Beyond the Loop: Why Monolithic AI Agents Fail and How to Build a Microkernel Architecture
Programming Central
If you have built an AI agent recently, chances are your codebase started with a simple, elegant loop. You sent a prompt to an LLM, parsed its tool calls, executed those tools, appended the results to a list of messages, and looped back. It felt magical. But then reality set in. You wanted to add a vector database for long-term memory. Then you added a context compression engine to keep API costs down. Next came a dynamic skills system, a background review step, and custom toolkits for specific