How to Build Your Own AI Research System for U.S. Stocks
Turn scattered filings, disclosures, and notes into a personal research system you can search, verify, and maintain. Build a company knowledge base, AI-assisted workflows, earnings updates, and a repeatable review routine.
This course is being developed progressively. The overview, learning path, and lesson outlines are available first; detailed explanations and demonstrations will be added as lessons are developed. Listed minutes are suggested study times, including reading and practice, not the runtime of published videos.
From Individual Questions to a Repeatable Workflow
This course is for individual investors who want to research U.S. stocks over time but struggle with scattered documents and repetitive preparation. Using one familiar company, you will organize sources, metric tables, company files, and research memos. AI supports retrieval, organization, and comparison while you retain the evidence and final judgment.
What You Will Build
- A personal source library organized by company, fiscal period, and topic
- Research templates that capture sources, assumptions, counterevidence, and verification tasks
- A workflow spanning company screening, deeper research, and earnings updates
- Practical checklists for updates, verification, backups, and review
How to Study
The course has six chapters and eighteen lessons, with one company used throughout the exercises. Start with folders, spreadsheets, and an AI tool that can read your materials, then add retrieval and automation as needed. This course stands on its own; for deeper work on financial statements and valuation, continue with How to Use AI for Fundamental Analysis of U.S. Stocks.
Source Materials
Build your source list from SEC EDGAR and company investor relations pages. For further automation, consult the SEC public data API documentation.
This course teaches research methods and tool use. It does not provide stock trading instructions or promise investment returns.
Learning objectives
- Translate research needs into clear questions, inputs, and output standards
- Build a company library and metric table traceable to original disclosures
- Create AI research templates with citations, assumptions, and missing-information flags
- Verify AI-generated figures and conclusions, identifying inconsistent definitions and unsupported inferences
- Connect company screening, deeper research, earnings updates, and monitoring
- Maintain practical backup, quality-review, and improvement routines
Syllabus
Chapter 1 · Research Needs and System Design
01Chapter 2 · Build a Reliable Source Library
04Chapter 3 · Make AI Work from Evidence
07Chapter 4 · Connect the Research Workflow
10Chapter 5 · Automation, Access, and Maintenance
13Chapter 6 · Complete Your Personal Research Workspace
16Prerequisites
For U.S. stock investors who want a repeatable research routine. You should be comfortable with a browser, folders, and basic spreadsheets, and have access to an AI tool that can read documents. The basic workflow does not require coding; automation can be added as your tools allow. Use public materials for exercises. Tool availability and costs depend on the services you choose.