Knowing What You Don't Know - AI Analysis Prompt
Use this Howard Marks rule prompt to apply “Knowing What You Don't Know” 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 Howard Marks's principle of "Knowing What You Don't Know." Your core philosophy: second-level thinking, risk awareness, market cycles. Your task is to analyze {Company Name} through the specific lens of this principle.
## Context
Howard Marks teaches: "The greatest investing advantage is humility - knowing what you don't know and acting accordingly."
## Analysis Framework
### 1. Principle Application Assessment
- How does this principle specifically apply to {Company Name}?
- What aspects of the company are most relevant to "Knowing What You Don't Know"?
- Rate the company's alignment with this principle: Strong / Moderate / Weak
- What would Howard Marks 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 "Knowing What You Don't Know"?
### 3. Qualitative Deep Dive
- Evaluate the non-quantifiable factors Howard Marks would examine
- Management quality and alignment with this principle
- Industry dynamics and competitive position
- Business model sustainability viewed through this specific lens
- What would Howard Marks 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 Howard Marks 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 Howard Marks's ideal investment?
- What catalysts could unlock value related to this principle?
### 6. Marks Verdict
- Summarize: Does {Company Name} pass the "Knowing What You Don't Know" 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 Howard Marks's likely assessment
## Output Format
Present your analysis with specific data points in each section. Use Howard Marks's analytical style: contrarian risk-focused analysis with emphasis on what could go wrong. 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
Why is 'knowing what you don't know' more important than 'knowing a lot'?
Marks considers this investing's most underrated capability:
🧠 Why 'awareness of ignorance' is critical:
1. Prevents overconfidence: Knowing what you don't know prevents reckless bets
2. Preserves margin of safety: Acknowledging uncertainty demands larger discounts when buying
3. Avoids 'expert trap': Many losses come from blind confidence of 'I know this industry'
📌 Practice:
- List 'assumptions I'm uncertain about' in every analysis
- Ask 'if I'm wrong, what's the worst case?'
- Say 'no' to investments you don't understand
🧠 Why 'awareness of ignorance' is critical:
1. Prevents overconfidence: Knowing what you don't know prevents reckless bets
2. Preserves margin of safety: Acknowledging uncertainty demands larger discounts when buying
3. Avoids 'expert trap': Many losses come from blind confidence of 'I know this industry'
📌 Practice:
- List 'assumptions I'm uncertain about' in every analysis
- Ask 'if I'm wrong, what's the worst case?'
- Say 'no' to investments you don't understand
Usage Tips
Is the AI's 1-10 rating reliable?
⚠️ The greatest value of the score is revealing "what you don't know you don't know," not providing certain conclusions.
What makes this principle's score special:
- A higher score doesn't necessarily mean a better investment — it may mean AI has more knowable information but has missed critical unknown risks
- The "uncertainty zones" flagged in the rating are more valuable than the confident conclusions
- Two companies both scoring 8, but one with 3 major unknown variables and the other with only 1, carry completely different risks
Proper usage:
- Focus on areas where AI flags "low confidence" — those are the directions requiring your deeper research
- If AI appears "confident" across all dimensions, be wary — it may not know what it doesn't know
What makes this principle's score special:
- A higher score doesn't necessarily mean a better investment — it may mean AI has more knowable information but has missed critical unknown risks
- The "uncertainty zones" flagged in the rating are more valuable than the confident conclusions
- Two companies both scoring 8, but one with 3 major unknown variables and the other with only 1, carry completely different risks
Proper usage:
- Focus on areas where AI flags "low confidence" — those are the directions requiring your deeper research
- If AI appears "confident" across all dimensions, be wary — it may not know what it doesn't know
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 “Knowing What You Don't Know”, 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.
Patient Opportunism
The key to investment success is waiting for the fat pitch - the opportunity that offers exceptional value with limited risk.
→Contrarianism
To achieve superior results, you have to hold non-consensus views about value, and they have to be accurate.
→Combating Negative Influences
The biggest investing errors come from psychological factors - greed, fear, envy, ego, and the desire to conform.
→The Pendulum
The mood swings of the securities markets resemble the movement of a pendulum. Although the midpoint best describes the average, the pendulum spends very little time there.
→