It's not a tool its a SaaS. I own and control my tools. I think a John Deer tractor looses it's "tool" status when you can't control it. Sure there's the local models but those aren't what the vast majority of folks are using or pushing.
You cannot manually train it for your case.
You cannot tell it to not touch particular parts of your project either. It will stomp over all of the code.
You cannot even easily detect this tool has been used except for typical failures.
The tool may also leak your secrets to some central database. You cannot tell it to not do that.
(If you try either tack of those, it will lie to you that it complied while actually not doing that at all.)
When your networking fails, the tool does not work. It's fragile in all cases.
I've never seen so many false assumptions in one place.
These are hooked up to control theory algorithms based on aggregate and regional KV and prompt cache load. This is true of both fixed and per-token billing. The agent will often be an asset at 4am but a liability at 2pm.
You get experiment segmented always, you get behavior scoped multi-armed badit rotated into and out of multiple segment categories (an experiment universe will typically have not less than 10000 segments, each engineer will need maybe 2 or 3 and maybe hundreds of arms per project/feature, so that's a lot of universes).
At this stage of the consumer internet cycle its about unit economics and regulatory capture and stock manipulation via hype rollercoaster. and make no mistake about what kind of companies these are: they have research programs with heavy short-run applications in mind and a few enclaves where they do AlphaFold or something. I'm sure they created an environment Carmack would tolerate at least for a while, but I gibe it a year or two we saw that movie at Oculus and Bosworth is a pretty good guy, he's like Jesus compared to the new boss.
In this extended analogy about users, owners, lenders, borrowers and hammers, I'd be asking what is the hammer and who is the nail.
Not to say that LLMs are at the same reliability of tractors vs. manual labor, but just think that your classification of what's a tool vs. not isn't a fair argument.
Does what it says: When you swing a hammer and make contact, it provides greater and more focused force than your body at that same velocity. People who sell hammers make this claim and sometimes show you that the hammer can even pull out nails really well. The claims about what AI can do are noisy, incorrect and proffered by people who - I imagine OP thinks and would agree - know better. Essentially they are saying "Hammers are amazing. Swing them around everywhere"
Right to repair: Means an opportunity to understand the guts of a thing and fix it to do what you want. You cannot really do this to AI. You can prompt differently but it can be unclear why you're not getting what you want
People on HN love to bring up farm subsidies, and its a real issue, but big agriculture has special deals and what not. They have redundancy and leverage.
The only time this stuff kicks in is when the person with the little plot needs next harvest to get solvent and the only outcome it ever achieves is to push one more family farm on the brink into receivership and directly into the hands of a conglomorate.
Software engineers commanded salaries that The Right People have found an affront to the order of things long after they had gotten doctors and lawyers and other high-skill trades largely brought to heel via the joint licensing and pick a number tuition debt load. This isn't easy in software for a variety of reasons but roughly that the history of computer science in academia is kind of a unique one: it's research oriented in universities (mostly, there are programs with an applied tilt) but almost everyone signs up, graduates, and heads to industry without a second thought, and so back when the other skilled trades were getting organized into the class system it was kind of an oddity, regarded as almost an eccentric pursuit by deans and shit.
So while CS fundamentals are critical to good SWE's, schools don't teach them well as a rule any more than a physics undergraduate is going to be an asset at CERN: its prep for theory research most never do. Applied CS is just as serious a topic, but you mostly learn that via serious self study or from coworkers at companies with chops. Even CS graduates who are legends almost always emphasize that if you're serious about hacking then undergrad CS is remedial by the time you run into it (Coders at Work is full of this sentiment).
So to bring this back to tractors and AI, this is about a stubborn nail in what remains of the upwardly mobile skilled middle class that multiple illegal wage fixing schemes have yet to pound flat.
This one will fail too, but that's another mini blog post.
Something can be a SaaS, and a useful tool, at the same time.
> those aren't what the vast majority of folks are using or pushing.
Good for them.
If you do not want to use SaaS, use a local model.
More if you want to actually train it.