For an AI agent to do a good job at customer support, you would need to
1. literally document everything in the product and keep documentation up to date (could be partially automated?)
2. Build good enough search to find those things
3. Be able to troubleshoot / reason / abstract beyond those facts
4. Handle customer information that goes against the assumptions in the core set of facts (ie customers find bugs or don’t understand fundamental concepts about computers)
5. Be prepared to restart the entire conversation when the customer gets frustrated with 1-4 (this is very annoying)
Point 1 (document everything) is the utopia that killed the project. In any complex system, documentation is a lossy compression of reality. The actual truth about how to fix bugs doesn't live in Confluence; it lives in senior heads, Slack chats, and intuition, and AI has no access to this layer of tribal knowledge
1. literally document everything in the product and keep documentation up to date (could be partially automated?)
2. Build good enough search to find those things
3. Be able to troubleshoot / reason / abstract beyond those facts
4. Handle customer information that goes against the assumptions in the core set of facts (ie customers find bugs or don’t understand fundamental concepts about computers)
5. Be prepared to restart the entire conversation when the customer gets frustrated with 1-4 (this is very annoying)