11-05-2026 
TL;DR: APIs are excellent at helping independent systems exchange information, but they do not automatically give those systems a shared view of what has already happened. As AI agents and other autonomous systems begin interacting across companies, payments, inventory, ownership, permissions, and contract status may need to remain synchronized across many different platforms.
Key takeaways:
- APIs help systems communicate, but each system usually maintains its own version of events.
- Autonomous agents will increase the number of transactions and state changes taking place across organizational boundaries.
- Communication protocols like Google’s A2A can help agents discover and talk to each other, but communication alone doesn’t create a shared state, let alone an authoritative one.
- Reconciliation becomes harder when inventory, ownership, payments, permissions, and contracts exist across separate systems.
- A scalable public ledger could provide a common state layer beneath different applications and APIs.
The internet is excellent at helping computers talk to each other.
APIs allow one system to request data or trigger an action in another. Google’s (NASDAQ: GOOGL) Agent2Agent system extends the same idea to AI agents, allowing agents built on different platforms to discover each other, exchange messages, and manage tasks across systems.
Cloudflare now describes an emerging “agentic internet” in which websites and services become readable, discoverable, callable, and payable by machines rather than exclusively by humans.
However, communication is only part of the problem. APIs can tell one system what another is saying, but they don’t automatically give both systems an authoritative version of what already happened.
That record of what already happened will become increasingly important as machines move from merely exchanging information to taking actions which change the state of the real world.
APIs move messages, but every system keeps its own state
Imagine a manufacturer has 1,000 units of a component in stock.
A procurement agent working for Company A asks whether 500 units are available. The supplier’s API says yes, so the agent representing Company A places the order.
Almost immediately, another procurement agent from Company B asks whether 700 units are available.
Several systems are now involved. The supplier’s database needs to show that 500 units are reserved, Company A’s procurement system needs to show its order exists, a payment system needs to show funds were authorized, and a warehouse system needs to know those units are no longer available for the other customer.
APIs can pass all of these messages around, but each system still maintains its own state. Therefore, if one update is delayed, duplicated, rejected, or arrives out of order, the various systems may disagree.
These aren’t communication failures in the traditional sense, because the messages may have been sent successfully. The problem is that the various systems may no longer agree on the current state.
Autonomous agents make synchronization harder
This problem already exists in conventional software, which is why companies spend significant resources reconciling databases, inventory, orders, payments, and other records.
However, autonomous agents could make the problem much larger. For example, they’re already increasingly persistent, prompting companies like Cloudflare to build infrastructure for long-running agents with persistent sessions, durable execution, and coordination between sub-agents.
These agents may work across many independent services. For example, a procurement agent might talk to a supplier agent, which talks to an inventory system, which calls a logistics service, which waits for a payment provider, which itself may use another agent.
Google’s A2A system helps solve this problem at the discoverability and communication levels, but it doesn’t necessarily create a common record across all the organizations involved.
This limitation is already evident in standards work on agent-to-agent trust. A March 2026 Internet-Draft on cross-domain agent communication notes that transport protocols and local permission systems don’t, in and of themselves, provide an interoperable basis for identity, authorization, delegation, revocation, and audit across separate domains.
In other words, getting machines to talk isn’t the same as getting them to agree.
A shared state layer changes the architecture
One way to deal with all of this is to keep doing what the internet does today, whereby each organization maintains its own database and APIs pass messages between them.
This model works, but it means every participant maintains its own version of events and reconciliation becomes part of the architecture. An alternative is to give each system access to the same underlying state.
Imagine the purchase we used as an example earlier again:
Company A’s agent places the order, which changes the shared state to show that 500 units are reserved; a payment is then authorized and recorded; ownership or entitlement to the goods changes once the agreed conditions are met; and the logistics system later records dispatch.
Instead of every system maintaining an isolated authoritative history and exchanging messages to keep them synchronized, each can reference the same chronological record of state changes.
A scalable public blockchain offers one way to make this a reality. Applications would still use their own databases, APIs, user interfaces, and private data. The blockchain would not replace them, but would sit under them as a common state and settlement layer.
In a blockchain-powered system, transactions record payments, signatures show who authorized a change, hashes reference private records, and timestamps establish the sequence of events and which changes occurred.
As a result, independent applications could reference the same underlying record to establish what changed and in what order, and there would be no need to store private, sensitive information outside proprietary systems.
The next internet may be a web of persistent relationships
Now imagine state extends beyond a single purchase.
While the current web is built around pages, endpoints, and requests, a machine-driven internet may increasingly need persistent relationships between identities, assets, permissions, contracts, payments, credentials, and other systems.
In any given interaction, a machine may need to verify who owns an asset, which version of a contract is current, whether a permission has been revoked, whether a payment has settled, how much inventory is still available, which credential is still valid, and more.
A single API call can’t answer those questions because the relevant state may be held across several independent parties. This is where a common ledger can add something APIs alone can’t. While APIs can connect fragmented systems, a shared ledger can reduce the frequency with which those systems need to reconcile competing versions of the same event.
At scale, with millions of agents constantly updating ownership, permissions, payments, inventory, contracts, and other shared state, the underlying infrastructure must process a large volume of low-cost transactions without becoming a bottleneck.
The next internet will still need APIs, and machines will still need protocols that enable them to discover and communicate with one another. However, communication alone likely won’t be enough for an economy increasingly run by autonomous systems.
The next internet will also need a shared layer that allows independent machines to agree on what has already happened and what the current state of affairs is.
FAQs:
What is shared state?
Shared state is information about the current condition of a system that multiple participants can reference. Examples include who owns an asset, whether payment has settled, how much inventory remains, or whether permissions are still valid.
Why do APIs not automatically provide shared state?
APIs allow one system to communicate with another, but each system generally maintains its own database. Therefore, the receiving system must update and reconcile its state based on the messages it receives.
What is Google’s Agent2Agent protocol?
Agent2Agent, or A2A, is an open protocol designed to help AI agents built on different systems discover each other, exchange messages, and collaborate on tasks. It standardizes communication between agents but does not replace all the underlying systems maintaining identity, payments, permissions, or other state.
How could blockchain provide a shared state?
A public blockchain can provide a common timestamped record of transactions and state changes for independent applications to reference. Payments, signatures, ownership changes, permissions, and cryptographic references to private records can all be associated with that shared history.
Why does scalability matter for shared state?
Autonomous systems could generate very large numbers of state changes involving payments, assets, permissions, contracts, and other data. If a public blockchain provides part of that shared state layer, it needs to process large numbers of transactions at low cost.
In order for artificial intelligence (AI) to work right within the law and thrive in the face of growing challenges, it needs to integrate an enterprise blockchain system that ensures data input quality and ownership—allowing it to keep data safe while also guaranteeing the immutability of data. Check out CoinGeek’s coverage on this emerging tech to learn more why Enterprise blockchain will be the backbone of AI.
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