VVamsi Krishna·Jul 18Day 56: Why evaluating the model is not enoughWhy evaluating agents means measuring the whole workflow users experience.3 min read·blog.vamsiannamreddy.com
DDr Hernani Costa·Jul 17You Don't Trust AI Output by Hoping It's Right, You Verify It With a Second AIHallucination fear blocks AI adoption. Learn how verifier and adversarial agents engineer trustworthy AI output before it reaches a customer or regulator.10 min read·radar.firstaimovers.com
LLearn with HJ·Jul 11Evals: Unit Tests for AI's Squishy BrainExplain offline evals, golden datasets, human grading, regression tests, and rubrics.6 min read·hardeepjethwani.hashnode.dev
VVamsi Krishna·Jun 20Day 28: Why weak evidence should trigger recovery, not confidenceWhy weak evidence should trigger recovery, not a fluent answer with false confidence.3 min read·blog.vamsiannamreddy.com
TTalvinder Singh·May 7AI-Assisted Peer Review Is a Feedback Loop Problem--- title: "AI-Assisted Peer Review Is a Feedback Loop Problem" description: "AI-assisted peer review systems fail because their feedback loops amplify bias without governance, not because of AI capabilities." date: 2026-04-17 categories: ['AI Qualit...6 min read·talvinder.hashnode.dev
AAnup Karanjkar·May 2Why Your AI Prompts Suck (And How to Fix Them Today)The most common prompt engineering mistakes with before/after examples. Fix these 10 errors and immediately get better AI output from any model.4 min read·wowhow.hashnode.dev
AAnup Karanjkar·May 2The Prompt Engineering Framework That Gets 9/10 Quality Every TimeThe CRTSE framework for prompt engineering that consistently produces professional-grade AI output. Detailed guide with before/after examples for every step.5 min read·wowhow.hashnode.dev
