This article introduces Agentic Experience (AX) Design, a new field focused on mapping and automating business workflows for autonomous AI agents rather than humans. It outlines the AX designer’s role—investigating real processes, structuring machine-readable systems, and defining guardrails—to ensure reliable, scalable automation.

• AX design shifts the "user" from humans to autonomous AI agents, requiring workflow maps, feasibility studies, and failure-state definitions instead of wireframes and personas.
• The three AX roles—Detective, Enabler, Builder—cover uncovering real (not documented) processes, building agent-readable infrastructure, and setting success/failure guardrails for unsupervised runs.
• When companies rush to deploy agents, the bottleneck is usually undocumented or flawed underlying processes, not the AI technology itself.
• Some workflows are too variable, legally sensitive, or costly to automate, so part of the job is deciding whether a process should be handed to an agent at all.

The Compounding Engineering plugin enhances development workflows by systematically improving the planning, execution, and review stages of coding. It leverages AI to create comprehensive issues, manage isolated tasks, and conduct thorough code reviews, ensuring that each unit of engineering work makes future tasks easier. By documenting processes and refining quality, this tool aims to build a more efficient development system over time.

• Turns Claude Code into a workflow that ties planning, coding, and review into one system rather than three separate steps
• Uses AI to generate detailed issues and manage isolated tasks, aiming to reduce ambiguity before code gets written
• Automates thorough code reviews as part of the pipeline, not just execution
• Core philosophy is "compounding" - each piece of work is meant to make future engineering tasks easier rather than adding one-off effort