterns, watched them break, redesigned them, shipped the fix. That produces a deeper understanding of what transfers to a large design team than managing people who adopted someone else's AI tools and reported back.
The specific language:
"I built these solo because the design patterns for agentic trust didn't exist yet. Now they do. The next step is installing them as process and craft standards across an organization. That's this role."
This reframes solo work as R&D that produced transferable methodology. The published essay is what makes the reframe hold. "I built things alone" reads as IC preference. "I built things alone and codified what I learned into a published framework" reads as someone who generates institutional knowledge. The essay is the difference between those two readings.
Regulated-environment credibility
Capital One's design org operates under regulatory review processes that most design candidates have never encountered. When the conversation advances past the first screen, Thermo Fisher becomes your proof that you've navigated compliance-heavy environments where design decisions carry regulatory weight. Financial services and life sciences share the structural constraint: design choices are auditable, not just user-facing. That parallel is specific enough to be useful without overstating it.
Outreach starter
I've spent the past year building a design operating model for agentic systems and shipping four live products that implement it (junochen.com). The model is a five-handoff framework for how humans should oversee, verify, and trust AI-driven workflows, and the R243245 role reads like the organizational-scale version of exactly that work: AI tooling roadmaps, process evolution, talent upskilling. I'd welcome the chance to discuss how the model translates to Capital One's design org.
Do not lead with Alibaba or Thermo Fisher. If the conversation advances, those become your proof of enterprise navigation and regulated-environment credibility.
The role has been live a month. Holiday week compresses everything. Send Tuesday or Wednesday morning. Thursday and Friday are dead zones with the observed holiday Friday and the Fourth on Saturday. Decision-makers at companies this size often use pre-holiday days to clear hiring queues. A well-timed message this week lands in a quieter inbox than anything sent July 6.