Why Agent Orchestration Is the Next Platform Shift
AI agents are moving from chat interfaces to always-on background workers. Here's why orchestration matters.
Every major computing era has had its platform layer. VMs had VMware. Containers had Kubernetes. Serverless had AWS Lambda. AI agents will have orchestration platforms.
The Shift from Chat to Background Workers
The first wave of AI was chat-based. You talk to a model, it responds. Useful, but limited.
The next wave is agents — AI systems that run autonomously in the background, completing tasks without human intervention. They monitor your GitHub repos, manage customer tickets, process data pipelines, and coordinate complex multi-step workflows.
Why Orchestration Matters
Running one agent is easy. Running dozens — each with different runtimes, integrations, and monitoring needs — is an infrastructure challenge. That's where orchestration comes in.
Agent orchestration handles:
The Parallel to Kubernetes
Just as Kubernetes abstracted away container management, agent orchestration abstracts away the complexity of running AI agents at scale. Teams shouldn't need to become infrastructure experts to deploy a code review bot.
What This Means for Teams
Teams that adopt agent orchestration early will move faster. Instead of spending weeks on infrastructure, they'll deploy agents in minutes and iterate on what matters — the agent's behavior, integrations, and impact.
The infrastructure layer for agents is being built right now. We're building it at Padiso.