On September 3, the Solana Foundation introduced a payment channel solution designed for AI agents and high-frequency, small-value transactions, claiming that it can support up to 1 million payments per second. This figure is easily misinterpreted. The core of the payment channel is not to allow the Solana mainnet to record 1 million independent transactions per second, but rather to have users authorize a certain amount first, conduct a large number of off-chain measurements within the channel, and then settle the aggregated results on-chain. What this approach achieves is an improved ability to process payment events, while simultaneously reducing the actual number of on-chain settlements.
This design is aimed at a problem that is becoming increasingly real: AI proxies may continuously invoke search, data, model, or computing services within a single task, each time paying only a very small amount. If each invocation required the user to sign and wait for on-chain confirmation, the experience would be extremely cumbersome, and the costs would outweigh the value of the small transactions themselves. The payment mechanism is similar to a prepaid allowance or a bar bill, where the maximum expenditure is determined in advance, with transactions recorded individually during the period, and then settled in one lump sum at the end.
Move signing and settlement away from each step.
The process described officially includes four steps: the user or agent first establishes a payment channel and locks or authorizes a quota; when a service call occurs, both parties update the verifiable payment status; these statuses do not need to be submitted to the mainnet every time; after the task is completed or the agreed conditions are met, the final balance is settled. For machine payment protocols such as x402 and MPP, this allows for "multiple calls, one settlement" instead of "one call per time on the blockchain."
One million times per second should be understood as the payment update capability that the channel system can measure, rather than a new record for the throughput of the Solana consensus layer. The more off-chain processing that occurs, the higher the requirements for channel software, state synchronization, and dispute resolution. If there is a disagreement between the parties regarding the final balance, the system must have a clear format for evidence and an exit mechanism; in the event of a service interruption, users must also be able to retrieve any unused funds. Speed cannot replace the security of funds.
Payment channels are suitable for scenarios with high frequency, small individual transaction amounts, and repeated interactions between both parties over a period of time. AI proxy purchases, API calls for computing resources that are billed per second, streaming media content, or in-game services all fit this description. However, they may not be ideal for one-time large transactions, as large transactions place more emphasis on immediate finality and clear audit trails, rather than compressing multiple payments into a single settlement result.
For developers, the new complexity comes from quota management. Once a proxy obtains prior authorization, it must comply with limits per transaction, total budgets, service allowlists, and expiration times. Otherwise, model execution errors or abnormal server-side billing could quickly deplete the balance without user confirmation for each individual transaction. A mature implementation should provide real-time balance updates, revocable permissions, rate limit exceptions, and manual pause options, rather than merely pursuing seamless payment experiences.
Payment channels must also handle offline situations and timeouts. When a user's device loses connection, a proxy process crashes, or the service provider stops responding, funds should not be permanently stuck in the channel. A reasonable design typically includes time locks, proof of the latest status, and a unilateral exit mechanism. The specific mechanisms are subject to the subsequent code after Solana and the protocol specifications; the performance claims stated in announcements cannot replace audits of boundary conditions.
The bottleneck of the machine economy is not just in throughput.
For AI proxy payments to truly become widespread, it is still necessary to address issues such as identity verification, pricing, disputes, and compliance. How service providers can confirm that calls are from authorized proxies, how users can know how much each call costs, whether refunds are possible if the result quality does not meet standards, and what obligations need to be assumed when providing services across regions are not issues that can be automatically resolved by simply increasing throughput. Payment channels have reduced transaction friction, but they have shifted more responsibilities to the application layer rules.
Stablecoins may be a more natural pricing asset in such scenarios, as API and computing services are usually sold at fiat currency prices. Developers do not want their income to fluctuate significantly with the price of SOL. However, when using stablecoins, one still needs to consider the issuer, on-chain liquidity, and account management. The specific asset to be used, whether a channel requires collateral, and how settlement fees are allocated should be determined based on actual implementation and protocol documentation. It cannot be inferred from the "Solana payment channel" that all transactions must use SOL.
The business model also determines whether a channel is useful. Only when the value of each transaction is small enough, the frequency of calls is high enough, and there are repeated transactions between both parties, will reducing on-chain settlements significantly lower costs. If the service itself is subscribed to on a monthly basis, traditional billing methods may already be sufficient; however, if immediate payment is required for each API result, then the advantages of using a channel become more pronounced. Technical capabilities should match real billing needs, rather than being created just to use the blockchain for transactions.
This approach will also change the interpretation of data on the chain. If a large number of micro-payments occur off-chain, the mainnet will only see the opening, replenishment, and closing of channels, rather than each individual service call. The number of transactions on-chain may underestimate the actual economic activity; therefore, the project team needs to provide verifiable aggregated indicators while avoiding disclosing users' sensitive behaviors. A new balance between transparency and privacy will need to be established.
The announcement from the Solana Foundation outlines the goals and capabilities of the payment channel, but the industry still needs real-world load testing, fault recovery, and open implementation to verify its effectiveness. A processing capacity of one million payments per second is a metric at the channel level and should not be misconstrued as indicating that the mainnet has been continuously handling the same number of on-chain transactions. What is more noteworthy is whether this system allows agents to purchase services continuously within a defined budget and to exit safely at any time. If this experience proves viable, the value of blockchain in machine payments will no longer lie in “every step being recorded on the chain,” but rather in using on-chain assets and final settlements to provide a credible foundation for a large number of off-chain interactions.
