"Entry-level coder": an AI can be given natural language descriptions of coding tasks (emails, issues on a tracker, a spec, etc) and go through the full "just out of undergrad" coding loop: branch/fork, make edits, write tests, submit PRs, go back and forth with managers about testing / requirements, etc.
If extra infrastructure to enable the AI (e.g. tooling to let it work with CI) has to be built, that still counts.
Related to these markets:
1,000
3.00@Thomas42 Presumably it would have to be good enough that many companies start actually using AI coders to do tasks that they once hired entry-level just-out-of-undergrad humans to do. So, the AI wouldn't have to be quite as good as existing entry-level coders (since the AI would be much cheaper, so somewhat worse performance might be an acceptable tradeoff), but it would have to be kinda close (because the kind of coder you could hack up today, AutoGPT-style, probably wouldn't actually save enough time/effort that it would be adopted by many companies).
@Thomas42 As well as an entry-level coder. The most straightforward way for this to resolve is if tech companies start using AI to do entry-level coder work.
@vluzko "The most straightforward way for this to resolve is if tech companies start using AI to do entry-level coder work."
Seems nebulous to me. I imagine the default state is that, "At least some companies have full-AI-loops in their systems, but they don't work too well. They don't 1-1 replace real people, but they help amplify them."
There's already a company that does AI PRs for codebases. It's not too hard to do a shitty job at the basics, and for that to be used at least somewhat.
