Web3 with Sam Kamani

I sat down with Mitch from Steelwave at BTC Vegas to explore how one of the West Coast's most established real estate developers is bringing institutional-grade assets onto the blockchain. Steelwave has done over $24 billion in acquisitions, building campus-style properties for tenants like Google and Anduril — and now Mitch is on a mission to give international family offices and eventually everyday investors access to deals they were previously locked out of. We talk about the tokenization roadmap, why power is the single most valuable commodity in real estate right now, how AI companies are driving 20 million square feet of lease demand in Silicon Valley, and why the next generation SPV could be a global syndicate of investors from China, Africa, and Australia all coming together on a single deal. This one gets into the real mechanics of how private real estate becomes liquid — and why the window to act is right now.
Connect with Steelwave
https://www.steelwavellc.com/token-lab
Key Points with Timestamps
• [00:00] Mitch teases the core thesis: 20 million sq ft of AI-driven lease demand and tokenization as a liquidity layer for family offices
• [00:41] Sam introduces himself — 5 years podcasting, 400+ founders interviewed, occasional angel investor
• [01:22] Mitch's origin story: found a crypto volatility hedge fund, spotted a gap for institutional-grade real estate on-chain, joined his father's firm Steelwave
• [02:24] What Steelwave does: campus-style premium real estate for tenants like Google and Anduril, formerly known as Legacy Partners
• [03:22] The Westfield San Francisco moment — why real estate values crashed post-COVID and why that's now the best buying opportunity in a generation
• [04:39] Sam's perspective on the global demand for US-based assets and why real estate remains far harder to access than equities for international investors
• [06:03] The Anduril deal: Steelwave bought the LA Times printing facility in Orange County and it became Palmer Luckey's Anduril headquarters
• [07:40] Plans to fractionalize: starting at $50M minimums with family offices, then introducing token liquidity in 12–18 months for secondary market access
• [08:54] The next-gen SPV model — syndicating global investors from China, Africa, and Australia into a single deal
• [12:26] Where tokenized assets will trade: likely international exchanges first before entering the US market
• [13:30] The hardest part of the business: connecting next-gen crypto capital to old-school real estate financial structures
• [14:43] Expanding beyond real estate — sports teams, esports, TV shows, athletes, and cricket teams in India as the next tokenization frontier
• [17:14] Why BTC Vegas matters: Bitcoin capital is maturing and looking for scalable institutional assets to deploy into
• [18:18] Mitch's asks: capital partners, team members who understand the space, and the right regulatory framework
• [19:23] How Mitch pitches family offices: lead with the real estate, sell the tokenization as a liquidity unlock that cuts lock-up from 8–10 years down to 2–4
• [20:04] How Steelwave builds trust: $24B in acquisitions, zero bad assets, deep broker relationships across West Coast markets
• [21:17] 2026 real estate outlook: 20 million sq ft of AI-driven demand in Silicon Valley, tech giants scaling infrastructure, 12–24 months to buy before institutions pile back in
• [23:17] Power is king: if a site has power capacity, it gets a tenant immediately regardless of what's built on it
Disclaimer
Nothing mentioned in this podcast is investment advice and please do your own research. It would mean a lot if you can leave a review of this podcast on Apple Podcasts or Spotify and share this podcast with a friend.
Be a guest on the podcast or contact us - https://www.web3pod.xyz/

I sat down with Mehow, founder of American Fortress, right here in Miami during Consensus week, and this conversation genuinely blew my mind. Michal has been a hacker since age 15 and has spent four and a half years and 13 patents building something the crypto industry has never had before — a universal identity and privacy protocol that makes sending crypto as simple as typing a name. We go deep on why crypto addresses are still the root cause of most theft and fraud, how stealth addresses and zero-knowledge proofs work together to give you PayPal-style usability without sacrificing privacy, why institutions like Brinks are already on board, and what wrench attacks and kidnappings in France have to do with on-chain transparency. We also talk quantum computing, the confidentiality machine, and why perseverance is the only real entrepreneurial lesson that matters. This one is packed.

--- CONNECT ---
Website: https://americanfortress.io 
Twitter/X: https://x.com/Americanfort_io 
Web3 with Sam Kamani: https://www.web3pod.xyz 

--- KEY POINTS WITH TIMESTAMPS ---
• [00:01:32] Michal shares his background as a hacker since age 15 and what drove him to build American Fortress
• [00:03:14] The core problem: crypto addresses are confusing and exploitable, leading to rampant theft and fraud
• [00:06:09] User journey walkthrough — how Fortress Knok lets you send crypto by name, like PayPal, with no address interaction
• [00:08:00] How stealth addresses work and why only sender and recipient ever know where funds went
• [00:09:00] Zero-knowledge proofs running through encrypted chat to confirm sender identity and defeat address poisoning
• [00:10:00] How cryptographic KYC via Sumsub is tied directly to transactions, the first protocol to do this
• [00:14:00] Why on-chain transparency is a physical safety risk, kidnappings in France and the Ledger executive story
• [00:15:44] The confidentiality machine, one button to hide your balance while still proving your identity to the recipient
• [00:17:39] Quantum resistance built in automatically when you use the privacy shield, with no extra steps for the user
• [00:26:15] MetaMask integration as a Snap, you don't need the American Fortress wallet to use Fortress names
• [00:29:00] Four and a half years of grinding on $9 million raised, 15 engineers, launching on 12 chains simultaneously
• [00:34:10] What's next, Austin office, token launch in 4–6 weeks, Brinks as a customer, and a potential Series A

Disclaimer:
Nothing mentioned in this podcast is investment advice and please do your own research. It would mean a lot if you can leave a review of this podcast on Apple Podcasts or Spotify and share this podcast with a friend.

Be a guest on the podcast or contact us - https://www.web3pod.xyz/

In this episode, I sit down with Tom, co-founder of Ratehopper.ai, to dig into one of the most underrated problems in DeFi — people are overpaying on their loans and leaving yield on the table. Tom walks me through the journey from mining ETH in 2015, to building APY Vision with 70,000 users, to now launching an AI agent platform that automatically deploys borrowed funds into liquidity pools to pay off your loan. We talk about how the agents work, what signals they use, how they handle risk, and why the self-repaying loan concept is resonating with users. Tom also shares how they are keeping funds secure, what the Ratehopper agent competition looks like, and where they see the platform going next. If you are curious about DeFi, AI agents, or just want your money to work harder without the manual work, this episode is for you. 
Connect:
Website: https://ratehopper.ai/
X: https://x.com/RatehopperAI
Telegram: https://t.me/RatehopperPortal
Web3 with Sam Kamani: https://www.web3pod.xyz/
Key points with time stamps
• [01:00] Tom shares his background — mining ETH in 2015, learning the EVM, and building a paper trading game
• [02:39] Tom discovers DeFi farming in 2020 and builds APY Vision, a portfolio and P&L tracker for DeFi users
• [03:47] APY Vision reaches 70,000 users but faces monetisation challenges without an execution layer
• [06:08] The core problem Ratehopper solves — people are paying too much on DeFi loans and not optimising rate differentials
• [07:20] The rich person strategy — borrow against your assets instead of selling, then use borrowed funds to generate yield
• [08:37] Beta launch update — nearly 1,000 users and 450 agents deployed in the first month
• [09:01] Real user example — depositing collateral, setting up an agent, providing liquidity to earn fees that pay off the loan
• [09:55] How liquidity range settings affect APY and how the agent uses the options market to set optimal ranges
• [11:06] How risk tolerance settings shape the agent — 25 signals analysed hourly, tuned to the user's preference
• [12:26] The hardest technical challenge — building and back-testing the risk versus reward signal matrix
• [13:42] Early Ratehopper iteration focused only on refinancing and saving on borrowing costs
• [15:11] Market feedback — users wanted higher returns, leading to the self-repaying loan concept
• [17:00] User demographics — early adopters and experimenters who want to test if the product actually works
• [19:50] How Ratehopper handles trust and security — segregated multi-sig wallets, Zodiac module, no fund transfers to unknown addresses
• [21:37] Tom shares experience using other financial agents and why most still require too much manual input
• [24:25] Future scaling challenges — agent interoperability and fragmented wallet standards
• [25:45] DeFi infrastructure parallels — just as it took five years from Ethereum launch to mainstream DeFi, AI on-chain will take time
• [27:01] DeFi TVL discussion — one hack every 26 hours in the last 30 days, and 93% of losses from infrastructure and private key hacks, not smart contract exploits
• [28:23] Will AI make DeFi safer or more dangerous — Tom argues AI will help defenders more than attackers
• [30:09] Upcoming Ratehopper agent contest — 10-day competition, NFT-represented agents, prize for most loan repaid
• [31:54] Community question — can users copy a winning agent instead of building their own? Tom hints at a future vault model
• [33:24] The ask — try the product, give feedback, and consider depositing more if confidence grows
• [34:32] Experimenting with Polymarket decaying odds markets as a future agent use case
Disclaimer:
Nothing mentioned in this podcast is investment advice and please do your own research. It would mean a lot if you can leave a review of this podcast on Apple Podcasts or Spotify and share this podcast with a friend.
Be a guest on the podcast or contact us - https://www.web3pod.xyz/

--- EPISODE DESCRIPTION ---
In this episode, I sit down with Alex Dominguez, who is building SafeBets, a prediction market platform with one massive twist: you never put your own money on the line. Alex breaks down why Polymarket and Kalshi are getting banned in over 53 countries and sued by 19 US states, and how SafeBets is stepping into that gap. He shares how the platform launched today at the first-ever prediction markets conference in Las Vegas, how users can earn Unicoin and cash prizes just by making accurate predictions, and how they plan to reach 100 to 200 million users in the next few years. If you have ever wanted the thrill of a prediction market without the financial risk, this episode is for you. Nothing mentioned in this podcast is investment advice and please do your own research. It would mean a lot if you can leave a review of this podcast on Apple Podcasts or Spotify and share this podcast with a friend. Be a guest on the podcast or contact us - https://www.web3pod.xyz/
--- CONNECT ---
SafeBets Website: https://www.safebets.world
Unicoin: https://www.unicoin.com
Web3 with Sam Kamani: https://www.web3pod.xyz/
--- KEY POINTS WITH TIMESTAMPS ---
• [00:00] Sam introduces SafeBets as a competitor to Kalshi and Polymarket with a key differentiator — no money at risk
• [01:42] Alex shares his background in finance and his role as Chief Investment Officer at Unicoin, which powers SafeBets
• [03:05] Alex explains why Kalshi and Polymarket are banned in 53+ countries and sued by 19 US states due to gambling classification
• [04:22] The core differentiator: SafeBets users never put their own money in, yet can win cash and Unicoin for correct predictions
• [05:44] How SafeBets makes money — by using collective prediction data and copy trading on other platforms
• [07:38] SafeBets targets markets where competitors are banned — France, Argentina, Australia, India, Pakistan and more
• [09:29] Alex compares SafeBets to Uber and Robinhood disrupting their industries by offering a free, superior model
• [12:55] The platform officially launched today at the first-ever prediction markets conference in Las Vegas
• [14:00] Sports predictions are being added in May alongside financial markets like Bitcoin, Nasdaq and commodities
• [15:35] The Oracle leaderboard system — how top predictors are identified and rewarded
• [19:18] How Unicoin and SafeBets work as a flywheel ecosystem, with Unicoin buybacks creating token liquidity
• [21:40] Marketing plans include referral programs, branded Uber cars, airport billboards and international campaigns
• [24:24] SafeBets is currently in its second fundraising round at 25 cents per share, targeting $20 million with a $250 million valuation
• [28:44] Alex invites listeners to sign up at safebets.world for 100 free Unicoins and start predicting today

In this episode, I sit down with Vitali, co-founder of EasyStaff.io, a freelance payroll and marketplace platform processing over 20 million euro per month across its ecosystem. Vitali shares his journey from mining Bitcoin in Russia back in 2012 to building a multi-product fintech platform with a real, functioning DAO at its heart. We dig into why most DAOs fail to get participation, how EasyStaff Connect DAO distributes 90% of tokens to users based purely on business activity, and how the community is already voting on real product decisions. Vitali also opens up about the challenges of launching without venture capital, his plans to go fully open source, and why he sees blockchain-based legal token recognition as the natural next step for the platform.
Disclaimer
Nothing mentioned in this podcast is investment advice and please do your own research. It would mean a lot if you can leave a review of this podcast on Apple Podcasts or Spotify and share this podcast with a friend.
Be a guest on the podcast or contact us - https://www.web3pod.xyz/
Connect:
EasyStaff Website: https://easystaff.io
EasyStaff Connect DAO: https://connect.easystaff.io
LinkedIn: https://linkedin.com/company/easystaff
KEY POINTS WITH TIMESTAMPS
• [00:00] Introduction to Vitali and EasyStaff.io and the focus on DAOs
• [01:00] Vitali's crypto origin story — mining Bitcoin in 2012 with an ASIC device, selling at $300 per coin
• [03:40] Clarifying that EasyStaff Connect DAO tokens are currently centralised — blockchain integration is a future stage pending legal jurisdiction decisions
• [04:49] Overview of the two core products: EasyStaff Payroll (B2B) and EasyStaff Invoice (B2C), and how the DAO marketplace bridges the gap
• [07:03] How EasyStaff handles remote payments across multiple currencies, entities, and compliance requirements including sanctions
• [09:14] The core DAO problem: low participation and how EasyStaff tackles it with a 20% quorum, public backlogs, and personalised outreach
• [11:35] Tokens are earned through business activity only — no token sale, no secondary market, purely rewarding real transactions
• [12:44] Token holders receive monthly fiat dividends from platform profits, with the platform retaining only 3% of transaction fees
• [13:40] Community governance in practice — token holders collectively hold 90% voting power versus the founders' 10%
• [19:10] Real example of community governance: users voted to add PayPal to fast payment options
• [20:40] EasyStaff ecosystem now processes around 20 million euro per month, with one entity alone clearing 140 million euro in 2025
• [22:32] EasyStaff Connect focuses on design and graphics freelancers historically but is expanding broadly, including AI professionals
• [23:42] Upcoming addition of a recruiter network to expand the platform through intermediaries
• [25:05] Marketing strategies: AI-powered cold outreach on LinkedIn, rebranding, YouTube integrations, Forbes articles, and this podcast
• [28:43] If starting again — the biggest challenge was lack of capital, which forced a bootstrapped, revenue-first approach
• [30:36] Roadmap: completing hard-voting mechanics, moving to open source, separating DAO from the operating company, then going on-chain via a legally recognised jurisdiction such as Liechtenstein, UAE, or Singapore
• [34:37] AI adoption internally — using Claude for development and exploring Gemini for internal compliance and treasury processes, with a freeze on new linear hires