[JoshuaDavid]

I read the argument as "the hard part of software engineering is understanding the codebase and the world well enough to turn a description of a desired change in how a system should act into a diff that actually changes the system behavior in the intended way (and only in the intended way), not taking clear requirements and turning them into fresh code".

Of course humans aren't exactly great at that part either. But I do think I'd bet against, within the next 4 years, an AI tool being able to take tickets in the form

1. Expected behavior

2. Observed behavior

3. Steps to reproduce

and produce a changelist that legibly fixes the problem, and does not break anything else, at a level better than a typical junior software developer. I think the ability to do that is probably AGI complete.

[izzygonzalez]

I think you’re right that code models are a vital research path toward AGI.

The steps you elucidated are all expressible in natural language, and we see models like Codex Edit making headway there. One of the most fascinating parts of this is that once access to the known baselines are provided to high-level engineers, they then go on to do much more than what the models alone can do.

The main hinderance to enterprise was compliance but the move toward Azure, etc, will dissolve those barriers this year.