Loop Engineering for Agentic AI — Building Reliable AI Systems
Move beyond basic prompt engineering. Join Microsoft AI Leader Murari Ramuka in this exclusive masterclass to architect resilient, stateful multi-agent systems that evaluate, self-correct, and continuously improve over time.
The world isn't waiting.
Neither should you.
*Based on industry reports from Gartner, McKinsey, and World Economic Forum 2025–2026.
of Fortune 500 companies are piloting multi-agent AI systems
of AI leaders say agentic AI is their top investment priority in 2026
demand-supply gap for certified agentic AI professionals
Traditional linear prompt chains and basic Retrieval-Augmented Generation (RAG) pipelines frequently hit a wall in enterprise environments. When faced with complex, non-deterministic tasks, single-shot LLM calls struggle with memory retention, tool errors, and edge-case handling.
The industry is shifting toward "Loop Engineering"—architecting autonomous, stateful, and cyclic multi-agent workflows that can evaluate their own outputs, recover from tool failures, and self-correct over time.
In this exclusive ADaSci Masterclass, Murari Ramuka (Senior Generative AI Leader at Microsoft, Ex-Google, and AIM 40 Under 40 AI Builder 2026) breaks down the practical frameworks required to build production-grade agentic loops. You will learn how to design Planner-Executor dynamics, manage state across prolonged executions using frameworks like LangGraph, implement Human-in-the-Loop (HITL) governance, and leverage semantic memory for continuous system improvement.
Beyond Linear Prompts: Transitioning from static RAG pipelines to cyclic, stateful multi-agent workflows.
ReAct & Planner-Executor Dynamics: Designing agents that break down complex enterprise tasks, route tools, and assess their own outputs.
Self-Correction & Reflection Patterns: Implementing autonomous evaluation checks (LLM-as-a-judge) and graceful API/tool error recovery.
State & Memory Management: Maintaining execution state with LangGraph and using episodic memory to learn from past trajectories.
Governance & HITL Checkpoints: Setting up interruptible loops for human oversight on high-stakes enterprise actions.
Live Interactive Q&A: Direct AMA with Microsoft’s Murari Ramuka on enterprise AI architecture and career growth in 2026.
Architect production-ready multi-agent systems using cyclic, stateful design patterns.
Implement self-correction mechanisms to prevent agent loops from stalling or crashing on API timeouts.
Master state management frameworks (such as LangGraph) for multi-step reasoning.
Design Human-in-the-Loop (HITL) safety checkpoints for enterprise compliance and governance.
Optimize token consumption and execution latency across autonomous agent trajectories.
AI Engineers & Developers building production-grade LLM applications and agentic workflows.
Data Scientists & ML Architects transitioning from prototype notebooks to enterprise AI pipelines.
Tech Leads, Engineering Managers & CXOs evaluating multi-agent systems, build vs. buy choices, and AI governance.
ADaSci Candidates (CFDE, CAASA, AIDP) seeking deep technical insights directly from industry leaders.
Fundamental understanding of Python and Generative AI concepts (LLMs, Prompts, RAG).
Familiarity with agentic frameworks (e.g., LangChain, LangGraph, AutoGen, or CrewAI) is helpful but not mandatory.
Basic understanding of cloud infrastructure or enterprise software architecture.
Complete Live Recording access to the masterclass.
Presentation Deck & Architecture Blueprints shared by the speaker.
Access to ADaSci Community Forum for post-webinar Q&A and networking.
Learn from the best
Murari Ramuka
Senior AI Leader & Technology Strategist at Microsoft | AIM 40 Under 40 AI Builder
Murari Ramuka is a transformative technology leader and AI Strategist at Microsoft, specializing in enterprise-grade Data and AI platforms, Generative AI adoption, and autonomous agentic workflows. With prior leadership roles at Google, KPMG, and HSBC, Murari brings deep cross-industry experience in building resilient, cost-optimized production AI systems. He was recognized as one of AIM’s 40 Under 40 AI Builders and is currently pursuing his PhD in AI at IIT Ropar. As a global speaker, author, and Mentor of Change at the Atal Innovation Mission, he is dedicated to advancing responsible AI execution and mentoring the next generation of tech leaders.