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AI benchmarks are broken. Here’s what we need instead.

For decades, artificial intelligence has been evaluated through the question of whether machines outperform humans. From chess to advanced math, from coding to essay writing, the performance of AI models and applications is tested against that of individual humans completing tasks.  This framing is seductive: An AI vs. human comparison on isolated problems with clear […]

AI benchmarks are broken. Here’s what we need instead. Read More »

Fine-Tuning vs RAG vs Prompt Engineering 

AI demos often look impressive, delivering fast responses, polished communication, and strong performance in controlled environments. But once real users interact with the system, issues surface like hallucinations, inconsistent tone, and answers that should never be given. What seemed ready for production quickly creates friction and exposes the gap between demo success and real-world reliability.

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When AI Breaks the Systems Meant to Hear Us

On February 10, 2026, Scott Shambaugh—a volunteer maintainer for Matplotlib, one of the world’s most popular open source software libraries—rejected a proposed code change. Why? Because an AI agent wrote it. Standard policy. What happened next wasn’t standard, though. The AI agent autonomously researched Shambaugh’s code contribution history and published a highly personalized hit piece

When AI Breaks the Systems Meant to Hear Us Read More »

When AI Breaks the Systems Meant to Hear Us

On February 10, 2026, Scott Shambaugh—a volunteer maintainer for Matplotlib, one of the world’s most popular open source software libraries—rejected a proposed code change. Why? Because an AI agent wrote it. Standard policy. What happened next wasn’t standard, though. The AI agent autonomously researched Shambaugh’s code contribution history and published a highly personalized hit piece

When AI Breaks the Systems Meant to Hear Us Read More »