A RAG store is often introduced as a vector database. That description is too narrow for a real application. Retrieval needs text and vectors, but ingestion also needs checkpoints and publication sta...

  Introduction Field engineers operating in remote substations frequently encounter connectivity limitations when evaluating the safety of proposed grid adjustments. While physics-informed neural...

Introduction I had an Azure model deployment, an endpoint, and an API key. Getting that model into OpenCode looked like a configuration task: register a provider, paste in the connection details, s...

The shortest path to local inference is not to begin with a web server, an agent framework, or a full RAG pipeline. Begin with a spike that proves five things on the target machine: the SDK initializ...

A retrieval-augmented generation prototype can look convincing after an afternoon: load a few documents, create embeddings, retrieve passages, and ask a model to answer. A health-records system is ha...

  Building an AI agent is getting easier. Building an agent system that knows which agent should act, what context to share, when the work is done, and where a person must approve is the harde...

Building the Local RAG System The system was designed as a fully local RAG pipeline, with both retrieval and model inference running on the same machine. The knowledge base came from two equipment ...

Project Overview Rather than relying on the model to know when the student understands, we built a pipeline where progress itself is gated: a student cannot move forward until they can demonstrate ...

      Firmware can look perfectly reasonable in the editor. That does not tell you whether the pulse on the pin is the right width or what your I2C bus is actually sending. The oscillosc...