A Guide to Using Windsurf.ai

As developers, we're always looking for tools that genuinely enhance our workflow rather than getting in the way. And with advancements in AI and the release of endless AI tools, it's hard to know where to start. Being a developer myself, I love to try out new tools and see how they can help me be more productive. One such tool I came across recently is Windsurf.ai. It's an AI-powered IDE just like Cursor, Copilot and many others but it stands out with some of its unique features. Let's dive in and see how it can help you be more efficient.

What is Windsurf.ai?

Windsurf.ai is fundamentally a VS Code fork that's been re-imagined to create a more natural collaboration between developers and AI. While there are plenty of AI coding assistants out there, Windsurf takes a different approach by focusing on maintaining your development flow rather than just providing code suggestions.

What makes it interesting is how it combines both copilot-style collaboration and autonomous agent capabilities. Instead of just being a chat interface that responds to prompts, it actively maintains awareness of your codebase and your actions. This means when you're working on a feature, it understands the context across multiple files and can help with coherent changes throughout your project.

The core idea behind Windsurf is to reduce the context-switching that often comes with AI coding assistants. Rather than having to stop what you're doing to carefully craft prompts, you can interact with it more naturally through features like inline commands (⌘ + I), code lenses, and its Cascade interface. It's particularly helpful when you're working on larger codebases where understanding the relationships between different components is crucial.

That said, it's worth noting that it's still an AI tool - it's meant to augment your development workflow, not replace your decision-making. Think of it more as a really knowledgeable teammate who has perfect memory of your codebase, rather than a magical code generator.

Getting Started

Let's get started by installing Windsurf.ai and getting familiar with the interface. It's available on Mac, Windows and Linux. Head over to the downloads page and download your preferred version.

Here are a few system requirements you can expect:

• Mac: OS X Yosemite or later
• Linux: Ubuntu 20.04+ (or equivalent glibc/glibcxx versions)
• Windows: Windows 10 64-bit or later

Once installed, you'll be provided with an option to migrate your existing VS Code settings. I recommend doing this as it'll help you get started faster. Great, now you're in!

Core Features

They have a few core features that make Windsurf.ai stand out among other AI-powered IDEs. These were the first ones I directly saw on the website. So let's explore a few of them.

Cascade: Beyond Chat

Cascade is supposed to be a Chat interface but it's more than that. Cascade combines deep codebase understanding, a breadth of advanced tools, and a real-time awareness of your actions into a powerful, seamless, and collaborative flow. It is the most powerful way to code with AI. The best part was that I was able to prompt it to start a project and it was able to generate the entire project structure for me from scratch.

Here's how it went, I asked it to start a new Swift project for a MacOS application, with a menu bar and an about screen. It generated the entire project structure for me from scratch.

They have a "Write" and a "Chat" option and Write is enabled by default. With just a prompt, it started doing it's magic and before I knew it, it had generated the entire project structure for me.

It has two models from what I could see. One is "gpt-4o" and the other is "claude-3.5-sonnet". Which is good because "claude-3.5-sonnet" is known to be better at coding tasks and that's what I used for this project.

So overall when the "Write" option is enabled, it will have write access to your codebase. It will be able to make changes to your codebase and even create new files. It also runs commands in your terminal and shows output in the Cascade interface.

The "Chat" option is more like a traditional chat interface. It's not able to make changes to your codebase but it's able to understand your codebase and help you with coding tasks.

You can additionally also add Images and include specific files in your prompt using the @ mention feature. So to conclude the Cascade feature, these would be the key features:

• Deep Context Awareness: Cascade understands your codebase structure and relationships
• Multi-file Editing: Make coherent changes across multiple files
• Command Suggestions: Get contextual terminal command suggestions
• @ Mentions: Reference functions, classes, or files directly in conversations

Supercomplete: Predictive Coding

Supercomplete goes beyond traditional autocomplete by understanding your intent:

I found it to be pretty good. It's at par with Copilot in terms of the suggestions it provides. It's also able to understand your codebase and provide suggestions based on the context of the codebase.

Command Mode (⌘ + I)

Natural language code editing right where you need it.

Sometimes, you just want to make a quick change to your code. You don't want to chat via Cascade and you can't use Supercomplete because you need to do something which it is not aware of. But still you need to do it quick and use power of AI to do it. Command mode is the solution for this.

Just press ⌘ + I and start typing your request. Hit Enter and it'll be able to understand your intent and make the changes for you in-place.

PS: That condition was just for demonstration purposes. Please don't do that in production. Unless you want to summon the code gremlins! 🧙‍♂️👾

Understanding Flows in Windsurf

The concept of Flows in Windsurf represents a significant shift in how developers can work with AI. Unlike traditional AI coding assistants that either wait for prompts or try to work autonomously, Flows creates a real-time collaboration between you and the AI.

The Evolution of AI Coding Assistance

Let's break down how we got here:

1. Traditional Coding (Pre-2022)

   • Just you and your keyboard
   • Every line of code required manual input
   • Complete control, but also complete manual effort

2. Copilot Era (2022-2023)

   • Line-by-line suggestions
   • Chat-based assistance
   • Required constant context switching between coding and prompting

3. Agent Attempts (Early 2024)

   • Autonomous code generation
   • Tool-based reasoning
   • Often resulted in long wait times and code that needed heavy revision

4. Flows (Current)

   • Real-time collaboration
   • Continuous context awareness
   • Adapts to your coding style and patterns

How Flows Actually Works

Think of Flows as having a pair programmer who:

• Watches your code changes in real-time
• Understands the context of what you're building
• Adapts their suggestions based on your coding patterns
• Maintains awareness across your entire codebase

Here's a practical example:

When you're working on a feature, Flows might:

1. Notice you creating a new API endpoint
2. Automatically suggest related model changes
3. Identify necessary updates to existing tests
4. Propose documentation updates
5. All while maintaining awareness of your project's architecture

The key difference is that you're not stopping to ask for each of these things - they're suggested naturally as part of your workflow.

Indexing: Understanding Your Codebase

One of Windsurf's most powerful features is its ability to truly understand your codebase through indexing. This isn't just simple code parsing - it's a deep semantic understanding of your code that powers many of Windsurf's intelligent features.

Local Indexing: Your Personal Code Context

Local indexing is enabled by default in Windsurf and works like a really smart code librarian that:

• Generates embeddings that capture the meaning of your code
• Powers codebase-aware chat and autocomplete
• Can retrieve context from your entire codebase, not just recent files
• Stores everything locally on your machine for privacy

Here's what you should know about local indexing:

System Impact

• Initial indexing takes about 5-10 minutes for a typical codebase
• Uses ~300MB RAM for a 5000-file workspace
• CPU usage spikes during initial indexing, then returns to normal

What Gets Indexed?

By default, the indexing engine is smart enough to ignore:

• Everything in your .gitignore
• node_modules directories
• Hidden files (starting with ".")

Pro tip: You can create a .codeiumignore file in your repo root to customize what gets indexed, using the same syntax as .gitignore.

Remote Indexing: Team-wide Code Understanding

For teams using Windsurf Enterprise, remote indexing offers additional capabilities:

• Index repositories you don't have locally
• Share codebase understanding across your team
• Support for GitHub, GitLab, and BitBucket repositories
• Automatic re-indexing on configurable schedules

Security Considerations

For those concerned about code privacy with remote indexing:

• Only embeddings are stored (not the actual code)
• Processing happens on isolated tenant instances
• Code snippets are deleted after embedding creation
• Each team's data remains completely separate

Conclusion

Windsurf.ai is an IDE by developers for developers. It supports features like Cascade, Supercomplete, Command Mode and Flows. It's focused on agent based coding and is a really good tool to have in your workflow. It's still new and they're actively working on improving it. I'm sure they'll be adding more features in the future. If you wish to add any feature requests, you can do so here.