How Investors are using AI - [Business Breakdowns, EP.240]

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Feb 5, 2026

David Plon, founder of Portrait Analytics and former buy-side investor, applies AI to investment research and workflows. He discusses AI for portfolio monitoring, pre-buy triage, and templatizing due diligence checks. He covers AI-driven idea generation, writing effective prompts, when to upload documents, and how firms can experiment and adopt AI practically.

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ADVICE

Use AI As A Smart Filter

Cast a wider net and use AI to filter sparse but relevant signals across ecosystems for portfolio monitoring.
Use smart filters to surface signposts from suppliers, customers, and competitors that matter to your thesis.

ADVICE

Triage Ideas Rapidly With Automation

Use AI to perform pre-buy triage: surface fatal risks and baseline context quickly to kill weak ideas.
Move some deeper, structured analyses earlier by automating tasks like proxy or guidance-history extraction.

ADVICE

Prompt Like You're Emailing A Junior Analyst

Write prompts like instructions to a smart analyst: state the task, purpose, desired output, guidelines, and domain context.
Iterate prompts interactively and add constraints only when needed to avoid stifling creative synthesis.

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Today we have a special episode breaking down how investors are using AI.

This is a question I get from many of you, and while there is no shortage of content on the implications of AI, I know there's an appetite to learn more about tangible use cases, how to make sure you're getting the most out of these tools, how to think about advancements in the technology, and ensuring that you're keeping pace with the innovation curve.

So my guest today is David Plon, Founder of Portrait Analytics. Now, David and Portrait have been partners of Business Breakdowns since last year, but I specifically asked David to do this episode because, one, he is really front and center to how investors are using and applying AI. But two, and maybe more importantly, he and his team come with a background in investing.

So while the conversation doesn’t really focus on Portrait, you’ll hear references to what he and his team are building and how they’ve shaped it for investors, you’ll very much understand when you hear David talk that he is someone who understands the pain points of an investor.

I think everyone will find something in this episode that will benefit them in their day to day, and I would love to hear the feedback.

For the full show notes, transcript, and links to the best content to learn more, check out the episode page⁠⁠⁠⁠⁠⁠⁠ here.⁠⁠⁠⁠⁠⁠⁠

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This episode is brought to you by ⁠⁠⁠⁠Portrait Analytics⁠⁠⁠⁠⁠ - your centralized resource for AI-powered idea generation, thesis monitoring, and personalized report building. Built by buy-side investors, for investment professionals. We work in the background, helping surface stock ideas and thesis signposts to help you monetize every insight. In short, we help you understand the story behind the stock chart, and get to "go, or no-go" 10x faster than before.

Sign-up for a free trial today at ⁠⁠⁠⁠⁠portraitresearch.com⁠⁠⁠⁠⁠

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Business Breakdowns is a property of Colossus, LLC. For more episodes of Business Breakdowns, visit ⁠⁠⁠⁠⁠⁠⁠joincolossus.com/episodes⁠⁠⁠⁠⁠⁠⁠.

Editing and post-production work for this episode was provided by The Podcast Consultant (⁠⁠⁠⁠⁠⁠⁠https://thepodcastconsultant.com⁠⁠⁠⁠⁠⁠⁠).

Timestamps

(00:00:00) Welcome to Business Breakdowns

(00:04:05) Meet David Plon: Investor to Founder

(00:05:54) Pain Points in the Investment Process

(00:09:08) AI as a “Smart Filter” for News

(00:11:54) AI’s Role in the Pre-Buy Process

(00:14:34) How AI Enables Specific Quantitative Analysis

(00:17:24) Using AI for Investment Idea Generation

(00:21:42) How to Write Good Prompts for LLMs

(00:25:27) Structured vs. Creative Tasks

(00:27:47) The Value of Experimentation & Real-Time Feedback

(00:32:28) Best Practices for Deploying AI in an Institutional Setting

(00:35:57) Why Documenting Decision Making is Essential

(00:39:19) How Models Have Improved at Using Provided Context

(00:42:02) Memory in LLMs: Near-Term Limitations, Long-Term Potential

(00:46:24) Applying Agentic AI in Investment Research