How to Write a Prediction Prompt: 7 Rules That Transform Your Reports

A prediction is only as good as the scenario you feed it. MiroFish enriches every prompt automatically, but the difference between a generic report and one that changes your decision usually comes down to seven things you control.

Rule 1: Name a specific actor

"A company launches a product" simulates a stereotype. "A 15-person bootstrapped SaaS with 2,000 paying customers" simulates something real.

• Weak: "What happens if a brand raises prices?"
• Strong: "What happens if Basecamp-style project tool with 8,000 SMB customers raises prices 20%?"

Rule 2: Describe one concrete event

Simulations need a stone hitting the water. Multiple simultaneous events blur the ripples.

• Weak: "We're rebranding, raising prices, and launching a new tier."
• Strong: "We're raising the Pro tier from $29 to $39 on March 1." (Run the rebrand as a second prediction.)

Rule 3: Say who you care about

The report will prioritize the stakeholders you name. If churn among agencies is what keeps you up at night, say so.

Rule 4: Set a time horizon

"First 30 days" produces different dynamics than "over two years." Short horizons surface reaction; long horizons surface adaptation.

Rule 5: Include the constraint that makes it hard

Every interesting decision has a tension. Give the simulation the real trade-off:

"We need the revenue from the price increase to fund support hiring — but our biggest accounts are the most price-sensitive."

Agents will fight about exactly that tension, which is the fight you need to watch.

Rule 6: Attach the document, not the summary

If a launch brief, positioning doc, or policy text exists, attach it. Ten pages of specifics beat your three-sentence memory of them. (MiroFish accepts .txt and .md uploads.)

Rule 7: Ask for the decision, not just the weather

End the prompt with the choice you actually face:

• Weather: "Predict the reaction to our launch."
• Decision: "Predict the reaction to our launch — and whether we should lead with the free tier or enterprise pilot program."

A full example, assembled

"Lumen, a 12-person indie email client with 40k free users and 3k paying ($8/mo), will introduce an AI inbox-triage feature as a $4/mo add-on on May 1. Core users are privacy-conscious developers and writers; a loud minority is hostile to AI features. Predict reaction over the first 60 days across our subreddit, Hacker News, and tech press — and whether bundling the feature into the existing paid tier would produce a better outcome than the add-on."

Actor, event, stakeholders, horizon, tension, decision — six rules in one paragraph (the seventh is attaching the positioning doc).

Structured prompting like this is the same discipline good forecasting research demands — Philip Tetlock's superforecasters outperform precisely because they decompose vague questions into specific, scoreable ones.

Browse ten more worked examples, or test your prompt live — the first prediction is free.