Google's A2A Is Building an Internet of Bots — Not Agents

There's been a lot of excitement around Google's Agent-to-Agent (A2A) protocol, and for good reason. But we need to talk about what A2A really is... And more importantly, what it's not.

The Hype vs. Reality

Google's A2A protocol has been positioned as a breakthrough in agent communication—a way for AI agents to seamlessly interact and collaborate. The promise is compelling: imagine agents that can negotiate, coordinate, and execute complex tasks together without human intervention.

But here's the thing: what Google has built isn't actually an "Internet of Agents." It's an Internet of Bots.

Bots vs. Agents: Why the Distinction Matters

The difference between bots and agents isn't just semantic—it's fundamental to how we build the future of AI systems:

• Bots execute predefined workflows with some dynamic adaptation
• Agents have goals, reasoning, and autonomy to pursue objectives creatively
• Bots follow scripts (even sophisticated ones)
• Agents make decisions based on context and goals

What A2A Actually Does

Google's A2A protocol is impressive in its technical implementation. It enables:

• Structured communication between AI systems
• Standardized message formats and protocols
• Coordination of multi-step workflows
• Resource sharing and task delegation

These are valuable capabilities, but they're fundamentally about orchestrating sophisticated automation—not enabling true agent autonomy.

The Missing Pieces

A true Internet of Agents requires several components that A2A doesn't address:

1. Agent Identity and Verification

How do agents prove who they are and what they're authorized to do? A2A focuses on communication protocols but lacks robust identity verification systems.

2. Goal Alignment and Negotiation

Real agents need to negotiate conflicting objectives and find mutually beneficial outcomes. A2A assumes pre-aligned workflows.

3. Trust and Reputation Systems

In a true agent ecosystem, trust isn't binary. Agents need reputation systems to make informed decisions about collaboration.

4. Economic Incentives

Agents need ways to exchange value and create economic incentives for cooperation. A2A doesn't address the economic layer.

Why This Matters for the Future

Google's approach reflects a broader industry pattern: building increasingly sophisticated automation and calling it "agents." This isn't inherently wrong, but it's important to understand what we're actually building.

The risk is that by focusing on bot-to-bot communication, we're optimizing for the wrong future. We're building systems that serve existing workflows rather than enabling new forms of autonomous collaboration.

The Path Forward

To build a true Internet of Agents, we need to think beyond communication protocols. We need:

• Agent-native identity systems that enable verification and authorization
• Economic protocols that create incentives for valuable agent behaviors
• Trust and reputation mechanisms that enable safe collaboration between unknown agents
• Goal negotiation frameworks that allow agents to find mutually beneficial outcomes

Google's A2A is a valuable step in this direction, but it's important to see it for what it is: a sophisticated bot orchestration system, not a true agent internet.

The future we're building toward is one where autonomous agents can discover, negotiate with, and collaborate with each other to achieve goals that benefit their human principals. That future requires more than just communication protocols—it requires a fundamental shift in how we think about AI system design.

The question isn't whether Google's approach is wrong, but whether it's building the foundation for true agent autonomy or just more sophisticated automation. The answer will shape the next decade of AI development.