Bitcoin Lightning could power AI payments and machine authentication, LQWD chief says

Bitcoin’s Lightning network could support both payments between AI agents and machine authentication as software and robots take on more economic activity. Its potential uses extend from paying for services to helping machines verify one another before accessing data.

In a Bitcoin Magazine interview on November 9, Shon Anstey, CEO and chairman of LQWD Technologies, outlined how Lightning’s small, fast payments could serve AI agents. He also described a business model that puts the company’s bitcoin holdings to work routing payments.

Anstey described Lightning as a payment layer built on Bitcoin, with computers or servers operating nodes connected through payment channels. Operators must commit bitcoin to those channels to route payments, a structure he said suits frequent micropayments by AI agents.

LQWD combines bitcoin accumulation with network operations in what Anstey called “Treasury 2.0.” Payments pass through successive nodes on their way to a destination, with each intermediary collecting a small routing fee. He said expanding the business requires greater network scale and continued adoption.

Anstey said the company also supports using Lightning for stablecoins and other digital assets. He distinguished stablecoins, which can be frozen, from bitcoin, arguing that Bitcoin’s peer-to-peer network offers greater freedom from transaction restrictions imposed by a controlling party.

He argued that machine economic activity could eventually require more than 1 billion transactions per second. Meeting that demand, he said, would require an internet-like network with many nodes and routing paths. While describing Lightning as being at an early stage, he stressed the importance of its underlying design for handling larger volumes.

Beyond payments, Anstey proposed using Lightning wallets to authenticate AI agents and robots. A robot could send a tiny amount of bitcoin to demonstrate control of its wallet, he said, allowing machines to identify one another and pay for access to APIs and data.

Anstey expects agents initially to operate mainly within permissions and controls set by people. Companies could use scripts and execution rules to constrain their actions, he said, even as agents begin creating other agents and robots participate in economic activity.