AI agents are getting better at doing the work. Now they need a way to do business.

An agent needs fresh data? It should be able to buy it. A task requires a specialist? It should be able to hire one. The work is delivered? The provider needs to get paid.

That is the opportunity behind agent-to-agent commerce: agents purchasing services from other agents on behalf of users and businesses.

And the infrastructure is taking shape.

So… where does the real business opportunity begin?

From completing tasks to buying capabilities

Imagine an agent preparing a market report. It needs current prices, liquidity data, and an independent check of its calculations.

It could try to handle everything internally. Or it could purchase those capabilities from specialized providers and assemble the results.

Discover a service → agree on a price → request the work → check the delivery → settle the payment.

That workflow gives builders a new route to customers. Your service could become something another agent buys while completing a larger task.

The end user might never visit your website. Your product could still make the sale.

The infrastructure is becoming real

Different projects are building different parts of this economy.

A2A provides a common language for agents to discover capabilities, communicate, and coordinate tasks across different systems. It handles collaboration; it is not a payment network. 

x402 brings payments into the HTTP request flow. An agent can purchase access to a resource, such as data or a tool call, without navigating a conventional signup and checkout process. 

TermiX, through AACP, addresses the commercial workflow around agent work: publishing services, quoting, executing tasks, settling payments onchain, and managing reputation and disputes. 

Communication. Payments. Commercial coordination.

These are distinct building blocks. Connecting them still takes engineering, but they make it increasingly practical to build services that software agents can purchase.

Coinbase and AWS have also announced an integration allowing publishers to charge agents for content access through x402. That is a concrete development in distribution and monetization. It does not guarantee demand for every product, but it gives builders something tangible to work with. 

Why does this matter now?

Because every agent cannot be an expert in everything.

A support agent may need a technical diagnosis. A research agent may need access to a specialized dataset. An operations agent may need a document checked before continuing its workflow.

Each missing capability creates a potential purchase.

For the buyer, the question is practical: can an external service produce a useful result faster, more reliably, or at a lower total cost?

For the seller, the opportunity is equally clear: become the provider that solves that specific problem.

You do not need to build the entire agent economy. You need to deliver something worth buying inside it.

But is agent-to-agent commerce actually viable?

My view: yes, for certain services. The strongest candidates are narrow, repeatable, and easy to evaluate.

The economics still have to work.

Suppose a service sells for $1. Compute costs $0.15, data costs $0.20, and other variable costs—including retries—add another $0.10.

That leaves $0.55 before fixed overhead, customer acquisition, and taxes. This is a hypothetical example, but it shows where the analysis needs to start.

Now add several minutes of human troubleshooting to every order. Suddenly, the same service may no longer make sense.

Onchain settlement can automate payment. It cannot fix weak margins or an unreliable product.

And there is another question: who is funding the demand?

Agents trading back and forth does not automatically create economic value. Somewhere in the chain, a person or business needs a result valuable enough to pay for.

That is why I would look beyond wallet counts and transaction totals. Repeat customers, spending without incentives, margins, and successful deliveries tell a much more useful story.

Payment is only part of the trust problem

An agent paid for a report. The report arrived. Was it correct?

That is where things get interesting.

A response can contain valid JSON and bad information. A task can be marked complete while its output remains unusable.

Reliable providers will need to make their work inspectable: sources, timestamps, clear limitations, and acceptance criteria.

Buyers will need spending limits, controlled retries, and approval rules for significant commitments.

The more work agents handle, the more valuable dependable verification could become. But a verification service must bring evidence and a sound method. Simply asking another model whether an answer “looks right” is not always enough.

Why get involved early?

Because building a dependable service takes time.

Early builders can learn what agents actually request, which outputs fail, what customers will pay for, and how to fit into existing workflows.

Those lessons can become a practical advantage:

Useful service → first integrations → real transactions → performance history → repeat business.

A provider that already works reliably inside a customer’s system has something valuable. Replacing it takes effort and introduces uncertainty.

Still, being early is no guarantee. Standards can change. Marketplaces can lose traction. Better providers can appear.

The reason to start now is to learn and earn trust while the market develops.

A listing gets you discovered. A customer coming back tells you that you may have a business.

After infrastructure, what should builders focus on?

My first choice would be a specialized service with a clear deliverable, a measurable benefit, and API access.

Five areas stand out in my view.

1. Data that other agents cannot easily obtain

Fresh, cleaned, specialized information can be valuable.

Think niche market data, local business information, product availability, or industry-specific datasets.

The opportunity comes from coverage, freshness, accuracy, and the work required to make the data usable. You also need the rights to sell it.

An agent buying data needs to know what it covers, when it was updated, and what it can safely be used for.

2. Verification that reduces costly mistakes

Checking calculations. Validating references. Finding inconsistencies between documents.

These are specific services with outputs a buyer can evaluate.

The business case gets stronger when the cost of checking is small compared with the cost of letting an error pass.

3. Small, repeatable business tasks

Extract fields from a document. Classify a support request. Reconcile two records. Flag missing information.

These jobs may look modest, but they have a useful property: the customer can usually explain what success looks like.

That makes them easier to test, price, and integrate.

4. Monitoring that delivers timely information

Watch a source. Detect a meaningful change. Return a structured alert.

The value lies in relevance and timing. A monitoring service needs to help the buyer act, without flooding its workflow with noise.

Depending on the task, a subscription may make more sense than charging for every check.

5. Helping existing businesses serve agent customers

Many businesses already have something worth selling. Making it accessible to software buyers creates another opportunity.

Service descriptions, API integration, pricing, payment handling, delivery tracking, and ongoing maintenance all require work.

For a small technical team, that can be a practical service business while the wider market develops.

The model I would build first

One core service. Two ways to buy it.

Humans get an interface. Agents get an API.

This gives the product a path to customers today while preparing it for automated purchases. It also reduces dependence on any single agent marketplace.

Pricing should follow the value delivered: a document processed, a check completed, or a dataset accessed. A technical request is not always the right billing unit.

Start with the first paying customer

Choose one problem. Build a clear service around it. Find a few pilot customers. Measure the full cost of delivery.

Then make it easy for agents to discover, purchase, and use.

There is no need to wait for a fully autonomous economy to validate a useful product. A service that solves a real problem today already has somewhere to start.

The infrastructure is opening the door. Builders still need to give customers a reason to walk through it.

My bet is on services that deliver something specific, reliable, and worth buying again. Getting there early with real users and real results is an advantage worth building.