What should I input to get a useful analysis?
Provide context and constraints, not just a ticker. Add your time horizon, what you think is true, what could invalidate it, and the key risks you want stress-tested. If you have numbers, include sources (filings, transcripts, reputable data) so the model can reference them rather than invent them.
How do I validate AI output without wasting time?
Treat outputs as a draft decision memo. Verify only the load-bearing claims: revenue/cash flow trend, leverage, unit economics, and any quoted statements. If a claim cannot be traced to a source, label it “unknown” and re-run the prompt with a stricter cite-or-unknown rule.
Are these prompts investment advice?
No. These prompts are educational frameworks to help you think clearly and write down your assumptions. The output may be wrong or incomplete—use it to generate checklists and questions, then do your own research before making decisions.
Which master framework should I choose?
Pick the master whose edge matches your decision problem. If you need business quality and long-term durability, start with Buffett/Munger-style prompts. If you need cycle and risk framing, consider Dalio/Marks-style prompts. When in doubt, run two frameworks and compare where they disagree—those disagreements are your research tasks.
How do I turn a prompt result into an action plan?
Extract a short checklist (3–7 items), your explicit boundaries (what would change your mind), and a review cadence (weekly/monthly/event-driven). Then log it in your journal and run a toolkit-style cycle: scan → decide → guardrails → review. The process is what compounds, not the single output.