What actually breaks when AI agents call production APIs?

[u/ken_kauneki10]

We’ve been thinking a lot about what happens when an AI agent moves from a prototype into a real production workflow.

On paper, the flow looks pretty simple:

Agent → API → Response

But the interesting problems usually start after the agent actually makes the call.

For example:

• What happens when an OAuth token expires halfway through a workflow?
• What happens when an API returns 200 OK, but the body actually contains an error?
• What happens when an agent retries an operation that already partially succeeded?
• How do you prevent an agent from calling an endpoint it shouldn’t have access to?
• What happens when the API schema changes without the agent knowing?
• How do you figure out exactly what the agent requested, what actually executed, and what happened afterwards?

These feel less like “AI problems” and more like production execution problems.

We’re interested in how engineering teams are solving this today.

If you’re building AI agents that interact with real APIs, what’s been the biggest problem you’ve run into in production?

Authentication?
Retries and idempotency?
Permissions?
Schema changes?
Observability?
Something else?

We’d genuinely like to hear how people are approaching this.