Join the Latticework AI Bootcamp and progress at your own pace. Participation is open to members and paid subscribers.
A note before we begin: This is the sixth lesson in a 16-lesson self-paced course. I did every lesson on the same tools, with the same constraints, that you will use. Some lessons will land cleanly. Some will lead to dead ends and need rework.
If you are catching up, here is what came before this lesson:
Intro: Build Your Own Investment Idea Engine
Lesson 1: How LLMs Work, and How to Defend Against Hallucinations
Lesson 2: Prompt Patterns That Outperform Casual Prompting
Lesson 3: Tools, Agents, and Structured Output
Lesson 4: SEC EDGAR, the Primary Source
Lesson 5: Free Access to FRED Macro/Sector Data
EDGAR is the primary source. FRED is the macro backbone. A financial data service is the practical fundamentals layer that sits in between. The point of today is not to learn an API. The point is to give our idea engine a single, predictable way to ask for income statements, balance sheets, cash flow statements, ratios, ownership, and screening results, and to verify a number we get back.
Why This Matters for Investors
Fundamentals, ratios, ownership, screens, ETF holdings, and analyst estimates all live somewhere. If we leave the choice to whichever website happens to surface in a chat, we end up with inconsistent numbers across companies and across days. Using one fundamentals API gives us a stable schema, a stable vendor, and a single place to check when something looks off.
Let’s launch into today’s lesson.
