publishing-expertise

Content here examines what happens when hard-won expertise gets written down, packaged, and shared, whether through documentation, courses, or AI systems trained on your work. The recurring theme is the gap between explicit method and tacit judgment: the steps transfer cleanly while calibration, context-reading, and know-when instincts often do not. Expect practical takes on capturing knowledge, spotting what surface-level copying misses, and protecting the parts that make expertise trustworthy.

Glowing head dissolving into particles that rebuild a hollow empty copy, showing what knowledge distillation loses.

knowledge-distillation, tacit-knowledge, model-evaluation, ai-expertise, publishing-expertise

What Actually Gets Distilled: Copying the Method Is Not Copying the Judgment

Knowledge distillation reliably copies a model's outputs and benchmark scores while losing the properties that made them trustworthy: calibration, robustness, and reasoning faithfulness. The same split applies to human expertise absorbed by AI systems -- your explicit method transfers cleanly, but y