Pablo Albaladejo

Writing

Notes on making AI work in production — LLM evals, observability, agentic development, and GEO. Every claim links to a verifiable artifact.

A 90% pass rate is not a gate: four criteria, two thresholds
A tolerant OAuth server validates your broken client
Evaluating LLM outputs in production: 22 benchmarks, a 90% gate
Shipping production software with AI agents
GEO: how AI agents find you — a same-day case study
Observability for LLM pipelines: from streams to sinks

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Writing on other platforms.

Stop Chatting, Start Specifying: Spec-Driven Design with Kiro IDE ↗ Kiro blog
Observable AI Streaming on AWS ↗ dev.to · 4-part series