15,843 karma · joined March 11, 2013
Website: https://kay.is
Blog: https://fllstck.dev
GitHub: https://github.com/kay-is
Most smart juniors have no problem with learning. Perceptual exposure and deliberate practice works almost mechanically. However, if someone can't tell you what examples you should be exposed to, you'll learn crap.
My first thought was, well agents seem nice, but I think, AI workflows are a better bet. However, I don't really understood AI or agents in depth and felt like I was just "doing things the old way" and removing flexibility from agents was a ridiculous idea.
After some research I got the impression that I was right. A well defined workflow and scope is just what's needed for AI. It's cheaper and more consistent. It probably even makes the whole thing run well with non-SOTA models.
GPT and Claude would work much better than Gemini, even if the direct feedback was sparse or diffuse.
However, the moment I gave Gemini a fast testing framework that gave it instant feedback, it would mill through all kind of problems.
Claude and GPT are seniors.
Gemini is a very motivated mid level.
Anthropic even says, that an agent based solution should only be your last resort and that most problems are well served with a one-shot.
https://www.anthropic.com/engineering/building-effective-age...
You can use it with just European models if you want.
No, it aimed to solve the "out specs are bad and we need to iterate faster" problem.
"a massive lie exposed by LLMs"
No. LLMs add no insight about the problem and they expose nothing. They just help to engage this well-known problem with another tool.
I liked Ra, but I liked Fine Structures more.
Later I read the first version of the book and it was okay, but the vibes were a bit lost.
The new version of the book I didn't even finish.
Because to determine good code, you need to see it and I'd presume most open source code is free.
I mean, insurance is basically basically betting that bad things happen to you.
I just have the feeling that it doesn't get the job done anymore.
I hope we will see the rise of alternatives.
Is it?
I have the impression GenAI deteriorates the internet both from a content and tech perspective.
Bots that waste your time because they don't work well or because they are pushing an agenda, and low quality content that floods social media from people who want to make a quick buck.
GitHub and AWS became increasingly unstable. X, Instagram, and WhatsApp are suddenly sprinkled with subtle bugs.
Everything just got faster and we got more of it, but nothing of it is good anymore because everyone tries to replace 90% of their work with GenAI instead ofmaybe starting at 10-20% and then add more when you're sure it works.
It got better with COVID, but you still have to dig, to find something 100% remote.
I'm a huge burger fan and stopped eating meat at home, thanks to this wave of vegan alternatives.
Do long context windows make much sense then or is this just a way of getting people to use more tokens?
When I write an article and I notice that there are steps missing for a conclusion then I do some research and fill them in.
These gaps often only show up when drafting, so if the LLM drafts, it might see a need to fill them in. You read the draft and see no steps are missing, but since you didn't do the research for the filled in steps, and they "look good to you", you might miss errors.
Didn't make me less clueless, I think...
All my life I was bad at being a loser, somehow I never really felt I fit in. I thought this was because of psychopathic tendencies or something. However, after reading this I realized there was another option and I was just clueless.
I'd assume an LLM trained on the original would also be contaminated.