This page and its repo are the demo, not a description: Claude Code, wired to GitHub, an agent-built page shipped with its own automated eval suite. Below, every claim about fit against your JD is scored the same way your team is asked to score AI output: pass, adjacent, or disclosed gap. Not asserted.
Your JD asks for someone who sets up the modern AI dev stack themselves and shows the path instead of describing it. Here is the actual repo, public, with a real commit history and a real automated eval suite gating every change.
Every change in this repo went through the same agentic workflow the JD describes: prompted, built, committed, pushed. Open the commit history yourself.
A zero-dependency eval suite: document integrity, accessibility, brand rules, and a live parity check against the deployed page.
Read the posting, built the case, shipped a tested, deployed page. The cycle-time reduction your Year One outcomes ask for, demonstrated on this application.
Six claims, pulled straight from your JD's own experience profile and outcomes. Each one scored against the real record, with a citation, not a highlight reel.
Led transformation at scale, on an existing org, not a greenfield build. Scaled a 45+ person group across four practices, hired and developed a new manager layer, and cut the time to get a new team to its operating baseline from a quarter to days. Delivered a full status-program relaunch end to end, migrating 9M+ members, on an 89-year-old airline that had never done it this way before.
cite: the record, belowHands-on with the modern AI stack, not delegated. Claude Code wired to GitHub, agentic build workflows, a real eval suite gating every commit. This page and its repo are the proof, not a claim about a proof.
cite: the repo, aboveCross-functional executive influence without formal authority. Business champion for an 18-month redesign of the digital product operating model, from funding through ways of working, run in partnership with a global technology consultancy. Sits on the enterprise transformation council redesigning the end-to-end marketing value stream, in partnership with a global strategy consultancy. Both required moving CTO, CPO, and segment-leader stakeholders who reported to no one on my team.
cite: executive highlights, CV on requestPublic technical thought leadership. Keynote speaker on AI for builders and executives (AIAI Toronto), speaker on the AI-native product workflow (AI Product Summit Toronto), and an active BrainStation instructor for the AI Product Management Certification and AI Agents workshops. Teaching the exact uplift this role asks for, already, to people who aren't my own team.
cite: capability uplift, belowAI-native product experience, internal not customer-facing. I built and run the operating model where agents draft PRDs and user stories, prep executive reporting, audit initiatives, and plan capacity, in daily production use across my team. That's real agentic engineering, shipped and operated, not prototyped and shelved. It's an internal operating system, though, not a customer-facing AI product like the ones your JD's preferred companies ship. The discipline transfers; the audience was different.
cite: the repo, above; joseplatero.comOrg scale and company pedigree don't match your preference exactly. Your JD prefers someone from a 200+ PM organization at a specifically AI-native company. Mine is 45+ people across product, design, martech, and adtech, at a 89-year-old airline, not a 200+ PM-only org, and not on your named list. I also haven't done the founder or early-employee stage of an AI-native company that scaled. What I have done is pull an existing, non-AI-native organization through exactly the transformation you're describing, at meaningfully smaller scale. If that scale gap is disqualifying on day one, better to know now than in month two.
cite: none. this one's just trueYour Year One outcomes ask for AI fluency and agentic design uplift across 400+ PMs. I've already run versions of this curriculum, live, for people outside my own reporting line.
Plus workshops in AI Agents, AI for Designers, and rapid prototyping with Figma Make. Curriculum, not a one-off talk.
Speaking to both audiences at once is the same muscle this role needs: sell the future to executives, then pair with the engineer who ships it.
The exact demo this page is built from: agentic PRDs, executive reporting, and capacity planning, shown to a room, not just my team.
Mentoring the next cohort of product leaders before they're on payroll anywhere.
The same record the scorecard above cites from.
This came from chatting with Jose Platero who demo'd his workflow of connecting Jira with Claude via MCP to generate an executive insight report as a skill. I wanted to automate the workflow entirely so it did not have to be prompted and would run without me present.
One idea I'm particularly excited to explore came from Jose Platero's session on MCP integrations. The possibility of connecting tools like Jira to create executive-friendly reporting is a practical use case that I can see bringing real value within organizations.
Everything above is one scored run. joseplatero.com is where the operating system lives: demos of the same agentic workflow this page came out of, the origin story, and what people write after the talks, unedited.
Watch the agents workTwenty-five minutes on how I'd run the first ninety days: what ships week one, what the eval framework looks like for a 400+ PM org, and where the disclosed gap stops mattering. No prep required on your side.
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