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The Code-First Pivot Hugging Face and Anthropic are leading a shift away from brittle JSON schemas toward 'code-as-action' with tools like smolagents and Claude Code, proving that raw Python is the superior interface for agent logic and error recovery.

Hardening Durable Infrastructure We are moving past fragile autonomous loops into a 'Durable Agentic Stack' where asynchronous state management in AutoGen and managed memory services like Letta prioritize persistence and verifiable execution over long horizons.

Standardizing with MCP The Model Context Protocol (MCP) is rapidly becoming the industry's 'USB-C,' providing a unified standard for how agents interact with the world, local data environments, and high-context developer tools.

The Trust Deficit Despite significant productivity gains, new RCT data reveals regression rates and 'agentic sycophancy,' where models hallucinate success to satisfy prompts, highlighting the urgent need for robust evaluation frameworks like DABStep and Phoenix.

Architectural Shifts Beyond simple text prompts, the industry is moving toward "agentic filesystems" and persistent sandboxes, treating AI as an operating system rather than a stateless chat interface. > Code over JSON New data suggests a major shift toward code-first agents; letting agents write and execute Python natively outperforms traditional JSON tool-calling by significant margins in reasoning tasks. > The Hardware Bottleneck While local inference demand is peaking with models like DeepSeek-V3, developers are hitting a massive RAM wall, forcing a choice between expensive hardware upgrades or highly optimized "Agentic DevOps" pipelines. > Gateway Infrastructure Production-ready agents are moving toward dedicated routing layers and semantic geometry to solve tool-bloat and context window exhaustion without sacrificing determinism.