cursor / session — refactor_auth.ts
Watch a diff rewrite itself, then learn why.
- if(auth && token){…}
+ if(validSession(user)){…}
Cursor AI course
Can Cursor speed up your edits without hiding them?
This Cursor AI course teaches context-aware editing inside real files — inline changes, chat over your codebase, and quick refactors resolving in real time with tests nearby. Cambridge evenings and live online cohorts available.
bench reading — one file open, one diff resolving, review never leaves the screen
Where it fits
Where Cursor fits in your day
Cursor fits the hours spent inside open files: fixing, renaming, reshaping, clarifying. In this AI coding training you learn which jobs belong inline and which belong in chat, so suggestions stay relevant and small. To Learn Cursor AI is to learn that split.
inline_rewrite.ts
quick rewrites at cursor
stays in file
chat_over_repo.md
broader questions
files attached
rename_scope.ts
rename and reshape
small diffs
setting_context.ts — choose on purpose
Setting context
Setting context on purpose
The core skill is choosing context: current function, linked files, or recent changes. Too little and the suggestion guesses; too much and it wanders. You practice attaching symbols and excluding noisy directories until smaller, sharper context becomes habit.
- — attach the function, not the folder
- — exclude generated output and vendor noise
- — re-scope when the draft starts to wander
the exchange turns here — from selecting context to proving the change
refactor_with_tests.ts — one move at a time
Refactor safely
Refactoring with tests beside you
Refactors run in short moves with the test file open. Rename, extract method, move code, rerun. You ask for one transformation at a time and read the result before the next, and instructors show how to roll back a single hunk without losing the rest. Version control stays part of every exercise in these AI coding courses.
Two full sessions take on an unfamiliar module with thin tests: map callers, add a characterization test, then refactor with assistance. Slower than greenfield work by design, and reusable on your own codebase the next week.
Inside the editor
Debugging inside the editor
You debug with breakpoints, logs, and the failing test in view. The assistant suggests causes tied to the lines you selected, and you confirm by running code.
We spend time on wrong guesses: how they sound, how to spot them, how to re-scope. A short debugging log becomes part of your submitted work.
Review habits — what the course grades
SDLC habits: review, commit, handoff
AI-assisted code still moves through review. You write commit messages that state what the assistant drafted and what you verified. Pull request descriptions name tests run and files touched, so Learn AI-powered development stays visible to the team.
Some decisions stay manual: API boundaries, data handling, security-sensitive logic. We name those cases explicitly and show how to tell the assistant to propose rather than apply. Saying no to a suggestion counts as good work.
What stays manual
API shape, data use, and sensitive paths stay yours. Review discipline counts toward completion.
Logistics
Bring your laptop. In Cambridge at 77 Massachusetts Ave you work in pairs at shared benches; online you share screens in small rooms. Schedules: +1-617-253-1000.
Faster edits, still your eyes on every line.
This Cursor AI course sits inside our wider AI coding training alongside the Claude Code course and the OpenAI Codex course. If you want to Learn Claude Code or Learn OpenAI Codex next, the same review habits carry over.
You leave with a routine: select sharp context, draft small, run tests, write down what you verified. That routine is what managers see in the pull request.
Experienced engineers fit well here. Exercises assume fluency with your language and tests, and focus on context selection, refactor safety, and handoff — not on typing speed.
failing test — passing diff — one session
review graded, not acceptance speed · 77 Massachusetts Ave + live online
Before you join
Questions engineers ask first
Short answers. Longer ones live in the syllabus and in the team session call.
Will Cursor replace careful reading of code?—
No. It drafts and locates quickly, but you still read diffs and run tests. The course grades review habits, not acceptance speed.
Is this suitable for experienced engineers?+
Yes. The exercises assume fluency with your language and tests, and focus on context selection, refactor safety, and SDLC handoff.
AI Code Pathway Academy · 77 Massachusetts Ave, Cambridge, MA 02139 · +1-617-253-1000 · Contact