The Edge Has Shifted | Matt Reustle on How the Best Investors Use AI
TL;DR
Matt Reustle explains how AI evolved from basic search tools to agentic research assistants capable of automating due diligence and monitoring workflows, allowing investors to leverage technology for junior-level tasks while maintaining human decision-making at the core.
🧠The AI Inflection: From Toy to Tool 3 insights
Deep research models changed the game
The inflection point arrived in late 2024 and early 2025 with deep research models that function more like agents than traditional LLMs, moving beyond social experiments to professional-grade tools.
LLMs are calculators, agents are analysts
Basic LLMs operate like interns performing single Google searches, while agentic workflows use reasoning to deliver multi-step analysis resembling junior analyst output rather than intern-level summaries.
Premium tiers unlock reasoning capabilities
Free-tier models provide surface-level answers, but premium agentic tiers understand context and deliver synthesized research that investors can actually use for professional decisions.
âš¡ Agentic Workflows: Practical Applications 3 insights
Automated cross-sector monitoring
Investors can set up recurring monitors to track specific commentary across unrelated sectors, such as logistics mentions in CPG earnings calls, delivering synthesized alerts without manual transcript review.
Instant due diligence acceleration
Deep research capabilities eliminate the need for outdated sellside primers by generating comprehensive company summaries and thematic research almost instantly.
KPI tracking and position monitoring
Systems can automate quarterly recaps of key data points across entire portfolios, replacing the manual work of earnings-season transcript reviews previously done late into the night.
🚀 Implementation Strategy 3 insights
Journal your process first
Before adopting tools, document your current research workflow to identify specific friction points where AI can provide immediate leverage rather than applying generic solutions.
Progressive adoption path
Start with premium LLM tiers for communication and basic research, then graduate to specialized investment-specific tools for monitoring and thematic screening.
Compliance remains critical
While scraping capabilities exist, investors must navigate legal restrictions and API requirements when setting up automated data collection systems.
Bottom Line
Treat AI as a leverage tool that handles junior-level research and monitoring tasks, freeing you to focus on high-conviction decision-making and relationship-building that algorithms cannot replicate.
More from Excess Returns
View all
We Asked GMO’s Head of Asset Allocation Why This Bubble is Easy — But Investors Will Get it Wrong
GMO's Ben Inker argues the current AI-driven US stock bubble is "easy" to navigate because investors can rotate to fairly priced international assets while maintaining normal risk levels, unlike the "hard" bubbles of 2007 and 2021 when all risk assets were simultaneously overvalued.
Expensive Market. Record Issuance. Can the Story Still Hold It Up? | 6 Things We Learned This Week
Valuation expert Aswath Damodaran, IPO strategist Andy Constan, and value investor Tobias Carlisle discuss how to value story-driven companies like SpaceX, why issuers intentionally underprice IPOs, and why investors should avoid market timing despite extreme overvaluation by targeting undervalued segments like small-cap value.
The $2 Trillion Question | Tobias Carlisle on SpaceX, the AI Buildout, and the Rotation No One Sees
Tobias Carlisle warns that the market is at historic valuation extremes comparable to the dot-com bubble, but argues investors should rotate into deeply undervalued small and micro-cap value stocks rather than exit entirely, as early indicators suggest a potential decade-long rotation away from large-cap growth; meanwhile, he cautions that the massive AI infrastructure buildout risks following historical boom-bust patterns where value accrues to consumers, not creators.
The Trillion-Dollar Gap | We Asked Aswath Damodaran What SpaceX Is Really Worth
Finance professor Aswath Damodaran analyzes SpaceX's $2.7 trillion valuation, finding that while the space launch and Starlink businesses hold real competitive advantages, the AI division's projected $26 trillion market relies on terrible unit economics and a contradictory strategy of renting data centers to direct competitors.