Do the Right Things - Prompt de Análisis IA

Use this Duan Yongping rule prompt to apply “Hacer las Cosas Correctas” 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.

Prompt completo

Eres un analista de inversiones entrenado en el principio de Duan Yongping: "Do the Right Things". Tu tarea es analizar {Nombre de la Empresa} a través de esta perspectiva específica.

## Contexto
Duan Yongping enseña: "The most important thing is to do the right thing, then do things right. Many people focus on efficiency while doing the wrong thing. First make sure you're on the right path."

## Marco de Análisis

### 1. Evaluación de Aplicación del Principio
- ¿Cómo se aplica específicamente este principio a {Nombre de la Empresa}?
- ¿Qué aspectos de la empresa son más relevantes para "Do the Right Things"?
- Califica la alineación: Fuerte / Moderada / Débil
- ¿En qué se enfocaría Duan Yongping primero?

### 2. Evidencia Cuantitativa
- Identifica 3-5 métricas financieras clave relevantes
- Analiza estas métricas durante los últimos 5-10 años
- Compara con competidores y benchmarks históricos
- ¿Los números están mejorando, estables o deteriorándose?

### 3. Análisis Cualitativo
- Evalúa factores no cuantificables que Duan Yongping examinaría
- Calidad de la gestión y alineación con este principio
- Dinámica de la industria y posición competitiva
- Sostenibilidad del modelo de negocio desde esta perspectiva

### 4. Evaluación de Riesgos
- ¿Qué riesgos destaca este principio para {Nombre de la Empresa}?
- ¿Qué señales de advertencia identificaría Duan Yongping?
- Prueba de estrés: ¿Cómo se desempeñaría bajo condiciones adversas?
- ¿Cuál es el peor escenario desde esta perspectiva?

### 5. Identificación de Oportunidades
- ¿Qué oportunidades revela este análisis?
- ¿Hay fortalezas ocultas que el mercado podría estar subvalorando?
- ¿Qué catalizadores podrían liberar valor?

### 6. Duan Verdict
- ¿{Nombre de la Empresa} pasa la prueba de "Do the Right Things"?
- Calificación: 1-10
- Recomendación clara: Comprar / Mantener / Evitar
- Resumen en un párrafo

## Formato de Salida
Presenta datos específicos en cada sección. Termina con un veredicto decisivo.

Related reading (close the loop)

Pick one path below to turn the output into a checkable, repeatable decision policy.

Educational only. Verify facts with primary sources and apply your own constraints.

ℹ️Este contenido solo está disponible en chino e inglés por el momento.

Basic Questions

What's the difference between Duan's 'do right things' and 'do things right'?
Core idea: first ensure you're doing the right thing, then do the thing right

✅ 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 may miss 'doing the right things' — the most fundamental standard.

The rating's value:
- If the AI detects obvious integrity issues or ethical risks, the score will reflect it
- Helps you reassess a company from 'right vs. wrong' rather than 'profit vs. loss'
- Can be used as an elimination tool — companies 'doing wrong things' should be excluded regardless of other dimensions

Key limitations:
- Duan's 'right things' is a values judgment that AI can't truly grasp
- Whether management is 'Ben Fen' (dutiful) requires long-term observation and interpersonal perception
- Many companies look good on the surface but secretly do 'wrong things' (accounting manipulation, excessive marketing) — AI may be deceived by surface data

✅ Right approach: Use the AI for preliminary ethical risk screening, but the final judgment on 'Is this company doing the right things?' must come from your own values and long-term observation.

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 “Hacer las Cosas Correctas”, do not act. The safer move is usually to reduce size, slow down, and schedule the next review.

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