How To Build Agentic Coding Workflows with Cursor

The Problem with Ad-hoc AI Prompting

Most developers use AI assistants reactively — type a prompt, get some code, repeat. This works for one-off tasks, but it doesn't scale. Every session starts from scratch, context gets lost, and quality is inconsistent.

Agentic workflows fix this by encoding your intent once and letting the agent execute reliably every time.

The Three Primitives: Rules, Commands, and Skills

Cursor gives you three building blocks. Understanding what each one is for matters before you combine them.

• Rules (.cursor/rules/) — Always-on constraints. The agent reads these automatically on every task. Use them for coding standards, architecture decisions, and things that must always be true.
• Commands (.cursor/commands/) — Explicit, triggered workflows. You call them with /command-name. Use them for multi-step tasks like creating a post, scaffolding a feature, or running a release checklist.
• Skills — Portable playbooks available when the task calls for them. Unlike commands, they're not explicitly triggered — the agent discovers and uses them as needed.

Each layer has a different activation model. Mixing them up leads to noise or missed context.

How I Structure My Commands

How I Use Rules to Shape Every Response

A Real Workflow End-to-End

What Makes a Workflow Reliable

Conclusion