> For the complete documentation index, see [llms.txt](https://gitbook.edgen.tech/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://gitbook.edgen.tech/edgen-litepaper/store/megabrain-investors-picks.md).

# Megabrain Investors Picks

<figure><img src="/files/Cp1YKCSjCyVdUkeBNTPU" alt=""><figcaption></figcaption></figure>

### What it does for you

Megabrain lets you “chat” with AI versions of well-known investors and market personalities. Each persona carries its own style (aggressive, cautious, contrarian, or narrative-driven) and responds in that voice.

This makes it both entertaining and instructive, as you can test how different strategies interpret the same market data.

The experience includes:

* **Character-driven insights**: AI agents modeled on legendary investors and market personalities.
* **Conversation starters**: pre-set prompts for fast engagement (e.g., market-moving tweets, sector views, global trade).
* **Generated commentary**: real-time responses aggregated from data sources, then expressed in the voice of the persona.
* **Feedback layer**: users can upvote, downvote, or share outputs, which reinforces credibility scores.

<figure><img src="/files/aVfXoD6p0viWmzyX7TkF" alt=""><figcaption></figcaption></figure>

This feature blends intelligence with narrative simulation. Traders can stress-test their views against the “voice” of an archetype, while the community contributes to a sentiment layer that reveals bias and conviction in unique ways.

### How it works

Megabrain is powered by narrative simulation agents. EDGM’s router classifies the query as simulation, retrieves relevant market and news data, and activates the Sentiment/Narrative sub-agent. That data is reformulated into commentary styled to the chosen persona’s bias and tone.

The result is a living layer of market dialogue grounded in data, but colored by personality.