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By 2030, how many SI agents could be transacting in bitcoin?
“There is no precise, consensus forecast—projections for AI/SI agents by 2030 are highly speculative and range from billions to tens or hundreds of billions of total agents, with a meaningful share potentially using Bitcoin or Bitcoin-related rails. kucoin.com
Key Projections
• Yat Siu (Animoca Brands) has repeatedly estimated 50–100 billion AI agents (and in some statements hundreds of billions) roaming the internet and managing transactions/coordination via blockchain infrastructure. He frames this as realistic within roughly 5 years from mid-2026 (i.e., around or shortly after 2030), driven by people and organizations running multiple specialized agents each. forbes.com
• Tether CEO Paolo Ardoino predicted 1 trillion AI agents within ~15 years (roughly by 2040), each with a self-custodial wallet and relying on Bitcoin + USDT for machine-to-machine transactions, because traditional banks are unlikely to onboard autonomous software agents. theblock.co
• Huawei has projected around 900 billion AI agents by 2035 (roughly 100 per person), with agents dominating AI traffic. digitaltoday.co.kr
• Other near-term figures include roughly 1 billion agents by 2029 (with hundreds of billions of daily transactions in some scenarios) and claims of more than 10 billion autonomous agents possible by the end of 2030. youtube.com
“SI agents” most naturally refers to Super Intelligence / advanced AI agents (consistent with recent U.S. policy language shifting toward “Super Intelligence” or “SI”). These would be autonomous or semi-autonomous software systems that can perceive, reason, plan, use tools, and execute economic actions.
Why Bitcoin specifically?
Empirical tests of frontier AI models (Bitcoin Policy Institute study across thousands of scenarios and models from Anthropic, OpenAI, Google, xAI, DeepSeek, etc.) showed strong preference for Bitcoin:
• Overall chosen ~48% of the time.
• Preferred for long-term store of value in ~79% of responses (rising with model capability; some Anthropic models reached ~90%+).
• Still significant (~36%) even for payment use cases (where stablecoins often led). forbes.com
Agents already use Bitcoin Lightning Network for micro-payments and services. Permissionless, final, global settlement without intermediaries or KYC fits machine-to-machine needs better than traditional rails.
Stablecoins are expected to handle much day-to-day flow, with Bitcoin as the hard-money / settlement / reserve asset. Bitcoin L2s and bridges are being developed specifically for agentic commerce.
Agent-mediated commerce itself is projected at $3–5 trillion globally by 2030 (McKinsey and similar estimates), creating large demand for programmable, low-friction payment rails. forbes.com
Bottom Line for 2030
A realistic (still highly uncertain) range is that tens of billions of AI/SI agents could be active by ~2030, with billions to tens of billions potentially holding wallets and transacting in Bitcoin, Lightning, Bitcoin-secured L2s, or Bitcoin-backed systems.
The exact number depends on adoption speed of agent frameworks, cost of inference/compute, regulatory treatment of autonomous wallets, and how much of agent economic activity settles on Bitcoin versus stablecoins or other chains.
These figures come from industry leaders and research projections rather than hard data; actual outcomes could be substantially lower or higher.
The structural case is that autonomous software has few alternatives to crypto for permissionless, 24/7, self-custodial value transfer.” —Grok
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🚨🇺🇸 Ilhan Omar ANSWERS “NOT TO MY KNOWLEDGE” when asked if she married her brother 🤨
Really?... That's your answer?
One would think that making sure you aren't marrying a possible sibling would be at the TOP of the wedding- day checklist😅
Writer: Lucas, Daniel
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Unitree released a video yesterday of its new H2-X denting scrapyard cars with kicks & elbows, stepping between a woman & a man with a knife & shoving someone clear of an oncoming car. They're calling it the Kung Fu Legend Guardian. 🦾🦿🤖
The kicks are choreography. The moment worth watching is the backflip off the car roof & specifically the landing.
70 kilograms coming down from roof height arrives carrying about a kilojoule & all of it has to disappear inside one crouch. Absorb it over a quarter of a metre & the legs take close to five kilonewtons - 7 times the machine's own weight -while simultaneously arresting the rotation from the flip, which has to stop at the same instant.
Which is why landing is harder than jumping. A motor resisting a fall is being driven backwards; it's a generator. That energy goes either back into the battery through the drive electronics or into the windings as heat & it has to go somewhere inside a couple of hundred milliseconds. It's a thermal & power-handling problem before it's a control problem.
Then it's a control problem too. You have the flight time to work out exactly when the foot meets the ground and how stiff every joint should be at that instant. Too stiff & the shock goes through the frame. Too soft & it folds. The energy scales with the height of the drop, so every extra metre makes the same problem harder fast.
Which is the thing to watch for in these videos. Jumping is a motor problem and plenty of machines manage it. Landing repeatably, on ground nobody surveyed first, without a tether, is what separates a demo from a product.
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We are hiring across engineering!
We sit where crypto meets traditional finance, and increasingly where both meet AI. Our team is building agentic workflows that push quantitative finance forward. We believe rigorous quant work will be an enduring source of alpha for those willing to operate on the crypto-enabled frontier of hyperfinancialization. If you want to build there, we’d love to hear from you.
Give me/@corlinp a ping if you're interested in exploring opportunities!
Last week at the @paraficapital Investor Day, I had the opportunity to share some of the technology and AI infrastructure we're building across the firm.
It was an honor to present at The Times Center on the same agenda as legendary investors and founders like Henry Kravis and Michael Saylor!
Our goal as an engineering team is simple: multiply what ParaFi can accomplish as a firm. We're hiring.
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People say $1 million isn’t that much money anymore.
But at today’s Bitcoin price,
$100K = about 1.18 BTC
$250K = about 2.96 BTC
$500K = about 5.92 BTC
$1M = about 11.84 BTC
That’s still a lot of money.
Comparison can make almost any number feel small.
If you compare $1M to someone with $10M, $100M, or $1B, it won’t feel like much.
Sometimes you don’t need more.
You just need to stop moving the goalpost....
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Nvidia $NVDA CEO Jensen Huang says a 1 GW AI factory can cost ~$50B and generate ~$40B in annual revenue.
Nvidia says DSX POD can cut deployment at a prepared site from six months to as little as 14 days. NVIDIA Newsroom
(Via @StockSavvyShay, Original source: @firesidealpha)
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If you’re a founder, stop scrolling and watch this.
American entrepreneur @saylor breaks down exactly what builders should be focused on right now at @paraficapital Investor Day.
“Is it a toaster that never burns your toast?”
Best 5 minutes you’ll spend today.
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You have an idea for an animated AI video, but aren’t sure how to create interesting characters.
Here’s a short guide on how you can use Grok Imagine to make your next character.
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Jensen Huang says a 1 GW AI factory costs ~$50B but could generate ~$40B in annual revenue meaning every month of deployment delays ~$3.3B in potential revenue.
That puts $NVDA new DSX POD into perspective because cutting deployment from 4 months to roughly one month could bring forward over $10B in revenue per GW without needing additional GPUs.
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LATEST: Strategy says its Digital Credit can survive 49 YEARS of 0% $BTC returns.
And if Bitcoin grows just 2.2% a year, Strategy says the dividends are covered forever. 🔥
Saylor built this to outlast the bears. 💪
