A PM's Guide to AI Agent Architecture

I really don't understand how people given access to a pile of tools and data sources and unleash them on customers. It's horrible UX in my experience and at times worse than a phone tree.

My view is that you need to transition slowly and carefully to AI first customer support.

1. Know the scope of problems an AI can solve with high probability. Related prompt: "You can ONLY help with the following issues."

2. Escalate to a human immediately if its out of scope: "If you cannot help, escalate to a human immediately by CCing bob@smallbiz.co"

3. Have an "unlocked agent" that your customer service person can use to answer a question and evaluate how well the agent performs in helping. Use this to drive your development roadmap.

4. If the "unlocked agent" becomes good at solving a problem, add that to the in-scope solutions.

Finally, you should probably have some way to test existing conversations when you make changes. (It's on my TODO list)

I've implemented this for a few small businesses, and the process is so seamless that no one has suspected interaction with an AI. For one client, there's not even a visible escalation step: they get pinged on their phone and take over the chat!

The purpose of customer support is to convince the customer that it is not worth their time to pursue support. A worse experience achieves that goal faster.

Using GenAI is a huge breakthrough in this field, because it is a socially acceptable way to tell someone you don't care about their issue.