Stavros Zenios
33.5K posts

Stavros Zenios
@StavrosZenios
Professor, father, hiker, blogger -not necessarily in this order.


Turn your ideas into published books faster than ever. 🎨 Design, research, and upload – all in one platform. From coloring books to storybooks, Book Bolt helps you publish faster and smarter.








If you have working papers that are not too polished and you're willing to let Coarse use them as demonstrations on its examples page, let us know - we'll give you endless not-for-profit full reviews as a token of appreciation. Please DM or reply.






What happens when you let an LLM autonomously improve its own prediction market strategy for 9 days straight? It learns to give up. Me and @ahall_research worked on a LLM pipeline on Polymarket (Bitcoin, NYC weather, miami weather) and every 4 hours it made predictions. Every night a separate AI reviewed performance, picked one thing to change and committed code. No human in the loop. Timeline: - Day 1: It added confidence prompts - "don't hedge, commit to your prediction" - Day 2: It turned down the shrinkage parameter that pulls predictions towards market consensus - performance got worse - Day 4: It reversed course and turned shrinkage back - Day 6: It tried a clever prompt trick for weather contracts (also made things worse and got autoreverted) - Day 7-9: It stopped changing anything By the end, the squared error was down 54%. This sounds impressive until you realize that the improvement came almost entirely from the system learning to deviate less from market prices. The self improvement loop worked perfectly as engineering but the problem is that the underlying system doesn't have an information edge on any of these contracts since it's reading the same news the market already priced in. To actually beat the market, the system would likely need faster or better information or contrarian accuracy (i.e., correct predictions specifically in the cases where the market is wrong).









The core idea is that this lets you skip writing but it doesn’t let you skip reading and thinking. And the surprising result is that this works. Personally I process most of what I file by reading it, reading its summary, reading the LLM’s opinion on how it fits into the wiki and what is new/surprising, etc. depends on the documents this is flexible and up to you



The book of Genesis, 84% created by AI! 🤣🤣🤣 Happy Easter/Happy Passover!

All of this is meaningless if you are not actively reading and writing the notes, which knowledge management enthusiasts tend not to. Most of the most complex pieces of writing in history were composed with linear notebooks. You can't outsource reading and its metabolisation.






