NVIDIA's Nemotron 3 Ultra, tuned with LangChain's Deep Agents harness, achieved benchmark-leading performance at 10x lower inference cost than top closed models, enabling enterprises to build speciali…
The AI agent development stack is shifting from frameworks to harnesses—control loops that wrap models and manage task decomposition, retries, and context. Leaders from LlamaIndex, LangChain, Anthropi…
OpenAI's 'Practical Guide to Building Agents' has sparked a debate with LangChain CEO Harrison Chase, who called it 'misguided' and published a detailed rebuttal. The conflict highlights a core tensio…
LangChain co-founder Harrison Chase argues that AI agents can learn at three distinct layers—model, harness, and context—but most teams focus only on retraining the model. The harness layer, which opt…
Focused Labs has identified that agentic payments require a new architectural pattern where spending authority is delegated to the runtime rather than the AI agent itself. The company argues that agen…