Advanced AI & Markets
AI Agents in Finance: Research, Trading and Risk Controls
Evaluate AI agents in finance through primary evidence, a worked calculation and the assumptions that can break the thesis.
AI research learning path
AI Business Models and Company Economics
Connect AI adoption, agents, pricing, revenue quality, margins, capital expenditure and return on invested capital across company disclosures.
22 source-backed guides. Start with the broader frameworks, then follow the related research paths.
Advanced AI & Markets
AI Financial Analysts: What They Can Do and How to Check Their Work
A practical workflow for AI financial analyst, connecting dated sources and unit economics to valuation, portfolio and risk decisions.
Advanced AI & Markets
AI CapEx Explained: How to Read Big Tech's Spending Boom
A source-checked framework for AI capex, with the evidence, calculations and failure modes an investor should examine.
Advanced AI & Markets
Hyperscaler CapEx: What It Means for Earnings and Free Cash Flow
Evaluate hyperscaler capex through primary evidence, a worked calculation and the assumptions that can break the thesis.
Advanced AI & Markets
AI Revenue vs AI Spending: How to Test the Investment Case
An investor’s research guide to AI revenue vs spending: what to measure, how to verify it and where confident conclusions can fail.
Advanced AI & Markets
AI Agent Trading: Architecture, Controls and Systemic Risk
Evaluate AI agent trading through primary evidence, a worked calculation and the assumptions that can break the thesis.
Advanced AI & Markets
AI Inference vs Training: Cost, Demand and Investment Exposure
Evaluate AI inference vs training through primary evidence, a worked calculation and the assumptions that can break the thesis.
Advanced AI & Markets
AI Token Economics: Cost per Token, Pricing and Gross Margin
An investor’s research guide to AI token economics: what to measure, how to verify it and where confident conclusions can fail.
Advanced AI & Markets
AI Cloud Economics: Utilization, Backlog and Return on Capital
A source-checked framework for AI cloud economics, with the evidence, calculations and failure modes an investor should examine.
Advanced AI & Markets
AI Infrastructure Backlogs: What They Reveal—and What They Don't
Evaluate AI infrastructure backlog through primary evidence, a worked calculation and the assumptions that can break the thesis.
Advanced AI & Markets
Open-Source AI and the Economics of Model Providers
A source-checked framework for open source AI economics, with the evidence, calculations and failure modes an investor should examine.
Advanced AI & Markets
AI Model Commoditization: Who Keeps Pricing Power?
Evaluate AI model commoditization through primary evidence, a worked calculation and the assumptions that can break the thesis.
Advanced AI & Markets
AI Software Economics: Seats, Usage and Outcome-Based Pricing
An investor’s research guide to AI software economics: what to measure, how to verify it and where confident conclusions can fail.
Advanced AI & Markets
AI Agents and the SaaS Business Model
A practical workflow for AI agents saas, connecting dated sources and unit economics to valuation, portfolio and risk decisions.
Advanced AI & Markets
AI Monetization: How to Separate Adoption From Revenue
A source-checked framework for AI monetization, with the evidence, calculations and failure modes an investor should examine.
Advanced AI & Markets
AI Productivity and Profit Margins: What Company Disclosures Can Prove
Evaluate AI productivity margins through primary evidence, a worked calculation and the assumptions that can break the thesis.
Advanced AI & Markets
AI Adoption KPIs: The Metrics Investors Should Watch
An investor’s research guide to AI adoption metrics: what to measure, how to verify it and where confident conclusions can fail.
Advanced AI & Markets
AI Revenue Quality: Recurring Sales, Services and Pass-Through
A practical workflow for AI revenue quality, connecting dated sources and unit economics to valuation, portfolio and risk decisions.
Advanced AI & Markets
AI Partnerships Explained: Revenue Sharing, Compute Credits and Circularity
A source-checked framework for AI partnerships, with the evidence, calculations and failure modes an investor should examine.
Advanced AI & Markets
AI Company Backlogs: Bookings, RPO and Capacity Commitments Explained
An investor’s research guide to AI backlog rpo: what to measure, how to verify it and where confident conclusions can fail.
Advanced AI & Markets
AI Gross Margins: Software, Cloud and Hardware Compared
A practical workflow for AI gross margin, connecting dated sources and unit economics to valuation, portfolio and risk decisions.
Advanced AI & Markets
AI Mentions vs AI Revenue: A Better Earnings-Call Framework
An investor’s research guide to AI mentions vs revenue: what to measure, how to verify it and where confident conclusions can fail.