Azeem Azhar

And if you think back to the

Wharton HBS BCG paper study from a year or so ago, what it showed was that people who were of below average competence were getting better improvements than those who are top quartile, which could proxy in software development to junior and senior.

So what's going on here?

AI autocomplete tools are skewed with juniors.

Senior developers are much more likely to accept

AI generated code than junior developers.

The reason we'll get into in a second.

When the academic looked at one particular company and they made AI agents the default, code output jumped by about 39%.

there was a difference in the way the developers approached it.

So experienced developers were much more likely to ask the AI to help them plan before starting coding.

So they were going to ask for the AI to do that architectural work with them.

And then they were more likely to accept the code that was presented.

Whereas junior developers were much more likely to go straight into implementation.

And if you've worked with developers before, if you've written software before, you know that thinking through your plan is a surefire way to get the project done more quickly.

I mean, if you literally just pop open your code editor and start typing, that's probably a recipe for mangled code, lots of bug fixes and late nights.

And so in a sense, what it's showing is that where the experienced workers are benefiting is that they have better mental models of both the code base of what they want to do and how AI can help them.

And what's happening there is agents are shifting programming from typing syntax.

And, you know, that was my downfall is when I used to develop in Java, I would always get my syntax slightly wrong, specifying the semantics.

And so the new skills that are needed are abstraction and clarity and evaluation.

You need to know what to ask for, how to ask precisely, how to judge what comes back.