Dev.to
7/16/2026
Building a multi-vendor AI agent control plane: lessons and doubts from a solo developer
Original: I rewrote my AI-agent tool from Bash to Python. That was the easy doubt.
Short summary
A developer shares lessons from building Docket, a Python-based control plane for running OpenClaw AI agent fleets across projects. The real challenges weren't the Bash-to-Python rewrite but deeper doubts: whether a control plane makes sense for a solo developer, whether first-party tools from OpenAI and Anthropic obviate the need, and how to test non-deterministic agent behavior. The niche is multi-vendor agent orchestration with governance and budget controls.
- •Docket is a Python control plane for running multi-model AI agent pods across projects
- •Author questions whether solo developers need Kubernetes-shaped orchestration for agent fleets
- •Niche: mixed-vendor agent orchestration with spend caps and approval gates that walled-garden tools don't offer
Generated with AI, which can make mistakes.
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