Product Leader @ Holmusk | Data Products, Healthtech, Consulting | MBA @ Kellogg | MicroSaaS +SwaS
From BI to AI, the interface is changing and the data team's responsibility is getting wider: preserve the foundations, add workflow context, and stop when the system cannot support a trustworthy decision.
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AI can produce dashboards in seconds. Healthcare data leaders still need a way to decide what deserves to be built and prove it creates value.
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Intelligence is getting cheaper. Coordination is not. Role Operating Systems close the gap between individual productivity and team execution.
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A practitioner's guide to governed objects, executable data contracts, stewardship that ships, and why catalogs won't save you in the agent era.
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Part 2 of 5: The 15 principles that form the foundation of the Data Product Operating System. Seven philosophical beliefs about how data products work differently, and eight strategic principles for making decisions.
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Part 0 of 5: The Problem. The first dashboard I built at HCA got opened four times. Total. Not four times a day. Four times ever.
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Your day looks like this: standup, sync, planning, review, requirements. Somewhere in there you're supposed to actually analyze data. The system was designed for software teams, not data teams. DPOS fixes that.
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I spent four years in the Navy not as a pilot, but as the person telling pilots where to go. The E-2C Hawkeye is an unglamorous aircraft. No missiles. No guns. Just a massive radar dome bolted on top and a crew inside watching screens. While fighter pilots got
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Last week I read Peter Yang's "25 Things I Believe in to Build Great Products." 25 Things I Believe In to Build Great ProductsWhat I believe in is often the opposite of how big companies like to workBehind the CraftPeter Yang His first principle? "Speed
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Last Thursday at 3pm, I coached a PM through her first 30 minutes in Claude Code. She'd never touched a terminal. By minute 7, she stopped being scared. By minute 20, she was synthesizing customer feedback across 12 call notes—something that used to take her half a
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It's 10:47am on a Wednesday. In the last 47 minutes, I've switched contexts six times: Reviewed a dbt pull request changing how master_person_stats.total_psych_visits is calculated * Debugged why the exec dashboard shows different numbers than Marketing's report * Analyzed a
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"Your gut is the world's most sophisticated machine learning model ever created." - David Lieb, General Partner at YC The $2M Dashboard That Nobody Used Three months into my role at a healthcare analytics company, our CEO pulled me aside with a problem. We'd just
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Three months ago, I watched a senior PM at a healthcare company spend two hours "collaborating" with ChatGPT on market analysis. The conversation meandered through competitor research, customer interviews, pricing models, and go-to-market strategies. At the end: 47 screenshots, three different documents, and no clear next
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The best way to look at a problem is not to view it as a problem at all but as an opportunity to grow stronger, more skilled, more confident. - John C. Maxwell The Continuous Sprint Dilemma Six months into leading Revive's data product team, I faced a familiar
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A product manager recently shared their breakthrough on LinkedIn after completing Shreya Shankar & Hamel Husain's AI Evaluation course: "Been hunting for repeatable frameworks for building AI products as a PM. The problem: AI products are non-deterministic by nature. Manual testing doesn't scale. I
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