>The not-so-quiet goal of the LLM push by big tech was to homogenise intellectual labour such that it can be made fungible. When labour is fungible you can swap it out whenever you like for an alternative, decreasing the bargaining power of workers.

Especially if you replace people with robots that don't need days off and have the people train their replacements.

idk. I get more stuff done, faster, that I wouldn’t have been able to. You have to use it judiciously and with supervision - I can see how letting it get out of control would negate the benefits. But with good use, its undeniable.

To the author’s point about there not being enough evidence to support pro-AI claims — Additionally, there are studies and articles coming out showing those people are wrong and AI only makes people barely more efficient. Not the 10x tech CEOs are claiming while slashing thousands of jobs

https://getdx.com/blog/ai-productivity-gains-are-10-percent-...

I think the fundamental rebuttal to this is merely that, we’re still so early, the $1.5 trillion number is irrelevant for developing technologies in the same way two women can’t birth a baby in 4.5 months

are open ai, anthropic, zai, deepseek, cursor etc not new players? that benchmark seems like one defined to never be good enough

"Well, actually, vim doesn't make you faster"

AI skeptics hate him. Here's how he doubled his productivity using AI with one simple trick.

You have to stop thinking like an employee or a worker bee, and start thinking like a boss.

Guess what, the work you give your boss isn't 100% gold either. And sometimes you are preoccupied, or tired, so what you deliver isn't the best of all possible deliverables. Sometimes you hallucinate, i.e. you are dead wrong when you think you are dead right.

This is the job of a boss: take fallible employees and turn what they produce into something actually valuable. The boss lets the grunts do the grunt work, and then they combine the output together, and do the due diligence, etc etc.

It's an entirely new skillset. But learning the new skillset isn't the real blocker--the real blocker is that you've got to stop thinking like a grunt and start thinking like an executive.

WHAT is it that you really want to do? Frame that question as clearly and as concretely as you can. Then farm out thee work to human or AI grunts, and be prepared to do your due diligence on the result.

The last bullet point is the most important. The industry is most hyped about AI so that they can pay software developers $70k instead of paying them $200k.

I don’t really agree that AI can’t make development faster, though. What the author describes as the negative AI outcome is blind vibecoding. There are many other ways to use it, and even the basic “enhanced autocomplete” is a net benefit, especially since that functionality is dirt cheap or free.

> Software development was one of the last ‘guild fields’ and now we are seeing its industrialisation occur.

Doesn’t really support the rest of the argument. If you’re a skeptic and think it’s all hype, there’s nothing to worry about.

>The not-so-quiet goal of the LLM push by big tech was to homogenise intellectual labour such that it can be made fungible. When labour is fungible you can swap it out whenever you like for an alternative, decreasing the bargaining power of workers. Software development was one of the last ‘guild fields’ and now we are seeing its industrialisation occur.

I think that the industrialization of software development already happened decades ago. The common professional software development methodologies, both waterfall and sprint-based, ARE the industrialization of software development. Isn't modern "agile", sprint-based software development methodology directly influenced by Japanese manufacturing methods? I don't know when software development actually was a guild field, and my personal experience doesn't reach back this far, but based on what I've read at least, it seems to me that even back in the 1990s it was already not a guild field.

I think an argument can be made that some software has gotten more secure.

I don’t think it can be denied that the models do show an ability to find security vulnerabilities that may have otherwise been missed

I have started using AI a bit, but I'm still trying to be careful in that if I ever lose access I can still perform my job at pre-AI ability. My understanding is that tokens are still heavily subsidized, and when that well runs dry I don't want it to be some nightmare to go back to the way I was doing my work in like 2022.

I agreed right upto the last quote. That made the post political, similar to the ones being written by the AI evangelists.

The thing about complex systems is that they are not predictable. Right now the answer is whatever you think is right, and a lot of scenarios seem plausible.

It is a fun intellectual moment trying to make sense, but maybe only time will tell how the dynamics work out.

the way i see, LLM's in their current shape are neither good enough to replace software engineers but they have become a necessary part of everyone tool kit. ergo, actual companies themselves aren't getting much benefit because their competitors are using the same tools and they can't fire their human labor either just it's just an extra cost. At my org, i see good engineers use LLM's in wise ways and bad engineers just let it write slop for them. What gets to me is the verbosity and noise though, i consider brevity, and curation to be hallmarks of intelligence but most people at work just spit out so many words in their design docs or code comment these days.