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We learned that an AI customer agent shouldn't try to answer everything

Hey Indie Hackers! đź‘‹

After launching MySampark, we've been thinking a lot about one question:

What should an AI customer agent actually do?

At first, the obvious answer seems to be: answer every customer message.

But the more we looked at real business conversations, the more we realised that's not really the goal.

Businesses get a lot of repetitive questions:

“What's the price?”
“Is this available?”
“Do you deliver?”
“How long does delivery take?”
“What are your opening hours?”

These questions don't necessarily need a person sitting there waiting to answer every few minutes.

But then you get a completely different type of conversation:

“I received the wrong product. What should I do?”

“I have a problem with my order.”

“Can I speak to someone?”

That's where we think the human still matters.

So with MySampark, we're working toward a simple principle:

🤖 AI handles the routine.
👤 Humans handle what needs a human.

The AI Agent can respond to customer conversations using the business's information, while the team can step in when a conversation needs personal attention.

We're also trying to avoid the old-school approach of only responding when someone types an exact keyword.

A customer shouldn't have to say exactly “price” for the system to understand that they're asking about the price.

We're still improving this and learning from real conversations.

For founders building AI products:

What's one thing you've learned about where AI should stop and a human should take over?

I'd genuinely love to hear how others are approaching this.

— Hemangi
MySampark

posted toAvatar for product My Sampark
My Sampark
  1. 1
    I tend to find it easier to define the boundary by what the agent is allowed to see and do, rather than by whether a question is “easy” or “difficult.” For example, imagine a bookstore. If the official website already shows shelf location, stock status, price, and opening hours, I’d consider all of that safely inside the agent’s boundary. If the business also allows access to a reservation system, then the agent can go one step further and guide the customer to reserve the book. If it is allowed to see incoming-stock data, then it can say something like: “This title is currently out of stock, but the next shipment is expected around Tuesday.” I think of it a bit like a dog park. The Human builds the fence. Inside the fence, the AI is free to move. So the AI only really has to decide one thing: Is this inside the fence, or outside it? Inside: answer or act within the allowed scope. Outside: hand it back to the Human. That feels much cleaner to me than asking the AI to repeatedly decide: “Is this question simple enough?” “Is this safe enough?” “Does this need a person?” Define the information and action boundary first, then let the AI move freely inside it.
  2. 1
    The interesting part is that the boundary probably shouldn't just be 'routine vs difficult'. A task can be technically easy for the AI but still need a human because the consequence is high, the information is uncertain, or the customer is asking for something the business hasn't actually authorised. So I've started thinking about handoff less as 'the AI got stuck' and more as 'this has crossed a judgement or authority boundary'... That also makes human involvement feel like a well-designed system rather than a failure of autonomy.
    1. 1
      Thanks for this perspective — really insightful. I like the way you frame handoff as a success of the system’s governance rather than a failure of AI autonomy. The idea of defining clear authority boundaries is especially interesting for social media management, where the impact of a reply or post can be significant. It’s definitely something we’re thinking about as we continue developing MySampark.