Databricks has released KARL, an RL-trained RAG agent that it says handles all six enterprise search categories at 33% lower cost than frontier models.

Agent skills shift AI agents toward procedural tasks with skill.md steps; progressive disclosure reduces context window bloat in real use.

Ten AI concepts to know in 2026, including LLM tokens, context windows, agents, RAG, and MCP, for building reliable AI apps.

Databricks' KARL agent uses reinforcement learning to generalize across six enterprise search behaviors — the problem that breaks most RAG pipelines.

A 2025 study shows that an AI-based tutor improves learning when it prompts reasoning and is paired with peer discussion.

Library Futures Academy, an open-source retrieval-augmented generation (RAG) pipeline is being developed using historic newspapers held in the archives. This combined with optical character ...

MCP is the USB‑C of AI context: one protocol, endless integrations. Ship one server, hook it into Claude Desktop, Claude Code, VS Code, or your own chatbot – the host handles UI, auth, and ...

Experimental - This project is still in development, and not ready for the prime time. A minimal, secure Python interpreter written in Rust for use by AI. Monty avoids the cost, latency, complexity ...