LLM evaluation: build an eval suite and gate deploys in CI
LLM evaluation, step by step: define failure modes, build a golden dataset, choose metrics, run an offline suite, compare to a baseline, and gate CI.
11 min readEvals and observability
Loops that let a model call tools, keep state, and work toward a goal. Framework comparisons, orchestration patterns, and failure modes you will hit in production.
LLM evaluation, step by step: define failure modes, build a golden dataset, choose metrics, run an offline suite, compare to a baseline, and gate CI.
11 min readEvals and observability
What is an AI agent? A tested agent loop in TypeScript, run offline against a scripted model, with traces of runaway loops, tool errors, and token growth.
9 min readAgents and frameworks
Context engineering is choosing what a model reads on each call. Size each section, order it for prompt caching, trim inputs, and test every layout change.
11 min readPrompting and context
What is an MCP server? Build a tested TypeScript one with a confirmed write tool, debug it with MCP Inspector, and apply the spec's security requirements.
12 min readMCP and agent protocols