Is anyone else feeling the "AI agent hangover"?
We are dumping millions into raw model intelligence, expecting that a "smarter prompt" or a larger context window will magically run a smarter business.
It won't.
Right now, running AI agents in an enterprise environment is an architectural nightmare. It looks like microservices scattered across separate cloud accounts, random tools, unmonitored logs, and disjointed permissions.
Without a single control plane.
We keep confusing concurrency with organization. Running four agents in a single chat window or a script doesn’t make them a team. It just scales the fragmentation and turns the human operator into an overloaded, manual operating system trying to stitch pieces together.
We are officially in the pre-Kubernetes phase of AI.
Intelligence is everywhere. Orchestration is nowhere.
If agents are the new digital workforce, they can't remain homeless. They need structure. They need a workplace where they actually perform with identity, secure VM workstations, and persistent memory.
That is why we are building Aeon Neon https://aeonneon.com/ the Industrial Base for the AI Economy. Not another prompt wrapper, but an operating infrastructure.
But I want to know how this looks on your battlefield.�
Let’s open the floor:
1 What is the biggest bottleneck keeping your agents from full-scale production? Identity, infrastructure, or memory?
2 What is the most "expensive" or absurd mistake an unmanaged AI agent has made (or almost made) in your current setup?
Let’s talk in the comments