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Back to Applied AI Engineering
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Phase 9

Production AI Engineering & LLMOps

Observing what a non-deterministic system is actually doing, measuring quality with real evaluation instead of vibes, controlling cost at scale, and layering security guardrails before a wide launch.

1

Observability, Tracing & Debugging

Why 'the bot gave a confusing answer in 14 seconds' is undebuggable from a final log line, and what tracing every span of an agent request actually captures.

observabilitytracingdebugging
2

Evaluation Frameworks: RAGAS & LLM-as-Judge

A prompt tweak shipped two weeks ago — did it help or quietly make things worse? Turning that question from a guess into a measurement.

evaluationragasllm-as-judge
3

Cost Optimization & Model Routing

The bill is growing faster than usage justifies — prompt caching, semantic caching, and routing simple requests away from the expensive model.

prompt-cachingsemantic-cachingmodel-routing
4

Security, Reliability & Guardrails

What a pre-launch red-team exercise finds that ad-hoc defenses miss, and how to layer input/output guardrails and graceful degradation before a wide rollout.

guardrailssecurityreliability
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