Engineering notes on AI, ML, custom apps, and the messy bits of shipping production software.
A practical, ordered playbook for lowering production LLM costs. Prompt hygiene, caching, model routing, retrieval, budgets, and the measurement that ties it all together.
Hype free engineering principles for AI products that serve users, not nudge them. Grounding, refusal, evals, cost bounding, the boring decisions that actually ship.
A working model is not a working product. The full production ML stack, data pipelines, deployment patterns, monitoring, and drift detection.