Why don't we currently have AI agents?
16Matt Goldenberg
2ChristianKl
4Matt Goldenberg
2ChristianKl
4Nathan Helm-Burger
7Buck
7Leon Lang
4Caleb Biddulph
2Gordon Seidoh Worley
1Sodium
New Answer
New Comment
3 Answers sorted by
163
When you start trying to make an agent, you realize how much your feedback, rerolls, etc are making chat based llms useful
the error correction mechanism is you in a chat based llms, and in the absence of that, it's quite easy for agents to get off track
you can of course add error correction mechanism like multiple llms checking each other, multiple chains of thought, etc, but the cost can quickly get out of hand
Is answer assumes that you either have a fully chat based version or one that operates fully autonomous.
You could build something in the middle where every step of the agent gets presented to a human who can press next or correct the agent. An agent might even propose multiple ways forward and let the human decide. That then produces the training data for the agent to get better in the future.
4
This exists and is getting more popular, especially with coding, but also in other verticals
2
Which one's do you see as the top ones?
4
I've been using Aider recently with coding. It's a mixed bag, but overall I think I like it. You can configure whether it just acts, or asks for permission first.
70
I have an AI agent that wrote myself; I use it on average 5x per week over the last 6 months. I think it's moderately useful. I mostly use it for simple shell tasks that would otherwise require copy-pasting back and forth with claude.ai.
My guess is that the big AI companies don't think the market for this is big enough to be worth making a product out of it.
41
Anthropic's computer use model and Google's Deep Research both do this. Training systems like this to work reliably has been a bottleneck to releasing them
I can't help but wonder if part of the answer is that they seem dangerous and people are selecting out of producing them.
Like I'm not an expert but creating AI agents seems extremely fun and appealing, and I'm intentionally working on it none because it seems safer not to build them. (Whether you think my contributions to trying to build them would matter or not is another question.)
I think the actual answer is: the AI isn't smart enough and trips up a lot.
But I haven't seen a detailed write up anywhere that talks about why the AI trips up and what are the types of places where it trips up. It feels like all of the existing evals work optimize for legibility/reproducibility/being clearly defined. As a result, it's not measuring the one thing that I'm really interested in: why don't we have AI agents replacing workers. I suspect that some startup's internal doc on "why does our agent not work yet" would be super interesting to read and track over time.
Curated and popular this week