Why you should listen
Most of the RWA conversation so far has been about putting Treasuries on-chain and trading price exposure to gold. Michael argues that this barely scratches the surface; by his estimate, only about five percent of the opportunity has been unlocked. His real estate example shows what he means. Tokenizing a house is the easy part. The hard part is everything underneath it: deed settlement, county records, property taxes. Once those are bundled into the asset, mortgages and home equity lines of credit can follow it on-chain. The same reasoning turns tokenized gold from a trading instrument into a way for a mine to finance its next production run. That breadth is how Lumia positions itself against specialists like Ondo. Michael concedes they will win their chosen verticals, while Lumia tries to cover all the asset classes nobody has taken on yet.
The bigger bet is on the United States, and Michael is candid about what that costs. Lumia says it is deliberately building its US rails before the law arrives. He compares it to a racehorse that stays at the gate rather than wandering off to other tracks. The company has assembled a bipartisan bench of former Congressmen, including Tim Ryan and David McIntosh, with Gibson Dunn as counsel. The timing is pointed: the CLARITY Act failed a 49–50 cloture vote in the Senate in September. Michael says the stall was expected and that the US is still the market that matters, noting that institutions like BlackRock do not commit to a market without a path forward. He also explains LGP-01, which Lumia’s community passed with 95 percent support in early October. It retires the HyperNode program through a USDT buyback of future rewards and redirects the recovered tokens into a foundation fund for growth. He presents it as removing a structure that did not fit what institutional and government partners need.
The most provocative part of the conversation is about AI agents. Michael predicts, echoing Animoca Brands’ Yat Siu, that agents will become the largest holders of tokenized assets. He describes agents that score an asset against its listed price before buying, which speeds up price discovery. They would also source deals and send owners a daily summary, all within whatever permissions and spending limits the owner sets. A self-driving taxi that earns income around the clock is his example of an RWA category that does not exist on-chain yet. In the hot take round, Michael keeps at least half his heart with Bitcoin. He says agents combined with RWAs could take blockchain daily active users from one million to fifty million. He also sketches a ten-year future of reputation-based agent networks and “agentic billionaires”, and names The 100 as his favorite science fiction show.
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