I think my biggest annoyance with the way we rolled out AI is that nobody seemed to want to use it to augment already working solutions.
Just throw everything out and have an LLM do it instead.
I wanted to hurl my laptop out to the window.
Pasting something directly into the chat interface seems weird, but if you could somehow just see where P(token | context) falls off a cliff, that's a pretty good hint that your writing has problem.
Even Haiku is massive overkill for this use case.
In comparison to non-AI traditional tools, AI has the advantage of "understanding" the text, reducing the number of "stupid" mis-corrections. And its spelling correctness is usually already impeccable, so what is there to gain by interfacing it with traditional solutions, and how can it be achieved?
Don't do a stupid thing like that in the first place.
> In comparison to non-AI traditional tools, AI has the advantage of "understanding" the text, reducing the number of "stupid" mis-corrections.
I doubt it, but if that's true, run a normal spell checker, and then give the output to your LLM to filter.
> what is there to gain by interfacing it with traditional solutions,
About a billionfold improvement in compute efficiency, and a lower error rate.
> and how can it be achieved?
10 seconds of actual thought.
You just don't need AI to do spell checking. It's a waste of energy, bandwidth and tokens. It's like Java Enterprise Fizz-Buzz - 1000x more complicated than it needs to be and complete overkill.
But at least you can tell your manager you're using AI!
Traditional methods might not be perfect, but they also easily fit in the memory of even low power devices. Perhaps it isn't a problem worth burning a dollar of tokens for every spelling mistake.
I guess that works if you aren't a programmer or don't want to hire somebody, but then wtf would I pay for your service or product?
Check out left pad or the two dozen other "utility" packages that could be done in a single line of code.
I work on a large C++ codebase, with large files. Human developers jump around between files with the Visual Studio fuzzy search, set breakpoints to trace execution in the Debugger, use the IDE's refactoring tools.
Microsoft's answer to this was to just ... expose none of this to their Agent Mode!? Replace the working semantic autocomplete with fucking lies!?
Maybe it's changed, I haven't been paying that much attention after bouncing off of this. I've gotten mild acceleration from using gptel-mode in emacs, manually adding references to context, and having models do various mechanical transformations on code. And I've even had some limited success writing tools for it to do LSP lookups.
Anthropic added LSP support to claude-code, but the current implementation is worse than useless, because any changes aren't reflected fast enough, so it's constantly working on outdated views / compilation caches, and it gets in a right muddle between its "internal" state / understanding in context, the real-world file, and the LSP.
If it could just leverage LSP to apply refactorings it would be amazing, but it feels like the LSP can't keep up, and I don't know if that's an LSP problem or a claude problem.
So we binned the LSP plugin and we're back to watching a machine find/replace, because while waiting on that is slower than LSP, it's a "Action => Wait" which the tooling understands, while LSP is "Possibly Wait for LSP to catch up => Action" which it doesn't understand nearly as well.
I suspect the LSP plugins also need better skills that pair with them so it reaches for them more often.
It hurts my soul to see it reach for find/replace to rename a class, complete with mistakes made in complex solutions where you might have name clashes in different namespaces. Something the LSP handles without problem, but can trip up an LLM.
It reminds me of working with a junior dev and he was pushing his code to dev, then waiting for it to build for every update because he couldn’t get it to build locally. 5 minutes of my time fixing his config surely saved him hours over the project. He wasn’t a bad dev either!
You have to do a lot of the meta thinking for the agents, because they’ll take an “everything looks like a nail if you have a hammer” with their toolkit.
Writing an entire local generated asset pipeline using flux and hunyuan3D-2.1 was a really fun experience. I’ve done software for years but never game dev and it’s just so much fun even if it’s junky little games to impress my kids and get them involved in the creative process.
MyModel.obj
MyModel.objects.all().delete()It's never occurred to me to even try getting an LLM to design or layout a circuit for me.
Instead, I have dozens or hundreds of chats in my history where I debate the merits of different parts for different tasks and scenarios, the nuances of decoupling strategies (package size vs deregulation), work out resistor network ratios from the reels I have on hand.
Then being able to feed an LLM a datasheet and have it write a custom driver against the registers I need so that it does exactly what I want without the cognitive overhead of a buggy package with someone else's strong opinions about how a part should be used is amazing.
Frontier models are incredibly good at electronics, and it's got nothing to do with what happens inside the EDA.
We're still a ways off from that, and that's likely because board layout requires a much more nuanced perspective of the enclosure shape, power requirements, heat dissipation, RF...
It's really not about placing ICs with caps nearby. I actually really enjoy that part anyhow. That's the fun part!
I think the bitter lesson is severely misapplied in the current situation: If progress from "just add more resources" is very slow, and a huge amount of money is at stake, continous work on hand-engineering can give a continuous and very valuable competitive advantage.
The labs all seem to be going for AGI through bigger LLMs, and I am reasonably sure that it's not going to happen like that.
I don't know if this is still the case. Labs like anthropic and openai are spending a huge amount of their time on custom model wrappers. Something which they used to leave to their customers.
It's a tantalizing thing, but far too treacherous to actually go for it, most of the time.
Plenty of people do, but that only produces a blog post that will get you to the front page of HN. If you want VCs to drop $40M on your head, you need to pretend to reinvent the world.
Then, to further appease the rain gods, you need to sue the bloggers on the front page of HN who are challenging your world-changing narrative. Which will, heh, drop you on the front page of HN.
Our community is, literally, eating itself at this point. There was a time when we actually took "make something people want" literally. Now it's just part of the fiction.
That's exactly how I use it, but I'm just a geezer on his own, writing free software for people that can't pay for it.
The future is using AI to do everything, and nobody gets funded saying they're taking a small step forward.