MIT reports ~95% of AI pilots fail to deliver value, and Gartner predicts 40% of agentic AI projects will be canceled by 2027. The gap isn't model quality — it's governance. Here are the bounded autonomy patterns that work.
Multi-Agent AI Systems in 2026 — practical architecture analysis and enterprise guidance for Azure and AI platform teams.
Azure AI Foundry rebranded to Microsoft Foundry with managed long-term memory, A2A protocol support, and a consolidated SDK. Here is when to use the managed runtime vs self-hosted frameworks.
Google Cloud Next 2026 shipped the pieces that ended framework fragmentation. The three-pillar enterprise stack is now defined: MCP for tool calls, A2A for agent communication, and ADK for orchestration.
Microsoft Conductor lets you define multi-agent workflows in YAML with deterministic routing — zero tokens spent on orchestration decisions.
MAF 1.0 unifies AutoGen and Semantic Kernel into a single cross-platform SDK with production-grade agent harness, CodeAct, and Foundry hosted deployment.
Production AI agents need observability, error handling, fallback visibility, and cost control — not just better prompts.
A practical comparison of Hermes Agent and OpenClaw for AI agent operations, gateways, orchestration, automation, and production reliability.