# Cursor Features and Practical Usage 🧭 Code now, plan first, or just investigate? Cursor lets you switch the agent's behavior with a single `Shift+Tab`. 🏷️ Title: Agent Modes (Shift+Tab) 🔗 URL: 📘 Overview Cursor's agent has multiple modes so its behavior matches the task at hand. Press `Shift+Tab` in the chat input to rotate through modes, or pick one from the mode dropdown. When Cursor detects complex work, it may automatically suggest Plan mode. ⚙️ How It Works ・Agent mode: the standard implementation mode. Best for quick changes or familiar tasks where jumping straight into code makes sense. ・Plan mode: builds a plan before coding. The agent asks clarifying questions to understand requirements, researches your codebase to gather context, and generates a comprehensive plan for review. The workflow is: Questions → Research → Plan Creation → Review/Edit → Build. ・The plan is editable in chat or as markdown, and you proceed to build only once satisfied. Plans save to your home directory by default, but you can move them into the workspace for team collaboration. 🛠️ Practical Usage ・For features that ripple across many files, generate a plan in Plan mode, approve it, then implement — this minimizes rework. ・When you only want to investigate, use a read-only style mode and ask "How does this auth flow work?" to understand the current state without edits. ・For debugging, paste the stack trace or logs and walk through hypothesis generation → root-cause identification → fix strategy for steadier diagnosis. ・Use `Shift+Tab` to cycle modes quickly and match the granularity of the task. 💡 Use Cases Approve the big picture in Plan mode before a large refactor, investigate safely in a read-only mode, and pin down bugs from a pasted error to root cause. Splitting work into phases keeps the scope you delegate to the AI under control. ⚠️ Caveats The docs stress a key principle: when the agent's output misses the mark, reverting the changes and refining the plan is often faster than chasing fixes with follow-up prompts. Figuring out what to change is the hard part — delegate the implementation to Agent. #Cursor# #AICoding#