Building Production-Ready Agentic AI Systems for Enterprise Software Delivery

Episode 1: From POCs to Production - What I Learned Building Agentic Engineering Workflows 1. Context: The Gap Between Potential and Reality Over the last year, we’ve all seen how rapidly AI capabilities especially Large Language Models (LLM) have advanced. From code generation to reasoning tasks, the progress has been significant and genuinely impressive. Agentic AI: the Gap Between Potential and Reality Agentic AI GAP between Production Ready and Reality In controlled environments: Proof of Concepts (POCs) look promising Concept validations show strong efficiency gains Early experiments demonstrate clear potential However, once you move beyond demos and prototypes, a different challenge emerges: ** How do you make these capabilities reliable, repeatable, and production-ready within real engineering teams?** This is the gap I’ve been working on over the past few months. 2. My Starting Point: Encouraging Experiments, Limited Impact Like many teams. I started with: Code assistants Promp