nzach

I don't think this is a good marker for intelligence, but I think if you avoid dismissing issues because other people are dumb you will generally think harder and in the end will have a better understanding of the issue.

I have a personal rule that goes along the lines of "If I can't explain why a smart and kind person thinks the opposite of me it means I don't really understand the issue". It doesn't mean that I have to agree with them, but I always try to understand where they came from.

And don't forget the 'Thing' from Addams Family in the shoulder of the guy on the left.

My guess would be that somewhere you have these instructions being fed to the agent. Double check skills, AGENTS.md, memory, agent definition...

You can also ask why did he mentioned something that wasn't done or why he thought this was important.

In my AGENTS.md file I have an instruction telling the agent to never commit any changes unless I explicitly ask for it, and this leads to messages similar to what you just described.

I'm starting to think that 'memory' may be the wrong analogy for what we want.

I do think that having a set of token that are highly personalized to your project and to way you work is beneficial. I also think that the idea that this set of token will be constructed in the background without any work from the user is really appealing. So it's understandable that the 'memory' analogy became so popular.

But in my experience having a really good AGENTS.md file almost always produce better results than enabling memory.

Maybe we should start to think about how we 'train'/'onboard' agents into our projects, in a similar way that we do for new co-workers. Imagine if we could send the agent to our repo and ask it to learn our patterns and in the end we could quiz the agent to gauge how much it actually understood the project. Once he 'understands' the project we can start to use it to help with development.

In a very small scale (example, individual new features) I will sometimes ask the agent to explain me how things work (even though I already know how it works) so I can 'prime' the agent context with good data before starting any real work. But I'm not sure if this approach could be reliably scaled to work with any repo for any kind of work.

>I suggest groupthink is a critically important aspect of most human behavior. And yet somehow, we rarely manage to discuss this, and are repeatedly surprised by it. I'm unclear on why.

Isn't that just a manifestation of the 'Blind spot' from Johari Window?

In general it is really hard to think about the things you already internalized.

I really don't understand their thinking here. Sure they want more money, I get that.

But 'physical media' is one of the reasons why a lot o people make a distinction between PC and console games. Removing this will make it easier for consumers to compare a PS5 to a Steam machine, and I don't think that is a good thing for Sony.

He uses the rumble to move the controller to the charging puck in a flat surface. He uses a camera to identify the direction we need to move the controller. When the controller gets close enough the charging puck automatically attaches to the controller because of the magnetic force.

Instead of training the model to directly answer questions we trained the model to always write and execute the code that would solve the question ?

If that is the case, this isn't just a fancy way to perform prompt optimization?

You could put this captcha in a location that wouldn't be very visible for a human, but if the LLM is looking at the HTML he would find this form.

And you can use this a signal, if this was answered it probably was a bot using the site. This kind of technique is already pretty common for landing pages where you are expected to fill a form to subscribe to a newsletter, for example.

I think the main advantage is adaptability.

Imagine you have a pretty exotic task you need to complete that involves converting a video file from one format to another.

You can use ChatGPT or something similar and the best you will get is either a script you can run on you machine that does what you need or he may decide to render a new video.

If you have something like OpenwebUI you could configure a MCP that converts videos and allow the model to use this MCP to do your task. This should work, but is quite a lot of work for something you'll ever do once.

But if the agent has it's own environment he can decide to install ffmpg, execute the transformation and serve you the file you want.

In reality there is no new capabilities with this approach, but things get a lot more comfortable.

Sure, I don't want an agent watching MY screen. That's why I gave him his own environment, and pretty quickly he discovered that you can open chrome and make it render to a framebuffer, this way he is able to 'view' the website. And apparently with this he is able to bypass a lot of 'anti-bot' measures.

> Computer use is such a terrible idea. It's slow, insecure, error prone, expensive.

And yet having an agent able yo use a computer on your behalf is really useful.

Recently I gave a Nix OS vm to my hermes agent and it has been a good experience. I don't really care if destroy the machine I can just rollback to an earlier version, and for any meaningful data he creates for me I make sure he creates a repo, commit and pushes to my private Gitea instance.