I'm building AthenaOS: https://athena-os.ai/

Basically OpenClaw but with investing dashboards for my portfolio, additional tools specifically for investing, and exploring an AI-Human collaboration on researching economics (check the 'community' tab).

The data models are all in markdown and Excel so that there's no lockin and you can manually edit positions, personalities, etc.

This comes from frustration around most investing tools basically scraping your personal data + forcing you to lock into subscriptions. I think it's now possible to just vibe code most of what one needs, aside form raw data subscriptions.

It's all open source, too: https://github.com/wgryc/athena-os

I'll add one more point. If you scroll through his Substack, a lot of his posts are incredibly negative and unproductive. I was (and continue to be) someone who cares deeply about responsible AI... But there's a difference between working on AI responsibly or pushing the debate, versus simply criticizing everything that is done as folly, useless, crap, etc.

"Everything can be taken from a man but one thing: the last of the human freedoms—to choose one’s attitude in any given set of circumstances, to choose one’s own way."

Fantastic book.

I hate all the portfolio tracking tools out there + don't understand why tools like FactSet or CapitalIQ cost so much.

... so I'm building an open source version.

Track all your trades in Excel, and get Sharpe ratios, Sortino ratios, or even pass it on to an LLM to have it recommend trades based on news feeds.

Planning to open source it in the next week or two, once I add the proper tests and docs! :)

I'm a huge Malick fan. If you are curious about his very unique style, this 20-minute video outlines why his cinematography is so unique and so powerful: https://www.youtube.com/watch?v=waA3RXy13aA

That's a fascinating point, thanks for sharing. I wonder if prediction markets will 'asymptotically converge' into similar sports betting strategies.

The article talks about how prediction markets' sports books are significantly more profitable. This has less to do with financial structures and more to do with who wants to make bets and where.

According to the article, prediction markets make magnitudes more money on potentially illegal (by today's standards in the US, anyway) sports betting than true event contracts.

That’s a fair point. I agree the current profitability is largely driven by demand patterns and regulatory arbitrage rather than pure market design. My comment was more about why the underlying event-contract model struggles to scale sustainably, even when interest exists.

Have you considered launching your own weather prediction market instead?

Parametric insurance, energy traders, etc could be good markets.

No I haven’t but I think the lack of liquidity as a chicken and egg is a huge barrier to entry in these markets specifically. They are small right now but there are climate derivatives on the Chicago mercantile exchange so this isn’t a new concept I think.

Could you tell me more? https://discord.gg/HPpN42SKQ

Seems like this is the _President_ of the division, so sounds like there's a nontrivially-sized team to manage.

> Background Tasks.

Amazing. If this means no more management of Celery workers, then I am so happy! So nice to have this directly built _into_ Django, especially for very simple task scheduling.

You will have to keep Celery for the foreseeable future. The current implementation is just a stub which provides a unified interface for some future backends.

Background tasks production backend is unfortunately the battery that is not included.

Meanwhile, Huey works just fine: https://huey.readthedocs.io/en/latest/django.html

I remember huey! Glad to see leifer is still maintaining it. I liked it way back when it first came out, was a breathe of fresh air compared to celery

Try RQ.