Invest with AI

Fundamental Edge

Brett Caughran and Khe Hy lead a deep dive into AI for investing, joined by guests at the cutting edge of the field. Our goal is to be your Sherpa through a rapidly changing landscape by distilling what's working, what isn't working, and how you can leverage AI in your own process. Follow along as we tackle AI's biggest challenges and opportunities, one episode at a time.

Episodes

  1. Deploying AI on the Buyside: A 20-Year Engineer's Playbook

    1 day ago

    Deploying AI on the Buyside: A 20-Year Engineer's Playbook

    What’s the biggest hurdle in deploying AI on the buyside? After 20 years of building software, PragmaNexus Founder Matt Stockton has found that the most difficult challenge is knowing your own process well enough to write it down. As he puts it, that’s 80% of the work. He, Brett, and Khe get into the shift from "single-player" AI (one person, one laptop) to "multiplayer" AI across a whole firm, the voice-memo trick Matt uses to pull his own process out of his head, and why he tells people to go try the one thing they're sure AI can't do yet. A grounded, practical conversation on what it actually takes to get AI working inside an investment firm.  Timestamps: [00:00] Intro [00:59] — 20 Years of Software, From Data Infra to LLMs [02:23] — Single-Player to Multiplayer: The Local-Machine Problem [03:18] — Building a Company "Resource Brain" [05:57] — Folder Structures and Markdown vs. Relational Databases [07:48] — The Excel Problem: 1.2M-Token Financial Models [10:46] — The Bitter Lesson of AI Engineering [12:36] — How Time-Crunched CIOs Actually Stay Current [15:42] — AI Psychosis and the Aha Moment [17:27] — Turning a Research Doc Into a Shareable Website [20:06] — Bucketing the Deployment Problem: Job to Be Done [23:29] — Investors as Intuitive Pianists: The Articulation Problem [24:07] — The Voice-Memo Hack for Extracting Your Own Process [25:22] — Why It's Not a Tech Problem [28:49] — The Last Mile: Getting From Prototype to Production [29:42] — Assembling Existing Tools vs. Building Custom [32:06] — Moving Beyond Basic Synthesis Skills [34:20] — Skill Creation, Hill Climbing, and the Red Pen [36:27] — Building Evals and LLM-as-Judge [40:06] — Debugging the Model: The Goodwill Impairment Trap [42:25] — The Tool Stack: Claude Code, Codex, and Mobile [49:45] — Chinese Models, Open Weights, and Token Efficiency [52:13] — Frontier Intelligence for Judgment, Cheap Models for the Rest ----------------------------------------------- Want to actually build these workflows yourself? The AI Accelerator is Fundamental Edge's 6-month cohort for investors who want repeatable AI workflows. Learn More below: https://www.fundamentedge.com/ai-accelerator Watch the full podcast series on our site: https://www.fundamentedge.com/invest-with-ai Follow Invest with AI on: Spotify Apple Podcasts YouTube

    56 min
  2. Stoic Point Co-Founder: AI is Bringing Back the Lean Hedge Fund

    26 Jun

    Stoic Point Co-Founder: AI is Bringing Back the Lean Hedge Fund

    In this episode, Brett Caughran and Khe Hy sit down with Raj Shah, co-founder of Stoic Point and a former partner at Light Street, to get into how a two-person fund can run resourced like a firm ten times its size. Raj makes the case that AI lets a lean, concentrated fund compete with much larger teams and argues he's more worried about AI replacing him than the junior analysts everyone else is fretting over. We get into: How a lean fund recreates the institutional resource stack without the institutional headcountThe three buckets where AI fits the process: screening, research, and monitoringThe "meta-screen" that surfaces ideas across 50 filters at onceThe black-box quirk where the same prompt run twice returns two different stock listsSeparating the deterministic screen from the non-deterministic one — and why he starts in BloombergHow automated monitoring caught a read on Lux Experience from an unexpected placeWhy AI makes a strong junior analyst more valuable, not lessTurning your own process into an intern training guide — and a sparring partner that rips apart a pitchWhy Excel with AI was the biggest positive surprise of everything he testedSingle managers vs. platforms, and what an AI-native fund means for raising capitalWe're not coming at this as "experts" with all the answers. We're in it every day, testing, breaking things, and trying to understand where this is going. The goal of the podcast is simple: bring you along as we learn, and give you a clearer view of how AI is actually being used in investing. If you work in equity research, at a hedge fund, or on the buyside and you're trying to make sense of AI, this is a good place to start. ***DISCLAIMER: Everything you hear on this podcast is for informational and educational purposes only and should not be considered investment advice. Any companies, securities, or strategies mentioned by our guests or hosts are discussed for illustration and shouldn't be taken advice to buy or sell. Markets carry risk and individual situations differ, so please do your own research or consult a licensed financial advisor before making any investment decisions. The views expressed are those of the individual speakers and don't necessarily reflect those of Fundamental Edge or its affiliates. Chapters (Timestamps) Timestamps: [00:00] Intro [01:21] — Greenhill to Highline to Light Street: Building Stoic Point [04:00] — Recreating the $5B Resource Stack at a Lean Fund [06:30] — The Three Buckets: Screening, Research, Monitoring [12:00] — Same Prompt, Two Different Stock Lists [14:39] — Deterministic vs. Non-Deterministic Screening [15:31] — The UI Problem and the "Meta-Screen" [17:54] — When Computer Use Got Good Enough to Click Through Bloomberg [18:49] — Can Codex Run Your Screens Today? [20:00] — Automated Monitoring: How AlphaSense Caught the Lux Experience Read [22:30] — The Narrative Violation: Why Juniors Get More Valuable [25:16] — Turn Your Process Into an Intern Training Guide [26:55] — Building a Sparring Partner That Rips Apart a Pitch [27:36] — Excel + AI: The Biggest Positive Surprise [32:35] — If Big Firms Automate Juniors, Does the Pipeline Break? [34:41] — What Happens When LLMs Develop Judgment [35:59] — Measuring ROI in P&L, Not Hours [38:25] — Single Managers vs. Platforms in an AI World [43:42] — The Magnetar Read: Build the Product Around the LLM [47:25] — Flip It: Human on Idea Gen, AI on Risk [50:42] — Advice for the AI-Native Analyst [54:34] — Using AI to Deepen an Experience, Not Skip It Want to actually build these workflows yourself? The AI Accelerator is Fundamental Edge's 6-month cohort for investors who want repeatable AI workflows.  Learn More below: https://www.fundamentedge.com/ai-accelerator Watch the full podcast series on our site: https://www.fundamentedge.com/invest-with-ai Follow Invest with AI on: Spotify: https://open.spotify.com/show/033xcEEovVViS7hIYwNuGZ Apple Podcasts: https://podcasts.apple.com/us/podcast/invest-with-ai/id1896918892

    56 min
  3. Investing with AI: From Chatbots to Agents (What Changed for Investors)

    12 Jun

    Investing with AI: From Chatbots to Agents (What Changed for Investors)

    Welcome to episode one of Investing with AI Podcast for Financial Analysts. We’ve spent years in investing, and over the past couple years, we’ve been deep in the weeds with AI. Testing tools. Working with firms. Trying to understand what matters versus what’s just noise. For a while, most of it didn’t feel that useful but that’s starting to change rapidly.  In this episode, we talk through what’s shifted, from basic chatbots to more agent-based workflows, and why that’s starting to matter for investors, analysts, and buy-side teams. We get into: The difference between AI chat tools and agent workflowsWhy AI felt overhyped before and what’s different nowWhere AI is actually useful in investment research todayThe limitations that still exist (and there are a lot)How investors should start thinking about using AI in their processWe’re not coming at this as “experts” with all the answers. We’re in it every day, testing, breaking things, and trying to understand where this is going. The goal of this podcast is simple: Bring you along as we learn, and give you a clearer view of how AI is actually being used in investing. If you’re working in equity research, hedge funds, or the buy side and trying to make sense of AI, this is a good place to start.  Chapters (Timestamps) 00:00 – Intro: Why We Started Investing with AI  00:21 – Khe’s Background (BlackRock → AI Consulting for Hedge Funds)  02:06 – Brett’s Background (Hedge Funds → Fundamental Edge)  03:30 – The Real Shift: From Chatbots to AI Agents  04:17 – When AI Actually Started Working (2025 Inflection Point)  06:11 – “AI-Pill” Moments: What Changed Our View on AI  07:43 – What Are Agent Workflows in Investing?  10:04 – Why AI Tools Failed Before (and What’s Better Now)  11:43 – How Much of an Investor’s Workflow Can AI Handle?  12:20 – Defining “Agentic” AI (Simple Explanation)  14:42 – Data Accuracy, MCP, and Why This Matters for Finance  17:19 – The Biggest Unlock: Using AI for Validation  19:57 – Common Problems Firms Have with AI Adoption  22:02 – Why Most Investment Workflows Are “Vibes”  24:00 – Turning Intuition Into Process (Hardest Part of AI)  26:44 – Expectation vs Reality: What AI Can’t Do Yet  28:39 – How to Start Using AI in Your Investment Process  30:10 – How We Stay Ahead in AI (Learning, Tools, Research)  33:20 – Translating AI Into Real Investing Workflows  35:14 – Why There Is No “Final State” of AI  36:09 – What AI Means for the Future of Investing Careers  37:30 – Outro: What to Expect From This Podcast

    38 min

About

Brett Caughran and Khe Hy lead a deep dive into AI for investing, joined by guests at the cutting edge of the field. Our goal is to be your Sherpa through a rapidly changing landscape by distilling what's working, what isn't working, and how you can leverage AI in your own process. Follow along as we tackle AI's biggest challenges and opportunities, one episode at a time.

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