Lesson 4b - Validation: Testing the gate itself

<h1> My Exit Rule Said '2 Periods' — My Code Was Counting Something Else Entirely </h1> <p>My funding-rate bot has an exit rule that reads like plain English:<br /> </p> <div

<h2> The Asymmetry of Change: Why Your Tests Are Looking the Wrong Way </h2> <p>A passing build is often treated as a certificate of correctness. In reality, it's a narrow

<h3> Intro </h3> <p>There's a pitch behind every "AI writes your tests too" workflow: more coverage, less manual toil, a safety net that used to take a sprint now takes

<p>On January 28, 2026, Moltbook launched to considerable fanfare. The pitch was bold: an "agent-first, human-second" social network where 1.5 million autonomous AI agents could

<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1s1ckkm/why_llms_sound_right_but_fail_to_actually_do/"> <img alt="Why LLMs sound right but fail to actually

<p>Most companies shipping AI have never once tried to break it.</p> <p>Not because they don't care about security. Because they assume the model handles it. The model was trained

<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>The gate was a fixed 90% threshold on an intent-classification eval. The change came in at 91%, cleared the bar, went out. A fixed pass-rate gate catches collapses, not drift.