Sreekanth Iyer

Most AI initiatives fail not because the model is weak, but because teams lack a shared, reusable pattern language that turns experimental wins into production systems.This session distils three decades of engineering into 8 eras and 300+ patterns — showing how each technology wave (structured programming, OOP/GoF, SOA/events, cloud/microservices, cloud security, AI/ML, and now agentic AI) accelerated once solutions were named, standardised and made communicable. Attendees will learn the core pattern families behind production-grade agentic systems: reasoning, memory (RAG), tool use (ReAct), orchestration and enterprise safety controls including human-in-the-loop gates. The session concludes with a live Spec-Driven SDLC demo — where the spec acts as the contract coordinating a multi-agent delivery pipeline, from architecture through deployment. The talk closes by connecting the methodology to BITS Pilani Digital's AI Engineering & MLOps programmes, demonstrating how industry–academia partnerships enable learners to apply these patterns to real-world problems and move from prototypes to production with engineering rigour.