Software Development with Cursor
Learn to use Cursor’s modes, rules, context prompts and agents to refactor, test, debug and manage Git in an AI code editor.
Cursor is a code editor built around an AI assistant. The lessons treat coding with AI as a loop in which the developer sets rules, supplies context and checks what comes back. Topics include picking the right mode for a task, grounding prompts in specific files, handing changes across a project to agents, and keeping version control and privacy in order along the way.
What You Will Achieve
- Pick between inline edits and Agent Mode depending on how large a coding task is
- Steer Cursor toward accurate output with @ references, slash commands and project rules
- Carry out a refactor that spans several files, write tests before the code and debug with precise context
- Commit code with Git, resolve merge conflicts with AI help and automate routine work with custom commands
Program Overview
Cursor Foundations: Modes, Agents, and Rules
How the developer and AI work together in Cursor, how to pick a mode or Agent feature, and how rules shape the assistant’s memory.
- First setup and how Cursor changes the code editor
- The developer–AI collaboration loop
- Choosing modes and Agent features
- Writing and validating Cursor rules
Prompting, Refactoring, Testing, and Debugging
Prompts grounded in context, changes spread across many files, and a test-first habit backed by the Cursor Agent and Cursor Browser.
- Context-rich prompts, @ references and slash commands
- Multi-file refactors and reviewing the changes
- Testing with the Cursor Agent and Cursor Browser
- Debugging with clear context
Git, Privacy, Automation, and Large Codebases
Version control and privacy settings inside the editor, then automation and scale through custom commands, Composer, Max Mode and MCP servers.
- Committing, syncing and AI-assisted merge conflicts
- Privacy settings and controlling what code you share
- Custom commands, the Agent Window and parallel agents with Composer
- Max Mode and MCP servers for complex codebases
Certificate Awarded (Paid)
Job Outlook
An AI code editor fits into everyday software development work: building features, refactoring shared code, writing tests, debugging, and managing changes in Git on personal or team projects.
Good for: Programmers adopting Cursor who want a clear routine for prompting, multi-file changes, testing and Git work inside the editor.
Keep in mind: Despite the intermediate label it teaches Cursor from the ground up, and every lesson is built on Cursor’s own features, so the methods center on this one editor.
Bottom line: A Cursor course that gives as much attention to rules, context and parallel agents as to everyday edits.
Frequently Asked Questions
What does the Cursor Agent do in these lessons?
The agent takes on multi-step work such as full-featured builds and refactors that span several files. The lessons show when to hand a task to it, how to review the changes it makes across files, and how to use it for testing.
What role do Cursor rules play?
Rules are standing instructions that shape what the assistant remembers about a project and how it responds. The first chapter has you create rules for an application and sort valid rules from invalid ones.
How are MCP servers used in the course?
In the final chapter, MCP servers are connected to give Cursor more context when working on complex codebases. They appear alongside Max Mode, which expands how much of a project the assistant can take into account.
Which privacy and security steps are covered?
The last chapter pairs Git work with privacy settings that control which code you share with the AI, as part of keeping projects secure while you commit, sync and resolve merge conflicts.
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