From Cursor to Claude Code & OpenCode: How I Unlocked Next-Level Development Speed

I thought I had reached peak productivity with Cursor. I was wrong.

After trying out Claude Code and OpenCode (SST's open-source, model-agnostic alternative), I'm experiencing a development velocity I didn't think was possible. The difference was so dramatic that I immediately upgraded to Claude Code Max's $200/month tier—I was burning through rate limits that quickly.

The Speed Difference Is Real

What makes this combo special isn't just raw coding speed. It's the mental bandwidth it frees up. While Claude Code and OpenCode handle the implementation details, I'm simultaneously planning the next three features. It's like having a senior developer pair programming with you 24/7, except they never get tired and can context-switch instantly.

This isn't "vibe coding" where you're just throwing prompts at an AI and hoping for the best. This is structured, intentional development with AI as a force multiplier.

What I'm Building: An AI Agent Platform

To really put these tools through their paces, I'm building a comprehensive AI Agent Platform. Here's the tech stack:

Core Infrastructure

⚡ Pydantic AI - For robust data validation and serialization
⚡ Groq Cloud - Lightning-fast inference
⚡ Google Gemini - Multi-modal capabilities
⚡ FastAPI - High-performance async API framework
⚡ Vercel AI SDK - Streamlined frontend AI integration
⚡ Extensive unit testing - Because speed without reliability is just fast failure

Agents and Tools in Development

The platform already includes several sophisticated agents:

🖼️ Image Generation & Editing - Powered by Nano Banana
🐍 Python Sandbox Execution - Safe, isolated code execution
📊 Mermaid Diagram Generation - Visual representation of complex data
🔎 Semantic Document Search - Context-aware information retrieval

And this is just the beginning. The modular architecture makes adding new agents straightforward.

The Learning Curve as a Full-Stack AI Engineer

Building this platform has been an intensive masterclass in modern AI engineering:

File Upload to Context Pipeline

Handling multi-modal inputs efficiently requires careful consideration of file processing, chunking strategies, and context window management. Each file type needs its own preprocessing pipeline to extract meaningful content.

Streaming Protocol Translation

Different AI providers use different streaming formats. Building a unified interface that translates between these protocols seamlessly was a fascinating challenge that deepened my understanding of real-time AI communication.

Multi-Modal Model Integration

Working with models like Gemini for both image generation and editing revealed the nuances of prompt engineering for visual tasks versus text generation. The same model behaves very differently depending on how you structure your requests.

Why OpenCode Deserves More Attention

While Claude Code gets a lot of buzz (deservedly so), OpenCode from SST is the unsung hero here. Being open-source and model-agnostic means:

No vendor lock-in
Ability to switch between models based on task requirements
Community-driven improvements
Complete transparency in how your code is being processed

Today the best agentic coding models are Anthropic but that could very well change tomorrow. If it changes I don't want to be locked into Claude Code.

The Bottom Line

The productivity gain isn't incremental—it's exponential. Tasks that would have taken days now take hours. Complex refactoring that I would have postponed indefinitely gets done in an afternoon.

If you're still on the fence about trying Claude Code or OpenCode, consider this: the time you save in the first week will likely offset the cost for months. And if you're already using Cursor, you owe it to yourself to see what the next level looks like.

Has anyone else made this switch? I'd love to hear about your agentic coding experience on LinkedIn - what tools you're using, what you're building, and how it's impacting your development workflow.