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The AI economy is shifting from "Model-centric" to "Workflow-centric." While the hardware and foundational layers capture headlines, the real $6 trillion frontier lies in the Application Layer. By targeting the cognitive labor of the service economy, Applied AI is moving beyond software—it is selling outcomes. Backed by Stanford HAI 2024 data, this analysis deconstructs the 5-layer stack to show how verticalized AI will capture the greatest economic surplus of our generation.

As generative AI models grow their context windows, a hidden problem emerges: more information often leads to worse answers. Known as context rot, this phenomenon reveals a U-shaped performance curve where accuracy peaks at moderate context sizes, then degrades as signal is buried in noise. Bigger memory doesn’t guarantee better reasoning—effective context does.

raditional JSON tool calling is fragile. "Code Mode" changes the game: convert MCP tools to TypeScript APIs and let AI agents write executable code. It’s faster, handles complex logic, and uses secure sandboxes. Get the full code demo here.

Agriculture Meets AI: Precision Crop Planning and Sustainable Farming Using GenAI

dots.ocr: A compact 1.7B AI model transforming multilingual document scanning into lightning-fast accuracy.

GenAI is reshaping CRM by enabling personalized, proactive, and scalable customer experiences across industries.

Letta's new .af format standardizes AI agent portability, memory, and sharing—powering the next-gen agent ecosystem.

​Discover how Model Context Protocol (MCP) servers revolutionize AI by seamlessly connecting models to external data sources and tools