Most AI coding assistants are just fancy autocomplete. After testing them all, I found one that actually understands software development – not just syntax, but architecture, workflows, and the full dev lifecycle.
The story
I’ve tested every major AI coding assistant over the past few years, and most feel like autocomplete with extra steps. They’re helpful for syntax, sure, but they don’t really get what you’re building.
Then I started using Roo Code, and something clicked.
Here’s what sets it apart:
1. Multiple modes that match how you work
Architect Mode for planning, Code Mode for implementation, Debug Mode for fixing issues. Each mode can use different AI models. When I’m sketching features versus tracking down bugs, I need different kinds of help.
2. Real context awareness
It reads your codebase through semantic indexing, so it understands how components relate. This isn’t just scanning for keywords – it grasps architecture.
3. Works with your existing workflow
Open-source. Runs locally if you want. Supports Anthropic, OpenAI, Google Gemini, AWS Bedrock, or local models through Ollama. You’re not locked into one vendor’s ecosystem.
4. Git-like checkpointing system
Changes are tracked and you can revert when needed. After three decades of coding, I appreciate tools that respect the “trust but verify” principle.
5. Handles the full development lifecycle
It can execute terminal commands, manage browser automation for testing, coordinate complex workflows. For DevOps work where you’re constantly moving between development and operations, this is huge.
It’s the first coding assistant that feels like it was built by people who understand the entire software development process, not just the typing-code-into-an-editor part.
Worth checking out if you’re tired of tools that only help with
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