Mycroft
An open source educational experiment in AI-powered investment intelligence. Named after Sherlock Holmes's enigmatic elder brother, the Mycroft framework explores how a ecosystem of specialized agents might work in concert to analyze the AI sector while implementing disciplined investment strategies.
About the Project
The Mycroft framework represents an educational experiment in AI-powered investment intelligence. With its tagline "Using AI to Invest in AI," this open-source platform explores how a ecosystem of specialized agents might work in concert to analyze the rapidly evolving artificial intelligence sector while implementing disciplined investment strategies.
Led by Professor Nik Bear Brown, PhD, MBA, this experimental project emphasizes learning by building, inviting contributors to discover what approaches actually work in practice rather than claiming to have definitive solutions.
The Four Agent Categories
Our framework is built on four essential agent categories that work together to provide comprehensive investment intelligence:
1. Analytical Agents
Gathering, processing, and interpreting vast amounts of information about AI companies and their competitive landscape.
2. Portfolio Agents
Testing approaches to transform knowledge into actionable investment strategies with proper diversification and risk management.
3. Advisory Agents
Exploring human-AI interaction through conversational financial advising, goal-setting, and educational components.
4. Intelligence Agents
Maintaining market awareness by monitoring news, social sentiment, financial reports, and regulatory developments.
The Mycroft Orchestration Layer
Cross-Agent Validation
Testing approaches to identifying when different agents reach contradictory conclusions and resolving analytical conflicts.
Dynamic Task Allocation
Exploring approaches to distributing computational resources based on changing market priorities.
Pattern Recognition
Experimenting with identifying connections across seemingly unrelated developments in the AI landscape.
While AI technology evolves rapidly, the Mycroft framework is designed to adapt and learn. Our open-source approach emphasizes transparency, allowing contributors to understand the reasoning behind each component, challenge assumptions, and discover through experimentation which approaches yield the most valuable insights.
The Mycroft project offers educational resources through videos, documentation, and collaborative development opportunities. We invite you to join us in this experimental journey of building and learning together.
Key Features
Research Intelligence
Experimental agents that gather and analyze financial statements, earnings calls, patent filings, and technical documentation to construct comprehensive profiles of target AI companies.
Investment Strategy Testing
Portfolio agents that explore different approaches to diversification, risk management, and rebalancing to discover effective methodologies for AI sector investing.
Market Awareness
Intelligence agents that monitor news, social sentiment, financial reports, and regulatory developments to ensure analyses remain current in the rapidly evolving AI landscape.
Educational Philosophy
A transparent, open-source framework designed for learning what actually works in AI-powered investment analysis through collaborative experimentation and discovery.