Today I forgot an oncology checkup. Let's celebrate!
For the first time in over ten years, an oncology appointment slipped my mind completely. That's worth celebrating!
Thoughts on developer tools, infrastructure, building in public, and the art of using and building AI tooling. Join us as we share lessons learned, failures overcome, and the occasional rant about DevOps.
The head of Claude Code says his job is writing loops now. Fair enough. But there are at least five different concepts wearing that word right now, and the only question that sorts them is whether the context window survives the iteration.
The portal holds ten clonoSEQ results and every one of them is undetectable. The lab sent back the six earlier years, including one that went from 563 to 758,033. Both deliveries are complete, both are correct, and neither mentions that the other exists.
Everything up to the download automates. The download does not. And the gap between what a browser reports and what is actually on disk is where a pipeline quietly starts lying to you.
Epic will export your entire chart on request. The document it hands you first caps its results section at 200 entries, keeps the newest, drops the oldest, and says nothing about it.
The census said twelve health systems. Opening the portals one by one, twelve became seven, the hardest paper chase evaporated, and the record turned out to start seven years earlier than I thought.
I built a shared standards harness so Claude would follow the same rules across eleven repos. It had tests. The tests checked the harness, not the repos, and the first real audit came back with 34 failures. Then the standard started paying for itself.
I pointed an AI at seventeen years of my own medical records. It was confidently wrong three times before it was right once. No current AI untangles this alone.
TouchDown isn't a fantasy football tool. It's a teaching artifact, a working agentic team built on a framework everyone already understands. The football team model for agent orchestration, in working code.
Before extracting a single lab value, the project needed a census: who holds my blood work, from which years, and how each system expects me to get it back. The answer was about a dozen, and my inbox found them.
A decade of my blood work exists, scattered across ten health systems. I am going to collect all of it into one dataset I own. Part one: the plan.
A decade of blood draws scattered across four patient portals. Starting the project to collect them all took one paragraph typed into a chat box.
For years the AI coding tools didn't impress me. Then last October someone said the word 'Cursor,' and I haven't come up for air since. The honest inventory, with benchmarks.
Agentic coding didn't delete the work. It picked it up out of the middle of the pipeline and set it back down on the two ends. Same total, redistributed.
We curse hallucination as the cardinal sin of LLMs. It's the same property we praise when the model writes a test we didn't think of. The bug and the feature are one thing, pointed two directions.
The founder story I've been avoiding telling for years. A medical AI startup, a few hundred lessons, and where it all came apart. It's the reason I'm finally writing about agents.
Most prompts get treated like a Slack message to your past self. The ones that actually work get treated like code somebody else is going to read.
A first post. Twenty-five years in tech, startup life, strength training, leukemia, and a moment in AI I want to write about while it's still happening.
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