Sunny autumn and a good book. If you're serious about building reliable and scalable AI apps, you need to move past duct-taping LLM APIs together. Think about: - Where is the state stored? - What can the agent access? - Can it recover from a failed tool call? - Can you inspect the decision path? - Can you stop stale context from poisoning the next run? Anyone can slap a nice UI on top of an LLM API. The hard part is building the system around the model: memory, tools, permissions,…