Never trust an LLM's output directly. Here's the validation layer I put on every

<p>For a long time the trick to force a model into JSON was to prefill the assistant turn with an opening brace. That trick is dead on the current Claude models. It returns a 400.

<h2> Introduction </h2> <p>Most LLM tutorials assume you start from nothing. A blank project. A clean architecture. No constraints. No legacy code. No deployment history. No

<p>Every developer who has worked with LLMs has been there. You ask the model for JSON. You describe the schema. You say "please only respond with valid JSON." And sometimes, it

<h1> How I Built an AI-Powered Code Review Bot That Saves 10 Hours/Week—Here's the Cheapest Way to Deploy It </h1> <p>My team was drowning. Every pull request meant 20-30 minutes

<p>Your agent tests pass. Your monitoring says "green."</p> <p>Meanwhile, your agent just hallucinated a refund policy, leaked a customer's SSN, and burned $2,847 in a token

<p>Last week my research agent failed at step 15 of a 30-step run. Langfuse showed me exactly where it broke. The writer sub-agent hallucinated, citing a stale 2019 population

<p>I shipped a structured-output endpoint to production in March. The schema was clean, JSON mode was on, the model was GPT-4.1, the eval suite was green. Three weeks in, the

<p>Deterministic agent tests become much more valuable when they are expressed as reusable quality gates rather than one-off assertions scattered across test files.</p> <p>A gate