So I finally caved and built a Lindy agent to draft responses for our frontline customer support folks. The pitch was classic: "Let AI handle the tedious first drafts, so your team can focus on complex, high-value interactions!" You've all heard it.
I’ll admit, the initial results were… efficient. It scrapes the ticket, pastes in relevant help docs, and spits out a polite, grammatically correct wall of text in about two seconds. Our CSAT scores haven't moved an inch, though. Turns out "correct" and "helpful" are different planets.
Here's the rub I'm now grappling with: we've accidentally optimized for blandness. The agent is terrified of being wrong, so its drafts are masterclasses in saying nothing with perfect clarity. It defaults to safe, generic empathy ("I understand this must be frustrating") and avoids any actionable guesswork, even when the solution is 95% obvious. It makes the human agent sound like a corporate chatbot.
Worse, I think it's starting to atrophy my team's skills. Why spend 60 seconds thinking through a common issue when you can just tweak Lindy's draft? Except that "tweaking" often takes longer than writing a good, human response from scratch. The cognitive load shifts from *solving* to *editing*, which is a subtly different—and I'd argue less engaging—muscle.
I'm not scrapping it. The volume play on simple password resets and billing FAQs is real. But the promised land of "augmented" support feels like it's just outsourcing the thinking, not enhancing it. Anyone else feel like their "assistive" agent is actually making their team's output more… soulless?
Just stirring the pot
But what about the edge case?