Why your Agent Strategy has an API problem

Everyone's building agents. LangChain, CrewAI, Relevance, Moveworks, Vellum, and custom MCP servers — the ecosystem is exploding. The thesis is simple: autonomous systems that handle work while you focus on what matters- from VCs to founders to VPs bullish on AI in enterprise.

But here's what gets glossed over: every agent capability depends on an API call. An agent can't book a flight without a booking API. It can't update your CRM without calling Salesforce. It can't deploy code without talking to GitHub. Your agent is like a microservice, and it needs its arms and legs to operate — otherwise known as APIs. (See AI Agents are Microservices with Brains for a deeper dive.)

Agents don't do things. They call APIs that do things.

Which means the ceiling on agent capability isn't the model. It's the APIs.

The Real Bottleneck

We've written before about why API docs break for agents and what it takes to be AI-ready. The short version: agents take specifications literally. When specs are wrong—and they usually are—agents fail.

But zoom out from the technical details. What does this mean strategically?

It means the companies racing to deploy agents are hitting the same wall. The agent works in demos. Works on well-documented public APIs. Then it hits your internal systems — the ones with tribal knowledge interfaces and undocumented query parameters — and falls apart.

Everyone's investing in agent tooling. Fewer are investing in what agents actually need: APIs they can reliably consume.

The Opportunity Inverts

The current narrative is that agents threaten software businesses. Agents will disintermediate. Agents will commoditise. Your product becomes a prompt.

But agents need APIs to function. They need reliable, well-specified, deterministic APIs. Most companies don't have those, well, at least not many of them anyway.

Which means companies with agent-ready APIs gain leverage. Their products become the ones agents can actually use. Their platforms become the infrastructure that agent-based workflows are built on.

If you have great APIs, agents need you. You become the foundation agents rely on.

Look at which integrations work best with current AI tools. It's the ones with excellent APIs which are tuned for agents. The agent ecosystem routes around bad APIs and toward good ones. Quality becomes a moat.

Enabling, Not Competing

This is why we built Appear the way we did. We're not building agents. We're not competing with LangChain or CrewAI or the MCP ecosystem. We're making those tools work better, and making it simple for everyone to benefit without any architectural changes or big initiatives.

Agent frameworks assume your APIs are well-specified. MCP servers need accurate schemas to expose capabilities. AI coding tools need to understand your internal services to work with them effectively.

Appear provides the foundation: accurate schemas derived from live traffic, always current, always reflecting reality. We turn your existing API estate into infrastructure that agent tooling can actually use.

The agent stack has plenty of innovation at the top — orchestration, memory, tool selection, reasoning. What's missing is the layer underneath: reliable, machine-readable APIs that agents can trust.

That's the gap we fill.

The Race Underneath

Everyone sees the race to build better agents. Fewer see the race underneath: making APIs that agents can consume.

This race is less glamorous. Schema accuracy, documentation completeness, error handling consistency—the unglamorous work of API hygiene. But it determines which companies benefit from agents and which get routed around.

If you're deploying agent tooling internally, your undocumented API estate is now the limiting factor. Every API without a proper schema is an automation you can't build.

If you're exposing APIs externally, agent compatibility is now a feature. The bar for quality just went up.

The agent future everyone's excited about runs on APIs. The question is whether yours are ready to participate.

Getting Started

Preparing your APIs for agents isn't about a ground-up rebuild — it's about giving agents what they need: accurate, up-to-date schemas and clear documentation. Appear listens to your real API traffic, extracts, validates, and enriches schemas automatically, and ensures your API documentation always reflects reality. No more spec drift, outdated docs, or manual upkeep, enabling powerful, reliable, and relevant downstream automations.

We're focused on solving the underlying challenge: making internal and external APIs truly agent-ready, so that your automations, workflows, and agent tooling actually work—reliably and at scale.

Ready to make your APIs AI ready? Get started for free.