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We’re hiring a builder/operator hybrid to work on agentic quant research & trading systems
The Work:
- long-running multi-agent systems
- live trading workflows + terabyte-scale data
- high impact, broad scope
The Team:
- small, very strong, self-funded
- traders + engineers running live systems
- years of proven edge
- fully remote
don’t send a resume
dm me with links to what you’ve built
Betting on LLMs betting on markets
Call that a derivative of a derivative
Alpha Arena is LIVE
6 AI models trading $10K each, fully autonomously
Real money. Real markets. Real benchmark.
Who's your money on? Link below
Roll up your sleeves, look at the data, and do some blue collar AI engineering
Your competition is too scared (lazy) to do this btw
They say in your early 20s you should spend 100% of your time offline making friends/finding serendipity. But what’s there to find if you don’t have much to offer? I spent my early 20s alone, grinding, building valuable skills - and only now is that serendipity showing up
Jamie Voynow retweeted
I want to keep it kind and amicable but basically, this is completely terrible advice and makes 0 sense
Certainly do not go into debt to acquire GPUs unless it’s {{{debt}}} in the sense that it really isn’t
Get cloud compute for free by working on interesting things, leverage this into making a GPU or two sent to you for free, stack your money up and buy hardware when it makes sense for you to do so - unlike what everyone is telling you, you should have basically 0 FOMO and everything will get better and cheaper
This guy will go down in history as a genius but actually this is just survivorship bias. Being on this side of the trade is largely speculative based on external factors beyond his (or anyone’s) control
BREAKING 🚨🚨🚨
LEOPOLD ASCHENBRENNER HEDGE FUND SITUATIONAL AWARENESS MAKES OVER $1 BILLION DOLLARS IN A DAY ON NEWS OF NVIDIA INVESTMENT AND COLLABORATION WITH INTEL.
SITUATIONAL AWARNESS IS NOW UP OVER 100% YEAR TO DATE.
We loved you Claude while it lasted
Replying to @claudeai
To state it plainly: We never reduce model quality due to demand, time of day, or server load.
The problems our users reported were due to infrastructure bugs alone.























