[rowanseymour]

Now feels like a very good time to be a small team of experienced developers who can largely work on stuff by themselves and not a corporation of hundreds of developers of varying abilities all now trying to show how much code they can generate and how many tokens they can burn.

[niwtsol]

100% - I think that is also part of the divide you see online. Devs who work on massive codebases w/ 100s of engineers and see the bugs the LLMs create vs devs who work on smaller codebase w/ small <5 person team.

[aantix]

It's a tradeoff.

Generating a feature that is 90% correct in a tenth of the time is a reasonable tradeoff if you're trying to gain traction.

Generating a feature that is 90% correct in a tenth of the time, risking a multi-billion-dollar business, is a terrible tradeoff.

[2001zhaozhao]

I think it's rather:

Small teams building continuously get to write features that are 90% correct in a tenth of the time.

Big enterprises get to write features that are 90% correct barely twice as fast, because all of the bottleneck lies elsewhere. They also spend more on AI per user because of the internal dynamics pushing people to adopt AI irresponsibly. They can correct the 10% of errors slower than small teams because of bureaucracy, increasing the cost of errors that show up in the product. Furthermore, they have less to gain from a given amount of speedup because they had plenty of engineering velocity anyway compared to small teams.

I don't think big enterprises will start winning from AI technology until AI truly can automate almost everything in a company and let said company outproduce competitors by burning tokens alone. That's nowhere near possible right now.

[bensyverson]

I don't think "90% correct in a tenth the time" is really the tradeoff. For a well-specified task, it's closer to 100% correct in 1/100th the time. But that undersells the time required to generate a good spec.

For under-specified tasks, it's not really accurate to talk about "correctness," because the machine isn't psychic. I would suggest that given a high-level feature request like "add streaming support" it's more about acceptance probability. In a well-structured and well-documented codebase, and a reasonably sized feature request, there might be an 80% chance it will generate something which is 100% acceptable. But there's about a 99% chance it will generate something which is acceptable after 1-2 revisions.

[dylan604]

Even small teams are not immune from the AI push. I work in a small <10 people with 3 devs. I'm the only one not using AI while receiving push that I'm a problem for not. To the point, VP of company says if we don't all start using AI we'll be out of business because other people will. :face-palm:

[niwtsol]

You don't use AI at all? What is your main justification for not?

[dylan604]

I don't like outsourcing learning and prefer to do the actual learning. Just like taking notes via recorder vs writing them down during a lecture causes you to not remember the information as well. Allowing something else to create your code tends to mean you're not going to remember/know the how/why it works and you just accept it works and moves on. Eventually you don't know how any of it works and you're totally dead in the water without the LLM. My understanding of the code I write is much more valuable than some arbitrary deadline that means nothing

[chaoz_]

Do you also inspect and study what assembly code your program was compiled to?

// Obviously LLMs are non-determenistic etc and it depends on your domain, but your VP's point 100% makes sense if you folks are trying to cook up another demo-CRUD apps to convince investors for another funding round

[eska]

I keep hearing this argument on HN. Yes, if performance is something you care about you totally look at the disassembly. You don’t even need to write assembly, just be able to read it. By now I assume that programmers who argue they don’t need to understand and review what the LLM generates for them are simply not that skilled and don’t realize that skilled programmers do this.

[chaoz_]

If you're just building a non-security-sensitive frontend to validate market traction, it makes total sense to go full AI. The commenter working at a 10-person company getting flamed for not using AI to iterate aggresively against competitors has a super valid point.

Validation methods will evolve to accommodate human laziness. Insisting on doing it the hard way is no different than the old-timers who used to claim engineers 'weren't skilled' if they didn't know how to use punch cards.

[nitwit005]

I'd definitely say IntelliJ improved my productivity. No one cared. If anything, management viewed it as a nuisance as they had to deal with the license.

Now there is demands to justify not using AI like this, but people don't care about details. Which AI tool I use apparently doesn't matter at all, even if there are presumably productivity differences between them.

Edit: typo

[pesus]

Seems like you should have a justification for introducing a new tool instead, no? There are thousands of other tools they're also not using, but we're not asking about those.

[bigstrat2003]

I'm not the same person, but I don't really use it. I write better code than an LLM, and I do it faster than the time it takes to review and correct the LLM's bad code. The tool has no value to offer me.

[alfiedotwtf]

!RemindMe 2 years

[rowanseymour]

To be clear I meant it's good to be small team on the assumption that we're all using AI... I honestly can't imagine not using AI in May 2026.

[sscaryterry]

He could be wrong, but in my opinion, he is probably right. Others are, and will be using AI.

[foldr]

I think the jury’s still out on how big an impact AI will have on overall, average productivity. But it’s definitely a productivity boost for someone who’s capable of writing code without it. If you want to be super conservative, don’t even have it write any code. Use it to search through existing codebases, review your code, find the root cause of bug reports, evaluate pros and cons of alternative approaches, etc. etc. You’re really missing out by not using it at all.

Here’s a concrete example of conservative AI usage: I use Claude to vibe code my nvim config. Now, who cares if my nvim config is AI slop? What’s the worst that can happen? Nvim works for me now way better than it ever did when I was limited by the time I was willing to spend configuring it manually.