@ahmetcantryk
6 min read
LLM Structured Outputs: JSON You Can Trust
Field notes on getting reliable JSON from an LLM: schema modes vs tool-calling, Zod/Pydantic validation at the boundary, and the failure modes that still bite.
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Field notes on getting reliable JSON from an LLM: schema modes vs tool-calling, Zod/Pydantic validation at the boundary, and the failure modes that still bite.
Four levers — prompt caching, model routing, batch APIs, and context hygiene — stack to cut real LLM bills 50–70%, with a one-page cost-audit template.
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Model Context Protocol explained for 2026: MCP is now a Linux Foundation standard, and the July release candidate deletes the stateful session you learned.
Reduce LLM hallucinations in production with grounding, confidence gating, strict structured output, and evals — plus 2026 numbers on why the pipeline wins.
The five prompt engineering patterns that carry most production LLM work in 2026: role priming, few-shot, chain-of-thought, structured output, self-check.