Programmable Assets and Token Economics: Bogart’s “Great Repricing” Bet
Blockchain Capital’s Spencer Bogart argues that the next crypto cycle’s biggest winners will be “net-new” products enabled by programmable assets—not incremental upgrades to existing TradFi.
Bogart’s framework, rooted in his February 19, 2026 research post “The Great Repricing,” says crypto has excelled at value creation (new protocols and on-chain capabilities) but lagged on value capture for token holders. He expects the decade’s largest opportunities to come from products that could not exist before programmable assets.
In a June 2026 discussion/podcast, Bogart highlights three near-term themes where programmable assets could reshape markets:
- Stablecoins: adoption is clear, but the value-capture path is contested across issuers, chains, and applications. The key trading question is whether holding a specific token entitles holders to growing value as usage rises.
- Privacy vs regulatory compliance: programmable assets can enable advanced privacy features, and the eventual resolution may create new market categories.
- Public vs private blockchains: the decision matters more now due to higher stakes and more mature technology.
Across all areas, the “token economics” sorting problem remains unresolved. Bogart calls this process “The Great Repricing,” and positions it as the investment opportunity—especially for non-consensus strategies that overlook “obvious” AI-crypto crossover plays.
For traders, the actionable takeaway is to focus on tokens with credible mechanisms for value accrual, not just projects with rising usage.
Neutral
Bogart’s thesis is directionally supportive for parts of crypto that depend on programmable assets (stablecoins, privacy tooling, and token value accrual), but it is not a near-term catalyst tied to a specific token’s immediate cash flows or protocol change. That makes the likely market reaction more about positioning and sector sentiment than about an instant repricing.
In the short term, traders may rotate attention toward tokens with clearer value-accrual mechanics (fees, buybacks, revenue sharing, or explicit entitlement structures) and away from “usage-only” narratives. In the medium to long term, if the market indeed performs the “Great Repricing” Bogart describes, winners should emerge from categories where programmable assets enable genuinely new product-market fit.
Historically, similar thesis-driven narratives often lead to cycles of hype around “new primitives,” followed by a gradual selection process where liquidity concentrates in assets that can demonstrate measurable value capture. Until tokenomics details become observable in earnings-like metrics (on-chain revenue, distributions, or controllable fee flows), the impact on broad market stability is more likely neutral than bullish or bearish.