There's a moment every solo founder hits with AI agents. You've wired up the automation. The agent has a good system prompt. It worked great in testing. Then you deploy it and three days later it starts doing weird stuff. Missing context. Repeating decisions it already made. Acting like it has amnesia. You tweak the prompt. It helps a little. You add more instructions. Marginally better. You're chasing symptoms instead of the problem. The problem is you're still thinking about this like a prompt engineering challenge. It's not. It's a context engineering challenge. This is the thing that actually separates AI systems that run themselves from ones that need constant babysitting. What Prompt Engineering Actually Is Prompt engineering is choosing the right words to get the right output from a model in a single exchange. "Act as an expert copywriter. Write in a direct tone. Here are three examples..." That kind of thing. It's not useless. Prompts matter.…