The real value of AI coding models isn't speed — it's lowering the barrier to doing things you'd otherwise skip
By
@ayende
Summary
The article argues that the true value of AI coding models isn't their speed at generating code, but their ability to make previously expensive or impractical tasks suddenly feasible. The author illustrates this through three real-world examples from their week: debugging a production issue by having a model analyze 25-30 MB of logs, using a model to write a complex SQL query for a one-off data analysis task that wouldn't have been worth the manual effort, and leveraging the model to refactor legacy code that had been too risky to touch. The core thesis is that the best metric for coding models is not code generation speed but the reduction in "activation energy" required to tackle valuable but marginal-effort tasks.
Source
bskyThe real value of AI coding models isn't speed — it's lowering the barrier to doing things you'd otherwise skipayende.comKey quotes
· 3 pulledThe story isn't about how fast the model writes code I would have written anyway. It's that the model lets me do things that I might have done before but were expensive enough that I didn't bother.
We had a production problem on an instance and no clear idea what was going on. What we did have was the log: something like 25-30 MB of compressed text describing everything that happened.
The best code is the one you shift+delete — because it means you solved the problem without adding permanent complexity to your codebase.
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