Ssehgalnamitinarticles.namitsehgal.com·1d ago · 7 min readAgentic AI Governance: Operationalizing MAS SAFR, Federated Gateways, and Human-in-the-Loop FlywheelsAs enterprise AI evolves from passive chat interfaces to fully autonomous multi-agent networks, classical governance architectures fail. Pre-deployment model evaluations, benchmark scores, and static 30
Ssehgalnamitinarticles.namitsehgal.com·1d ago · 12 min readMulti-Agent Operations: GovOps, Distributed Tracing, and Enterprise ResilienceBuilding a multi-agent system is only half the engineering challenge. Once autonomous agents start interacting, dynamically routing tasks, calling APIs, and updating state stores in production, non-de00
Ssehgalnamitinarticles.namitsehgal.com·1d ago · 7 min readMulti-Agent Architecture: Topology, State Machines, and Inter-Agent ProtocolsTransitioning enterprise AI from single prompt chatbots into autonomous multi-agent networks requires a fundamental shift in software engineering. While individual LLM agents excel at contained sub-ta00
Ssehgalnamitinarticles.namitsehgal.com·2d ago · 4 min readThe Runtime Frontier: Why Agentic AI Kills Static Compliance and Demands Continuous GovOpsThe Artificial Intelligence governance landscape has officially reached a tipping point. As Google DeepMind CEO Demis Hassabis recently outlined, humanity is standing in the foothills of AGI, where re00
Ssehgalnamitinarticles.namitsehgal.com·Jul 31 · 28 min readBuilding Production-Grade Multi-Agent Ecosystems: The Enterprise Architectural BlueprintExecutive Summary & The Problem Space Building a functional AI agent prototype using a raw LLM API call is simple. Moving that agent into a mission-critical enterprise production environment is an ent32M
