AI and the Future of Fundamental Investing

Day 1 · Oct 13 Day 1 digest · More from this day

In a Kepler-hosted fireside, former Citadel PM and Candlestick Capital founder Jack Woodruff argues that AI will not change long-term stock picking or divergent-view alpha, but will flatten analyst prep work and turn investing into a time-management game where humans stay the bottleneck.

Read the official edition ↗ A detailed reading edition with a searchable transcript.

TL;DR

Long-term stock picking will not change much: there has always been a mosaic, and alpha comes from divergent views. That stays.
What changes completely is table stakes: what everybody has, and how they synthesize information. Traditional portfolio manager and analyst roles get “completely thrown upon their heads.”
Humans are still the bottleneck. Information must still get into your head, so the open question is how man and machine work together.
AI compresses prep work that took six to eight hours into about five minutes. The freed time goes to proprietary research, channel checks, and industry backdrop work.
Reading 10-Ks and transcripts will not disappear for analysts truly close to a name. Big-data grinding will be outsourced.
The winners are the people who use these tools to spend the right amount of time on the right names.

Key lessons

Split the question “what changes” in two. Long-term stock picking itself will not change, because the mosaic and divergent-view alpha creation have always existed and stay the same [05:56:50]. What changes completely is how people synthesize information and where table stakes land [05:57:09].
Expect role upheaval, but do not expect a clear blueprint yet. Woodruff says the traditional roles of portfolio manager and analyst “are going to be completely thrown upon their heads,” yet it is too early to say what the new roles look like because the tools are so new to users [05:57:23, 05:57:31].
Humans remain the constraint. At the end of the day you have to get the information into your head, so the design problem is how man and machine work together [05:58:12, 05:58:24].
Treat investment management as a time management exercise. One stock gets world-class knowledge but no action; spread time across more names and you hit diminishing returns per name [05:58:32 to 05:58:55].
Quantify the AI saving concretely: preparation work that used to take six to eight hours can now take about five minutes with an AI program [05:59:11]. That raise in table stakes frees time for proprietary research, channel checks, and industry backdrop work [05:59:51].
Do the headcount math against competition, not in isolation. His career data points: 18 people covering 400 stocks at Citadel (Surveyor) and 30 stock pickers at Candlestick [05:58:02]. AI “perhaps” helps cover more names, but if you finish in two hours, a competitor still works 16 hours a day to find the extra edge [05:59:36, 06:00:04].
Sort junior analyst work into two buckets. Reading 10-Ks and transcripts stays, because analysts truly close to a name must still process that information; summaries only cut the time. Going through big data gets outsourced [06:00:45 to 06:01:17].
Redefine the analyst job as triage. The AI or agent pushes you toward the right names, and the winners are the people who use the tools to spend the right amount of time hunting a divergent view [06:01:27, 06:01:43].

Watch this session

Jack Woodruff, Vinoo Ganesh · 2:43:50 PM ET–2:51:42 PM ET · fireside · Watch on YouTube from 05:55:58

Notable quotes

“So the biggest issue is humans are still the bottleneck.” [05:58:12 | 2:46:03 PM]
“Investment management is a time management exercise.” [05:58:32 | 2:46:23 PM]
“The roles, the traditional roles of, say, a portfolio manager or an analyst are going to be completely thrown upon their heads.” [05:57:23 | 2:45:14 PM]
“What I mean by that, if I spent all of my time working on one stock, that’d be great.” [05:58:36 | 2:46:27 PM]

Session narrative

Vinoo Ganesh, CEO of Kepler, opened the fireside at 2:43:50 PM and brought Jack Woodruff to the stage. Woodruff introduced himself as the founder and former Chief Investment Officer of Candlestick Capital Management, a long-short equity hedge fund in Greenwich, Connecticut. Before that, he was a partner and portfolio manager at Surveyor Capital, a division of Citadel. Ganesh framed the format: the two had held this conversation before, and he called Woodruff one of the most enlightening people to talk with, because Woodruff spent his career picking stocks while the environment changed faster than ever.

Ganesh’s first question asked what fundamental investing looks like in the age of AI, five years from now. Woodruff split the answer. Long-term stock picking will not change much, because the mosaic and divergent-view alpha have always existed. What changes completely is the synthesis layer: where table stakes go, what everybody has, and how they process data. He predicted the traditional portfolio manager and analyst roles would be upended, but he refused to draw the new org chart. The tools are too new to users, and nobody has proven the endpoint yet.

The core of the chat turned to capacity. Ganesh cited the numbers from Woodruff’s career: 18 people covering 400 stocks at Citadel, and 30 stock pickers at Candlestick. Could one great analyst cover all 400 by 2030? Woodruff answered that humans are still the bottleneck, because information must still get into your head. He framed investment management as a time management exercise, with diminishing returns per name as coverage widens. AI can perhaps raise coverage, and it can compress six to eight hours of preparation into five minutes. But he warned against reading that as a headcount story: the industry is competitive, so a rival who works 16 hours a day will absorb the same tools, and the work you paid an analyst for a year or two ago is not what you will pay an analyst to do in a year.

On junior analyst work, Ganesh asked what would look absurd in five years. Woodruff pushed back on the popular take that analysts stop reading 10-Ks and transcripts. If you are truly close to a name, you still need to process that information; summaries only cut the time. Big-data grinding, by contrast, is easy to outsource. The agent’s real job is triage: pushing you toward the right names, since the winners are the people who spend the right amount of time hunting the divergent view. The record ends abruptly: after Ganesh’s “Very cool” at 2:49:51 PM, the transcript holds only the fragments “And on.” and “All right.” through 2:51:42 PM, so the capture cuts off before any formal close. Note also that the verified stream timing (2:43:50 PM to 2:51:42 PM) runs earlier than the published agenda slot of 2:55 PM to 3:13 PM; the day ran ahead of schedule.

Speaker details

Jack Woodruff - Senior Advisor, Kepler. Founder and former Chief Investment Officer of Candlestick Capital Management (CCM); he led the firm from 2019 through 2025 and built its investment, research, and risk frameworks. Before that he was a portfolio manager in Citadel’s equity unit, Surveyor Capital, from 2010 to 2019, where he built and led an 18-person team and invested in more than 400 global equities. He also worked at Sigma Capital (a division of SAC Capital Advisors), Northsound Capital, and Trivium Capital; he began at Ernst & Young and holds an MBA in Finance from NYU Stern and a B.S. in Accounting from USC.

Vinoo Ganesh - CEO, Kepler. CEO of Kepler, the ground truth platform for AI, starting with finance: language models interpret financial questions and plan analysis, while deterministic software retrieves source data, runs calculations, and records how every result was produced. He spent seven years at Palantir, was CTO of Veraset (acquired after reaching $15M ARR), and was Head of Business Engineering at Citadel. Website: https://www.kepler.ai

Full timestamped transcript

[05:55:58 | 2:43:50 PM] Kepler, excited to have Jack Woodruff with me.
[05:56:00 | 2:43:52 PM] Quickly introduce yourself.
[05:56:01 | 2:43:53 PM] Yeah, hi, I'm Jack Woodruff.
[05:56:03 | 2:43:55 PM] I am the founder and former CIO of Candlestick Capital Management, a long-short equity hedge fund based in Greenwich, Connecticut.
[05:56:11 | 2:44:02 PM] Before founding Candlestick, I was a partner and portfolio manager at Surveyor Capital, which is a division of Citadel.
[05:56:22 | 2:44:13 PM] Very cool.
[05:56:23 | 2:44:14 PM] Thanks, Jack.
[05:56:24 | 2:44:15 PM] So the reason we did this this way is we've had this conversation before, and I think this is one of the most enlightening folks to chat with, given that Jack has spent his career picking stocks in an environment that's changing more than it ever was before.
[05:56:38 | 2:44:29 PM] So we'll treat this really as a fireside chat.
[05:56:41 | 2:44:32 PM] So, Jack, paint the picture for us.
[05:56:44 | 2:44:35 PM] What does fundamental investing look like in the age of AI, say five years from now?
[05:56:49 | 2:44:40 PM] Well, it's hard to say.
[05:56:50 | 2:44:42 PM] Like, long-term stock picking, I don't believe is really going to change much at all.
[05:56:57 | 2:44:48 PM] There's always been a mosaic, and there's always been alpha creation by finding a divergent view.
[05:57:04 | 2:44:55 PM] So that isn't going to change at all.
[05:57:07 | 2:44:58 PM] I think that that still will stay the same.
[05:57:09 | 2:45:00 PM] Now, how people synthesize all of the information and where table stakes go to in terms of, like, what everybody has, and then how you synthesize that data is going to change completely.
[05:57:23 | 2:45:14 PM] The roles, the traditional roles of, say, a portfolio manager or an analyst are going to be completely thrown upon their heads.
[05:57:31 | 2:45:22 PM] And I still think it's, like, too early to say what that's all going to look like, as these tools are just so new, especially to the users.
[05:57:42 | 2:45:33 PM] You've got a lot of people doing a few things, but it's just not clear to me.
[05:57:46 | 2:45:38 PM] That it's like we're there and, oh my gosh, it's going to be these new things.
[05:57:51 | 2:45:43 PM] Like, we have a bunch of other things to kind of talk about, but I think it's going to be super fascinating to watch how it all plays out.
[05:58:01 | 2:45:52 PM] Very cool.
[05:58:02 | 2:45:53 PM] So at Citadel, you had 18 people covering 400 stocks, and at Candlestick, you had 30 stock pickers.
[05:58:08 | 2:45:59 PM] Could one great analyst cover all 400 by 2030?
[05:58:12 | 2:46:03 PM] So the biggest issue is humans are still the bottleneck.
[05:58:16 | 2:46:08 PM] I mean, like, at the end of the day, you have to get the information into your head.
[05:58:24 | 2:46:15 PM] So it's really all about sort of how man and machine can work together.
[05:58:32 | 2:46:23 PM] Investment management is a time management exercise.
[05:58:36 | 2:46:27 PM] What I mean by that, if I spent all of my time working on one stock, that'd be great.
[05:58:42 | 2:46:33 PM] I'd probably know it better than anyone else in the world.
[05:58:45 | 2:46:36 PM] But, like, if there wasn't anything to do in that stock, I'd be kind of—there isn't much to do.
[05:58:50 | 2:46:41 PM] Well, if I do two, well, then I have half as much time and so forth until I go.
[05:58:55 | 2:46:46 PM] So you start getting diminishing returns on how much time you could spend on any particular stock.
[05:59:03 | 2:46:54 PM] So, you know, what can AI do?
[05:59:06 | 2:46:57 PM] Can AI help me cover more names?
[05:59:09 | 2:47:00 PM] Perhaps.
[05:59:11 | 2:47:02 PM] Maybe it allows me to raise the table stakes on what I just kind of, like, have as a general knowledge, because that work used to take me hours to prepare to get me ready for what it was, and now maybe, you know, an AI program can, you know, help me prepare a lot of that work in five minutes, which used to take me six to eight hours.
[05:59:33 | 2:47:24 PM] So that allows me to do other things.
[05:59:36 | 2:47:27 PM] Again, like it's a very competitive industry, so it's not like if I get rid of all these people or if I have like five analysts, whereas before I had 30, yeah, maybe those people can do more.
[05:59:47 | 2:47:39 PM] But now all of a sudden this opens up other time.
[05:59:51 | 2:47:42 PM] This opens up time that I could spend doing either more proprietary research, channel checks, more sort of like...
[05:59:59 | 2:47:50 PM] Like industry backdrop work, because again, like you're going to need to find these divergent views.
[06:00:04 | 2:47:55 PM] So it's like, if I do the exact same thing I was doing before and it's like, hey, wow, I can get my work done in two hours, well, someone else is going to be still working 16 hours a day trying to find, like, that extra thing that's going to make you money.
[06:00:21 | 2:48:12 PM] Because, you know, just doing this stuff is obviously, like, what we used to pay an analyst to do, you know, a year or two ago is not what we're going to be paying an analyst to be doing, you know, in a year.
[06:00:36 | 2:48:27 PM] Very cool.
[06:00:37 | 2:48:29 PM] And on that, what is something today that a junior analyst does that you think will be absurd if they're still doing in five years?
[06:00:44 | 2:48:36 PM] Well, it's funny.
[06:00:45 | 2:48:37 PM] Like, it's like, oh, you're not going to be reading 10-Ks, you're not going to be reading, you know, transcripts.
[06:00:51 | 2:48:43 PM] I actually don't believe that to be true.
[06:00:53 | 2:48:45 PM] Like, if you're truly close to a name, you're going to still need to, like, process a lot of that information.
[06:01:01 | 2:48:53 PM] Now, you might be able to get, like, summarized versions that can cut down the time it takes you to do those things, but you still need to get that information sort of into your head.
[06:01:11 | 2:49:03 PM] Like, we used to have a lot of analysts that would be going through a lot of, like, sort of like big data and things like that.
[06:01:17 | 2:49:09 PM] I definitely think that that can sort of be outsourced, and that'll be super easy to, you know, I would be surprised if a lot of these guys aren't necessarily doing that stuff.
[06:01:27 | 2:49:18 PM] But what I believe the AI is going to do, or the agent or whoever it is, is going to be pushing you in the right direction to work on the right names.
[06:01:41 | 2:49:32 PM] Like I said, this is time management.
[06:01:43 | 2:49:34 PM] It's all about how do I know to work on the right things, and that's where the winners are going to be, is the people who can figure out how to use these tools to get you to spend the right amount of time working on potentially finding, like, a divergent view.
[06:01:59 | 2:49:51 PM] Very cool.
[06:02:37 | 2:50:28 PM] And on.
[06:03:50 | 2:51:42 PM] All right.