AI Foundations
Prompting for Market Research
Neural networks, LLMs, and machine learning for markets.
In this lesson
- How to prompt for market research
- How to separate summaries from verified facts
Key takeaways
- 1Good prompts define the question, source standard, assumptions, and output format
- 2Primary-source checks matter more than polished wording
- 3A useful AI answer states uncertainty instead of hiding it
Lesson summary
Prompting for market research is about making the model's work auditable.
Mental model
Prompting for Market Research, without the jargon
Prompting for market research is about making the model's work auditable. A good prompt states the question, source standard, assumptions, output format, and what uncertainty should be shown.
- How to prompt for market research
- How to separate summaries from verified facts
Mechanics
How to reason about prompting for market research
The prompt should define the market, timeframe, and decision being supported.
Source requirements should prefer primary documents, official data, or clearly labeled secondary analysis.
The output should separate facts, inference, and open questions.
- Good prompts define the question, source standard, assumptions, and output format
- Primary-source checks matter more than polished wording
- A useful AI answer states uncertainty instead of hiding it
Example
A concrete prompting for market research example
Instead of asking which token is best, ask for protocol revenue drivers, token unlocks, liquidity conditions, source links, and risks that would invalidate the thesis.
Common mistakes
What to unlearn about prompting for market research
A polished AI summary can feel like due diligence, but it may simply compress stale or weak sources into confident language.
Risk notes
Before you rely on prompting for market research
Hallucinated citations, outdated numbers, source laundering, and missing downside cases can make AI-assisted research dangerous.
- State the decision.
- Require source quality.
- Separate fact from inference.
Practice
A short drill for prompting for market research
- State the decision.
- Require source quality.
- Separate fact from inference.
Review
Key terms
- Liquidity
- How easily an asset can be bought or sold without moving its price much.
- Machine Learning
- Algorithms that learn patterns from data instead of being explicitly programmed.
- Large Language Model (LLM)
- An AI model trained to predict and generate text from context.
- Backtesting
- Testing a strategy on historical data before risking real capital.
Source notes
Editorial references
These references are starting points for verifying the mechanisms, risk checks, and product context behind this lesson.
Before you continue
Can you do these?
- State the decision.
- Require source quality.
- Separate fact from inference.
Related learning
Keep reading
Checkpoint
Finish this lesson
Pass the check to save progress, then continue through the track in order.
Lock in this lesson
Answer every question correctly to complete the lesson.
A good market-research prompt should include…