GENERATIVE ATTITUDE

Extensive Guide to AI Observability How to monitor, understand, and improve production AI systems across ML models, LLMs, and autonomous agents. AI systems are now embedded in revenue-critical workflows, customer support, fraud detection, search, recommendations, forecasting, and enterprise automation. As organizations move from experimentation to production AI, one truth becomes…

What Is Agent Skills? A Practical Guide to How AI Agents Learn, Use, and Reuse Capabilities AI agents are moving beyond simple chat. They can now search documents, call APIs, write code, automate workflows, and coordinate multi-step tasks. One term that appears more often in this shift is agent skills:…

Latest Trends on A2A Protocol The A2A protocol, short for Agent-to-Agent protocol, is quickly becoming one of the most discussed building blocks in the emerging AI agent ecosystem. As organizations move from standalone chatbots to multi-agent systems that can coordinate tasks, exchange context, and delegate work across tools and services,…

The artificial intelligence landscape is evolving at breakneck speed, and one of the most significant developments reshaping how we interact with AI tools is the emergence of Model Context Protocol (MCP). This standardized approach to AI tool integration is fundamentally changing how developers build, deploy, and connect intelligent applications. MCP…

The landscape of work is undergoing a seismic shift. At the heart of this transformation are AI agents—intelligent systems that can perceive their environment, make decisions, and take actions to achieve specific goals. Unlike traditional software that simply executes predetermined commands, AI agents operate with a degree of autonomy that’s…