Tech

Scale a web app by measuring the real constraint, making the smallest useful change, and recording the new guarantee and failure mode that change introduces.

An AI coding spec is a plain-English plan for what the agent should change, what it must not touch, how success is checked, and when a person steps in.

AI evals are repeatable tests of whether a specific AI system can handle realistic cases, respect important boundaries, and keep working after it changes.

A vector database helps software find similar meaning across text, images, and other data. Here is the plain-English mental model, the system behind it, and a practical path from prototype to reliable product.

RAG can help an AI agent find the right evidence. Safe action also depends on shared meaning, connected operational state, explicit constraints, narrow permissions, and human-owned controls.

AI has made it easier to produce code. Reliable software still depends on five human disciplines: clear intent, strong boundaries, small changes, executable evidence, and ownership.