Windsurf is an AI-native code editor from Codeium, built on VS Code’s foundation and designed around deep AI integration from the ground up. Released in November 2024, it quickly became one of the main alternatives to Cursor for developers who want an AI-first IDE rather than an AI extension bolted onto an existing editor. This guide covers what Windsurf offers, how to get started, and what you need to know to use it effectively for day-to-day development work.
What Makes Windsurf Different
Windsurf’s central design decision is that AI should be a first-class citizen of the coding experience, not a sidebar or a chat panel. The editor was built from scratch with AI integration in mind, even though it runs on VS Code’s codebase and inherits its extension compatibility. The result is that AI interactions feel more embedded than in a tool like VS Code with Copilot: the AI has native access to the full codebase, the terminal, and the ability to make multi-file edits in a way that feels integrated rather than bolted on. Windsurf’s agentic system, called Cascade, can be invoked for any task and works through a streaming interface that shows you each action the AI takes in real time — file reads, code edits, terminal commands, and test runs — with the ability to intervene at any step.
Installing and Setting Up Windsurf
Download Windsurf from the Codeium website (codeium.com/windsurf) for macOS, Windows, or Linux. The installer is straightforward and Windsurf launches into a setup flow that imports your VS Code settings, themes, and keybindings automatically — the goal is zero-friction migration from VS Code. You will need a Codeium account (free tier available) to activate the AI features. On the free tier you get a limited number of Cascade interactions per month, which is sufficient for evaluation. The Pro tier at $15/month removes the limit and adds access to more powerful models. After setup, open a project folder and Windsurf indexes the codebase automatically — this takes a few minutes for large projects and runs in the background without blocking your work.
Cascade: The Core Agentic Experience
Cascade is Windsurf’s agentic AI system, invoked from the AI panel on the right side of the editor. You describe a task in natural language — “add rate limiting to the authentication endpoints using Redis” — and Cascade works through it: reading the relevant files, understanding the existing architecture, making the necessary changes across multiple files, and running tests to verify the result. What distinguishes Cascade from similar systems is its step-by-step transparency. Rather than disappearing for 30 seconds and returning a batch of changes, Cascade shows you each action as it happens. You can see it reading your auth module, observe it writing the rate limiting middleware, watch it update the endpoint decorators, and track the test run. At any point you can add a message to redirect it: “actually, use a token bucket algorithm rather than fixed windows.” This real-time transparency makes the agentic experience feel collaborative rather than opaque.
Figure 1 — Windsurf feature overview
Writing Instructions Files
Like Cursor’s rules files, Windsurf supports a .windsurfrules file in the project root that provides persistent context to the AI. The content and structure are the same as a Cursor rules file: project description, tech stack, code style conventions, architecture constraints, and testing expectations. This file is read by Cascade at the start of every interaction and shapes the AI’s default behaviour throughout the session. For teams migrating from Cursor, the rules file can be copied directly — rename .cursorrules to .windsurfrules and the same context applies. If you work across both editors, maintaining both files (which can be identical) ensures consistent AI behaviour regardless of which tool is being used for a given session.
Model Selection in Windsurf
Windsurf supports multiple AI models, selectable from the model picker in the Cascade panel. The default Windsurf models (SWE-1, SWE-1-mini, SWE-1-lite) are fine-tuned versions of OpenAI models optimised specifically for software engineering tasks — they tend to produce more directly applicable code with fewer explanatory preambles than general-purpose models. Claude Sonnet and GPT-4o are also available for tasks where you prefer those models’ characteristics. The SWE models are generally the best starting point for standard coding tasks; switching to Claude is worth trying for tasks involving complex reasoning or when you want more detailed explanations of the generated approach. Model usage is counted against your Cascade credit allocation on the free and Pro tiers — more capable models use more credits per interaction.
Windsurf for Code Review and Explanation
Beyond agentic task completion, Windsurf’s AI is useful for code review and explanation. Select any block of code, right-click, and choose “Explain” to get a natural language description of what the code does. “Review” runs a code review focused on bugs, security issues, and style. These quick interactions are useful for understanding unfamiliar code in a large codebase, onboarding to a new project, or getting a fast sanity check before committing. The explanations are generated with the full codebase context available, which means the AI can reference how the selected code interacts with other parts of the project rather than analysing it in isolation — producing more useful explanations than a simple “what does this function do?” prompt in a context-free chat.
Managing Cascade Credits and Costs
On the free tier, Cascade interactions are limited to a small number per month — enough to evaluate the tool but not for daily professional use. The Pro tier at $15/month provides a generous monthly credit allocation that covers typical full-time developer usage. Credits are consumed per Cascade interaction, with more complex multi-step tasks consuming more credits than quick questions. To use credits efficiently: be specific in Cascade prompts so it completes tasks in fewer steps, use inline completion (which does not count against Cascade credits) for routine autocompletion, and reserve Cascade for the multi-step tasks where its agentic capability genuinely adds value. Single-question interactions are often better handled through the chat panel which has a separate, more generous credit pool than Cascade on the Pro plan.
Migrating from VS Code or Cursor
The migration experience from VS Code is genuinely smooth — Windsurf imports settings, extensions, and keybindings on first launch and most developers report feeling at home within minutes. The main friction points are extensions that depend on VS Code’s specific extension API internals, which occasionally need alternatives, and keybindings for Windsurf-specific features (Cascade invoke, accept/reject change) that need to be learned. From Cursor, the main adjustment is Cascade’s streaming presentation versus Composer’s diff-review approach — experienced Cursor users sometimes find the streaming model more distracting initially before appreciating its transparency. Give yourself a week of real project work before forming a firm opinion on the UX difference; first impressions of unfamiliar interaction patterns often reverse with familiarity.
Windsurf for Teams
Windsurf Teams (available at higher price tiers) adds organisation-level features: centralised billing, usage dashboards, private model access, and admin controls over which models team members can use. For teams standardising on an AI IDE, the centralised administration makes Windsurf Teams more manageable than individual Pro subscriptions. The .windsurfrules file committed to the repository ensures all team members work with consistent AI context — a significant benefit in a team setting where different developers might otherwise give the AI different instructions and produce inconsistent output. Security-conscious organisations can configure Windsurf Teams to disable code snippet telemetry, ensuring that proprietary code does not contribute to model training.
Windsurf is a mature, well-designed AI-native IDE that is a genuine alternative to Cursor for developers who want deep AI integration in their coding workflow. Its distinguishing strengths are Cascade’s transparent streaming approach, the SWE-tuned models optimised for software engineering tasks, the smooth migration from VS Code, and a lower price point than Cursor. Start with the free tier, spend a week using Cascade on real project tasks, and compare the experience to whatever tool you currently use. The best AI coding tool is the one that fits how you actually work — and Windsurf’s approach resonates strongly with developers who value visibility into what the AI is doing at each step.
Keyboard Shortcuts Worth Learning
A handful of Windsurf-specific keyboard shortcuts significantly speed up the workflow once internalised. The primary Cascade invoke shortcut (Cmd+L on macOS, Ctrl+L on Windows/Linux) opens the Cascade panel ready for input. Cmd+I triggers inline editing — a lightweight AI edit mode that applies a change to a selected block of code without opening the full Cascade panel, useful for quick targeted edits. Cmd+K runs a quick AI command on selected code without entering chat mode. Tab accepts inline completions. Escape cancels an in-progress Cascade action cleanly. Learning these five shortcuts takes about ten minutes and removes the friction of reaching for the mouse between coding and AI interactions, keeping the development flow continuous rather than interrupted by UI navigation.