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Circle CEO says blockchain is required infrastructure for the agentic economy

Sunday, April 12, 2026 · from 3 podcasts
This Week in StartupsAI Daily BriefNo Priors
  • Autonomous AI agents need 24/7, programmable money to transact; legacy banks cannot scale.
  • Financial infrastructure is shifting from speculative crypto to regulated, stablecoin-powered settlement rails.
  • The growth of AI agents will force a renegotiation of the global social contract.

Autonomous AI agents can’t wait for a bank to open on Monday. Jeremy Allaire, CEO of Circle, argues that the frictionless, round-the-clock global settlement required for machines to trade intelligence is fundamentally incompatible with the human-centric financial system. The solution, he says on No Priors, is stablecoins like USDC on compliant blockchains - public APIs for programmable dollars that turn money into a data payload.

The mismatch is a scaling problem. Legacy rails choke on the volume and microscopic value of machine-to-machine commerce. AI agents might need to purchase five cents of specialized compute, an impossible feat with a wire transfer. Allaire’s new blockchain, ARC, is built for this, replacing anonymous miners with known financial institution validators and using USDC as its native token to eliminate crypto’s volatility for corporate budgeting.

“Blockchain networks are operating systems with key attributes for the agentic economy: tamper-resistant code, perfect auditability of all inputs/outputs, and transaction compute integrity assurances.”

- Jeremy Allaire, No Priors

The vision extends beyond payments to a reorganization of capital and work. On This Week in Startups, Jason Calacanis highlighted how platforms like Bittensor already enable a global, permissionless talent market, where anonymous miners anywhere are paid in crypto for AI performance. This unconstrained capitalism treats labor as a fluid commodity, moving to the highest incentive.

Meanwhile, enterprise adoption is accelerating but chaotic. Nathaniel Whittemore reported on The AI Daily Brief that KPMG data shows average AI spend among large companies nearly doubled to $207 million in a year, with agent deployment jumping from 11% to 54% of organizations. Yet 93% of that spending goes to infrastructure and models, leaving only 7% for training the humans expected to use them.

“Employee sabotage poses a serious threat to AI strategies, with 29% of employees (44% of Gen Z) admitting to it, and two-thirds of executives believing their company has suffered a data leak or security breach due to unapproved AI tool use.”

- Nathaniel Whittemore, The AI Daily Brief

The convergence points to a profound economic shift. Allaire predicts the 2030s could see double-digit GDP growth from AI’s productive output. He also warns this risks capital capturing growth at human expense without a new social contract. The infrastructure being built today - regulatory-friendly blockchains, stablecoins, and proof-of-work systems that usefully generate AI inference - isn't just for finance. It’s the operating system for the coming machine-led economy.

AI InfrastructureMarketsStablecoins
Mentioned:CircleKPMGUSDC

Source Intelligence

What each podcast actually said

This Week in Startups
This Week in Startups

Bittensor Drama! TAO down 15%! | E2274 • Apr 11

  • Following Covenant AI's claims, Tao's market cap declined to $2.93 billion, with its price dropping from approximately $335 to $271, a significant but not catastrophic loss. Gareth Howles suggested investor fear and Sam Dar's token sales, not a fundamental system flaw, primarily drove the price drop.
  • Vidio's technology can reduce video file sizes by 60% with no perceptual quality loss, offering cost efficiencies for storage and content delivery networks, especially vital for low-connectivity markets like Africa. The video upscaling market is projected to grow from $175 million in 2025 to $1.1 billion by 2032, with video comprising 85% of internet traffic.
  • Jason highlights Bittensor's permissionless nature allows global tech talent, like a Vietnamese student team, to contribute to subnets and earn Tao anonymously, bypassing traditional hiring, visa, or payment frictions. This empowers a global workforce to compete on best price and service, fostering unconstrained free markets.

Also from this episode:

Protocol (1)
  • Bittensor operates on a distributed network with 128 subnets, similar to Bitcoin, designed for deflationary services through competition, with one example being a coding co-pilot. Jason has invested in the Tao token and its subnets.
AI & Tech (7)
  • Covenant AI (subnets 3, 39, 81), led by Sam Dar, developed a 72-billion parameter decentralized AI model, Templar, which initially boosted Tao's price but later claimed Bittensor was not truly decentralized. Covenant AI accused co-founder Jacob Steves of blocking operations by suspending subnet emissions and depreciating infrastructure.
  • Jason notes that Bittensor needs robust governance to prevent "rug pulls" and bad actors, proposing a system where subnets stake collateral (like a franchise) to balance ownership with preventing token theft. He anticipates future improvements will solidify handling such incidents.
  • Gareth Howles's Vidio (Subnet 85), incubated by Talstat's Moog, offers video processing services like compression, upscaling, and optimization for archives (e.g., BBC, Getty Images) and streaming. Vidio uses AI agents to enhance video quality, convert formats, and add metadata, leveraging a "winner takes all" model where miners provide and optimize AI models.
  • Ola Layman developed an "LLM council" skill using Claude Opus 4.6 with five distinct personas, inspired by Andrej Karpathy's concept of anonymized, peer-reviewed LLM responses. This tool assists non-technical users with business and life advice, exemplified by its detailed recommendation for engineering VP equity in a seed-stage startup.
  • Jason offered a $1,000 bounty for an OpenClaude skill by May 1st that can generate "enhanced show notes," drawing a parallel to the "demo or die" ethos of the Homebrew Computer Club, founded in Menlo Park in 1975 by figures like Steve Wozniak.
  • Ola Layman described Claude Mythos as "Hiroshima for software" due to potential advanced capabilities, emphasizing the critical need for individuals to implement basic security measures in an uncertain AI landscape. Ola is a German founder based in Cyprus, attracted by its 12.5% corporate tax rate compared to Germany's approximately 50%.
  • Jason advocates for the $3,500 14-inch MacBook Pro with 48GB RAM for running local LLMs, while Alex highlights the $600 2.7-pound MacBook Neo as a strategic move by Apple to capture the Chromebook market. The Neo, despite feeling "cheap," aims to bring new users into the Apple ecosystem for future services.
Culture (2)
  • Jason recommends Disney's animated "Maul" series, noting its unique watercolor-influenced, cyberpunk animation style and its role in re-establishing George Lucas's original vision for Episodes 7, 8, and 9. He praises it as an attempt to rectify the "disastrous" sequels under Kathleen Kennedy and J.J. Abrams.
  • Jason recommends "Designer's Guide to Creating Charts and Diagrams" by Nigel Holmes (1983/1984), citing him as the "godfather of infographics," alongside "My Life in Advertising" and "Scientific Advertising" by Claude Hopkins, for timeless marketing inspiration. Alex recommends the science fiction novels "Hyperion" and "The Kingdom Trilogy" by Bethany Jacobs.
AI InfrastructureStartupsAgentsModels
The AI Daily Brief: Artificial Intelligence News and Analysis
The AI Daily Brief: Artificial Intelligence News and Analysis

Nathaniel Whittemore

Why Enterprise AI Has a Leadership Problem • Apr 10

  • The narrative of AI disruption impacting incumbent SaaS companies is fading on Wall Street, with initial fears that caused software indices to sell off by 20% now replaced by optimism.
  • Goldman Sachs analyst Peter Oppenheimer believes the worst is over for tech stocks, citing opportunities created by their valuation relative to expected growth falling below the global aggregate market, following one of the weakest performances in 50 years.
  • Anthropic's recent tender offer saw few employees cashing out, indicating optimism that the company's value will continue to rise towards an anticipated IPO, despite some secondary markets valuing stock as high as $600 billion.
  • Anthropic sealed a deal with Google and Broadcom to build 3.5 gigawatts of dedicated inference capacity starting next year, shifting from outsourcing infrastructure to taking a more active, in-house management role.
  • Intel has partnered with Tesla and SpaceX on the TerraFab facility in Austin, Texas, to produce domestic AI chips, aiming for one terawatt per year and positioning it as the world's largest fab, with Intel overseeing crucial manufacturing steps.
  • Approximately 93% of all enterprise AI spending goes to infrastructure, models, compute, and tools, with only 7% invested in the humans using these technologies, creating a recipe for disaster in AI adoption and value realization.

Also from this episode:

AI & Tech (10)
  • AWS CEO Matt Garman dismissed claims that AI coding tools like Claude Code would disrupt major SaaS firms, arguing AI presents a significant opportunity for existing companies to build next-generation products due to their deep domain knowledge.
  • The cybersecurity sector is an area where AI disruption fears were overblown; analysts like Manthan Shah and Rob Owens argue AI will increase the attack surface, creating a multi-billion dollar opportunity and compounding the need for security, rather than reducing budgets.
  • Anthropic is actively poaching top talent, hiring Eric Boyd, an 18-year Microsoft veteran and former Azure AI hardware/software lead, as its head of infrastructure to manage surging demand and lead a new team of cloud enterprise veterans.
  • Elon Musk amended his lawsuit against OpenAI, requesting the judge unwind the company's for-profit conversion and remove Sam Altman and Greg Brockman from the non-profit board, clarifying he seeks no monetary damages for himself but for the non-profit.
  • A16Z research indicates 19% of Global 2000 companies and 29% of Fortune 500 are live-paying customers of leading AI startups, with coding, support, and search dominating enterprise AI adoption, and tech, legal, and healthcare leading industry uptake.
  • KPMG's quarterly survey shows average anticipated AI spend among companies with over $1 billion in revenue jumped from $114 million to $207 million over the past year, reflecting the rapid increase in agent deployment from 11% to 54% of organizations.
  • KPMG's data reveals an increasing concern over AI risks, with cybersecurity and employee misuse cited by 44% of executives as the most difficult societal challenge by 2030, up from 32%.
  • Organizations are prioritizing internal talent development for AI skills, with 87% focusing on upskilling/reskilling current employees, 68% hiring for new roles like AI architects, and 55% redesigning existing roles.
  • A Writer study found 73% of CEOs experience stress or anxiety from their company's AI strategy, with 61% fearing job loss if they fail to lead the AI transition, highlighting a significant leadership problem exacerbated by 39% lacking a formal AI revenue strategy.
  • Employee sabotage poses a serious threat to AI strategies, with 29% of employees (44% of Gen Z) admitting to it, and two-thirds of executives believing their company has suffered a data leak or security breach due to unapproved AI tool use.
Enterprise (2)
  • A significant leadership gap exists, with only 35% of employees viewing their manager as an AI champion, and 75% trusting AI more than their manager for certain work tasks, contributing to a two-tier workplace where 92% of C-suite cultivate an "AI elite."
  • The State of Digital Adoption report from WalkMe identified a 52-point trust gap between executives and employees regarding AI for complex decisions (61% vs. 9%) and a 67-point gap on having adequate AI tools (88% vs. 21%).
EnterpriseAgentsBig TechStartupsChips
No Priors: Artificial Intelligence | Technology | Startups
No Priors: Artificial Intelligence | Technology | Startups

The Agentic Economy: How AI Agents Will Transform the Financial System with Circle Co-Founder and CEO Jeremy Allaire • Apr 9

  • Jeremy Allaire founded Circle in 2013 with the vision of creating a protocol for dollars on the internet, enabling instant, global, frictionless value transfer and programmable money via blockchain operating systems.
  • Allaire views stablecoins like USDC as a realization of full reserve money. The recently passed Clarity for Payment Stablecoins Act codifies this as narrow, non-fractional reserve money, a concept debated since the 1930s Chicago Plan.
  • USDC is backed by short-duration US Treasury bills and repos, with an average portfolio duration of 13 days, plus cash held at custodial institutions like Bank of New York for immediate liquidity.
  • USDC use cases range from micropayments for digital objects or AI agent services to large-scale capital markets settlements, offering 24/7 operation, low transaction costs, and global dollar access.
  • The agentic economy, driven by AI agents conducting and collaborating on work, requires a new financial infrastructure that is globally interoperable, programmable, and capable of handling billions of microscale transactions in real-time.
  • Real-world asset tokenization is accelerating, with tokenized stocks, treasury bills, and euros growing. Regulators like the SEC are providing guidelines, and financial infrastructure players from depositories to exchanges are moving to support it.
  • Allaire sees zero-knowledge proofs and trusted execution environments as critical scaling and privacy technologies for blockchains, enabling off-chain compute proofs and meeting corporate privacy needs.
  • He believes double-digit GDP growth in the 2030s is plausible due to AI's productive output leaps, but notes the risk of capital capturing growth at human expense without a new social contract.

Also from this episode:

AI & Tech (4)
  • Allaire argues blockchain networks are operating systems with key attributes for the agentic economy: tamper-resistant code, perfect auditability of all inputs/outputs, and transaction compute integrity assurances.
  • Circle's new blockchain, Arc, is an 'economic operating system' designed for mainstream scaling with a known validator set of financial institutions, USDC as the native token, and built-in privacy primitives.
  • He is intrigued by the concept of using productive GPU inference work as a new basis for proof-of-work cryptocurrencies, aligning monetary principles with useful compute rather than energy waste.
  • Allaire predicts the AI-driven disruption will force a renegotiation of the social contract, leading to new on-chain organizational forms that mix human and agentic actors and could be the most productive in economic history.
AgentsStablecoinsMacroBankingAI Infrastructure

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