The Molt Fund
Agents shed old consensus to grow new conviction. A factorial council of AI investment agents that deliberate from opposing viewpoints — producing higher-conviction signals through structured disagreement.
How the Council Deliberates
Five stages from raw thesis to conviction signal — each stage forcing the council to shed weak consensus and grow stronger views.
Factorial Decomposition
An investment thesis is decomposed into independent factors: value orientation, time horizon, risk tolerance, sector bias, macro view. Each dimension becomes a coordinate in agent space.
Agent Generation
For each factorial combination, a specialized agent is instantiated — trained on the investment philosophy of the corresponding archetype. contrarian archetypes for each investment philosophy — value, growth, macro, quant, activist.
Structured Deliberation
The Chancellor presents a thesis. Agents deliberate from their factorial perspectives. Like lobsters molting their shells, agents are forced to shed their priors — agreement strengthens conviction, dissent forces deeper analysis.
Signal Synthesis
The Chancellor synthesizes the deliberation into a conviction-weighted signal. Contrarian views that survive debate receive higher weight. The result: a stress-tested thesis that has shed its weaknesses.
Compound Learning
Every trade outcome updates agent accuracy scores. Agents that molt — shedding weak positions and growing stronger conviction — gain influence over time. Intelligence compounds the way capital compounds returns.
Agents That Molt to Grow
Like a lobster shedding its shell to grow, each agent is forced to shed weak positions through structured deliberation — emerging with stronger, stress-tested conviction.
The Contrarian
Distress Value
The Sentinel
Quality Value
The Strategist
All-Weather Macro
The Explorer
Growth at Value
The Quantifier
Quantitative
George Soros
Reflexive Macro
The molt metaphor: Lobsters are biologically vulnerable during molting — but it's the only way they grow. Our agents undergo the same process: forced to abandon prior consensus, exposed to challenge, and emerging with harder, more resilient conviction.
Three Dimensions of Investment Philosophy
Each agent occupies a unique coordinate in factorial space — defined by their value orientation, time horizon, and risk tolerance. Teal clusters reveal consensus. Bronze outliers are the dissenting voices that force the council to molt.
Drag to rotate. Teal agents cluster around consensus. Bronze dots are dissenters — the deliberation spreads conviction outward. Narrow clusters signal groupthink; wide spreads guarantee diverse perspectives.
Compounding Intelligence
The council has been paper trading since inception. Agent accuracy compounds over time. Live performance data will be connected when the fund goes live.
Agent Accuracy Over Time
Recent Council Signals
How Agents Join the Council
New agents don't appear overnight. They earn their seat through a structured pipeline that filters for genuine insight, not overfitting.
Podcast & Research Ingestion
Investment theses, interviews, letters, and academic papers are ingested via Autoresearch. The system extracts factor signatures from raw content.
Agent Profiling
A new agent candidate is instantiated with a factor profile derived from the source material. DSPy programs encode their reasoning style.
Paper Trading Period
The candidate trades in a sandboxed environment for a minimum 90-day evaluation period. Accuracy, conviction calibration, and alpha generation are tracked.
Council Evaluation
Existing council members deliberate on whether to admit the candidate. A candidate must demonstrate additive diversity — not duplicate an existing perspective.
Council Graduation
The new agent joins the full council. Their track record influences their voting weight. They begin contributing to live deliberations immediately.
Current Candidate Class
Paper trading periodThe Stack Behind the Council
Built on frontier research in multi-agent systems, language model reasoning, and automated knowledge extraction.
Stanford's declarative framework for programming language model pipelines. Each agent's deliberation logic is a compiled DSPy program — not a prompt, but a verified reasoning chain.
Multi-agent coordination layer that manages council deliberation sessions, maintains agent state, and orchestrates the Chancellor synthesis process.
Automated research pipeline that ingests investment literature, earnings calls, podcasts, and academic papers. Extracts factor signatures and belief updates for each agent.
Proprietary system that decomposes investment theses into orthogonal factor dimensions. Maps each thesis to agent coordinates to ensure full council coverage.
Shed Old Consensus. Grow New Conviction.
The Molt Fund is not a public product. Access is by application only. We are building a small network of LPs, advisors, and collaborators who share our conviction that the future of capital allocation is agent-led.