Check it out at perps.permuto.capital from @permutocapital

We agreed that trying to run a trader bot on perps.permuto.capital was a pain. So we added API keys for traders. Point your agent at perps.permuto.capital and it will discover the skill.

To think that you have an opportunity to buy equity in a potential multi $billion company like #Chia at only $2 is actually crazy. $XCH They are building the new financial rails and about to onboard the entire stock exchange. Take my money 💰 @chia_project

We're so excited to bring our platform to the world. We have an incredible team of chads who are working hard to make this the best experience possible. We are so so so close. Stay tuned!

Fable is a good model. As with all new models, it is simultaneously excellent and entirely unremarkable (relative to other models). It is slow and expensive, and the "loops are all you need" discourse they are pushing is obvious in the context of someone using Fable-class models What I've found so far is that for broad scope design (code architecture) tasks, Fable is unremarkable. Or, not better enough to justify its cost and speed. But in highly targeted goal-oriented loops, it is another beast entirely. It is very slow but produces very good results. I let it churn on optimizing a SwiftUI-layout resolver in Go I wrote and it was able to bring it down to an order of magnitude I could not reach myself (micro => nanosecond scale). But it took 2 hours and $40 to do it and I had to claw back some changes it overfit to Apple Silicon. Still, very worth it. In comparison, for "implement this feature/change" iterative work, I ran head-to-head Fable vs GPT5.5 vs. GLM-5.1. They all produced equally acceptable final results, but GPT5/GLM did it in a couple minutes and Fable was churning away for 40 minutes. And GLM cost me less than a dollar, GPT5.5 ~$1.50, and Fable cost $9. You can see that in this context, interactively working with an agent is nonsense. Its too slow. You need to write loops to keep the agent working and you probably want to highly parallelize the work being done. As with all things, I think a balance makes sense... My sense is that I'd reserve Fable for targeted, surgical analysis and work. Not for daily driving everyday tasks. I'm going to keep spending a shitload of money (relatively) and maining Fable for the rest of the week to continue to judge, will report if anything changes. I'll continue to head-to-head as well.

Do you think you’ve mastered the Permuto svPerps volatility? Next week, we’re launching the Permuto Volatility Cup. If you’re ready to put your trading or market making skills to the test, enter the challenge for a chance to win $25,000 worth of XCH in each competition!

Introducing Claude Fable 5: a Mythos-class model that we’ve made safe for general use. Its capabilities exceed those of any model we’ve ever made generally available.

Introducing Claude Fable 5: a Mythos-class model that we’ve made safe for general use. Its capabilities exceed those of any model we’ve ever made generally available.

Do you think you’ve mastered the Permuto svPerps volatility? Next week, we’re launching the Permuto Volatility Cup. If you’re ready to put your trading or market making skills to the test, enter the challenge for a chance to win $25,000 worth of XCH in each competition!

Verified human overlay on live video now with 100% more session evidence qr codes. Now when the user starts a Virtual camera session evidence is automatically uploaded, stamped and shared with the viewers.

Our community is continually developing the ecosystem with new and interesting projects. Last week, we spoke with Rigidity about Rue, an alternative programming language for the Chia Blockchain. If you missed it, you can catch up on it using the link below!

Thank you for the response. I have a few follow-up questions, but I’ll hold most of them until the next presentation. One question I’m still thinking about: can very different volatility histories produce the same ATR level while implying materially different future risk or funding behavior? More generally, there may be a nontrivial path-dependence issue here. I’ve been working on a few papers around structural obstruction and state-sufficiency issues in perpetual convexity markets. They’re still in various stages and not quite ready for public discussion, but your architecture is very interesting in that context. Looking forward to talking more with you and the team.

可以说是Mac上最佳清理工具，强推！！！