Thought Experiment: New Capital Forms for Outcome-Based AI Services
curious_vii · x · 2026-08-28
The author explores a scenario where AI Labs seal off their services, accepting only "context + desired result + budget" and returning a "verified outcome."
Key Points & Challenges:
- Token Pricing Breakdown: Charging per token becomes irrelevant in a black-box outcome delivery model.
- Equity Stakes are Cumbersome: Direct equity swaps are hindered by securities laws.
- The Labs' Dilemma: Enterprise agreements often prohibit Labs from retraining on user data, limiting their ability to expand the depth and breadth of their "trillion-dollar metered common knowledge pools."
Proposed Solution: The author hypothesizes a new capital form resembling a "liquidity pool" composed of cash plus "pseudo-shares" (equity-shaped stakes) in both the buyer and the Lab, where liquidity is contingent upon outcome verification. This aims to balance the Labs' need for retraining data with the enterprise's need to solve problems via rented intelligence.
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