Getting Started with Delta's AI Assistant

After spending years researching human-AI interaction at a major AI lab, I've seen firsthand how AI can transform developer workflows. Delta's AI assistant represents a thoughtful approach to this transformation—one that prioritizes learning from your patterns while respecting your autonomy.

Understanding the AI Architecture

Delta's AI assistant isn't just another LLM wrapper. It combines several AI techniques to create a genuinely helpful experience. The initial setup is straightforward:

[deltacli] ∆ :ai on

This activates a carefully tuned model that balances performance with accuracy. Under the hood, Delta uses a combination of transformer-based models and traditional ML algorithms to understand context and intent.

Model Selection and Trade-offs

Different models excel at different tasks. Delta's model ecosystem reflects this reality:

[deltacli] ∆ :ai model list

[deltacli] ∆ :ai model phi4:latest

The phi4 model, for instance, offers excellent performance for code completion while maintaining a smaller memory footprint. For more complex reasoning tasks, you might prefer larger models—though always consider the latency trade-off.

The Feedback Loop: Teaching Your AI

What sets Delta apart is its emphasis on continuous learning through user feedback. This isn't just about correcting mistakes—it's about building a personalized model of your preferences:

[deltacli] ∆ :feedback helpful

[deltacli] ∆ :ai feedback correction "The correct command is git commit -am 'message'"

Each piece of feedback contributes to a reinforcement learning process that adapts the AI's behavior to your specific needs. This is where the real magic happens—your Delta instance becomes uniquely yours.