> For the complete documentation index, see [llms.txt](https://docs.monnfts.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.monnfts.com/mirror-protocol/faq.md).

# FAQ

#### Is Mirror an AI forecasting platform?

Yes. Mirror is an AI simulation and forecasting platform designed to help teams explore how markets, customers, competitors, stakeholders, and other actors may react to a decision.

Rather than producing a single prediction, Mirror uses scenario simulation to surface plausible outcomes, risks, assumptions, and alternative paths.

#### Is Mirror a multi-agent simulation platform?

Yes. Mirror uses multi-agent simulation to model how different actors and perspectives may respond within a scenario.

Agents can interact across multiple rounds, helping reveal second-order effects, conflicting incentives, behavioral patterns, and reactions that may not appear in a traditional one-shot AI analysis.

#### How is Mirror different from ChatGPT or other AI chatbots?

Chatbots are primarily designed to answer questions, summarize information, generate content, and reason from a prompt.

Mirror is designed to **simulate what may happen after a decision is made**.

Instead of asking only:

**“What do you think will happen?”**

Mirror allows teams to explore:

**“How might different actors react, how could those reactions influence each other, and what outcomes could emerge?”**

#### What can I simulate with Mirror?

Mirror can be used for scenarios where human or market reactions influence the outcome, including:

* Product launches
* Pricing decisions
* Market entry
* Customer demand
* Competitive strategy
* Go-to-market decisions
* Public opinion
* Brand narratives
* Crisis communication
* Policy impact
* Strategic business decisions

The most useful simulations start with a clearly defined decision or hypothesis.

#### What information should I provide to Mirror?

Provide information relevant to the decision you want to test.

Depending on the scenario, this may include:

* Product briefs
* Market research
* Customer insights
* Pricing information
* Competitor intelligence
* Business plans
* Research reports
* Launch strategies
* Policy documents
* Public narratives
* Internal assumptions

A focused scenario generally produces more useful results than uploading large amounts of unrelated information.

#### Can Mirror predict the future?

No AI system can predict complex human behavior or market outcomes with certainty.

Mirror should be treated as a **decision simulation system**, not an oracle.

Its purpose is to identify plausible scenarios, reactions, assumptions, risks, and evidence gaps so teams can make better-informed decisions before committing resources in the real world.

#### How should I evaluate a Mirror simulation?

Before acting on a simulation, review several factors:

* Are the important actors represented?
* Are their incentives realistic?
* Are important assumptions visible?
* Is the underlying evidence sufficient?
* Are alternative scenarios considered?
* Where is uncertainty highest?
* Does the simulation reveal a clearer next action?

A strong simulation should make the decision easier to examine—not hide uncertainty.

#### Who should use Mirror?

Mirror is useful for teams making decisions where reactions, competition, uncertainty, or multiple stakeholders can affect the outcome.

Typical users may include:

**Founders, product teams, marketers, strategists, market researchers, consultants, investors, communications teams, and business leaders.**

Mirror is particularly useful before decisions that are expensive, difficult to reverse, or exposed to significant market uncertainty.

#### Is Mirror a replacement for market research?

No. Mirror is better viewed as a complementary decision-intelligence layer.

Traditional market research provides evidence about customers, markets, competitors, and historical behavior.

Mirror can use that evidence to explore hypothetical scenarios and simulate how different actors might respond to a future decision.

The stronger the underlying evidence, the more useful the simulation can become.

#### When should I use Mirror instead of a traditional forecast?

Traditional forecasting is particularly effective when reliable historical data can be used to estimate future outcomes.

Mirror becomes useful when the outcome depends heavily on **interaction and behavioral response**—for example, how customers respond to a price change, how competitors react to a launch, or how a narrative evolves after entering the public market.

In those situations, the question is not only:

**“What is likely to happen?”**

but:

**“What happens when everyone starts reacting?”**

***