LLM engineering
30 posts
Why LLM Outputs Fail in Production-and How to Fix It
Non-deterministic LLM behavior leads to silent failures in production when outputs aren't validated. Learn how structured validation prevents cascading errors in real-world systems.
Why AI Systems Fail in Production - And How to Fix It
AI systems fail in production not because of poor models, but due to uncontrolled inputs and unchecked outputs. Learn how deterministic validation and structured pipelines ensure real-world reliability.
Why Most AI Automation Fails in Practice - And How to Fix It
Most AI automation fails in practice because it redistributes effort rather than eliminating it. Learn how to build systems that actually reduce human workload through bounded domains, structured outputs, and rigorous pre-rollout validation.
Agents Need Orchestration
Managed agents aren't plug-and-play. Real reliability comes from structured pipelines with validation, state tracking, and fallbacks-no exceptions.
Claude Code's System Prompt Is a Production AI Agent Blueprint
Claude Code's system prompt is a working engineering spec for production AI agents. Six concrete patterns for context isolation, tool selection, parallelism, error recovery, memory, and blast radius management.
The Real Architecture Behind Reliable AI Systems
Reliability in AI systems comes not from smarter models or autonomy, but from deterministic control, validation, and predictable failure recovery-patterns already proven in real-world production environments.