> LLM coding will split up engineers based on those who primarily liked coding and those who primarily liked building

as the former, i've never felt _more ahead_ than now due to all of the latter succumbing to the llm hype

LLM coding splits up engineers based on those who primarily like building and those who primarily like code reviews and quality assessment. I definitely don’t love the latter (especially when reviewing decisions not made by a human with whom I can build long-term personal rapport).

After certain experience threshold of making things from scratch, “coding” (never particularly liked that term) has always been 99% building, or architecture, and I struggle to see how often a well-architected solution today, with modern high-level abstractions, requires so much code that you’d save significant time and effort by not having to just type, possibly with basic deterministic autocomplete, exactly what you mean (especially considering you would have to also spend time and effort reviewing whatever was typed for you if you used a non-deterministic autocomplete).

I do feel a big mood shift after late November. I switched to using Cursor and Gemini primarily and it was big change in my ability to get my ideas into code effectively. The Cursor interface for one got to a place that I really like and enjoy using, but its probably more that the results from the agents themselves are less frustrating. I can deal with the output more now.

I'm still a little iffy on the agent swarm idea. I think I will need to see it in action in an interface that works for me. To me it feels like we are anthropomorphizing agents too much, and that results in this idea that we can put agents into roles and them combine them into useful teams. I can't help seeing all agents as the same automatons and I have trouble understanding why giving an agent with different guideliens to follow, and then having them follow along another agent would give me better results than just fixing the context in the first place. Either that or just working more on the code pipeline to spot issues early on - all the stuff we already test for.

> the ratio of productivity between the mean and the max engineer? It's quite possible that this grows *a lot*

I have a professor who has researched auto generated code for decades and about six months ago he told me he didn't think AI would make humans obsolete but that it was like other incremental tools over the years and it would just make good coders even better than other coders. He also said it would probably come with its share of disappointments and never be fully autonomous. Some of what he said was a critique of AI and some of it was just pointing out that it's very difficult to have perfect code/specs.

I'm curious to see what effect this change has on leadership. For the last two years it's been "put everything you can into AI coding, or else!" with quotas and firings and whatever else. Now that AI is at the stage where it can actually output whole features with minimal handholding, is there going to be a Frankenstein moment where leadership realizes they now have a product whose codebase is running away from their engineering team's ability to support it? Does it change the calculus of what it means to be underinvested vs overinvested in AI, and what are the implications?

> if you have any code you actually care about I would watch them like a hawk, in a nice large IDE on the side.

This is about where I'm at. I love pure claude code for code I don't care about, but for anything I'm working on with other people I need to audit the results - which I much prefer to do in an IDE.

HN should ban any discussion on “things I learned playing with AI” that don’t include direct artifacts of the thing built.

We’re about a year deep into “AI is changing everything” and I don’t see 10x software quality or output.

Now don’t get me wrong I’m a big fan of AI tooling and think it does meaningfully increase value. But I’m damn tired of all the talk with literally nothing to show for it or back it up.

> It's so interesting to watch an agent relentlessly work at something. They never get tired, they never get demoralized, they just keep going and trying things where a person would have given up long ago to fight another day. It's a "feel the AGI" moment to watch it struggle with something for a long time just to come out victorious 30 minutes later.

The bits left unsaid:

1. Burning tokens, which we charge you for

2. My CPU does this when I tell it to do bogosort on a million 32-bit integers, it doesn't mean it's a good thing

> It hurts the ego a bit but the power to operate over software in large "code actions" is just too net useful

It does hurt, that's why all programmers now need an entrepreneurial mindset... you become if you use your skills + new AI power to build a business.

The AGI vibes with Claude Code are real, but the micromanagement tax is heavy. I spend most of my time babysitting agents.

I expect interviews will evolve into "build project X with an LLM while we watch" and audit of agent specs