I think a lot of investors fall into a trap in deploying AI by asking the question, "How do I automate what I already do?" And then get very uncomfortable with the idea of handing over that existing process to an agent. Then end up saying "I feel like I won't understand the name as well if I let AI do it". And that is very fair and probably correct feedback. A reframe that has helped me is this: imagine you had a small clone army of yourself. At your quality bar, working in parallel on whatever you assign them. 12 Brett's showing up, eager, with capacity, & the same process knowledge, going deep on various deep dive or tracking projects that never bubble up to the top 3 spots on my to do list. That simple visualization, for me, sparks my creativity on agentic system design. "Wouldn't it be nice if i had another me to go in an build a master healthcare trend tracker across public company data, unstructured transcripts, publicly available data, and private claims data, then update it every week, giving me a weekly report on trajectory of healthcare cost trend." Public equity investing is an endless game of triage, a Pareto optimization of your daily work to focus on what matters. With a clone army, that triage can end, and I can scale depth in a way that was never possible (I lived this struggle trying to scale Tiger-style depth to the multi-manager approach and can attest to how difficult it is). So, don't speed read through the filings, bypassing comprehension. Stick with the parts of your process that drive real company & situational understanding. But, in parallel, spin up a team of mini agent "clones" of you to go broader & deeper on your existing investment process. > A clone that triple checks every financial model and pushes back on every assumption > A clone that runs a 7-year bull/base/bear model or distributable FCF analysis on top of your existing 3-statement model, in a new tab > A clone that listens to every public statement from every competitor, whether on an earnings call, investor conference or podcast, pinging you with relevant read-thoughts > A clone that gives you the devil's advocate on every position, encoded with your own custom thesis creep prevention checklist > A clone that does a deep proxy/form-4 analyses on equity incentives for all of your management teams > A clone that helps you analyze the buy-side whisper on every name heading into print > A clone that highlights "hockey stick" guidance risk across your coverage > I could give you 50+ more, some of which are possible today with existing agentic capabilities, many of which are a wager on the continuation of improvement in the agentic ecosystem (both model intelligence, model harness & data infrastructure) These are all analyses that you could do if you had infinite time. But the reality is that a public equity investor is fundamentally time constrained. You, intentionally or not, have learned to focus your time on the highest leverage parts of the investment process. Great analysts & investors are ruthless in spending time on the most important thing. If you have been successful, be very careful in making fundamental changes to your investment process. And the reason I've seen the most impressive results from AI from senior (not junior) investment professionals is that they know what to do and turn that domain knowledge into structured agentic workflows. The junior doesn't know what to do (yet), and can have poor judgment on which parts of the workflow to augment. (this can start of a whole new conversation about onboarding junior analysts with the existing Senior Analyst clone architecture and process checklists for the junior, but that's a tweet for another day...) On the other side, you vs. a team of you + 12 clones should be an unfair fight. You will have broader & deeper information capture that definitionally should drive more accurate insights on businesses & stocks. AI doesn't natively have good investment judgment, but a talented investment professional surrounded a swarm of agent clones should make much better investment decisions over time.