Your API Wasn't Designed for AI Agents. Here Are 5 Fixes.

<p>Most of the failures I see in production AI agents aren't reasoning failures. The model picks the right tool, fills in the right arguments, and makes a perfectly sensible

<p>A VentureBeat survey of 40 enterprise organizations published in Q1 2026 found that 72% of enterprises believe they have meaningful control over their AI deployments. They have

<p>Most developers who build AI agents make the same mistake: they spend weeks designing the orchestration layer, tuning the system prompt, and picking the right model — then hand

<p><strong>TL;DR:</strong> Your agent lives for 2 minutes. Its credential lives for 60. That mismatch is your attack surface. A broker that issues task-scoped, short-lived

<p>AI agents will need to pay for compute, data, and API calls as they become more autonomous. Today's AI agents rely on humans to manage API keys and billing — but what happens

<p>You've built the demo. It works. The LLM responds, the tools fire, the output looks great.</p> <p>Then you push it to production — and everything breaks.</p> <p>API calls fail

<p>Your agent passed all the tests. It's been running in production for three weeks. And it has been quietly wrong the entire time.</p> <p>This is not a hypothetical. Galileo's