📰 Dev.to · JaviMaligno

I set out to reproduce a DeepMind result and instead found a clean way verification can lie to you: a code world model that passes its gate at 100% accuracy, st

Say the same thing to a language model far past what any human would tolerate, and the polished ones don't break — they quietly give up. Strip the alignment lay

Reviewing used to mean reading the implementation. Increasingly I verify what the model produced, not the path it took — and what 'verify the result' means chan

Before you write a judge prompt, you owe three decisions: the context, the unit, and the dimension. Here is the framework, applied to evaluating my production D

How I built an AI agent that investigates infrastructure issues autonomously — with read-only guardrails, output compaction, and infrastructure knowledge baked

How a simple question about vitamin D synthesis turned into a Claude artifact, then a full PWA with D3.js visualizations, push notifications, and 6 languages.

What we write is becoming markdown skills, what users see is becoming generated pixels, and the middle keeps getting thinner. A look at where software is headin

Why most AI-driven tests should be reproducible scripts, not CLI exploration — and how to use each approach effectively based on real deployment automation expe

How Azure's content filter blocks legitimate browser automation tools based on word choice, not actual risk—and simple workarounds that expose the flaw.

A workflow for running multiple Claude Code agents simultaneously on different features, using git worktree to manage branches and automating PR reviews.