## Most early LLM apps start the same way: “Let’s just put everything into one prompt and let the model handle it.” So we write a prompt that tries to: validate input transform data generate output summarize add reasoning handle edge cases …and somehow do it all in one call. It works—until it doesn’t. The Problem with “God Prompts” As the prompt grows: Instructions start conflicting Context becomes noisy Accuracy drops Outputs become inconsistent You end up with: a very expensive confusion engine I’ve hit this multiple times while building AI systems. What’s Actually Happening You’re increasing what I call LLM cognitive load. The more responsibilities you push into a single call: the harder it is for the model to prioritize the easier it is to miss instructions the more likely it is to hallucinate Even with better models, this pattern doesn’t go away. A Better Approach: Think Like a System Designer Instead of one big prompt, break the problem into smaller, focused steps.…