AI Operating System
AI as the operating system for the fund.
Funds that effectively utilize and implement AI will win, it's becoming an absolute necessity and we're making it a key part of our vision.
Within six months, ~80% of day-to-day operations run through Agent Edge, our in-house AI partner that analyzes investments, streamlines decisions, and accelerates execution.
What Agent Edge Does
Investment analysis: Reads decks, estimates risk/reward, and monitors projects post-check, flagging shifts in fundamentals or sentiment.
Portfolio oversight: Tied to treasury and on-chain data, it watches performance in real time and recommends buy/sell actions of post launch portfolio tokens; the Council remains final decision makers.
Fund improvements: Digests meetings, proposals, and feedback to surface bottlenecks and suggest structural changes.
Operational legwork: Summaries, agendas, and research prep, so humans focus on high leverage decisions.
Data & Architecture
Agent Edge will be powered by a large language model, with a continuous stream of new data feeding into its knowledge base. By integrating:
Zoom Transcriptions & Discord Logs: Every Fund council meeting and message will be transcribed in real time and used to train Agent Edge.
Investment Opportunities: Any deal the Fund sees, Agent Edge will analyze and learn from.
Crypto Market Feeds: Key metrics (price movements, liquidity shifts, on-chain data) will be injected into Agent Edge for real-time market awareness.
To handle these large, diverse data sets, we’ll implement vectorization and indexing pipelines so Agent Edge can quickly retrieve relevant historical discussions, proposals, or market events. This approach ensures it’s making decisions and suggestions based on an ever expanding corpus of Fund-specific information, rather than just generic internet data.
Roadmap To ~80% Automation
Phase 1 (0–2 mo): Stand up environment; wire transcripts/Discord; produce investment and org notes.
Phase 2 (2–4 mo): Integrate real-time market feeds; deepen context-aware recommendations.
Phase 3 (4–6 mo): Broaden ecosystem metrics; add sentiment/correlation analytics; route outputs into governance workflow.
Phase 4 (ongoing): Continuous fine-tuning as new data lands; Agent Edge evolves into a near-autonomous scout and strategist.
Long-term Potential
As Agent Edge compounds a high-fidelity memory of our conversations, investments, and outcomes, it becomes more predictive—surfacing deals early, catching red flags sooner, and proposing creative governance improvements pulled from the fund’s cumulative experience.
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