The workflow collision
The article discusses the conflicting workflows between human teams and AI agents. It highlights how team workflows prioritize self-organization and flexibility, while AI agent lifecycles enforce strict planning and control. The differences in trust, planning, state management, and failure perception create challenges when integrating both systems.
- ▪Team workflows typically use a pull-based Kanban system that allows members to self-organize and choose their tasks.
- ▪AI agent lifecycles require operator initiation for tasks and enforce strict planning and review processes to ensure security and compliance.
- ▪The contrasting approaches to planning and failure highlight the incompatibility of human and AI workflows when applied to the same tasks.
Opening excerpt (first ~120 words) tap to expand
The Workflow CollisionYour team's workflow and your agent's lifecycle want different thingsMay 17, 2026 · 6 min · Sean EscrivaA collision is coming that most teams have not noticed yet.On one side you have the workflow your team actually uses. If you run a platform or operations team, it probably looks something like Kanban: pull-based flow, WIP limits, design sessions before implementation, a small number of states that everyone understands. The workflow exists to serve the people. You have spent years tuning it. It works.On the other side you have the lifecycle your AI agent needs.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Webframp.
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