“The shift was quiet. They'd been using cursor for weeks, mostly out of obligation. Then multi-file editing with AI awareness solved a problem they'd been routing around — and suddenly the friction of suggestions that are confident and wrong — especially when they're wrong in subtle ways felt absurd. They couldn't go back.”
When I'm onboarding to a new codebase — a 150k-line python monolith they've never, I want to move through unfamiliar codebases at a speed that would have been impossible before, so I can use AI to handle the mechanical parts of coding so they can focus on the architectural decisions.
A software developer with 2–10 years of experience who switched to Cursor after a trial period and didn't go back. They've restructured how they code around the assumption that AI is in the loop. They write less boilerplate. They spend more time reviewing and directing than typing. They're faster on unfamiliar codebases than they've ever been. They're also developing opinions about when AI help hurts — about the kinds of errors that look right until they don't.
To move through unfamiliar codebases at a speed that would have been impossible before — reliably, without workarounds, and without becoming the team's single point of failure for cursor, leveraging AI-powered code completion with codebase context.
A software developer who trusts their setup. Move through unfamiliar codebases at a speed that would have been impossible before is reliable enough that they've stopped checking. Codebase-aware context that spans multiple files accurately reduces the. They've moved from configuring cursor to using it.
They're onboarding to a new codebase — a 150k-line Python monolith they've never seen before. They have a bug to fix. In VS Code this would take 90 minutes of reading. In Cursor they're going to ask it to explain the relevant module first, then walk through the data flow, then suggest the fix. They'll read the suggestion carefully. They'll accept 80% of it. They'll rewrite the part that's wrong in a way Cursor helped them understand how to write.
Uses Cursor as their primary IDE, replacing VS Code 3 months ago. Uses Claude and GPT-4 models depending on the task. Has keyboard shortcuts for Cmd+K and Cmd+L memorized as naturally as their old Vim bindings. Uses Cursor's codebase indexing for large repos. Works on Python and TypeScript primarily. Has a mental model of "when to prompt" vs. "when to just write" that they've built through trial and error. Has introduced Cursor to their team; adoption is split.
Two things you'd notice: they reference cursor in conversation without being asked, and they've built workflows on top of it that weren't in the original plan. Cmd+K inline editing with natural language has become part of their muscle memory. They're now focused on use AI to handle the mechanical parts of coding so they can focus on the architectural decisions — a sign the basics are solved.
Not a feature gap — a trust failure. Suggestions that are confident and wrong — especially when they're wrong in subtle ways happens at the worst possible moment, and cursor offers no path to resolution. The AI's confident-but-wrong completions slowed them down more than manual coding. Their belief — aI coding assistance is a skill, not just a feature — learning to use it well takes months — has been violated one too many times.
Pairs with `github-primary-user` for the full AI-assisted development to PR review workflow. Contrast with `vscode-primary-user` to map the AI-extended vs. AI-native IDE philosophy gap. Use with `senior-engineer-skeptic` antagonist for realistic team conversations about AI coding tool adoption.