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11 results for “user expectations”
...the consumer expectations. What we learned was chat interfaces are very powerful, but they're very limiting to do daily work. Why are they limiting to do daily work? Because our kind of end users expect the software to do work. So they essentially wa
38:57 / 40:04
from transcript38:57 – 40:04
...expectations. What we learned was chat interfaces are very powerful, but they're very limiting to do daily work. Why are they limiting to do daily work? Because our kind of end users expect the software to do work. So they essentially want workflows,
38:14 / 39:16
from transcript38:14 – 39:16
“Dating apps fail because users expect to find their soulmate in days”
...So expectations have to be lower. Because when you go to a b two b fair, you don't expect to find your partner there. But you might but that's that's
22:40 / 23:13
market insight22:40 – 23:13
...user, but how you get to that magical TEDx. Let's take the concrete example of ITSM, IT service management. This has traditionally been the domain of powerhouse company ServiceNow. I chatted with the head of IT recently who told me for the first time
11:03 / 12:17
from transcript11:03 – 12:17
...is basically taking a lot of extra effort to train whichever AI app it's using to have as much context about their behavior and how they perform their work as humanly possible. These will utilize larger context windows. These will utilize memory that
4:22 / 5:34
from transcript4:22 – 5:34
...of our users are they don't care too much about the technology because they're trying to get away from the technology. They're trying to do their day job, and the technology is trying to avoid them having to do some things, whether it's legal or regu
13:29 / 14:40
from transcript13:29 – 14:40
memories, just explicit preferences, if you set them up, do definitely affect the results you get. Now, again, obviously, they're they're still using traditional search. So the search index itself is not necessarily personalized, but you can definite
29:08 / 30:25
from transcript29:08 – 30:25
Ultimately, maybe where this ends up is, like, there's no single Chativity. Every single person kinda has their own, right, their own fully personalized experience. And I think if you're, like, a marketer who's, like, how do I measure this stuff, tha
29:58 / 31:14
from transcript29:58 – 31:14
Use cases as well. Customer service is one template. Customer service, the, like, ramp use case. We use this internally and externally. Like, our customer support helped openair.com already powered on agent kit and then various other, like, internal
33:48 / 34:57
from transcript33:48 – 34:57
is most legible. And by legible, I mean, you can basically write it down. It's relatively replicable, mostly deterministic, so it's more likely that AI will do it well. And we actually built the agent, and then we keep a human in the loop. But from t
16:30 / 17:32
from transcript16:30 – 17:32
The second thing is I think that LLMs and search are gonna converge. And so you're seeing that with Google Search where they're having LLM AI overview. You're seeing that with LLMs where they're incorporating maps and shopping carousels and it's conv
59:01 / 1:00:21
from transcript59:01 – 1:00:21
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