Beyond the Chatbot: Reality-Based Architectures for Agentic Workflows
About six months ago, I was sitting in a post-mortem for a high-profile 'AI Assistant' project. On paper, it was a success—it could answer questions about company policy with 90% accuracy. But the business stakeholders were frustrated. Why? Because when a user asked, 'Change my shipping address for order #456,' the bot just gave them instructions on how to do it themselves. It couldn't actually do the work. This is the gap we are bridging as we move toward 2026. We are moving past 'Generative AI' as a search interface and into the era of agents that actually execute. In real enterprise environments, this isn't about some sci-fi autonomous brain; it’s about architecting systems where LLMs are treated as reasoning engines that can call existing APIs, navigate legacy database schemas, and manage state across long-running workflows. The shift from static blueprints to these 'brains' requires us to stop thinking about sequential code and start th...
