I'd say it's more like: every time you start a new conversation with him, it's like his first day on the job.

But also: within the span of one interaction with him, he advances from junior to senior engineer in your specific domain.

Only if your expectation of senior engineers is that they often hallucinate and you'll constantly have to double-check their work

The big advantage to me is it's an unexperienced junior with approximate knowledge of every API and style on the internet. It's a super junior.

TODO.md and FEATURE_TODO.md are also very valuable for keeping on track.

Like economists, who have predicted 7 of the last 3 recessions, AI knows 17 out of 11 API calls!

And in the case it's wrong, I will know pretty quickly and can fall back to the old methods.

It's definitely been said before, but the fact that they're calling out these non-existent functions in the first place can tell library devs a lot about what new features could be there to take up the namespace.

If you stop the need of having juniors you're never going to get more experienced people.

Juniors today can learn exponentially faster with LLMs and don't need seniors as much.

Take me for example, I've been programming for 20 years, been through C, C++, C#, Python, JS, PHP but recently had to learn Angular 18 and Fastapi. Even though I knew JS and Python before hand these frameworks have ways of doing things I'm not used to so I've been fumbling with them for the first 100 hours. However when I finally installed Copilot and had a little faith in it I boosted my productivity 3-4x. Of course it didn't write everything correct, of course it used outdated angular instead of latest (which is why I was so reluctant to ask stuff for it at the start) but it still helped me a lot because it is much easier (for me) to modify some bad/outdated code and get it to where I want it than write it from scratch without the muscle memory of the new framework.

So for me it's been a godsend. I expect for stuff that's not as cutting edge as new framework oddities that appeared in the last 12 months it is even more helpful and % of it being correct would be way higher so for juniors that are doing say Python coding on frameworks that have at least 3-4 years and are stable enough the seniors would need to intervene much much less in correcting the junior.

You are not a junior, you already rely on 20 years of experience.

Last time i did any sort of web development was 20 ago, but i thought to try some C# (touched last time ~10 years ago) + Blazor for an idea i had and it took me a couple of days to feel comfortable and start making stuff. While i haven't written for the web in a very very long time, my experience with other tech helped a lot.

probably the more we sacrifice of our own productivity the quicker they gain experience (and seniority) right? the only confusing thing that confused me personally in your statement was that they would have to be loyal. Isn't that something that one can only hope but must be proven over time. Meaning that at the time you trust that they turn out well you have no way of proving that they are "loyal" yet. Loyalty is nigh impossible to request upfront? I mean, ... you have to deserve it. And a lot can also go wrong on the way.

And it happily wrote something. When I proceeded to add an actual spec he happily wrote something reasonable which couldn't work, because it assumed all 'is_something' functions can be used as guard statements. Ah oh.

The LLM costs a minute fraction of the cost of employing a human junior developer.

Which seems to work pretty well, in my experience.

However the current generation of models needs a specific form of training set that is quite different from what a human would produce through direct interaction with the model.

For one it needs many more examples than a human would need. But also the form of the example is different: it must be an example of an acceptable answer. This way a model can compute how far it is from the desired outcome.

Further research in how to efficiently fine tune models will make this gap narrower and perhaps senior devs will be able to efficiently give learnable feedback through their normal course of interaction

I think this also applies to AI having an early or intermediate senior engineer on your team.

So in effect it would be having less engineers and probably 1 or 2 at best senior engineers and the rest are guiding the AI senior engineer in the codebase.

I didn't need to hire any senior engs for a while for my SaaS and only needed good juniors for 3 months.

Everyone in the future is going have access to senior engineers building projects.

Not only that, but one who is infected with terminal Dunning-Kruger syndrome. Of all the things that LLMs are great at, demonstrating a hopeless case of Dunning-Kruger has to be at the very top.

And in the near future the mid/senior level will have no replacements as we've under-hired juniors and therefore don't have a pipeline of 5YOE/10YOE/etc devs who have learned to stop being juniors.

There is a surprising lack of focus on code reviews as part of that process.

A few months back, I ran into one company (a YC company) that used code reviews as their first technical interview. Review some API code (it was missing validation, error handling, etc.), review some database code (missing indices, bad choices for ID columns, etc.), and more.

I think more companies need to rethink their interview process and focus on code reviews as AI adoption increases.

Just the dialog with an AI I find instructive. Sometimes it suggests things I don't know. Often after 1-2-3 mediocre AI solutions I'll code up something that re-uses some AI code but has much better code that I write.