From Prompt Engineer to AI Manager: Why Your Agents Keep Breaking
Your AI agent says it's done. It's not done. It drifted off-task. It failed silently. You rewrote the prompt. Again.
Sound familiar?
Here's what most founders miss: AI agents don't have a prompt problem. They have a management problem.
In this 45-minute session, Sid Mathur shares the hard lessons from building Ashley, an AI executive agent that must act reliably in the real world—and why those lessons led him to build FRAIM, a platform for managing AI agents the way you'd manage people.
What You'll Learn
Why agents fail like junior employees
They claim work is done when it isn't
They drift off-scope mid-task
They fail silently and don't escalate
They need oversight, not just better instructions
The real culprits: async execution, timeouts, partial completion Most agent breakdowns happen in the gaps between tasks. Learn how to design workflows that account for this reality instead of ignoring it.
Management principles that actually work Scope. Verification. Escalation. Accountability. The same principles that work for teams work for agents—once you stop treating them like code.
Why human-in-the-loop makes you faster, not slower Strategic checkpoints increase trust and speed. You'll see exactly where and why.
Real examples from building in production Concrete breakdowns, design decisions, and trade-offs from someone who's shipped AI products in the real world.
Who This Is For
Founders building AI products who keep rewriting prompts hoping agents will "just work." Spoiler: they won't—until you manage them like team members.
About Sid
Sid Mathur is a founder and former senior product leader with two decades building complex software systems. While building Ashley, he hit the same agent reliability wall most founders hit—and built FRAIM to solve it.
Spring 2026 cohort starts April 22. Apply at fi.co/seattle
👉 Stop prompt debugging. Start managing agents.