AI agent architectures, MCP integrations, tool-use patterns, and multi-agent systems — from theory to production.
Three days ago, Microsoft open-sourced the Agent Governance Toolkit — seven packages, five language SDKs, sub-millisecond policy enforcement. The timing isn't coincidental. The EU AI Act's hig
Most agent loops work like this: the model picks a tool, calls it, gets the result, picks the next tool. Rinse, repeat. Somewhere between steps three and thirty, the agent starts contradicting itself
A 3.4 GB model just posted a 97.5% pass rate on a tool calling benchmark, beating models five times its size. If you're still defaulting to the biggest model you can afford for your agent stack, y
Over the past three months, OpenAI retired Swarm and shipped the Agents SDK with first-class handoffs. Microsoft added handoff orchestration to its Agent Framework. AutoGen rebuilt its multi-agent coo
The MCP Dev Summit kicked off in New York today with 95 sessions about protocols, security, and scaling agent infrastructure. But the most consequential thing happening to the agent ecosystem right no
For the past year, MCP gave agents a way to reach tools. Good. But agents couldn't find or talk to each other without duct-taping custom HTTP calls between services and hoping for the best. A2A v1
Everybody wants a multi-agent system. A planner talks to a researcher talks to a coder talks to a reviewer — it feels sophisticated, it photographs well for architecture diagrams, and according to a p
A year ago, people were debating whether MCP would become the standard for connecting LLMs to tools. That debate is over — MCP won. What nobody prepared for is that winning the standard means inheriti
Most multi-agent failures trace back to orchestration bugs and handoff engineering, not model capability -- UC Berkeley's MAST framework found that 79% of production breakdowns are specification a