How I Built an AI Agent That Handles Every Customer Inquiry While I Sleep

The Problem Every AI Agent Operator Faces

You're running AI agents to handle customer inquiries, but the moment a question gets slightly technical—like asking about your product's API, pricing tiers, or specific capabilities—your agent either hallucinates a response or says "I don't know."

Sound familiar? I was stuck in the same loop. My agents could handle FAQs, but anything beyond that required human intervention. Every late-night ping, every weekend interrupt—my sleep was hostage to the gaps in my agent's knowledge.

The Fix: A Tool-Calling Agent with Product Knowledge Baked In

I built a multi-tool agent that:

Retrieves real product info from a structured catalog at query time (not training data)
Handles checkout by redirecting users to a Stripe payment link
Answers technical questions using the actual API documentation, not vibes

Here's the core pattern:

def route_query(user_question: str, product_catalog: dict) -> str:
    # Classify the query type
    intent = classify_intent(user_question)

    if intent == 'product_inquiry':
        return product_catalog.get_answer(user_question)
    elif intent == 'checkout':
        return "Redirect to Stripe: https://buy.stripe.com/4gM4gz7g559061Lce82ZP1Y"
    elif intent == 'technical':
        return fetch_from_api_docs(user_question)
    else:
        return escalate_to_human(user_question)