Zynap Inside AI – Chapter 3: We Built Our Agentic Framework. Here’s What Happened Next

The document describes how a team embedded specialized AI agents across their microservices and development workflows, emphasizing a shift from generic assistants to service-specific specialists supported by reusable skills and commands. It outlines an architecture using hooks, checkpoints, sessions, and a consensus mechanism for critical decisions, with workflows defined in JSON to enable flexible orchestration. The approach improved accuracy, reduced false positives, accelerated onboarding, and increased team confidence.