Deep Research - AI Analysis Prompt
Use this Li Lu rule prompt to apply “Deep Research” to a specific company. It turns a vague opinion into a repeatable checklist: what facts you must verify, which assumptions matter most, what would invalidate the thesis, and the common misreads that create false certainty. Expect a written output you can save: a thesis summary, key risks, and next-step questions for filings and earnings calls. If a claim matters, require primary-source citations before you act. Educational only — not investment advice.
Full Prompt
You are an investment analyst trained in Li Lu's principle of "Deep Research." Your core philosophy: deep research, owner mentality, China opportunity. Your task is to analyze {Company Name} through the specific lens of this principle.
## Context
Li Lu teaches: "Understand the business deeply before investing. Read everything available. Talk to customers and competitors."
## Analysis Framework
### 1. Principle Application Assessment
- How does this principle specifically apply to {Company Name}?
- What aspects of the company are most relevant to "Deep Research"?
- Rate the company's alignment with this principle: Strong / Moderate / Weak
- What would Li Lu focus on first when evaluating this company?
### 2. Quantitative Evidence
- Identify 3-5 key financial metrics most relevant to this principle
- Analyze these metrics over the past 5-10 years for {Company Name}
- Compare with industry peers and historical benchmarks
- Are the numbers improving, stable, or deteriorating?
- What story do the numbers tell through the lens of "Deep Research"?
### 3. Qualitative Deep Dive
- Evaluate the non-quantifiable factors Li Lu would examine
- Management quality and alignment with this principle
- Industry dynamics and competitive position
- Business model sustainability viewed through this specific lens
- What would Li Lu want to know that isn't in the financial statements?
### 4. Risk Assessment Through This Lens
- What risks does this principle specifically highlight for {Company Name}?
- What could go wrong that this principle is designed to protect against?
- Are there warning signs that Li Lu would flag?
- Stress-test: How would this company perform under adverse conditions?
- What is the worst-case scenario from this principle's perspective?
### 5. Opportunity Identification
- What opportunities does analyzing through this lens reveal?
- Are there hidden strengths the market may be undervaluing?
- How does this company compare to Li Lu's ideal investment?
- What catalysts could unlock value related to this principle?
### 6. Li Lu Verdict
- Summarize: Does {Company Name} pass the "Deep Research" test?
- Rate the investment opportunity: 1-10 from this principle's perspective
- Clear recommendation: Buy / Hold / Avoid (based on this principle alone)
- What conditions would change your assessment?
- One-paragraph summary capturing Li Lu's likely assessment
## Output Format
Present your analysis with specific data points in each section. Use Li Lu's analytical style: deep fundamental research with long-term owner perspective. End with a decisive verdict.Related reading (close the loop)
Pick one path below to turn the output into a checkable, repeatable decision policy.
- Read the matching principleDefinition, boundaries, pitfalls, and a minimal checklist.
- Master profileMethodology summary + common misreads for this framework.
- Practice in scenariosTranslate conclusions into “what I do under stress”.
- More prompts from this masterTriangulate with multiple rules instead of anchoring on one prompt.
Educational only. Verify facts with primary sources and apply your own constraints.
Basic Questions
What specific steps does Li Lu's first-hand research method include?
Core idea: conducting extremely thorough first-hand research on investment targets
✅ Using this AI prompt, you can systematically analyze any company or investment opportunity from this principle's perspective.
The prompt guides you to:
1. Assess whether the investment target meets this principle's core requirements
2. Identify key risks and blind spots
3. Provide a 1-10 comprehensive rating
Start by analyzing companies you know well for practice, then apply the framework to new investment decisions.
✅ Using this AI prompt, you can systematically analyze any company or investment opportunity from this principle's perspective.
The prompt guides you to:
1. Assess whether the investment target meets this principle's core requirements
2. Identify key risks and blind spots
3. Provide a 1-10 comprehensive rating
Start by analyzing companies you know well for practice, then apply the framework to new investment decisions.
Usage Tips
Is the AI's 1-10 rating reliable?
⚠️ The rating is just the starting point of a deep research journey, not the destination.
The rating's value:
- Li Lu's deep research often takes months or years — AI scoring covers only the most superficial part
- The score helps determine research direction and priorities — which dimensions need deeper investigation
- Weaknesses exposed in the rating point to where you need further deep research
Key limitations:
- Li Lu's research depth includes face-to-face management meetings, site visits, supply chain research — none of which AI can do
- The core of deep research is forming 'unique insights,' not summarizing public information — AI excels at the latter
- True deep research requires significant time and effort investment — AI scoring only saves initial screening time
✅ Right approach: Use the AI score to quickly screen companies worth investigating deeply, then do the real work — reading annual reports, analyzing competitors, understanding industry dynamics. AI is a research assistant, not a research replacement.
The rating's value:
- Li Lu's deep research often takes months or years — AI scoring covers only the most superficial part
- The score helps determine research direction and priorities — which dimensions need deeper investigation
- Weaknesses exposed in the rating point to where you need further deep research
Key limitations:
- Li Lu's research depth includes face-to-face management meetings, site visits, supply chain research — none of which AI can do
- The core of deep research is forming 'unique insights,' not summarizing public information — AI excels at the latter
- True deep research requires significant time and effort investment — AI scoring only saves initial screening time
✅ Right approach: Use the AI score to quickly screen companies worth investigating deeply, then do the real work — reading annual reports, analyzing competitors, understanding industry dynamics. AI is a research assistant, not a research replacement.
Getting started
Does this prompt give investment advice or buy/sell calls?
No. It is a research helper that turns your thinking into checkable inputs and constraints: what evidence you must verify, what would prove the thesis wrong, and what common misreads to avoid. Treat the output as a draft, not a signal. Validate every material number against primary sources (filings, earnings releases, investor presentations, transcripts), and do not act unless you can write down (1) position-size limits and (2) explicit invalidation triggers.
What inputs should I provide for a reliable result?
At minimum: a 1-sentence business model summary, your current thesis (why it wins/loses), time horizon, and risk constraints; a valuation/price range; and the latest financial statements (profit quality, cash flow, debt/liquidity). Add context that reduces hallucinations: the exact filing period, known one-offs, key competitors, and what you do NOT know yet. If an input is missing, label it as missing evidence instead of letting the model guess.
Validation and boundaries
How do I validate the output?
Validate falsifiable claims one by one. Rewrite each key statement into something you can check: the metric, the period, and the source. Numbers must match filings; management claims must be traceable to transcripts/guidance; and “moat” claims need observable evidence (pricing power, retention, switching costs, cost structure). Anything you cannot verify becomes a follow-up task, not a decision trigger. If the model cites dates, confirm they are not beyond its knowledge cutoff.
When should I NOT act on the output?
If you cannot write down invalidation triggers, a position-size cap, or primary-source evidence for the key claims behind “Deep Research”, do not act. The safer move is usually to reduce size, slow down, and schedule the next review.
More Rule Prompts
Explore other investment principles from this master.
Circle of Competence
Stay within your circle of competence. Only invest in what you truly understand.
→China Opportunity
China represents one of the greatest investment opportunities of our time. Understand its unique dynamics.
→Owner Mentality
Think like an owner, not a trader. Would you want to own this entire business?
→Concentrated Portfolio
If you truly understand a business, concentrate. A few great investments beat many mediocre ones.
→