An idea sounds so easy
And a taste of full autonomy
The story of today, which was a Green Day with all stocks up.
My main complaints are that not much of the buying power (roughly 3x actual deposits) was used, which is inefficient. And I worry that the conservative sizing logic is holding back some of the best performers. All to figure out.
But… today was the first morning I can remember with no warnings or emails from the machine, where I sat reading in the garden until 10am before visiting the office to see what Money Monster was up to.
Some thoughts whilst I’m feeling philosophical.
An idea sounds easy
A simple phrase doesn’t belie the million obstacles on the way.
“Do an AI to trade earnings calls” doesn’t exactly sound simple, but doesn’t reveal so everything that has to go right. This is true of any business, project, or endeavor.
Each morning this system tunes into all 25+ earnings calls, detects their completion, tracks financial metrics, summarizes the transcripts, passes them on to the analysts, queues up the trades, sends them for execution and reconciliation, and tracks throughout the day.
There have been so many frustrating mornings with things not working, missed trades or botched analysts, simple bugs, or even just the time it takes to build something, to make something real from your imagination.
A common response I got to this project is “aren’t people doing that already?”
Well yes kind of, but doesn’t mean one more can’t join them, especially with a few friends (Opus 4.6, GPT 5.2). It’s helpful when your friends have a pretty decent grasp of all human knowledge and the reasoning capabilities of a supercomputer from a an old sci-fi movie.
But I also think that only through the friction of being fully engaged with something can you begin to understand the opportunities. That’s why so many successful businesses are started by someone that was previously in that world and could see the opportunity.
But my bigger point is: things are achieved by the people that push ahead regardless of the chances. Founders, not that they are the only people that do this, but they are the ones I know, always have this slightly deranged zeal that propels them forward. Who knows if they will make it? We don’t - but we know that they certainly won’t if they don’t try.
Timing
Treading water in the right place is so key to a project like this. No matter how many hustle-bros tell you it’s all about grinding, the reality is that it’s about a lot more than that, and one of the most capricious ingredients is luck.
The harder I work, the luckier I get, as the old adage goes. Well, that’s kind of true. If you are going in vaguely the right direction this certainly speeds things up. But how key is luck? I often think about documentaries, the best ones out there are the ones where something crazy happens that the producers could not have possibly predicted.
Not as big as that, but this month Opus 4.6 was released by Anthropic. I was instantly building faster and smarter as soon as it be available than before.
Agentic ‘end to end’ AI takes over the hype cycle, but for most of us on the tools AI functions more as a cognitive exoskeleton, helping us ‘lift’ more and get more done. It is remarkable how much more productive I am in an hour than I was three years ago, and that’s not just because I need to make some money.
I still have to eat, exercise, sleep, get drunk, all important human endeavors, they are becoming the limiting factor which will bring us to…
Agentic AI
When you hear about people leaving their machines to code all night whilst they sleep, they are talking about agentic AI. You give it a goal and it does the rest, chooses the tools, remembers the context, adjusts based on results.
What would a true agentic AI software build given this prompt: “Build a service to trade earnings transcripts intraday for profit. “ ? It would be interesting to watch, it would probably come up with ideas that I haven’t yet. Thought I do think human taste and imagination have some value yet.
Better, faster, cheaper
One of the reasons I knew that crypto would not live up to its promises is that good technology should make things better, faster, and cheaper. Crypto doesn’t do that, except in very specific use cases like crime.
However AI is useful. These frontier models are surpassing our expectations every few months. If you used AI in the past and were not impressed, you need to try again now. Everything is better from reasoning, speed, multitasking, context size, it does more for you than before. And the previous state-of-the-art models are getting cheaper and cheaper.
Paying for Cursor or OpenAI is the fastest I’ve handed over my credit card. Cursor hit 100 million ARR faster than anyone in recent memory (credit: Aakash Gupta) because the value is obvious.
Learning
I did study AI in 2008 aka ancient history, but I tried to do the Harvard CS course more recently to get up to speed again. Of course it cannot possibly keep up with the state of the art, although it does teach the fundamentals of modern neural networks.
However, having a project like Money Monster has far surpassed (and made more fun) what I would’ve learned on a course. Applying it to my own projects and understanding how it helps with each objective has the emotional resonance to keep me learning. And to stay inspired.
Software engineering and AI
I generally avoid the dystopian topic of the future, especially as some parts seem to have arrived early. But it’s not lost on me that I used to run a business with 100 employees. Now I am buying computer power. And how many software developers does it need to change a light bulb now? I was struck in this video from a documentary about DeepMind and Demis Hassabis how antiquated this description of a software developer seems. What is the right description today ?
Signing off for the weekend , I’ll leave you with a final note from my friend Atlas on the topic of AI job displacement just today.
