How do you guys use AI in your research process?
Will add my two cents to kick things off. The pace of innovation was pretty astounding and thought there would be enormous utility to this tool. But frankly it seems to have leveled off where I actually use it a little less than I would have thought
It helps to build foundational knowledge on a name, as well as gather data points quickly. But that's kind of it, the analysis is boiler-plate (which makes sense of course) and a lot of the time saving 'hacks' don't really end up saving much time
Curious to hear if experiences differ across other folks / firms. How do you use it today vs. 6mo ago or in general your normal pre-AI process?
Yes, but only as a form of augmentation and not replacement. Helpful for expanding the surface that can be covered. The greater the surface, the greater the chances of coming up with a good idea or alpha.
Depth of insight and creativity are still very much human.
That's exactly my exp. Can cover more names since the 70% of work on a name that's table-stakes can be done 2-3x as fast now. Remaining ~30% has always been the area of differentiation even before AI, and I have not seen that be done by AI well (either myself or others are my firm)
It's reassuring from a fundamental equities career perspective. Also exciting in being able to turn over more rocks, though on flip side the boss always wants more productivity so have to balance that as well
did you see the perplexity stock pitch competition? like that hehe
I exited my company (I went to HBS) so now I just chill really
I use AI constantly for finance—everything from analyzing earnings calls and building financial models to researching industries, competitors, and market trends. The biggest challenge isn’t getting answers anymore; it’s keeping all the context organized across dozens of reports, filings, spreadsheets, and conversations.
That’s why I’ve been using Trustgraph. Instead of treating every prompt like a fresh start, it connects information into a context graph, so relationships between companies, metrics, assumptions, and previous analyses persist over time. It feels less like searching through notes and more like building a knowledge base that AI can actually reason over.
For finance work, that means I spend less time re-explaining context and more time analyzing the business. It’s become one of the more practical open-source AI tools I’ve used because it improves the quality of long-running research instead of just making individual prompts better.
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