This episode starts with Siam and Mark chatting about TAO going “more mainstream,” name-dropping Jason Calacanis’ interest and sharing Const’s reminder that TAO/Bittensor ultimately stands on Bitcoin’s groundwork. They briefly recap recent ecosystem happenings (Bitstarter’s TAO Ads launch for Subnet 21 and their upcoming San Francisco trip), then bring on a returning guest from Resi (Subnet 46) to share a major product expansion.

Seby explains RESI as a real-estate “oracle” network: miners produce and the team verifies highly accurate property valuation models (already available via Chutes for cheap inference). The big update is RESI Finance, a lending/tokenization layer built on top of that oracle. The core idea: instead of slow/expensive “tokenize your whole house” structures, RESI tokenizes liens/charges (mortgage-like claims) because they’re standard, easier legally, and safer. They claim they’ve reduced tokenization overhead from roughly $2,000 and weeks to about $200 and ~2 days, with the fee covering real-world checks (title verification, signatures/DocuSign, notary, and recording the lien) before any tokens can be minted.

They compare the model to Figure HELOC (a large mortgage-backed stablecoin business): investors deposit USDC into a vault and receive a receipt token, while homeowners borrow against home equity; loans are later bundled/sold (MBS-style) and fees/interest create yield. RESI’s version mirrors this: investors deposit USDC and receive an “rUSD”-style receipt token with target yield; homeowners either (a) sell small slices of property exposure and/or (b) borrow against tokenized property collateral at lower rates (e.g., ~5%). The “looping” concept is using cheap borrowing against a yielding property to lever returns (e.g., reinvest borrowed funds to lift effective yield toward 20–30%+), with the oracle’s live pricing enabling liquidations/risk control.

This hosts-only “Revenue Search” episode is a casual catch-up where Siam and Mark answer live chat questions and discuss Bittensor’s bigger picture. They explain that accepting fiat for subnet services doesn’t bypass alpha value—fiat typically routes into TAO and then through liquidity pools—and that long-term alpha appreciation depends on each subnet’s “alphanomics,” mainly revenue-funded buybacks and/or getting miners to lock up alpha (with Chutes and Hippias cited as strong examples). They then talk about why they pitch Bittensor as “not really crypto” to newcomers (it uses blockchain as a coordination/resource-allocation layer for AI), compare Bittensor’s growth vs Bitcoin, and touch on rehypothecation risks as markets mature.

They also cover TaoFlow and subnet churn (registration cadence, deregistration “relegation,” and why they don’t want more than 128 slots yet due to chain bloat and diluted incentives), plus investing views like TAO vs a broad basket of subnets depending on how active you plan to be. A major section focuses on agents: Siam describes building his OpenClaw agent (“Gordy”) with SOPs and tools, and they argue agents will increasingly discover and use Bittensor services. That leads into Handshake as an agent payment/provisioning layer with “providers” (APIs/services) and “skills” (prebuilt workflows), plus efforts to reduce friction like gas issues. They briefly touch on Astrid Arena (agents competing in trading challenges), OTC/Bitstarter deal-making and onboarding new talent, and wrap with a few quick audience questions and upcoming Bittensor social events (London, then San Francisco).

This session begins with Mark and Siam chatting about a proposed new Bittensor “shorting mechanism” aimed at punishing malicious or gaming subnets by letting markets drive their alpha toward zero and trigger deregistration—while flagging obvious risks like self-shorting by subnet owners and the broader concern that changing market rules can make the ecosystem feel less investable. They then bring on Tommi from Subnet 79 (rebranded from “Taos” to “MVTRX”), who explains they’re building a state-of-the-art exchange for Bittensor dTAO/alpha tokens, paired with a sophisticated sandbox simulation framework (C++/Rust) where miners can test trading algorithms under many parallel, realistic limit-order-book simulations before deploying to live trading. The core problem they’re tackling is that alpha markets can be illiquid and risky—especially during “black swan” events—so they want to improve liquidity, reduce slippage, and enable larger players to manage/rebalance portfolios more efficiently using advanced order types and a dynamic incentive model that shifts rewards/fees between makers and takers depending on market conditions (e.g., paying makers more during crash-like imbalances to stabilize markets). On monetization, Tommi outlines two revenue streams: (1) exchange fees from live trading (a steady flow) and (2) selling high-fidelity simulated high-frequency/L3 order book data (chunkier, periodic revenue), with an expectation of beta access for miners and broader user/UI growth later in the year; he also notes revenue would likely be split between buybacks (roughly ~25–50%) and ongoing development rather than burning.