Opus 4.5 is not the normal AI agent experience that I have had thus far

The tech industry just went through an insane hiring craze and is now thinning out. This will help to separate the chaff from the wheat.

I don't know why any company would want to hire "tech" people who are terrified of tech and completely obstinate when it comes to utilizing it. All the people I see downplaying it take a half-assed approach at using it then disparage it when it's not completely perfect.

I started tinkering with LLMs in 2022. First use case, speak in natural english to the llm, give it a json structure, have it decipher the natural language and fill in that json structure (vacation planning app, so you talk to it about where/how you want to vacation and it creates the structured data in the app). Sometimes I'd use it for minor coding fixes (copy and paste a block into chatgpt, fix errors or maybe just ideation). This was all personal project stuff.

At my job we got LLM access in mid/late 2023. Not crazy useful, but still was helpful. We got claude code in 2024. These days I only have an IDE open so I can make quick changes (like bumping up a config parameter, changing a config bool, etc.). I almost write ZERO code now. I usually have 3+ claude code sessions open.

On my personal projects I'm using Gemini + codex primarily (since I have a google account and chatgpt $20/month account). When I get throttled on those I go to claude and pay per token. I'll often rip through new features, projects, ideas with one agent, then I have another agent come through and clean things up, look for code smells, etc. I don't allow the agents to have full unfettered control, but I'd say 70%+ of the time I just blindly accept their changes. If there are problems I can catch them on the MR/PR.

I agree about the low hanging fruit and I'm constantly shocked at the sheer amount of FUD around LLMs. I want to generalize, like I feel like it's just the mid/jr level devs that speak poorly about it, but there's definitely senior/staff level people I see (rarely, mind you) that also don't like LLMs.

I do feel like the online sentiment is slowly starting to change though. One thing I've noticed a lot of is that when it's an anonymous post it's more likely to downplay LLMs. But if I go on linkedin and look at actual good engineers I see them praising LLMs. Someone speaking about how powerful the LLMs are - working on sophisticated projects at startups or FAANG. Someone with FUD when it comes to LLM - web dev out of Alabama.

I could go on and on but I'm just ranting/venting a little. I guess I can end this by saying that in my professional/personal life 9/10 of the top level best engineers I know are jumping on LLMs any chance they get. Only 1/10 talks about AI slop or bullshit like that.

I do need to steer it sometimes, but since it doesn't change a lot at a time, I can usually guide the agent and stop the disaster before it spreads.

A big caveat is I haven't tried heavy front-end stuff with it, more django stuff, and I'm pretty happy with the output.

And everything worked really well until they switched chip set.

At which point the same model failed entirely. Upon inspection it turned out the AI model had learned that overloading particular registers would cause such an electrical charge buildup that transistors on other pathways would be flipped.

And it was doing this in a coordinated manner in order to get the results it wanted lol.

I can't find any references in my very cursory searches, but your comment reminded me of the story

For some things you can fire up Claude and have it generate great code from scratch. But for bigger code bases and more complex architecture, you need to break it down ahead of time so it can just read about the architecture rather than analyze it every time.