Browsing: agents

There’s a lot of noise right now making it seem like you have to pick a side between MCP and Agent Skills. It’s being framed like…

Enterprises building AI agents often require more than what managed foundation model (FM) services can provide. They need precise control over performance tuning, cost optimization at…

Employees across every function are expected to make faster, better-informed decisions, but the information that they need rarely lives in one place. Workforce intelligence (who is…

For all the progress made in AI agent development over the past few years, one fundamental problem has remained largely unsolved: most people never actually interact…

Distilling insights with ReasoningBank ReasoningBank distills global reasoning patterns into high-level, structured memories. Each structured memory item contains the following:Title: A concise identifier summarizing the core…

You can use ToolSimulator, an LLM-powered tool simulation framework within Strands Evals, to thoroughly and safely test AI agents that rely on external tools, at scale. Instead…

In this tutorial, we build a universal long-term memory layer for AI agents using Mem0, OpenAI models, and ChromaDB. We design a system that can extract…

This post is cowritten by Renata Salvador Grande, Gabriel Bueno and Paulo Laurentys at Rede Mater Dei de Saúde. The growing adoption of multi-agent AI systems…

Following in the footsteps of the recently released Gemma 4, MiniMax has now made its latest model, MiniMax M2.7, completely open-weight. In simple terms, developers can…

AI agents struggle with tasks that require interacting with the live web — fetching a competitor’s pricing page, extracting structured data from a JavaScript-heavy dashboard, or…