It was never worth an associate's time to strip every KPI out of every CIM that crosses the desk. At $20 of tokens, it is. No guest this week. Brett Caughran and Khe Hy on the work that just became economic, and why the hard part is no longer the technology.

The Mac Minis people bought to run OpenClaw mostly run Codex now, and the reason is reach: sessions on your machine are reachable from your phone. No MCP for DealCloud? The agent drives your logged-in Chrome instead. Which moves the constraint. Both of them train investors on this, and both say the question changed two months ago, from how do I use these tools to what is worth building.

Brett is unsentimental about where that goes wrong. An agent turned loose for 24 hours gives you a long chain of mediocre work and a large token bill. The back half gets into what does work: the five layers, the 20/60/20 primer rebuild, why an out-of-the-box primer hands you Zacks and Motley Fool, and the headless RMS that goes and gets the research sitting in OneNote, Slack, Bloomberg IB, and Outlook.

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Timestamps:

[00:00] Intro
[01:13] — Grokbot, Cursor, and a Three Horse Race Again
[02:56] — Are the Mac Minis Mothballed?
[04:05] — Why the Power Users Moved to Codex
[06:22] — The Always On Machine You Run From Your Phone
[07:27] — No MCP? Let the Agent Drive Your Browser
[09:44] — What This Means for Wall Street's Claude Fluency
[10:49] — Training Shifts From "How" to the Art of the Possible
[13:05] — Brett on the 24 Hour Agent Slop Chain
[14:08] — The Faster Horse Era of AI
[15:00] — $20 of Tokens vs. a $100K Associate
[16:14] — Why AI Makes Lazy Research Easier
[17:24] — Five Layers, and Why Decision Support Is the One
[18:27] — From Answer Engines to Work Mechanisms
[20:38] — The Notion Problem: Staring at a Blinking Cursor
[22:21] — Every Investor Wants Something Different
[23:55] — Rebuilding the Primer Skill: The 20/60/20
[26:36] — Excel Fluent Models and the Boat Pricing Tracker
[28:02] — State of Play: MCP for Investment Firms
[29:57] — Why Out of the Box AI Hands You Zacks and Motley Fool
[31:42] — BlueMatrix, Third Bridge, and AlphaSense's Walled Garden
[32:46] — The Headless RMS and Where Research Actually Lives
[33:50] — The 16 Column Limit Nobody Documented
[37:12] — What a Real Research Dashboard Looks Like
[38:34] — Markdown Extractors as a DIY Knowledge Graph
[41:59] — The Always On Earnings Preview
[42:46] — The Codex Moment for Public Equity AI
[45:53] — Three Pillars of the Midsummer Inflection

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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:
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Doug Clinton started with one question in late 2022: can ChatGPT beat the S&P 500? The early results were promising enough that he built a company around it. Today he runs Intelligent Alpha, where frontier models do the investment analysis and the portfolio management and he's still a partner at Deepwater, making the same calls as a human.

He, Brett, and Khe get into where the models are already good enough, why he grades them a B+ analyst and not an A, and the contrarian call on which model is actually best for stock work.

A conversation on AI for hedge funds and the buy-side: knowledge graphs, ontologies, model routing, obsolescence risk, and what it takes to build an AI-native investment process.

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Timestamps:

[00:00] Intro
[02:39] — Can ChatGPT Beat the S&P 500?
[04:11] — Why LLMs Keep Handing You $NVDA
[05:05] — Prompt Engineering to Agentic Workflows
[06:45] — Organizational Context: Every Portfolio You've Ever Built
[09:07] — Public Markets Alpha Is a Power Law Game
[10:09] — Where Human Intuition Still Beats the Model
[11:14] — The Hybrid: Part Quant Book, Part Fundamental Book
[12:30] — The Three Buckets of Data
[13:58] — Can Agents Do Channel Checks?
[14:49] — Is MCP Institutional Grade Yet?
[16:11] — Grading the Models: A B+ Analyst
[16:55] — Knowledge Graphs Are the Frontier Right Now
[18:41] — Schemas, Ontologies, and the Gray Matter
[19:21] — Taste: Getting AI From B+ to A
[20:26] — What Building an EBITDA Ontology Actually Looks Like
[24:04] — The Dev Shop Wants to Interview Your PM
[25:37] — Trade Perfection for Speed
[26:36] — We've Built a Lot of Things We No Longer Use
[28:25] — The Vendor Cycle and Controlling Your Own Destiny
[30:23] — Model Routing and the IA 500 Benchmark
[32:36] — The Contrarian Take: GPT Over Claude for Stock Work
[33:53] — Codex vs. Co-work and a Branding Problem
[37:32] — Why There's No Harvey or Rogo for Investing Yet
[40:45] — Do Funds Want the iPhone or the Android?
[43:13] — You Need Someone in Leadership Who's AI-Pilled
[45:19] — Fable Built a 10-Stock Portfolio. It's All AI.
[48:28] — Brett Updates His Skepticism
[49:09] — Advice for Building an Asset Manager With AI
[51:33] — Getting Comfortable With Uncertainty
[53:03] — Go Get Lost in the Models

-----------------------------------------------

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

Former Point72 TMT analyst Thomas Li left the buyside to build Daloopa in 2019 with the goal of capturing market share from the data oligopoly of Bloomberg, FactSet and Cap IQ. Last year data consumption on the platform grew over 100x, and it wasn't the models that did it.

He, Brett, and Khe get into what separates a reliable MCP from a brittle one, why Claude in Excel still can't handle a real buyside model, and the one layer of the analyst job he thinks is already collapsing.

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Timestamps:

[00:00] Intro
[01:29] — Founding Daloopa in 2019 to Take On the Data Oligopoly
[02:29] — Accuracy, Latency, Trust: Why Human Data Collection Breaks
[03:54] — Coach-Built vs. Production Line: The Data Factory Analogy
[05:45] — From 5% of the Database Used to Almost All of It
[09:22] — The Real Unlock: Chatbot to Connected MCP
[10:12] — Not All MCPs Are Created Equal
[14:25] — Where MCP Reliability Is Actually Improving
[16:16] — The Cannibalization Debate: Should All Your Data Go in the MCP?
[17:54] — Building Your Stack: Which Pipe Do You Turn On?
[21:02] — One Pipe or Nine? Where Multi-Vendor Stacks Hallucinate
[24:31] — The Moat Is the Factory, Not the Tool
[26:59] — Going Deeper, and the 13-Week Problem
[31:30] — How Funds Are Building Their Orchestration Layer
[33:29] — Knowledge Graphs: Folders, Markdown, and Pre-Done Analysis
[35:44] — Open Weights vs. Frontier: Where Post-Training Wins
[40:08] — Post-Training Is an Objective Function Problem
[42:49] — If Knowledge Work Isn't Verifiable, Is There a Ceiling?
[45:28] — Can AI Pass Judgment? The Factor Investing Case
[51:40] — The Race to the Middle: Quants and Fundamentals Converge
[53:18] — Why Claude in Excel Still Can't Handle Operating Leverage
[58:47] — Eval-First Product Development
[1:01:17] — Spring 2027: Hiring, Training, and the Collapsing Middle
[1:04:45] — Coding Got Solved. Engineering Didn't.

-----------------------------------------------

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