About AI-Native Development
Exploring the intersection of architecture, context, and intelligence.
AI-native development isn't just about using models; it's about engineering the context that shapes their intelligence.
Context Engineering
Defining semantic boundaries and information hierarchies that ground LLMs in reality.
Neuro-Symbolic AI
Merging creative intuition of neural networks with rigorous logic of symbolic programming.
MCP
Standardizing how AI agents interact with local data sources and developer environments.
Models
Orchestrating specialized LLMs for complex multi-step reasoning tasks.
IDEs & Tools
The evolution of development environments into collaborative canvases shared between humans and agents.
Ecosystem
Building a sustainable network of tools that empowers developers to transcend traditional code limits.