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One part of me tries to resist and tell you that our craft is not becoming an archaic relic, the other half already knows you‘re right. We just can‘t put the ghost back into the bottle and now‘s a good time to re-calibrate your passion.
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I look at it like this: Yes, AI can write code. It can write it much faster than I can. Sometimes it can also write it better than I can.

But: programming languages, libraries, and abstractions are not going away. It is still possible (and might always be possible) to get deep into the weeds of Python or Rust or whatever to understand how those work and really harness them to their full potential, or develop them further. It just won't be _compulsary_ (in most industries) if your only goal is to trade lines of code for dollars in your bank account.

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> (the full impact of today's frontier models has yet to be felt by the general public - to say nothing of models that will be released in the next few years)

We definitely saw some kind of non-linear step function jump in quality around the beginning of the year - it's hard to express how good Claude opus/sonnet 4.6 is now. However, I wonder if we're going to see the same kind of improvement from here? It's kind of like we got to the 80% point but the next 20% is going to be a lot harder/take longer than that first 80% (pareto principle). Also, as more and more code out there is AI generated it's going to be like the snake eating it's own tail. Training models on AI generated code doesn't seem like it will lead to improvements.

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