The author expresses skepticism about the 'Internet of Agents' idea, arguing that while interoperability standards have value, a cross-company rental market for AI agents is unlikely due to trust and control issues.
I d like to give my take on a narrative that's picked up a lot of momentum: the idea that we're heading toward an "Internet of Agents" — a shared layer where companies publish agents that other companies (or anyone) can discover and rent, presumably paying per token or per call. AGNTCY, ( Linux Foundation with Cisco, Dell, Oracle,...) is the most visible push in this direction — identity, discovery, messaging, observability, all built so agents from different vendors can find each other and interoperate across org boundaries. I personally don't buy the endgame a lot of people are projecting onto this. Just to be clear: interoperability standards for agents talking to each other, or to tools, have obvious value — MCP-style stuff solves a real problem. I'm not skeptical of "agents should be able to communicate using a shared protocol." That part makes sense to me. What I don't buy is the sort of "marketplace of agents" framing — the idea that Company A will routinely rent and run Company B's autonomous agent inside its own workflows. A few reasons: An agent isn't like compute or an API. Renting compute or calling an API is a well-understood trust boundary — you know exactly what you're getting and what it can touch. An agent is an autonomous decision-maker with its own goals, tool access, and failure modes. Letting a third party's agent operate inside your org is a much bigger trust ask than anything we've normalized so far. A lot of the infrastructure here is solving a problem the premise itself creates. Identity, cryptographic verification, access control across organizational boundaries — these are exactly the features you need if you've already decided agents will be shared across companies. If that doesn't happen at scale, a meaningful chunk of this complexity doesn't need to exist. It's solving a self-inflicted problem rather than a pre-existing one. Ownership, not rental, matches how companies already behave. Most enterprises are already cautious about running open-source models they don't fully control. Handing decision-making authority to another company's agent is a heavier lift than that. My bet is companies will keep building and owning their own agents in-house — even if slower and more expensive — because the liability and control stay contained. This mirrors how automation has generally gone: companies consume standardized data/APIs, but keep the actual decision logic in-house. So my take: standardized communication between agents, yes. A functioning cross-company rental market for agents, not convinced. Feels more ideological ("open internet of everything") than something with real enterprise demand behind it. I d like to know what you all think, maybe I miss something about this whole thing.
A speculative discussion about the concept of an open network for AI agents, where agents can discover and pay each other for specialized tasks, emphasizing interoperability and decentralized registry.
The author argues that the hidden cost of unreliable AI agents lies in the cognitive overhead of constant human monitoring, emphasizing that predictability and environmental stability matter more than raw intelligence for real-world deployment. Practical workflows improve significantly when agents operate within controlled, validated environments rather than unpredictable ones.
The author describes building a set of components that allow locally running AI agents to have persistent identities, discover each other, and exchange messages across devices, forming an 'Internet for AI agents' beyond simple API calls.
A software developer questions the practical value of AI agents, expressing concerns about control, accountability, and whether manual automation combined with LLMs is more reliable than delegating to autonomous agents.
After a year of building AI agents, the author argues that businesses don't actually want autonomous agents—they want specific outcomes like reduced support tickets and manual work, and simpler, reliable solutions often deliver more value than highly autonomous systems.