Exploring Windsurf with Gemini 2.5

A hands-on review of Windsurf IDE with Gemini 2.5 for AI-assisted coding

Chris Mathias tutorials/coding-with-ai, tools windsurf, gemini, ai-assisted-coding, developer-productivity

Exploring Windsurf: Capabilities, Limitations, and Features for Streamlined Development

Recently, I've been experimenting with Windsurf, a promising alternative to tools like Aider and Cursor, designed to leverage powerful large language models (LLMs) to assist developers directly within their workflow. In this article, we'll walk through my experience using Windsurf—highlighting its features, practical capabilities, and some limitations I've encountered.

🎥 Watch the full demo on our YouTube Channel to see Windsurf in action!

What is Windsurf?

Windsurf is essentially an integrated development environment (IDE) overlay built upon VS Code, augmented with AI-powered capabilities. It enables developers to interact with multiple LLMs like OpenAI, Claude, Gemini, and others, directly from within their coding workflow.

Key features include:

  • Cascade Editor: Micro-agents analyze your codebase contextually, providing targeted edits.
  • Multiple LLM Integration: Seamless switching between powerful LLMs such as OpenAI, Claude, and Google's Gemini.
  • Microdiffs: Precise, incremental changes suggested by the LLM, allowing selective acceptance or rejection.
  • Visual Interaction: Ability to interpret and act upon screenshots, enhancing the interaction possibilities.

My Experience: Windsurf and Gemini 2.5

Initially, I explored Windsurf using Claude, but faced some roadblocks when tackling more complex tasks—particularly with my Eleventy-based website. Issues arose when trying to resolve tagging and categorization problems. Claude and OpenAI both struggled with the complexities of the site structure and tagging implementation.

Recently, Windsurf introduced Gemini 2.5, a highly anticipated LLM from Google. Eager to test it, I revisited the tagging issue on my Spillwave website, built using Eleventy (a static site generator that converts markdown files to web pages).

Practical Scenario: Fixing Tagging and Categories with Gemini

My site was having issues where clicking on tags resulted in 404 errors due to “missing” tag pages. After querying Gemini through Windsurf's intuitive chat-like interface, it quickly identified the problem—Eleventy requires explicit tag page templates to generate these pages automatically.

Gemini proposed a concise, elegant solution:

  • Created a template for generating tag pages.
  • Updated Eleventy's configuration to automatically generate tag lists.

Unexpectedly, Gemini also caught an additional subtlety—tag casing inconsistencies—which it swiftly resolved by converting tags to lowercase before processing.

The results? Clicking on tags now correctly directs users to relevant articles, a fix Gemini effortlessly handled where previous models struggled.

Strengths of Windsurf and Gemini 2.5

  • Microdiffs: Incremental edits provided by Windsurf allow precise control.
  • Model Switching: Quickly comparing outputs between different LLMs, which proved helpful in troubleshooting.
  • Intuitive UI: The Cascade Editor simplifies complex AI interactions, making them seamless and integrated.
  • Context Management: Ability to reset context or maintain ongoing conversations based on the task complexity.

Limitations and Considerations

However, Windsurf and the LLMs still face some hurdles:

  • Context Complexity: On larger projects, Windsurf occasionally gets confused without explicit context-setting.
  • Model Reliability: Gemini performed exceptionally in targeted scenarios, but struggled with broader, less-defined tasks—like categorizing content based purely on context from blog posts.
  • Token Costs: Windsurf's convenience features can lead to increased token usage if automated features are over-relied upon, potentially raising costs.

Recommendations for Effective Use

  • Explicit Context Setting: Specify relevant files upfront for clarity.
  • Selective Automation: Manage your token usage consciously by manually executing simple commands instead of always relying on automated actions.
  • Model Flexibility: Don’t hesitate to switch LLMs if one struggles—flexibility is a core advantage of Windsurf.

Final Thoughts

Windsurf, especially combined with Gemini 2.5, has demonstrated considerable strengths in streamlining developer workflows, especially in solving well-defined technical issues. While it isn't flawless and requires careful management of context and resources, it's undeniably a significant step forward in AI-assisted development tools.

Like any of these tools - remember your good ole human meat brain is the best, and use your critical thinking to carefully review any changes the tooling attempts/suggests

Stay tuned for more updates and insights as I continue to explore how these tools shape the future of software development.