NEWS · CODING · #86
How canvases make agentic workflows visible, steerable, and cost-efficient
A GitHub AI & ML blog post describes using canvases to surface, direct, and reduce the cost of agentic (multi-step AI agent) workflows, arguing that canvas-based views avoid the visibility and control loss that can occur in chat-based interfaces. The author explains how they apply canvases to their own agentic workflows and why other teams might benefit from the approach.
KEY POINTS
- A GitHub AI & ML blog post describes using canvases to surface, direct, and reduce the cost of agentic (multi-step AI agent) workflows, arguing that canvas-based views avoid the visibility and control loss that can occur in chat-based interfaces.
- The author explains how they apply canvases to their own agentic workflows and why other teams might benefit from the approach.
- Tooling that makes agent behaviour visible and steerable can improve developer oversight and cost control for agent-based automations, affecting how teams design AI workflows.
WHY IT MATTERS
Tooling that makes agent behaviour visible and steerable can improve developer oversight and cost control for agent-based automations, affecting how teams design AI workflows.