[bcyn]

Many SaaS products are tools. I'm sure when tractors were first invented, people felt that they didn't "control" it compared to directly holding shovels and manually doing the same work.

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.

[pempem]

I think the OP comment re: AI's value as a tool comes down this this:

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

[benreesman]

Intentionally or not the tractor analogy is a rich commentary on this but it might not make the point you intend. Look into all the lawsuits and shit like that with John Deere and the DRM lockouts where farmers are losing whole crops because of remote shutdown cryptography that's physically impossible to remove at a cost or in a timeframe less than a new tractor.

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.