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__mharrison__ • today at 10:17 PM • 1 reply • view on HN

As an educator and author, I feel Molly's pain (Anthropic owes me $60k for pirated books). My course and book sales have dropped significantly. I feel like much of the value in my book-based knowledge is harder to discover in AI agents. (One example might be inspecting SHAP values from XGBoost models and using that as feedback to feature engineering for a linear model (like Logistic Regression)). So I'm afraid more advanced techniques might go by the wayside in the name of delivery speed.

I use AI both in the cloud (I tend to avoid Anthropic...) and with local models.

I've probably written more code in the past year than in my whole career. I can now create what I desire (I just created a telemark skiing game over the weekend based on my Strava segments). I think this has helped my teaching as well. In a recent ML course, I created many interactive examples that in the past were just doodles on my whiteboard, but are now embedded in the notebooks I give students.

I've also taught a few AI courses to clients as well. However, with the inevitable rust/ASM-ification of everything, I'm not sure how long those skills will be valid. I do, however, think that having a human in the loop for ML and data analysis is still important.


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curt15 • today at 10:25 PM

The people reaping AI's benefits today generally developed their skills as juniors through old-fashioned struggling in the pre-ChatGPT era -- actually reading docs and articles, trial and error, puzzling over mysterious bugs, and generally doing lots of mental lifting.

How will skill building happen when LLMs and coding harnesses seemingly provide all the answers at one's fingertips?

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