If your team is only using AI as a glorified autocomplete in a chat window, you are missing 90% of the value. The real leverage comes from building agentic workflows.
What is an Agentic Workflow?
Unlike a standard prompt where you ask a question and get a single response, an agentic workflow breaks a complex problem into smaller, sequential tasks. The AI acts as an autonomous “agent” that can plan, execute, evaluate its own work, and correct mistakes before showing you the final output.
The Four Design Patterns
- Reflection: Having the AI critique its own output and self-correct.
- Tool Use: Giving the AI access to web search, code execution, or internal APIs.
- Planning: Asking the AI to create a step-by-step plan before generating the final deliverable.
- Multi-agent Collaboration: Using different AI personas (e.g., a “Writer” agent and an “Editor” agent) to debate and refine work.
Why PMs Need This
Product Managers are uniquely positioned to design these workflows because PMs already know how to map out business processes and state machines. An agentic workflow is essentially just a highly defined operational process where the “worker” happens to be an LLM.
Instead of manually writing user stories, imagine a workflow that pulls customer feedback from Zendesk, categorizes the pain points, drafts initial PRD sections, and flags edge cases for your review. That’s the power of moving from prompting to operating.