AI Infrastructure & Trust
What makes generative AI worth shipping, not just demo-able. Grounding, factuality measurement, evals, real-time data freshness.
Grounding · Factuality Agent · FreshServe · AI Search · Gemini
POSITIONING
Consumer product leader with the technical depth to build at the frontier. Twenty years driving acquisition, conversion, retention, and revenue — Amazon, Marriott, Walgreens, U.S. Bank — and four years at Google owning the grounding and factuality bar that generative AI clears to launch in the AI powering Google Search and Gemini. Next: consumer AI where the product is the AI.
A Claude-powered version of me, grounded on my real career. Ask about the Google work, the consumer launches, or whether I'm a fit for your role — then email the real me. Five questions per session — ask the good ones.
Hey — I'm a Claude-powered version of Adam, grounded on his real career. Ask me anything, or tap a starter below.
In May 2024, AI told users to put glue on pizza and eat rocks. Since then, teams like mine at Google have built the infrastructure that prevents that category of failure. Here's what grounding actually does — toggle between the two states.
Grounding is how AI learns to cite its sources. The left side is what a model says from training alone. The right side is what happens when that same model is forced to answer from verified, real-world sources. My team builds the measurement layer that tells us which is which, at scale.
Four projects where I owned the outcome — AI grounding & factuality at Google, a new-venture consumer launch for Marriott, a loyalty-meets-health platform at Walgreens, and a global marketplace at Amazon. Use the arrows to move through them.
Five additional projects from Google and Publicis Sapient — platform reliability, ML personalization, a national grocery partnership with Google Cloud, a customer data platform, and a top-ranked mobile banking app.
What I think the job of product manager has become — and what's about to become rare enough to matter.
What changes when software is no longer the bottleneck
The cost of turning an idea into working software has collapsed in 18 months. A PM with good judgment and a working AI workflow can prototype, test, and refine ideas at a pace that used to require an engineering pod. I know because I do it.
Here's what actually shifted: in under a year, autonomous agents went from breaking after three minutes to running unsupervised for a full workday. That's a phase change. The PM job quietly stopped being about issuing instructions and started being about architecting the systems agents run inside.
Tools you can learn in a weekend. Product sense and execution are the work of a career.
"Anyone can swing a hammer. Very few people can produce finished carpentry. Craft is still the job."Read the full essay
A mental map of twenty years — four themes, not a list of jobs. Every role I've had sits in one of these buckets.
What makes generative AI worth shipping, not just demo-able. Grounding, factuality measurement, evals, real-time data freshness.
Grounding · Factuality Agent · FreshServe · AI Search · Gemini
Taking ML from the lab into products people actually use every day.
Albertsons · Marriott · Walgreens · U.S. Bank · Amazon · Aetna
Shipping for millions when reliability and polish are the whole product.
Amazon Appstore · Amazon Kindle · Walgreens · U.S. Bank · Merrill Lynch
Building the function, not just working inside it — across retail, healthcare, financial services, and telecoms.
Publicis Sapient · KPMG · Razorfish · BearingPoint
Outside of work, I DJ under the name Bigfoot. Twenty years of digging through crates and playing sets around New York. Tell me a vibe and I'll find you something to play.
Recommendations are pulled from my Last.fm scrobble history — twenty years of every song I've actually played. Each result comes with a Spotify preview.