The framework establishes a specific division of labor between the human researcher and the AI agent. The system operates on a continuous feedback loop where progress is tracked via git commits on a ...
In this tutorial, we build an advanced multi-agent communication system using a structured message bus architecture powered by LangGraph and Pydantic. We define a strict ACP-style message schema that ...
Qwen team has just released Qwen3-Coder-Next, an open-weight language model designed for coding agents and local development. It sits on top of the Qwen3-Next-80B-A3B ...
What if the AI industry is optimizing for a goal that cannot be clearly defined or reliably measured? That is the central argument of ...
In this tutorial, we explore how we use Daft as a high-performance, Python-native data engine to build an end-to-end analytical pipeline. We start by ...
The Model Context Protocol (MCP), open-sourced by Anthropic in November 2024, has rapidly become the cross-cloud standard for connecting AI agents to tools, services, and data across the enterprise ...
What is an AI Agent? An AI Agent is an autonomous software system that can perceive its environment, interpret data, reason, and execute actions to achieve specific goals without explicit human ...
Generating publication-ready illustrations is a labor-intensive bottleneck in the research workflow. While AI scientists can now handle literature reviews and code, they struggle to visually ...
The AI industry is currently obsessed with ‘agents’—autonomous programs that do more than just chat. However, most current multi-agent systems rely on brittle, hard-coded heuristics that fail when the ...
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