Artificial intelligence is becoming part of ordinary decision-making. People use AI to think through work, research, business questions, education, relationships, health concerns, legal research, account issues, and personal planning.
That does not mean every AI response is dangerous. It means AI conversations can become important. When a conversation becomes important, the user deserves a way to pause and inspect what happened before acting.
CAF stands for Continuity Alignment Framework. It was created to help identify when an AI conversation starts drifting away from the user's original objective, becomes unstable, introduces contradictions, applies pressure, or presents confident guidance before enough context has been established.
CAFScansAI is the first public software product built from that framework. It is not a chatbot, not an autonomous agent, and not a system that secretly monitors users. It is a user-controlled review layer for conversation excerpts and continuity snapshots.
The goal is not to replace judgment.
The goal is to support judgment. CAFScansAI helps users look at an AI interaction more carefully, understand why certain patterns may matter, and decide whether to bring corrective guidance back into the same conversation.
The long-term vision is that AI conversation review becomes normal. Before acting on important AI guidance, people should be able to ask: Did this conversation stay aligned? Did it skip verification? Did it become too certain? Did it pressure me? Did it contradict itself? What should I ask next?
CAFScansAI exists to make that checkpoint practical.