This is the implementation half of the blog. Model APIs and their differences, prompting techniques that survive contact with varied input, retrieval and embeddings, structured output, streaming, caching, cost control, latency, and the deployment questions that follow once something needs to run for other people.
The posts assume you would rather see the mechanism than a summary of it. Where a technique has a failure mode, it gets described: what it looks like when it breaks, why it breaks, and what you can check. Where a tool is genuinely new enough that the answer may change, that is stated rather than papered over, because writing about this stack means writing about a moving target.
Topics range from small and immediately useful — token counting, retries, schema validation on model output — to larger architectural pieces on how retrieval systems are laid out and where they degrade as the corpus grows. Code is included where code is the clearest explanation, and left out where it would only be ceremony.
If you are building something end to end, these posts pair with the agents category for orchestration and with strategy for deciding whether the build is worth doing in the first place.
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