Evaluating LLM systems like production software
Most teams evaluate models. Very few evaluate systems. The gap between the two is where production failures live.
Tell us what you’re building and we’ll route you to the right team. Median first reply: under 4 hours.
Notes from production — LLM systems, cloud platforms and interfaces that had to survive real traffic. No newsletter filler.
Most teams evaluate models. Very few evaluate systems. The gap between the two is where production failures live.
Inference cost scales with success. The teams that model it before launch are the ones still running the feature a year later.
Twenty years of deterministic software taught people that the screen is right. Probabilistic systems break that contract.
Big-bang cutovers fail loudly. Incremental migrations fail quietly, early, and cheaply — which is the whole point.
Security controls that engineers route around are worse than no controls, because they create the illusion of coverage.
A prototype that proves the easy part proves nothing. Spend the two weeks on whatever could kill the project.
What we learned shipping AI systems, cloud platforms and interfaces that had to survive real traffic. No newsletter filler.