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.

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