OpenEval: Why LLM Evaluation Needs a Standard Format
Every LLM evaluation framework today invents its own test case format, its own grader definitions, and its own results schema. DeepEval, Promptfoo, In…
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Building AI Agents That Don't Hallucinate: Structured Workflows, Guardrails, and Per-Step Evaluation
Building AI Agents That Don't Hallucinate: Structured Workflows, Guardrails, and Per-Step Evaluation How we replaced fragile prompt chains with typed …
The Evaluation Debt You Don't Know You Have: Why Agent Evals Fail in Production
The Evaluation Debt You Don't Know You Have: Why Agent Evals Fail in Production By Paul Twist, Berlin | July 13, 2026 The Problem Nobody Talks About Y…
Evaluating Large Language Models: The Overfitting Problem
Introduction to Overfitting in LLM Evaluation We've all been there: you train a model, it performs exceptionally well on your test set, but when you d…
Agent = Model x Harness: Your Eval Layer Is Part of the Agent, Not a Tool Beside It
There's a formula I keep coming back to when people ask why their slick demo agent falls apart in production: Agent = Model × Harness The model is the…
What is an LLM evaluation harness? A deep dive into lm-eval-harness
What is an LLM evaluation harness? A deep dive into lm-eval-harness You fine-tuned a 7B model. It aced your smoke tests, your colleague ran a few prom…