{"id":5521,"date":"2026-09-26T04:11:14","date_gmt":"2026-09-26T07:11:14","guid":{"rendered":"https:\/\/tucumandevelopers.com\/index.php\/2026\/09\/26\/building-ai-customer-support-is-easy-trusting-it-is-hard\/"},"modified":"2026-09-26T04:11:14","modified_gmt":"2026-09-26T07:11:14","slug":"building-ai-customer-support-is-easy-trusting-it-is-hard","status":"publish","type":"post","link":"https:\/\/tucumandevelopers.com\/index.php\/2026\/09\/26\/building-ai-customer-support-is-easy-trusting-it-is-hard\/","title":{"rendered":"Building AI Customer Support Is Easy. Trusting It Is Hard."},"content":{"rendered":"
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AI customer support sounds simple.<\/p>\n

Give an AI your documentation, let users ask questions, and let the AI answer.<\/p>\n

That was roughly what I thought when we started building AI support into FeedLog<\/a>.<\/p>\n

Then we actually started testing it.<\/p>\n

And I realized the hardest part isn’t getting AI to answer.<\/p>\n

It’s deciding when it should answer at all<\/strong>.<\/p>\n

<\/a> The happy path is easy <\/h2>\n

When a user asks:<\/p>\n

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How do I export my data?<\/p>\n<\/blockquote>\n

And the answer clearly exists in your knowledge base, everything works beautifully.<\/p>\n

User asks \u2192 AI finds the right information \u2192 user gets an answer.<\/p>\n

Done.<\/p>\n

But real users don’t always ask questions your documentation can answer.<\/p>\n

They ask things like:<\/p>\n

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Why was I charged twice?<\/p>\n

My account stopped working. Can you fix it?<\/p>\n

I followed the documentation and it still doesn’t work.<\/p>\n<\/blockquote>\n

Now the AI has a decision to make.<\/p>\n

Should it answer?<\/p>\n

Should it ask another question?<\/p>\n

Should it admit it doesn’t know?<\/p>\n

Or should it bring in a human?<\/p>\n

That’s where AI support gets interesting.<\/p>\n

<\/a> A wrong answer is worse than no answer <\/h2>\n

With a normal chatbot, a hallucination is annoying.<\/p>\n

With customer support, it can become a real problem.<\/p>\n

If the AI confidently gives the wrong billing information or invents a feature that doesn’t exist, you’ve saved zero support time.<\/p>\n

You’ve probably created another support ticket.<\/p>\n

So we’re starting to think about AI support less as:<\/p>\n

“How many questions can AI answer?”<\/strong><\/p>\n

And more as:<\/p>\n

“How many questions can AI safely resolve?”<\/strong><\/p>\n

Those are very different metrics.<\/p>\n

<\/a> The goal isn’t to remove humans <\/h2>\n

I don’t think good AI support means humans disappear.<\/p>\n

The better model might be:<\/p>\n