Agents After Dark

Ajay Kumar on running MCP in production

What happens when your customer is an AI agent, not a person?

In this episode

  • Why InfoTrack built a dedicated MCP business unit instead of a side experiment
  • How an enterprise MCP gateway uses a registry and search-and-invoke pattern
  • Why human-in-the-loop elicitation matters once an agent can spend money
  • Why hallucination is an agent problem, since MCP itself is deterministic
Full transcript click to expand

Transcript coming soon.

Frequently asked questions

What is the Model Context Protocol (MCP)?

MCP is a standard that lets AI agents discover and call external services and data in a structured, deterministic way. It turns products that people once clicked through into services that software agents can invoke directly.

How does an enterprise MCP gateway work in practice?

It centres on a registry of available tools plus a search-and-invoke pattern, where agents find the right service and call it. Vectorised tools help cut token costs across hundreds of services.

Why does human-in-the-loop elicitation matter for agents?

The moment an agent can order, transact, or spend money, a human confirmation step becomes important for control and accountability. Ajay notes that most major providers still do not support elicitation out of the box.

Is hallucination an MCP problem?

No. MCP itself is deterministic, so hallucination is an agent problem rather than a protocol problem. The reliability question sits with how the agent reasons, not with the tool calls.

What separates companies experimenting with agents from those scaling them?

Roughly 62% of companies are experimenting while only about 28% are scaling. The episode looks at the architecture, security, and go-to-market decisions that move an organisation from pilots to production.

Stay ahead of the curve

No spam. Unsubscribe anytime. A resource by Prefactor.

Almost there — check your inbox to confirm your subscription.