12-part series

From Demo to Product

The AI Product Engineer's discipline: turning a working AI demo into a product a business can depend on.

The Afternoon and the QuarterWhy an AI demo takes an afternoon and an AI product takes a quarter, and what lives in the gapJuly 25, 20265 minJuly 25, 20265 min
AI Is Not a MoatThe model is electricity, not the factory. What actually makes an AI product defensible.July 25, 20266 minJuly 25, 20266 min
Evals Are the Product Discipline (and Writing Them First Backfires)Why eval-driven development done like TDD fails, and what error-analysis-first evaluation looks like insteadJuly 25, 20266 minJuly 25, 20266 min
Does Your Problem Even Need an LLM?The fit gate to run before you build, and what to do when the answer is noJuly 25, 20265 minJuly 25, 20265 min
Treat the Model as a Flaky, Expensive DependencyThe vendor changes pricing, retires models, and swaps tokenizers under your live product. Wrap it accordingly.July 25, 20265 minJuly 25, 20265 min
Ship on Containment, Not PerfectionHow to expose a non-deterministic feature to real users safely, without waiting for a flawlessness that never comesAugust 2, 202612 minAugust 2, 202612 min
LLMOps and the Data FlywheelLaunch is the start of the work. How you operate an AI product, and how production usage compounds into a moat.August 2, 20268 minAugust 2, 20268 min
The Unit Economics of an AI ProductEvery request costs real money. Why the unit is cost per task, not per call, and how to keep it profitable.August 2, 20268 minAugust 2, 20268 min
Detect, Contain, Monitor: The Risks That Sink AI ProductsYou do not eliminate AI-product risk. You bound the blast radius and watch the rate.August 2, 20267 minAugust 2, 20267 min
Who Owns Quality: The Benevolent Dictator and AI Incident ResponseOn an AI product, quality is a judgment call that needs one owner, and an incident whose postmortem output is a new eval exampleAugust 2, 20269 minAugust 2, 20269 min
The Reference Architecture for a Production AI AppThe model call is one box out of ten. The other nine are the engineering.August 2, 202611 minAugust 2, 202611 min
Designing UX for a Confidently-Wrong InternTraditional UX assumes the system is correct and fast. An AI feature is neither guaranteed. Design for that.August 2, 20267 minAugust 2, 20267 min