Orchestration Meets MCP: Building Governed Agentic Workflows With Quarkus Flow and AGENTS.md
Building autonomous AI agents with large language models (LLMs) is easy when writing single-turn demo scripts. However, moving multi-agent loops into production introduces serious architectural challenges. Agents hallucinate, loop infinitely without reaching convergence, require human approval for high-risk operations, and need standard tool-calling integrations alongside clear operational governance. Historically, Java developers faced a tough choice: either rely on heavyweight, external workfl
