Field notes on RAG, evals, agents, and LLM cost.
September 10, 2026 · TokenTailors
MCP makes it trivial to hand an agent thirty tools. Tool selection accuracy, schema discipline, permission boundaries, and how to measure whether the agent calls the right thing.
Read moreAugust 11, 2026
Most LLM cost problems are visibility problems. Per-feature token accounting, caching, model routing, and context discipline — with evals proving quality held.
Read moreJuly 20, 2026
A framework decision is an engineering decision, not a loyalty test. The signals that LangChain is costing more than it saves — and how to exit safely where it is.
Read moreJune 22, 2026
Checkpointing is the LangGraph feature that separates production agents from demo loops: resumable state, human-in-the-loop pauses, and replayable failures.
Read moreMay 18, 2026
You do not need a benchmark or a labeling team to start evaluating an LLM app. Fifty real traces, honest labels, and a runnable harness beat both.
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