jon cooper

Silicon Valley thinks AI agents are a $20/mo self-serve subscription. Main Street is paying local agencies $10,000 just to turn them on. Everyone assumes AI will be bought primarily online like Slack or Zoom. I think they are wrong. Some of the biggest winners in the AI boom won't be the software vendors. It will be the humans installing it. Here is the reality of SMBs right now: • 54% lack internal AI expertise. • 41% have data quality too poor for AI to even work. • 41% already prefer buying AI through a local IT provider. You cannot "1-click install" a genius AI into a messy CRM or a 15-year-old server. It will just execute the wrong tasks at the speed of light. The AI software will be cheap and a lot will absolutely be bought online. Making it actually work for a messy, real-world business will be expensive. Very bullish on the "Do It For Me" economy being back.

AI won't kill fundamental investing because more information doesn't kill alpha. We have decades of priors here (Excel, Bloomberg, alt data...all democratized analysis & information gathering, and didn't kill alpha). As measured by factor volatility, stocks are less efficient and more alpha-rich than ever (and empirically, the ability of multi-eight figure market neutral multi-managers to consistently grind out 10-15% returns in an idio-maximized way proves this point...15 years ago a $10bn hedge fund was considered to be impossibly large). Innovations in investment process have shifted alpha pools, for sure, and systematic investors have arbitraged many old, reliable fundamental alpha pools. But as the players at the poker table have shifted, the constraints of those new players have created new alpha pools. Long duration fundamental investing has been gutted, and definitionally competing against a group of non-fundamental (quants, factor/thematic investors, indexers) and duration-constrained (multi's) investors should be a huge competitive advantage, long term (however frustrating in the near term). To wit, a 9-month thesis where I "look through" the next two prints is now considered a long-term thesis. Rigorous investment process serves investment judgment, but the real alpha generation fits a power-law distribution and there is some ineffable "nose for money" that the great investors have, that cannot be trained necessarily. Investing is a very hard game, that cannot be distilled to a reinforcement learning sandbox (by the time it is, the regime will have shifted and new drivers move stocks). AI has no sense of materiality, no true discernment, and the lack of context of N of 1 situations (if you haven't noticed, we are living in an N of 1 world!). There is a irreducible element of humanness that is critical to success in fundamental investing, and that won't change. What does this all mean? In my opinion, there is no better time to be starting a careers as an investor. My first year on the desk, I spent a lot of time doing grunt work: updating Nielsen files, updating models for my PM, creating same store sales master files, building question lists for CEO meetings, etc. This is grunt work. I can automate this all now, and get more quickly to the deep, value added parts of learning the investment process. Will AI drive alpha? This is a debate people are having, which I find sort of silly. When used correctly, by the right investor, of course it will. Ask any great investor if they had another 4 hours of research time per day whether the quality of their research would improve? That's kind of a dumb question...of course it will. Compressing the mechanical part of your job to focus more on the artisanal part of the job is Step 1, and with agentic systems accelerating fast is now in the strike zone of possibility. This is before we start to layer in a broader monitoring net and use cases to go deeper and build more rigor, finding signals in unstructured data that were missed before, as well as turning your investment genius into a co-pilot pattern recognition system. The future is very bright for fundamental investing, in my opinion.

I am not sure "Forward Deployed AI Engineers" are going to deliver on what a lot of companies are hoping for. They are useful, yes, but AI applications are far less of a technical issue, and much more about rethinking the deep expertise & structure of your organization around AI.