I let the AI make decisions all the time. I often approve them, and I sometimes revert them. Most of the time they’re really good decisions based on my initial intent, but followed by analysis I didn’t make but agree with.
There's clearly some level where you want a human making decisions for even the most vibey of project, because without some kind of a spec about what you're trying to build and what features you want you'd get nonsense.
But like... maybe don't stress the details too much.
Yes, clearly. There was a meme out there, "just make something cool idk".
Statements like "Don't let AI make decisions" are made because of the loss of control we experience as mechanical parts of our work (such as writing to files) gets automated.
> A computer can never be held accountable
> Therefore a computer must never make a management decision > A computer can never be held accountable
> Therefore a computer must never make a management decision
the level of teaching involved would always mean the overall velocity of work slowed down.
some people say you can throw them the drudge work but i find that if you're doing coding right (e.g. you dont let your code base degenerate into a mess of boilerplate), there is barely any drudge work to do.
Me, too. But that doesn't mean I'm a great developer, just a shitty manager.
I suspect that will change sooner or later. Models will be cultivated over time the way we cultivate full-time employees now, with an acquired awareness of what they're building, new skills picked up in the process, and insight into how the larger system works.
There's a long-running instance of the model on the provider that's allocated to my organisation? Or are you thinking more of a server-side memory system, similar to the (currently very fallible) ones like Honcho and Mem0?
What happens when my org stops paying that provider? Do I get to take the now senior agent with me to the next provider? Does the provider have to delete it (and all that learning is lost forever)? Does that now become a free agent that can be hired by the next organisation like an employee (one that probably doesn't know how to keep industry secrets to itself)?
Karpathy's notion of a self-maintained wiki may suggest a direction for work in that area. As he points out ( https://gist.github.com/karpathy/442a6bf555914893e9891c11519... ) this is basically the latest of several attempts at implementing Vannevar Bush's "Memex" concept. I think it will find application in some form at organization-wide scope.
If the trend towards centralization holds, then yes, who gets to own and maintain the state in a stateful AI model is indeed going to be a big question. I hope it doesn't hold.
I just cant pretend that I'll get extra productivity while I'm training them.
Certain professions lend themselves well to a apprentice/master framework because the apprentice doing the drudge work that requires less skill frees up time. This can increase overall productivity while the apprentice is trained. Development isnt really like that though.
It is an investment, but it pays back for itself is my point.