Any experienced programmer worth their salt will tell you that •producing• code — learning syntax, finding examples, combining them, adding behaviors, adding complexity — is the •easy• part of programming.

The hard part: “How can it break? How will it surprise us? How will it change? Does it •really• accomplish our goal? What •is• our goal? Are we all even imagining the same goal? Do we understand each other? Will the next person to work on this understand it? Should we even build this?”

The effect of AI is to reduce the cost of •generating code• by a factor of X at the cost of increasing the cost of •thinking about the problem• by a factor of Y.

And yes, Y>1. A thing non-developers do not understand about code is that coding a solution is a deep way of understanding a problem — and conversely, using code that’s dropped in your lap greatly increases the amount of problem that must be understood.

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