| | Components | Deal-Investor Fit (2024-2025) | Product-Market Fit (2025-2026) | Probabilistic Program-Entrepreneur Fit (2026-2027) |
| ------------------------ | -------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------ | ---------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------- |
| a* = argmax E[u(e(s,a))] | **Objective Function** | Maximize alignment between deal terms and investor expectations | Optimize product features and positioning for target market segments | Maximize synergy between entrepreneur's decision-making and probabilistic program's outputs |
| | **State** | Investor preferences, market trends, company valuation metrics | Customer needs, market segmentation, competitive landscape | Entrepreneur's decision patterns, cognitive biases, strategic thinking approaches |
| | **Action** | Adjust investment amount, valuation cap, equity allocation | Modify product features, pricing, go-to-market strategy | Tune program interfaces, decision support algorithms, feedback mechanisms |
| | **Environment Model** | Financial markets, investor behavior, economic indicators | Market dynamics, customer behavior, technological trends | Decision-making contexts, entrepreneurial cognition, AI-human interaction |
| | | | | |
| | **Backward Process (Inference)** | Update beliefs about investor preferences and market conditions | Refine understanding of customer needs and market fit | Improve model of entrepreneur's decision-making patterns and biases |
| | **Forward Process (Simulation)** | Project outcomes of different deal structures | Predict market responses to product changes | Simulate entrepreneur's decisions with different AI support scenarios |
| | | | | |
| | **Simplify** | Decompose complex deal structures into key components | Break down market segments and product features | Identify critical decision points for AI augmentation |
| | **Choose** | Select optimal terms and conditions for the deal | Determine target markets and core product features | Decide on level and type of AI decision support |
| | **Reason Probabilistically** | Model potential outcomes of different deal structures | Estimate market size, adoption rates, and competitive responses | Apply Bayesian networks to complex business decisions |
| | **Calibrate** | Refine deal terms based on investor feedback and market conditions | Iterate product based on user feedback and market performance | Adjust AI suggestions based on entrepreneur's decisions and outcomes |
| | | | | |
| | **Pivot Levels** | 1. Operational: Adjust specific deal terms<br>2. Strategic: Revise entire deal structure<br>3. Dynamic: Adapt overall fundraising strategy | 1. Operational: Modify product features<br>2. Strategic: Pivot to new market segment<br>3. Dynamic: Transform business model | 1. Operational: <br>2. Strategic: <br>3. Dynamic: |
Key for visual separation:
- **Bold**: Core components (Objective Function, State, Action, Environment Model)
- *Italic*: Processes (Backward, Forward) and Cognitive functions (Simplify, Choose, Reason Probabilistically, Calibrate)
- Regular: Pivot Levels