Have you ever seen Claude Code launch a subagent? You've used it, right? You've seen it launch a subagent to do work? You understand that that is, in fact, Claude Code running itself, right?
Have you ever seen Claude Code launch a subagent? You've used it, right? You've seen it launch a subagent to do work? You understand that that is, in fact, Claude Code running itself, right?
They're tool calls. Claude Code provides a tool that lets the model say effectively:
run_in_subagent("Figure out where JWTs are created and report back")
The current frontier models are all capable of "prompting themselves" in this way, but it's really just a parlor trick to help avoid burning more tokens in the top context window.It's a really useful parlor trick, but I don't think it tells us anything profound.
The OP says AI requires human interaction to work. This simply isn't true. You know yourself that as agents get more reliable you can delegate more to them, including having them launch more subagents, thereby getting more work done, with fewer and fewer humans. The unlock is the Task tool, but the power comes from the smarter and smarter models actually being able to delegate hierarchical tasks well!
The only reason to launch subagents is to avoid poisoning the LLM's already small context window with unrelated tokens.
It doesn't make the LLM smarter or more capable.
Do you think this means "Build a car" can be accomplished just because an LLM can send a prompt to another LLM who reports back a response?
They create the illusion of being able to make decisions but they are always just following a simple template.They do not consider nuance, they cannot judge between two difficult options in a real sense.
Which is why they can delete prod databases and why they cannot do expert level work
Well this is just factually incorrect considering they are currently on par with grad students in some areas of mathematics.
Even then, they are most effective in assisting and are not able to produce results independently. If you have proof otherwise I would love to read up on it
With humans, you can kind of interview/select for a more normalized distribution of outcomes, with outliers being less probable, but not impossible.
The key break here is the lack of predictability and I think it's important that we don't get too starry eyed and accept that that might be a weakness - not a strength.
If that is software running itself, then an if statement that spawns a process conditionally is running itself.
AI in the hands of an expert operator is an exoskeleton. AI left alone is a stooge.
Nobody has built an all-AI operator capable of self-direction and choices superior to a human expert. When that happens, you'd better have your debts paid and bunker stocked.
We haven't seen any signs of this yet. I'm totally open to the idea of that happening in the short term (within 5 years), but I'm pessimistic it'll happen so quickly. It seems as though there are major missing pieces of the puzzle.
For now, AI is an exoskeleton. If you don't know how to pilot it, or if you turn the autopilot on and leave it alone, you're creating a mess.
This is still an AI maximalist perspective. One expert with AI tools can outperform multiple experts without AI assistance. It's just got a much longer time horizon on us being wholly replaced.