Why don’t more AI tools understand what matters to you?
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Why do knowledge workers struggle to keep track of information?
When I first joined Dropbox, I very much wanted to figure out what I was doing here. And so research and trying to read as much as possible was quite important to me. Day to day. The nature of my role in particular is that I'm I'm often juggling many threads at once. And there are times where I feel like honestly pretty bad about myself for not being able to keep track of all this stuff. I don't think I'm alone in that. By the way, I'm not tr trying to bring it to but I think a lot of people like when they are, you know, struggling to keep all the threads like in in their own context, it it can be kind of like frustrating and you know, maybe even like kind of bum you out some of the time.
Yeah, it's very relatable.
It and I don't want that for myself and I think that most people don't want that. So to me, that means that like we can help uh people do their job better in this way.
You are listening to this podcast, first welcome. It probably means that you do a lot of work on a computer. Where getting things done can feel a little chaotic at times.
I'm Sean Michael Lewis, I'm a principal engineer at Dropbox. One of the fundamental hypotheses of using AI for knowledge work is that there's just too much knowledge. How do I find all the information that I care about? I don't know where it was, was it a here or there or whatever.
We're talking about hundreds of tabs in your browser, knowledge that's buried in email threads and Slack, the 30 or more different apps and services where all of your content lives, not to mention the digital bird's nest of poorly organized files that, if you are anything like me, hangs over your entire existence. And it's not just about finding things amid all of this chaos. Answers, information, solutions, you also want to use that knowledge, understand it, and share it with your team.
So w we're looking at ways to give AI to more customers. Uh we're looking at ways to improve the quality of our chats, to improve the quality of our searches, uh and ways to build better context for AI usage more generally.
I'm Matthew Braga and this is Working Smarter, a podcast from Dropbox about how AI is changing the way we work and get stuff done. Over the last two seasons of this podcast, we've talked to chefs, archaeologists, an F1 team and roboticists about what it actually looks like to work alongside AI today.
We're developing machine learning methods in order to detect shipwreck sites. Yes, we're a Formula One team, but we are also just an entity that turns up to work. And I think, you know, AI plays a key role there. There's a nice balance in the kitchen and being able to use AI as a tool but not completely rely on it for everything.
But this season we're going to take a closer look at what it takes to solve some of the problems that make modern work so frustrating and chaotic.
I've always really enjoyed the experience of building something new that you don't quite understand how people are gonna find it useful. There's unique challenges with it. Everyone's getting used to how to use AI and their work and what AI means and how it's useful to, you know, different people and different roles. It's an exciting journey to sort of form that with people, especially as we think about the workplace itself.
That's Nuray Nurani, a product manager at Dropbox who's been doing some of that big picture thinking. Like, what if AI could help you find what you need when you need it, using plain language, just like talking to a colleague? Or make it easier to organize, understand, and share your team's work? What if AI could help you move just a little bit faster and focus on the work that matters most?
Like, hey, how do we actually get back to doing really cool things, really like creative tasks, um understanding people better, understanding um, you know clarity in our work, clarity in our communication, which I think AI like really requires. And uh that's been just an unexpected journey. I think it's really cool to be working on something that the entire world is sort of wrapping their heads around at the same given moment.
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Chapters
8 chapters
1
Why do knowledge workers struggle to keep track of information?
0:00–4:29
2
How does Dropbox define “context engineering” for AI?
4:29–7:59
3
What is “Dash” and how does it connect multiple work tools?
7:59–11:41
4
How does Dash decide where to search first when you ask a question?
11:41–15:08
5
What role does “delight” play in designing AI interactions?
15:08–18:32
6
How does Dropbox keep AI knowledge fresh and up‑to‑date?
18:32–21:47
7
How are relevance and ranking calculated from content and usage signals?
21:47–24:51
8
What future benefits does context‑aware AI bring to creative work?
24:51–29:30
Speakers
2 identifiedMore from Working Smarter
How the people building AI at Dropbox use AI themselves
Protecting your team’s content, wherever it’s stored—so you can safely use AI
Building AI that can search inside videos (and photos and audio too)
How agentic AI works behind the scenes to find the answers you need
Coming soon: Working Smarter season three