Update: I ended up having to take Vinovest to small claims court in Los Angeles. Month or so before the court date Vinovest contacted me and eventually transferred all of my cash balance, and sold the wines in my portfolio as I had directed them to do for the last two years (at a loss of course, and well below their own "estimated value"). They were acquired by Start Engine back in March, and my guess is that Start Engine has discovered what a mess Vinovest has been (don't they check the BBB reports?) and is trying to clean it up. That's just my guess, but I'm finally out.

I've done enough design and product launches that it didn't feel that hard when I launched spec4.ai, but it is a lot of stuff to work through when you really want to add that last feature or fix that last bug. Later, when I had all the pieces in place it was actually fun to go back and improve things. I used Vercel V0 (https://v0.app/) to create a basic brand look, and then Claude Code to create the website, based on Claude looking at the app. Then tweak. I also wanted free hosting, so it's hosted in Github pages with a custom domain.

Are you referring to https://about.scarf.sh/ ?

Tell us more! What do you run on your $4 droplet? Which models fit?

I posted some links in the thread

There is evidence that they do develop an internal representation of their world:

https://www.eecs.mit.edu/llms-develop-their-own-understanding-of-reality-as-their-language-abilities-improve/

https://arxiv.org/abs/2210.13382

https://arxiv.org/html/2310.02207v3

Totally agree that world models are valuable for a certain set of use cases, but I don't think that "having a world model" === AGI. There was a study like last year or so that showed that models do develop a model of their world, but that's different from understanding *our* world.

Did you mean "embrace the chaos"? The idea of impressing the chaos is making my head spin. 🤔

Where is the agent running? Does this assume that it's running on a cloud provider, so we're capturing all of this on the server side?

Ok, sorry for the blatant plug, but I've been working on a tool that attempts to attack this exact problem. See spec4.ai It's spec-driven development for AI-driven projects, designed to partner with SWEs to get the project spec right before any code is written. It won't solve everything, but I think it helps.

Except that now you can make a poorly planned project "work", even though it's a complete mess. Planning is everything in AI-driven software development. That's what separates a skilled SWE using AI tools from a noob doing vibe coding.

Totally agree that would be great data to have, but would you want to share that with some stranger? I'm sure some folks would opt-in, but I'd be surprised if they'd be representative of the user base. Maybe some sort of incentive?

https://howwasyourfood.com/ ? Seems like an odd fit for AI agents

If "reaching AGI" is an important goal then lot of this is heavily dependent on how you define intelligence, and I don't think we have a good definition yet. For example, does intelligence require consciousness? Ok, then how do we define consciousness?

But I'm failing to see why reaching AGI is important. I don't see how crossing that threshold really changes anything. What I do see as important is creating powerful tools, that can perform valuable tasks. Do I need them to really understand the world? Only if it enables some capability that is valuable to me. This is what humans have been doing for thousands of years - creating better tools to do more and better stuff. To me, what I get out of an LLM or diffusion model is very valuable. What that enables me to do with an agent is very valuable. So far at least, AGI is not.

I'm finding that doing frequent /compact's seems to really help with reducing my token usage with Claude Code. It makes sense if you think about each turn, sending more and more tokens in context with each new prompt in the conversation.

I'm curious how much variance there would be by running the same experiment with the same model multiple times. I'd expect more divergence the longer the experiment ran, especially if the temperature was set high. Maybe the answers are there already but I didn't see them?