From Answer Engines to Work Mechanisms: The AI Inflection on Wall Street

Written By Jessica Corbin

In this episode, Brett Caughran and Khe Hy go without a guest to work through what has actually changed in the last two months at the intersection of AI and investing. Their shared view: the models, the connectivity, and the institutional data are largely here now, and the constraint has moved to knowing what to point them at.

We get into:

  • Why the Mac Minis people bought to run OpenClaw mostly run Codex now, and why reach matters more than model quality

  • Running an agent on your logged-in machine from your phone

  • The DealCloud problem: when there's no MCP, the agent just drives your Chrome

  • Why the training questions changed two months ago, from how do I use this to what is worth building

  • Brett on why turning an agent loose for 24 hours gives you a long chain of mediocre work and a large token bill

  • The five layers: triage, execution, decision support, rigor enforcement, and idea tracking

  • Stripping every KPI out of every CIM, the analysis that was never worth an associate's time

  • Tearing down a 100-page primer skill and rebuilding it as a 20/60/20

  • Why an out-of-the-box primer hands you Zacks and Motley Fool, and what the FactSet MCP fixes

  • Where BlueMatrix, Third Bridge, and AlphaSense have landed on access

  • The headless RMS: your research isn't in Bipsync, it's in OneNote, Slack, Bloomberg IB, and Outlook

  • What Brett means by an assembly problem rather than a technology problem

We'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.

Chapters (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

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

Follow Invest with AI on:

Spotify: https://open.spotify.com/show/033xcEEovVViS7hIYwNuGZ

Apple Podcasts: https://podcasts.apple.com/us/podcast/invest-with-ai/id1896918892

Jessica Corbin
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Intelligent Alpha CEO: Letting AI Run the Portfolio