Blog
Long-form analysis of how language models actually behave — written from the probe library’s own dated results rather than from vendor release notes.
Everything here is downstream of the probe library: an article exists because a run produced something worth explaining, and it links to the runs it is built on so you can check the reasoning against the raw output rather than taking the argument on trust. Where a piece makes a claim this site has not measured, it says so in the piece.
Is It Safe to Use a Cheaper LLM? A Developer's Guide to Verifiable AI Safety
For AI developers, the safety of a cheaper LLM hinges on rigorous, reproducible testing against specific tasks, not its price tag. Learn how to verify performance.
Dana Mitchell
How to Benchmark an LLM on Your Own Task: A Developer's Guide
Discover the definitive guide for developers on how to benchmark an LLM effectively for your specific, real-world tasks, ensuring reliable AI performance and preventing model drift.
Dana Mitchell
Are LLM Leaderboards Reliable? A Developer's Critical Guide
This guide critically evaluates the reliability of LLM leaderboards for production-grade AI development, highlighting their inherent limitations and advocating for robust, task-specific evaluation methods.
Dana Mitchell
The Best LLM for Structured Data Extraction: A Verifiable Guide
Selecting the best LLM for structured data extraction requires rigorous, task-specific validation, not just generic benchmarks. This guide details how to identify models for production.
Dana Mitchell
Do LLMs Get Worse Over Time? Unpacking Behavioral Drift
Discover the complex reality behind LLM performance changes. This deep dive for developers explains behavioral drift, its root causes, and robust strategies for detection and mitigation.
Dana Mitchell
Top Free AI Tools Online for Everyday Developer Tasks Guide
Top Free AI Tools Online for Everyday Developer Tasks are rapidly transforming how developers approach coding, testing, and data management, offering powerful capabilities without a financial barrier. This guide will explore how developers can leverage these free resources not just for convenience, but as essential components of a robust AI model validation strategy.
Dana Mitchell