Research and
retrospectives.
We publish when a decision is worth documenting.
These are not tutorials. These are not opinion pieces. These are records of specific engineering decisions we made in production AI systems, and what we learned afterwards.
- 2026-03 ApplicationComing
Context Engineering Is the Product
Teams building on foundation models keep discovering the same thing, six months into production: the model was never the bottleneck. What enters the context window was. This note is what we learned when we stopped optimizing prompts and started architecting context.
- 2026-02 MethodologyComing
Evals Before Prompts
Most AI applications are built in the wrong order: prompt first, eval later (or never). The correct order is the reverse — define what "good" means in measurable terms first, then write the prompt that satisfies the evals. We explain why this order matters more than it seems.
- 2026-01 FoundationComing
Model Routing as Architecture
"Which model should we use?" is almost always the wrong question. Production systems use multiple models routed by request characteristics. We discuss how we design routing, why benchmarks often mislead routing decisions, and how the routing layer itself becomes an application.