Quick Answer
Vibe coding works when you have a system. Use Cursor if you want a visual IDE with checkpoints and rules files. Use Claude Code if you want terminal-first agentic coding with CLAUDE.md, skills, and hooks. Either way, commit to git before every AI interaction, learn to reset at three scales (undo, stash, branch), and build your instruction files early. The tooling finally caught up to the hype.
Andrej Karpathy coined “vibe coding” in early 2025. By the end of the year, 92% of US developers were using AI coding tools daily and the term was Collins Dictionary’s Word of the Year. The market hit $4.7 billion. Everyone wrote a “10 tips for vibe coding” article, and most of them said the same things: write good prompts, break tasks into small steps, test your code.
That advice is fine. It is also not enough. The vibe coding best practices that separate productive developers from frustrated ones are about tooling strategy, not prompting technique. Which editor paradigm fits your workflow? How do you configure persistent instructions so you stop repeating yourself? What do you do when the AI goes off the rails and you need to reset? This guide covers the real strategies, in depth, with specifics.
In This Guide
The Two Paradigms: IDE vs Terminal
There are two dominant ways to vibe code in 2026, and they are fundamentally different philosophies, not just different products.
Cursor is the IDE-first approach. It is a fork of VS Code with AI wired into every interaction. You see your code, your file tree, your terminal, and the AI side by side. Tab completions, inline edits, and full agent mode all happen inside the editor. If you are a visual person who wants to watch changes happen in real time, Cursor is your tool. We have a full comparison between Cursor and Claude Code if you want the head-to-head breakdown.
Claude Code is the terminal-first approach. You run claude in your project directory and interact through text. Claude reads files, edits code, runs commands, searches the web, and manages git, all through an agentic loop that cycles between gathering context, taking action, and verifying results. No GUI. No inline previews. Just you, your terminal, and an agent that can touch anything on your system.
Neither is better. They optimize for different things. Cursor gives you visual feedback and granular control at each step. Claude Code gives you autonomy and deeper system access. Some developers use both depending on the task. The important thing is to pick one, learn it well, and build your configuration files, because both tools get dramatically better once you tell them how you work.
Strategy 1: Cursor in Depth
Cursor gives you three levels of AI interaction, and using the right one for the right task is the difference between productive coding and fighting the tool.
Tab Completion
This is the passive layer. As you type, Cursor predicts what comes next. Not just the current line, but multi-line completions, auto-imports, and formatting. Press Tab to accept, Esc to reject, Cmd+Right Arrow to accept word by word. The September 2025 Tab model update cut suggestions by 21% but raised accept rates by 28%, which means fewer interruptions with better predictions. The trick is to write clear comments above your code. A comment like // validate email format and return error message gives the Tab model enough context to generate the entire function.
Inline Edit (Cmd+K)
Select code, press Cmd+K, type what you want changed. Cursor shows a colored diff preview. Cmd+Enter to accept, Cmd+Backspace to reject. This is the precision tool. Use it for refactoring a single function, adding error handling, or converting syntax. Do not use it for multi-file changes, that is what Agent mode is for.
Agent Mode (Cmd+I)
This is the real vibe coding interface. Press Cmd+I to open the Composer. In Agent mode (the default), Cursor works autonomously. It decides which files to create or edit, makes architectural decisions, runs terminal commands, and keeps going until the task is done or it hits the 25-tool-call limit per turn.
Cursor 2.0 (released October 2025) changed the game here. The Composer model is a custom mixture-of-experts model that generates at 250 tokens per second, completing most tasks in under 30 seconds. You can run up to 8 agents in parallel using git worktrees for isolation. Background agents run on isolated Ubuntu VMs and automatically create pull requests when they finish.
The best workflow pattern: start in Ask mode (Cmd+L) to plan. Ask a reasoning model like o3 to generate a step-by-step plan for your feature. Then switch to Agent mode and feed it the plan. Planning and execution are separate skills, and using separate models for each gets better results than asking one model to do both.
Context with @ Symbols
Type @ in any Cursor AI input to reference context. @filename points to a specific file. @codebase searches your entire project. @web searches the internet. @docs references indexed documentation. The recommended split is @codebase 60% of the time, @files 30%, others 10%. Also set up a .cursorignore file to exclude node_modules, build directories, and other noise. It can reduce indexing time from 5 minutes to 30 seconds and speed up AI queries by 61%.
YOLO Mode
Under Settings > Features, YOLO mode lets the agent auto-run terminal commands without asking for confirmation. You can set allow lists (e.g., vitest, npm test, tsc) and deny lists. When configured properly, the agent iterates on code until tests pass without needing you to approve every command. Use this only in sandboxed environments or with a solid git safety net. Reports of Cursor going rogue in YOLO mode are real, and Backslash Security demonstrated in 2025 that safeguards can be bypassed.
Cursor Rules: Teaching Your Editor How You Work
The old .cursorrules file (one monolithic file in the project root) is deprecated. The new system uses .cursor/rules/*.mdc files with YAML frontmatter. This is one of the most underused features in Cursor, and it is the biggest lever for improving AI output quality.
Each .mdc file has two parts: YAML frontmatter that controls when the rule activates, and a markdown body with the actual instructions.
The frontmatter has three fields. description is a human-readable summary that the AI reads to decide whether to include the rule. globs is a file pattern (like *.ts,*.tsx) for auto-attachment. alwaysApply is a boolean that forces the rule into every conversation.
These fields create four activation modes:
| Mode | Config | When It Loads |
|---|---|---|
| Always | alwaysApply: true | Every conversation |
| Auto Attached | globs: "*.ts" | When referenced files match the pattern |
| Agent Requested | description only, no globs | AI reads the description and decides |
| Manual | No globs, no alwaysApply | Only when you type @rule-name |
A practical setup: create an always-applied rule for project conventions (TypeScript strict mode, no console.log in production). Create auto-attached rules for React component patterns that trigger on src/components/**/*.tsx. Create an agent-requested rule for testing patterns that the AI pulls in when it detects test-related work. Keep each rule under 500 lines, use kebab-case filenames, and commit them to version control so your whole team benefits.
To find pre-built rules for your stack, check cursor.directory/rules and the awesome-cursorrules GitHub repo. If you find yourself repeating a prompt, it should be a rule instead.
Strategy 2: Claude Code in Depth
Claude Code is not an IDE extension. It is a standalone terminal agent. Run claude in your project directory and you get an interactive session where Claude can read files, edit code, run shell commands, search the web, and manage git. Everything happens through a three-phase agentic loop: gather context, take action, verify results.
The terminal-first approach has specific advantages. Claude Code sees your entire project, not just the current file. It can coordinate edits across dozens of files in a single turn. It has direct access to your terminal, so it can install packages, run tests, start servers, and commit code without you switching windows. It is also headless-capable: claude -p "prompt" runs a task without the interactive interface, which means you can script it into CI pipelines, git hooks, and automation workflows.
Permission Modes
Press Shift+Tab to cycle through three modes. Default asks before edits and commands. Auto-accept edits handles file changes without asking but still prompts for shell commands. Plan mode is read-only. This lets you calibrate how much autonomy you give the agent per session.
Session Management
Sessions persist locally. claude --continue resumes your most recent session. claude --resume opens a picker. /rename labels sessions for later (“oauth-migration”, “debugging-memory-leak”). /clear wipes the context window between unrelated tasks. /compact summarizes older messages to free up context without losing important information. Good context management is the single most important skill for productive Claude Code use.
Subagents
Claude Code can spawn subagents that run in their own context windows and report back summaries. This is powerful for parallel work: send one subagent to research a library, another to explore a codebase, another to draft tests, all running simultaneously while your main session stays clean. The Task tool handles this, and you can create custom agent types in .claude/agents/ with scoped tool access.
CLAUDE.md: Your Agent’s Memory
CLAUDE.md is a markdown file that Claude Code reads at the start of every session. It is the equivalent of Cursor rules but for the terminal workflow. The difference: CLAUDE.md supports a hierarchy of files that layer on top of each other.
| Level | Location | Shared With |
|---|---|---|
| Managed policy | /Library/Application Support/ClaudeCode/CLAUDE.md | All users in org |
| Project | ./CLAUDE.md | Team (via git) |
| Project rules | .claude/rules/*.md | Team (via git) |
| User | ~/.claude/CLAUDE.md | Just you (all projects) |
| Local | ./CLAUDE.local.md | Just you (this project) |
| Auto memory | ~/.claude/projects/<project>/memory/ | Just you (auto-saved) |
More specific files take precedence over broader ones. CLAUDE.md files can import other files with @path/to/file syntax (recursing up to 5 levels), so you can reference your README, package.json, or team docs without duplicating content.
What goes in CLAUDE.md: build commands Claude cannot guess, code style rules that differ from defaults, testing instructions, repository conventions, and gotchas specific to your project. What does not belong: anything Claude can figure out by reading code, standard language conventions, or long tutorials. The best CLAUDE.md files are under 300 lines. If Claude keeps ignoring a rule, the file is probably too long and the instruction is getting lost in noise.
Run /init in your project to generate a starter CLAUDE.md. Then edit it manually. This is your highest-leverage configuration point. Spend time on it.
Skills: Extending What Your Agent Can Do
Skills are one of the most powerful and least-known features in Claude Code. A skill is a directory with a SKILL.md file containing instructions that Claude loads when relevant. Think of them as reusable prompt templates with superpowers: they can include supporting files, scripts, and dynamic context injection.
How Skills Work
Skills live in three places: ~/.claude/skills/ (personal, all projects), .claude/skills/ (project-specific), and plugin directories. Each skill directory has a SKILL.md file with YAML frontmatter and markdown instructions.
The frontmatter controls behavior. name sets the slash command (/my-skill). description tells Claude when to auto-invoke the skill. allowed-tools restricts which tools the skill can use. context: fork runs the skill in a subagent with its own context window. You can even set model: opus to override the model for a specific skill.
A skill can reference dynamic context with the !command` syntax. For example, a PR review skill might include !gh pr diff` in its body. When the skill loads, that command runs and the output replaces the placeholder. Claude receives the fully-rendered prompt with live data.
Finding Skills
The awesome-claude-skills repository (7.3K stars) is the primary community hub. Anthropic also ships official skills for document handling (docx, pdf, pptx, xlsx), frontend design, web artifacts, and skill creation itself. You can install community skill collections as plugins with /plugin add.
Making Your Own Skills
Create a directory under ~/.claude/skills/my-skill/ and add a SKILL.md file. Start simple:
Save it and type /commit-review in Claude Code. You can add supporting files to the skill directory (templates, example outputs, validation scripts). Keep SKILL.md under 500 lines and put detailed reference material in separate files.
The real power shows up when you combine skills with hooks. Claude Code has 14 lifecycle events (SessionStart, PreToolUse, PostToolUse, Stop, etc.) where you can trigger shell commands, prompt evaluations, or even subagents. A PostToolUse hook on Edit/Write can auto-run Prettier after every file change. A PreToolUse hook on Bash can block destructive commands. A Stop hook can verify that all tasks are complete before Claude finishes. These are deterministic, not advisory, so they always fire.
The Reset Hierarchy: Micro, Meso, Macro
Every experienced vibe coder has learned this the hard way: AI goes off the rails. Regularly. The skill that separates productive developers from frustrated ones is knowing how to reset at the right scale. There are three levels.
Micro: Tool-Level Undo
This is your immediate “oops” button. In Cursor, checkpoints are created automatically before every Agent mode edit. Click “Restore Checkpoint” in the chat panel to roll back. The limitation: third-party testing found checkpoint restore only has an 8% success rate in some Cursor versions. Cmd+Z (standard undo) works 98% of the time but is linear, you cannot jump to a specific point.
In Claude Code, press Esc twice or type /rewind. You get three options: rewind conversation only (keep code), rewind code only (keep conversation), or rewind both. The community tool ccundo adds granular file-level undo by reading Claude Code’s session files directly.
Micro resets are for catching mistakes in the last few seconds. Do not rely on them as your safety net.
Meso: Git Stash and Reset Within a Branch
This is the workhorse level. The pattern is simple and it should become muscle memory:
Commit before every AI interaction. Not every hour, not at milestones. Every single time you are about to let an agent touch your code. If Agent mode edits 30 files and breaks your project, manually restoring is nearly impossible. git reset --hard gets you back to the starting point in one command.
git stash is useful when the AI has made partial progress you want to preserve while trying a different approach. Stash the current state, try the alternative, and git stash pop to bring back the original attempt if the alternative fails. git add -p lets you selectively stage changes hunk by hunk, keeping the good parts of an AI’s output while discarding the bad.
The community consensus is to commit every 10-15 minutes during active AI-assisted coding. Some developers use timestamped commits: git add -A && git commit -m "pre-agent-$(date +%s)" to create unique checkpoints before every agent invocation.
Macro: Branch, Explore, Reset
This is the most powerful strategy and the one most vibe coders underuse. When you want to try something ambitious, do not do it on your main branch.
The branch-and-reset strategy lets you be aggressive. Tell the agent to refactor the entire module. Let it try the risky approach. If it works, merge. If not, the branch is gone and main is untouched. You lost nothing.
Even better: git cherry-pick lets you rescue individual good commits from a failed branch. Log the branch with git log --oneline, find the commits worth keeping, cherry-pick them onto main, and delete the rest. Not every experiment is a total loss.
For parallel exploration, git worktrees let you run multiple branches simultaneously in separate directories. Create a worktree per experiment, run a separate AI agent in each, and compare results. Incident.io reportedly runs four or five parallel Claude agents this way as part of their standard workflow.
Going Autonomous: OpenClaw and TinyClaw
Once you are comfortable with the reset hierarchy and your instruction files are dialed in, the next step is letting your agent run without you watching.
OpenClaw (209K GitHub stars) is the project that kicked off the autonomous agent movement. Created by Peter Steinberger, it is an open-source AI agent that connects to 13+ messaging platforms (WhatsApp, Telegram, Discord, Slack, Signal, and more). Text it a task from your phone and it executes autonomously. It supports voice commands, browser automation, cron jobs, and has its own skills registry called ClawHub. The architecture is sophisticated: a WebSocket gateway, session management with vector-embedded memory, and Docker-based sandboxing for safety.
OpenClaw’s downside is complexity. It is a large framework, and users report frequent breakage during updates.
Our recommendation is TinyClaw. Created by Jian Liao, it started as OpenClaw rebuilt in about 400 lines of code. The key difference: TinyClaw wraps Claude Code directly from the CLI (claude --dangerously-skip-permissions -c -p), so it uses your existing Claude Code subscription with no separate API keys or OAuth setup. All the intelligence comes from Claude Code itself. TinyClaw just handles the messaging layer, queue management, and agent coordination.
We run TinyClaw ourselves. The file-based queue system (incoming, processing, outgoing directories) is dead simple. Messages come in from Discord, Telegram, or WhatsApp, get processed by Claude Code agents with isolated workspaces, and responses go back out. The whole thing runs in a tmux session.
What sold us on TinyClaw is how easy it is to modify. The codebase is small enough to read in a lunch break. We added a hook and plugin system ourselves, built a visualization layer, and customized the agent routing. Try doing that with a 200K-star framework. Jian Liao reported it running for 3+ days with zero maintenance, fixing and restarting itself when things went wrong. That tracks with our experience.
If you are curious about what AI tools can do for game development specifically, we cover that in a separate guide.
Frequently Asked Questions
What is the best vibe coding tool for beginners?
Cursor. The visual interface makes it easier to understand what the AI is doing. Start with Tab completion and Cmd+K inline edits before moving to Agent mode. Claude Code’s terminal-first approach has a steeper learning curve but more power once you learn it.
Should I use Cursor or Claude Code?
It depends on how you prefer to work. If you think visually and want to see changes as diffs in an editor, use Cursor. If you are comfortable in the terminal and want deeper system access with scripting capabilities, use Claude Code. Some developers use both: Cursor for frontend work where visual feedback matters, Claude Code for backend tasks and automation.
Is git required for vibe coding?
Technically no. Practically, yes. Without git, a bad AI edit to 30 files means manual restoration or starting over. With git, it is one command: git reset --hard. Commit before every AI interaction. This is non-negotiable advice from every experienced vibe coder.
Can non-developers use vibe coding to build apps?
Yes, with limits. Tools like Cursor and Replit Agent can build working prototypes from natural language descriptions. But you will hit walls when things break, because debugging requires understanding what the code does. The best approach for non-developers: learn basic git (init, commit, reset), learn how to read error messages, and keep each AI task small enough to test immediately.
What do I do when the AI goes completely off track?
Stop it immediately (Esc in both Cursor and Claude Code). Do not let it keep going hoping it will fix itself. Check git diff to see what changed. If the changes are salvageable, selectively stage with git add -p. If not, git reset --hard and re-prompt with clearer, more constrained instructions. Common fixes: break the task into smaller pieces, reference specific files with @ mentions, or explicitly tell the AI what not to do.
The Bottom Line
Vibe coding is not about finding the perfect prompt. It is about building a system: the right tool for your workflow, instruction files that teach the AI how you work, and a reset strategy for when things go wrong. Pick Cursor or Claude Code and learn it deeply. Write your rules files or CLAUDE.md early. Commit to git obsessively. Learn to reset at every scale. And when you are ready, let your agent run unsupervised with something like TinyClaw.
The developers who are productive with AI coding tools in 2026 are not the ones with the best prompts. They are the ones with the best systems. Build yours.