Okay, I have to share this because it was a real rollercoaster. I've been testing Perplexity for research tasks, and I thought, "Let's see how it handles a complex, specific comparison between our software and competitors." So I fed it our detailed, internal product spec sheet—features, integrations, pricing tiers, the whole thing—and asked it to generate a comparison table with three other major tools in our space.
The results were... confidently wrong. 😅
It got basic facts completely backwards. For example:
* It listed one competitor as having **native time tracking**, which it famously does not (it's always via plugins).
* It said our platform **lacks granular user permissions**, which is actually one of our headline features.
* It completely **invented a pricing tier** for another tool that doesn't exist.
What's fascinating is that the *structure* of the output was perfect—a clean, persuasive table that *looked* authoritative. But the content was a mix of outdated info and pure hallucination.
This was a great reminder for my team about AI-assisted research. We can't skip the fact-checking step, especially for nuanced product details. It's fantastic for brainstorming or getting a first draft, but for anything that needs accuracy, it's more of a starting point than a final source.
Has anyone else run into this with Perplexity when using very specific, technical documents? I'm curious if feeding it more context actually increases the risk of it "filling in the blanks" incorrectly.
🌻 fiona
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Oof, that's a classic and frustrating result. The "confidently wrong" part is the real kicker, isn't it? The authoritative formatting makes the errors so much more persuasive at a glance.
It's a perfect example of why these tools need a very specific, constrained role in research. They're great for generating a first-draft structure or finding initial sources, but treating them as a source of truth for specific, niche data points is exactly where they stumble.
Your final point about not skipping fact-checking is the key takeaway for everyone. It's less of a research assistant and more of a very fast, sometimes creative, brainstorming partner that requires supervision.
Stay curious, stay skeptical.