A Research Preview of Codex

Some engineers on my team at Assembled and I have been a part of the alpha test of Codex, and I'll say it's been quite impressive.

We’ve long used local agents like Cursor and Claude Code, so we didn’t expect too much. But Codex shines in a few areas:

Parallel task execution: You can batch dozens of small edits (refactors, tests, boilerplate) and run them concurrently without context juggling. It's super nice to run a bunch of tasks at the same time (something that's really hard to do in Cursor, Cline, etc.)

It kind of feels like a junior engineer on steroids, you just need to point it at a file or function, specify the change, and it scaffolds out most of a PR. You still need to do a lot of work to get it production ready, but it's as if you have an infinite number of junior engineers at your disposal now all working on different things.

Model quality is good, but hard to say it's that much better than other models. In side-by-side tests with Cursor + Gemini 2.5-pro, naming, style and logic are relatively indistinguishable, so quality meets our bar but doesn’t yet exceed it.

If you aren't hiring junior engineers to do these kinds of things, where do you think the senior engineers you need in the future will come from?

My kid recently graduated from a very good school with a degree in computer science and what she's told me about the job market is scary. It seems that, relatively speaking, there's a lot of postings for senior engineers and very little for new grads.

My employer has hired recently and the flood of resumes after posting for a relatively low level position was nuts. There was just no hope of giving each candidate a fair chance and that really sucks.

My kid's classmates who did find work did it mostly through personal connections.

This is a bit of a game theory problem. "Training senior engineers" is an expensive and thankless task: you bear essentially all the cost, and most of the total benefit accrues to others as a positive externality. Griping at companies that they should undertake to provide this positive externality isn't really a constructive solution.

I think some people are betting on the fact that AI can replace junior devs in 2-5 years and seniors in 10-20, when the old ones are largely gone. But that's sort of beside the point as far as most corporate decision-making.

That sounds like a dangerous bet.

I’m curious about other aspects of this: - leverage of countries who can host such AI over countries who can’t, will there be a point when countries can’t allow themselves not to have access to „emergency” talent in case they can’t use AI? Recent „choose european”, tariffs show that much of the high end stuff is concentrated in US and China. - outages happen, does the company stop because the cloud is not working? - highly regulated companies still can’t use copilot to its fullest because of „can’t show answer because it’s matching public code” - is replacing all talent safe - in terms of operational or national safety?