11 articles tagged with AI Agents.
AI apps add a new attack surface on top of the old ones. This is the map: the threats unique to LLMs and agents, and the controls that actually contain them.
Autonomous agents take real actions, so a single injected instruction can cause real damage. Here is how to contain them.
AI agents went from demos to production this year. This is the map: the frameworks, the protocol tying them together, and the patterns that actually ship.
A practitioner's tour of the reusable patterns for building reliable LLM agents, and when each one earns its keep.
Small language models now handle most agent steps at a fraction of the cost, so pick per step instead of defaulting to a frontier model.
A practical look at when multiple coordinating AI agents actually help, the orchestration patterns that work, and where they fail.
A practitioner's guide to tracing, evaluating, and debugging LLM agents in production with the tools that actually earn their keep.
A hands-on tutorial for building a Model Context Protocol server that exposes tools, resources, and prompts to any LLM host.
MCP is an open standard that gives AI agents one consistent way to reach external tools and data instead of bespoke glue.
A practitioner's comparison of the leading LLM agent frameworks, matching LangGraph, CrewAI, AutoGen and more to real use cases.
A practitioner's head-to-head on LangGraph and CrewAI, covering control, state, production readiness, and when each framework earns its place.
