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Comment by emp17344 | Hacker News Reader

The collaboration aspect is what many AI enthusiasts miss. As humans, our success is dependent on our ability to collaborate with others. You may believe that AI could replace many individual software engineers, but if it does so at the expense of harming collaboration, it’s a massive loss. AI tools are simply not good at collaborating. When you add many humans to a project, the result becomes greater than the sum of its parts. When you add many AI tools to a project, it quickly becomes a muddled mess.

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I look at it backwards: A few humans improves a project. But once you get to sufficient sizes, principal-agent problems dominate. What is good for a division and what is good for the company disagree. What is good for a developer that needs a big project for their promotion package is not what the company needs. A company with a headcount of 700 is more limber and better aligned than when it's 3,000 or 30,000. It's amazing how little alignment there ever is when you get to the 300k range.

AI, if anything, is amazing at collaborating. It's not perfectly aligned, but you sure can get it to tell you when your idea is unsound, all while having lessened principal-agent issues. Anything we can do to minimize the number of people that need to align towards a goal, the more effectively we can build, precisely due to the difficulties of marshalling large numbers of people. If a team of 4 can do the same as a team of 10, you should always pick the team of 4, even if they are more expensive put together than the 10.

Yes, which is why every successful company has exactly 4 people and no more. Collaboration goes beyond your immediate team members - if you work for an organization, you’re supported by it in ways you may take for granted. Replace this structure with AI models, and the whole thing would fall apart.

> AI tools are simply not good at collaborating

My primary use of LLM tools is as a collaborator.

I agree that if you try to use the LLM as a wholesale outsourcing of your thought process the results don’t scale. That’s not the only way to use them, though.

> When you add many humans to a project, the result becomes greater than the sum of its parts. When you add many AI tools to a project, it quickly becomes a muddled mess.

I have absolutely been on projects where there were too many cooks in the kitchen, and adding more people to the team only led to additional chaos, confusion, and complexity. Ever been in a meeting where a designer, head of marketing, and the CTO are all giving feedback on what size font a button should be? I certainly have, and it's absurd.

One of my worst experiences arose due to having a completely incompetent PM. Absolutely no technical knowledge; couldn't even figure out how to copy and paste a URL if his life depended on it. He eventually had to be be removed from a major project I was on, and I was asked to take over PM duties, while also doing my dev work. I was actually happy to do so, because I was already having to spend hours babysitting him; now I could just get the same tasks done without the political BS.

Could adding many AI tools to a project become problematic? Maybe. But let's not pretend throwing more humans at a project is going to lead to some synergistic promised land.

AI will allow us to collaborate on higher level decisions and not on whether we should use for loops or functional interfaces.

This attitude is acceptable for principal engineers, but anyone lower in the chain with this perspective typically presides over a product that is constantly breaking due to hundreds of unhandled edge cases, AI or not.

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