Logan Hutchinson

• 95% — Payer Acceptance Rate on AI-generated Appeals
• 1000+ — Headcount Organization Served in Production
• 60% — Reduction in Manual Appeals Processing Time

Knowtion’s internal teams each used AI differently, with no shared standard. Engineering, product, service delivery, training, and sales operated in silos, creating duplicated effort and a gap between what the company sold externally and how it operated internally.

Led company-wide Claude standardization: mapped team-specific use cases, built internal prompt standards and model cards, and developed a responsible AI framework presented across all functions with CEO and CTO alignment.

Established Claude as Knowtion’s default AI layer across five teams, reducing documentation and drafting overhead while strengthening external credibility with prospects who need confidence their AI vendor operates what it sells.

• Led the effort to establish the first product management practice at a Series A startup that was named one of Silicon Valley’s hottest startups in 2017. The company has grown to be valued at over $75 million.
• Set up product management best practices across the company, including roadmap development, formal requirement gathering, analysis, and build-out
• Built companies first with a product planning group to review business needs and prioritize requirements to better sync with stakeholders.
• Developed formal go-to-market, MRD, and PRD templates.
• Coached younger PMs and engineers on best practices.

• 2 — Secure Pilot Programs Deployed to Top 5 Pharma Brands
• **6 Months ** — End-to-End Consulting Engagement Across Healthcare and Automotive Verticals

BEN had a powerful multimodal AI platform (ELM) but no clear path into regulated healthcare and automotive markets. Top 5 pharma brands and national pharmacy chains demanded enterprise-grade security, healthcare data compliance, and proof that avatar-based AI agents could handle sensitive consumer interactions at scale without introducing regulatory or reputational risk.

• Led product strategy and pilot architecture across healthcare and automotive for over six months.
• Designed secure, compliant deployment frameworks for avatar-based digital agents tailored to pharma-grade data governance.
• Scoped use cases, defined success criteria, and built repeatable pilot playbooks bridging BEN’s core AI technology to Fortune 500 enterprise buyer expectations.

Deployed secure AI pilots to top 5 global pharma brands and leading national pharmacy chains. Established a repeatable pilot framework across healthcare and automotive, directly strengthening BEN’s enterprise credibility in regulated markets.

Cruise is building the world’s most advanced self-driving vehicles to safely connect people with the places, things, and experiences they care about. As a leader of the mapping product team, I was responsible for the internal navigation systems that are the brains behind the vehicle.

I was one of the first product managers working on the contract. We built the program from scratch and gained 70% adoption from the beta group in year one. We incorporated feedback from the beta program into the core app.

The product was in the cybersecurity and identity management market and was a direct competitor to companies like Okta and Sailpoint. I helped them create a strategic product plan and go-to-market plan after the technology was built. We crafted a monetization strategy and MVP test plans.

• 92% — Task Completion Rate Across Core Shopping Flows
• 94% — Catalog Retrieval Accuracy vs. Gold Dataset
• 0 — Hallucinated Prices, Policies, or Discounts in Demo
• 5 — Prospect Demos Delivered in 6 Weeks

CPS Industry and AWS needed a demoable agentic commerce solution to win enterprise prospects—built in 6 weeks, with the demo itself as the GTM asset. The risk wasn’t engineering; it was trust. An assistant that hallucinates pricing, policies, or discounts ends an enterprise sale in the room. No proof point existed, no clients signed—one shot to land it.

Owned PM delivery, CX design, evaluation strategy, and stakeholder alignment. Partnered with engineering on a multi-agent architecture (orchestration and catalog, decision, execution agents) on AWS Bedrock, Lambda, API Gateway. Drove an evaluation-first approach: a gold dataset and regression tests grounded every query in the system of record, to eliminate hallucination risk. Tied AI metrics (intent accuracy, task completion) to commerce KPIs (conversion, AOV, cart abandonment) so trade-offs were legible. Ran usability tests in week 4 and authored a customization playbook for AWS Marketplace.

Shipped the end-to-end assistant in 6 weeks: 92% task completion, 94% retrieval accuracy, zero hallucinations. The customization playbook made it repeatable, opening 3 prospect demos and validating AWS Marketplace as a scalable GTM channel.