0:00We've gotten computer use now to a place where it's faster than the average human. And I think we're getting really close where it is superhuman.
0:07What sorts of tasks do you think are ready to hand over to the agent versus the ones like okay it still requires some checking and correcting computer using agents now since Astra is now capable of doing anything that a person would do. We think a lot about what new consumer experiences can we enable with a faster better model. And then on the enterprise side that's kind of naturally why the safety becomes more interesting. How do we give the ability to control the amount of human the loop there is and then the auditability? It's unlike any other thing that we've built where the developer has to do some work
0:36to adopt it. Someone has to build a connector MCP server. You know, computer use works with everything. Now we have like capable models. They're getting cheap enough to run at scale. What should companies think of automating?
0:46I think of it as in two big categories.
0:48The first category is like Welcome to the A16Z podcast. I'm Sema Amble. I'm joined by my colleague Fbritzio Saraphiniti. In August, we wrote about uh computer using agents and how they're starting to do the real work inside companies. Uh today I'm joined by Ari Weinstein and James Sun from OpenAI um who are going to help unpack what is going on with computer using agents from their perspective and uh share some thoughts on the future. Ari James, thanks for joining us. Of
1:17course, happy to be here. Yeah, thanks for having us. Ari, kick it off and tell us a little bit about um what in Astra has made computer using agents move forward and what what's really unlocked.
1:28Yeah. Um so Astra's an amazing model.
1:32It's good at so many things. Our computer use models were already so good before Astra, you know, like Soul itself is amazing at computer use. So um Astra really helps with a few things around the edges in my sort of anecdotal experience. One is it is a little bit faster on average because it uses fewer thinking tokens to do the same task.
1:54It's better at certain kinds of creative work like for example we had this demo where um in our launch video where you were talking to it and it's drawing things on Microsoft Paint. Um it's way better at that sort of thing which I think probably transfers to other kinds of creative tasks also. And then the last thing I find is it's just more reliable around the edges. Like you know it's kind of I feel like I trust it a little more. like it's sort of the kind of thing where there's a little difference that is hard to perceive but really important between something being 99% reliable and 97% reliable. And I
2:24feel like it's sort of just a little a little higher in a way that feels uh pretty pretty concrete.
2:29Yeah. And I think adding on to some of those things, Astra is also our most aligned model. Yeah. Right. And so, you know, talking about trust a little bit.
2:36Um you know, if you look at the system card for it, it is much better at being resistant to prompt injection. um it's much better at not taking any kind of um unintended actions. And so when you think about it for like enterprise work, especially for companies using it for sensitive things, whether it's like procurement or you know talking to vendors or talking to customers, it's going to be just a you're going to feel a lot safer kind of using it and that's really really exciting. And then so some some fun things on the creative side. I think internally we had um you know
3:06Astra play video games against uh you know 5.6 and it wins every time. And so there are some cool tweets that people have made where, you know, Astro is able to beat Fallout in like 30 hours or something like that. And so it's also just really amazing at playing video games. So I don't know that probably translates to something, but yeah, it's very exciting.
3:24Maybe just to double click on that point, um consumer versus enterprise use cases of metering agents, very uh very different implications around kind of like all the scaffolding around I would say the um computer using agents. How do you guys think about where things are more exciting between consumer and enterprise if if you were to pick?
3:45I think you know our goal at OpenAI is really about building products that's useful for everyone. And so um you know actually it's interesting because Ari is definitely more of a consumer guy here and I spend a little bit more time on the enterprise side. Um I think the consumer is always the place where we try to push the frontier on what's possible. uh you know uh with Astra like Ari mentioned there is it's a much faster compared to the previous models and so we think a lot about like what new consumer experiences can we enable with a faster better model and then on the enterprise side that's kind of naturally why the safety becomes more
4:14interesting because I think the enterprise whenever we talk to large companies I think the use cases for comput is actually fairly obvious right inside enterprises there's lots of legacy software that doesn't have any MCP tools they are software that's been used for like 15 20 years and so there's and and and a lot of times it's actually kind of hard to use for a normal person.
4:35right? Lots of like UI that is like from the last, you know, decade. And so you don't even know how to operate some of the key key key things. And so we've seen companies build skills that kind of teach the model to be able to use them better. And so I think maybe the way the way to think about it is enterprise is where, you know, the capabilities have been there maybe for a little bit longer and the companies are catching up trying to understand how to deal with it and consumers where we're trying to figure out the next types of use cases that's not maybe possible today with software.
5:04Maybe you can share more.
5:05Yeah, I mean the consumer use cases are so fun for me because it's kind of like how can you put your agent to work doing the things in your daily life that are so annoying and save you tons of time and just have more time to focus on the things that um that you're excited about. Um I think it's been really fun to see dot uh where you know each dot gets its own computer and you can ask it to do things for you in the cloud. Um it gets a full web browser. It can buy things for you. can um you know book haircut appointments
5:34and uh you know anything else you wanted to do. So um so that that's been really fun and I think there's a lot more on the horizon. That's going to be really fun.
5:43Yeah. Know that was going to be my question on on on dots. I think James you probably use a dot to walk through product feedback. It would be cool if you could share share more about it or I'm just so curious to know on on your end guys like how are you using dots and like how does computer use play into kind of what you can do with them.
6:03Yeah, I mean I think dots is really cool for a few reasons, right? One is like really proactive and so um I've been very surprised a lot of times when in both my personal life and work when dots will just flag something that um I just completely slip through the cracks, right? Just the other day. So internally like on our our email system whenever we get an external email for an invite it doesn't actually show up on our calendars and so I end up missing a bunch of like external meetings and so dots now is like catching these things
6:31for me. It's like oh there's this invite that's in your inbox. It's not on your calendar. Do you want me to like accept it in your Gmail so it shows up? So that's been a lifesaver. It's a small thing but it matters a lot. Um, but I also have it proactively kind of looking at I think it's really good at proactively looking for tasks where it's the shape of it is not super uh, let's say concrete every single time. So, an example that I also haven't set up to do is um we use Slack internally and there's there's a ton of messages that's
6:59going on at all times and uh I used to have this Slack job uh using automations and codecs that's like every hour or every 30 minutes go and try to pull things and I've just ended up tuning out a lot of the notifications because it's just like sometimes useful sometimes not. With DOTS, I can give kind of a high level goal. It's like hey if anybody in my reporting chain says anything flag it to me, right? if anybody who's giving some critical feedback, use your judgment uh about certain products, go for it. And then because it has a cloud computer, um you
7:28know, I've had this pretty cool workflow where when someone reports, they usually have like a sentry log. I could have it go use the cloud computer, um you know, actually drive my local local browser while the DOS's going to control both your local computer as well as the cloud computer. Log into Sentry, pull the logs, analyze it, give me feedback. And so it's saving that entire loop of figuring out which feedback is important, looking at it, then going to Sentry, downloading the logs, feeding into codecs, asking for thoughts, and all that can now just kind of be
7:58automated. And so, um, yeah, DOS is great for for at least these proactive and kind of longunning tasks where they're not the same shape every single time.
8:05We talked a little bit about reliability, speed, token usage, and efficiency. How do you guys think about balancing all these things uh as you uh as you keep making improvements on what what you're releasing? I think we're really excited about computer use at OpenAI and we've invested in it a lot and we've gotten to a place where I think we have the fastest, cheapest and most reliable computer use product. Um, and I think there's actually so much further we can take that. Um, we spent a lot of time looking at speed. You know,
8:35speed is really interesting because on one hand the power of computer use is it can do tasks in the background. So in some cases it doesn't matter how long it takes because you can be going going and doing other things while it's accomplishing the task for you. But also sometimes you want to watch it to make sure it does it correctly. You need to wait for it because it needs to complete this before something else can happen.
8:53And so the speed is so important because um you know you don't want to get this feeling like oh I could have just done that myself and it would have been so much easier. So um you know we've gotten computer use now to a place where it's faster than the average human at using a computer. And I think we're getting really close to a place where it is superhuman, meaning it is faster than an expert computer user like probably one of us at this table. Um, and I think that's going to actually be a sea change when that happens. I think it's going to
9:21change the way we all interact with computers because all of a sudden anything that you you know that that you could do manually, it could do faster.
9:28So unless you really want to do it yourself for some reason, which I think actually there may be many reasons people would want to do that, but in a default case, you probably just want the agent to do it for you. And I think that's going to let us build all kinds of cool user experiences. So speed is something we think about a lot. And then obviously we have a strategy of offering multiple different models at multiple different you know qualities and price points. And so for different use cases you may want to use a different model.
9:50Um at the same time our um our less expensive models are getting much better at computer use over time. And so I think there will actually be more variation over time in which models people want to use for which tasks.
10:01adding on saying like I think another thought is like how do we give customers you know control over the safety reliability autonomy versus speed right like if you have like you know when when the model is slow you can kind of watch it do stuff but then you're limited to that to the task that you can do because you can't just sit here watching the thing doing it like it's actually less effective right because it's slower than than you um but once you can get to a point where you can no longer observe and audit everything it's
10:30doing um how do we give especially enterprises and businesses the ability to control um the amount of human the loop there is and then the auditability right like I think a few months ago it's part of access a few months ago it's part of Astra you know we we kind of launched a set of enterprise controls that let um businesses choose one like how much human in the loop is there like do they want the agent to automatically approve everything we have this really awesome system called guardian right or auto I think auto approve in the app
10:58that uh is a really smart model looking at every single action that the computer use agent is taking to decide if it's safe it's if it's aligned so there's no intent um a consumer might be like I just want it to do everything and I don't want it be asked for approval whereas an enterprise is able to kind of decide which type of actions actually go through and so I think the the the control part becomes more and more important as our computing agents become also superhuman and doing things totally I think as you try to you know
11:26roll out more enterprise use cases I think employers They're excited about the efficiency, but they're also, you know, wary of like what is what are what's sort of being unleashed.
11:35Maybe even on the other side, have you guys seen the response from application software around okay, now there's computer using agents accessing my legacy workflow software and how do you do you guys think at all about that?
11:49Are you more focused on just the the agent that's being used by the you know consumer enterprise user? M yeah I think there's like I think this problem becomes really interesting on the open web actually. I think when it's like within software that is like approved and used by the company it's actually more straightforward because it's like oh yeah 100% we want to have uh people automate and do work in here that they don't have to do tediously themselves.
12:16But when it comes to the internet, I think you kind of have a few different camps of folks, right? One is we run a our business model is not in line with having agents use our product, right?
12:27You think about advertisers, publishers whose business model is entirely on advertisement. If the agents using the website for them, then where's the ad revenue coming from? And I think most places a agent's ad impression does not actually count towards real uh revenue.
12:42Um and so that's like an interesting question that we're always working through and working with our partnerships team on. Um there's another question kind of around um for the companies who do really want to embrace having computer use agents using their sites. A lot of them are adopting kind of standards that let humans or people and agents to be able to use it together. So like WebMCP is a standard that we're really excited about. We we added support for in the app browser.
13:06And so you can kind of imagine these scenarios where the agent is elevating the experience of using the site, but it's not entirely replacing it. So like I think browsing the internet is still very fun in my opinion, right? I still like doing shopping. I still like looking at all the hotels and flights and places. And so, you know, you can you can imagine places where um the the agent does all the tedious work, but it kind of carves out an user experience where you're doing the browsing be like,
13:35"Okay, now I want to finish the the transaction and then put in my credit card and do all this stuff, then you can hand it back to the agent." And so, Web MCP is kind of an interesting way where your interface with the website is still the site itself versus an API, but then the person is kind of using it together. And so, those those are some thoughts.
13:51Yeah. Shifting gears, we want to double click a little bit on what it means to do the job or for get the end to end job done. Um, we'd love to hear a little bit from you guys around, you know, what works well. How do you guys define the right the right narrow repeatable task uh ver you know and what sorts of tasks do you think um are ready to hand over to the agent versus the ones like okay it still requires some checking and correcting as the on the user side. M I mean generally I found
14:19the model to be pretty capable to do anything that you can do on a computer now like um and and you know one exercise that I try to force myself to do um is that whenever I have a task the first thing I think about it is just can I just have the agent do it now there are obviously some sensitivities around you know if I'm sending a message to someone I want to feel like it's coming from me um but in general I think the way I think about it is the computer using agents now since Astra um is now capable of doing anything that a person
14:45can do and uh there are questions around I think before of like oh there are some like squishiness around like specificity and requirements I' I've generally found that the model is getting pretty good at whenever you're asking it to do something and there's some vagueness it will actually you know with Astra I think we launched this like uh flexible input right and so it will actually ask you about hey like I want some details and if you don't answer in time it'll just keep going and then pull the context that's necessary I think there are some things around you know if you
15:14have repeatable workflows it's nice to be able to kind of define, you know, the the requirements early, similar to like writing a product spec. Um, but in general, I I generally feel like unless there is something incredibly sensitive that you want to be in the loop for, I I just reach for the computer model for everything I I do now. I'm curious if the same for you.
15:34I Yeah, it is. I'm I'm trying to uh uh, you know, build that impulse to to reach for it because, you know, it's so good and sometimes it's so easy to get locked into the old way of doing things. Um I um I think the really cool thing about computer use as a technology is the universality of it. You know it works with every application. It's unlike any other thing that we've built where you know the developer has to do some work to adopt it. Someone has to build a connector MCP server. You know computer
16:03use works with everything. And it works by using the application the same way a human uses it. Um, which I think is something worth understanding if you haven't spent much time with this technology. It like it computer use uses computers the same way a human does. It makes the agent have all the capabilities you do. Um, which I think is so powerful.
16:23Yeah. And I guess like adding on to Ari saying like part of it is like I think over time I've stopped thinking about it as like am I using them on like a computer use task or a non-computers task. Frequently they're like connected, right? Like the way we think about computer use um is that like computer use is not like a thing you pick up and just say I want to do something with it.
16:42It's really like the universal kind of API that the model has to do whatever it takes. And so if you have an ambitious task and you want the agent to do it likely the more complex it becomes the more likely it will probably touch computer use at some point in that journey. Um, and so like maybe the only time that I I don't reach for computer use for some cases is if the task is so simple that then it's like easier for me to just go and like click two buttons
17:10and do it. But you know as computer use gets faster even faster then the question becomes maybe I don't need to do that I just you know drive voice and it just uses the computer with me. Um so those are some interesting thoughts there too. Yeah. Do you think there's anything you have to share with like an enterprise user to get them comfortable with that? Obviously, you guys are totally pilled on computer use, but you know, I think there's obviously like hesitance sometimes on enterprise user of like, okay, well, yes, the human would click through it and probably do it worse, but uh there is that feeling
17:40of like there's accountability and and you know, that person's trained and all you know, all the classic kind of rebuttals. I'm curious have to convince people around.
17:50For sure. lots lots of conversation with enterprises kind of over the last little bit and I think the the main thing is we think about it as two layers right the first layer is like how do we create deterministic controls I think that's really what gives um you know enterprises a lot of feeling of safety is when they can even though our model is the most aligned ever and it's I think better you know better than most people at you know protecting against prompt injections and things because it's like just you know the intelligence is so smart but um I think there is just
18:18a feeling of safety when the enterprise admins can basically say for certain task or for certain data sources just too sensitive to be used. Um and so we see kind of enterprise so we launched was two things right one is the ability to be able to deterministically create a sandbox around your agent. So being able to say it can use certain apps it can't use other apps it can use certain websites and not other websites. And then two is you know this kind of part of a human in the loop like what type of actions does it require a human to um be
18:48interveneed? And so we might say, okay, for anytime there's like a download and upload, a person has to kind of approve it. Anytime it goes to a new website, a person has to approve it. Now, again, these are all like dials an enterprise can kind of go through. And so it's really like that's one. And then two is really just showing the enterprise admins just how you know all the evals that we've run internally around how aligned these models are even compared to like you know both internal and kind of third party um evals. I think there's also some baseline stuff that we do
19:15across the board to just try to help people build trust with these kinds of products. You know, we know it's so new.
19:21It's such a magical and sometimes alien experience for people. And so, um, you know, we put a lot of work into the design of the product. So, you can always see the cursor if you want to watch it perform a task and it sort of animates in a fun way so it's not boring to watch.
19:36Um, and then like Jame was was saying, this is very, um, customizable for enterprises, but also for a regular user. You know, we ask you for permission before using a new application or website. Um, uh, depending on which sort of modes you're in. And, um, I think that helps people sort of not feel like it's going to go do some runaway stuff on their computer.
19:55You kind of want to have this trust building mode moment where you figure out what it feels like and what you um, want it to do for you and then um, and then you sort of feel more comfortable over time. The Codex cursor is so cute.
20:06I love it's like such a I know it's a small detail, but like watching it use the computer gives you like confidence and it makes the experience nice. So I think there's a kind of like a user experience point. Uh that's that's worth uh uh that's definitely worth investing on. And I guess I'm curious like in in a broader sense like okay now we have like capable models they're getting like cheap enough to run at scale.
20:32In your view, what should kind of companies think of automating? Like what would you what where do you see the most promising kind of use cases within enterprises? Are there some workflows?
20:44Maybe something around the ERP, maybe something around kind of u how like again humans and agents can work together to get tasks done. But like if you had to like pick where where are you most excited to see your models perform uh in the world like Yeah, I guess like from my perspective, I'd love to hear ours. It's like two two I think of it as in two big categories.
21:04The first category is like automating you know tedious workflows. That's like the more boring one and I'll give us some boring examples like boring boring as opportunity.
21:13Opportunity. Yeah, exactly. Um like ERPs is a really big one. Um and so all the all the acronyms you can think of ERPs, CRM, all the systems of record.
21:21Yeah. Every single system of record, right? And so we know we've seen folks you know procurement software like you know you're going to vendors and every year you're ordering a bunch of lab equipment uh instead of having this giant spreadsheet with like a thousand rows that then the ops team so it's like you know work companies like normally what they have done is you they have this giant spreadsheet that gets filled out by the teams themselves. Then an ops team takes that giant spreadsheet puts it into an internal you know procurement
21:49software and then that gets like you know finalized as a bunch of lines and then a sales team then goes procurement team then takes that giant software output and then goes out and reaches out to vendors. um computers can automate all of that, right? And so like procurement is a big one we see. Um finance is another really interesting category we've seen and so uh you know there's a lot of different ledgers within a company right and so you have like ledgers for expenses ledgers for all these things and so at the end of the month there's a lot of
22:18reconciliation and a lot of these recon financial software don't have APIs to be able to quickly pull things. Um, and so the finance team being able to have computer use, look through all these ledgers, reconcile, pull out anything that's like interesting, um, to flag either to a person or then do some investigation. Also a very boring but useful workflow. Um, for our sales team, a lot of sales teams uses a lot of different software for like transcripts, for getting data, all these kind of things. And so having computer use go
22:48and do prospecting and then going and uh putting that into a CRM or some kind of like you know outreach software and then all that. So all the system records is the boring part. Um and then like market research is another one that we see a lot. Um and so you know in my free time I've been building this like uh video annotation software for for Bmon. I pull out of Bmon and like I like to film myself playing the game and then uh having the agent kind of go and and look at stuff and I was like okay how do I
23:18make this thing really useful there's some software out there for like pickle ball for squash for tennis and so I just had computer use go log in create an account on these soft on these softwares try it take screenshots give me feedback and then try to build it back into the app and so these are all kind of like tedious workflows that could be done and then I think the some of the more like interesting creative work of like enabling more ambitious work is like, you know, we talked about um the model now being really good with like visual
23:45visual design. And so um circuit design, you know, being able like architecture work, hardware engineering, game design, these are also areas that I I think we're really excited about where Astro can take. Um less, you know, less common for enterprises to think about those right now because they're thinking about the boring opportunities. But I think as folks understand the capabilities of model more, that's where, um I think we'll we'll kind of see more usage next.
24:09But curious if any thoughts. Sorry.
24:11Yeah, I think kind of similarly on the consumer side, there's a lot of things where it's sort of automating drudgery or just doing things you don't want to do. It's filling out DMV forms for you.
24:21It's helping you uh unsubscribe from a bunch of emails in your inbox. Um and then I think there's also things that are more like um I'm I'm hearing from a lot of people stories of people doing things that they just wouldn't have time they wouldn't have had time or wouldn't have thought to do otherwise.
24:36like I don't know for me personally I'm um uh maintaining spreadsheets about my finance and spreadsheets about meal planning and uh I have a friend who's a personal trainer who's making customized things for his clients and um you know some of these things um would just be so so time prohibitive to do in your in in in your personal life. Um but this makes it so easy. Um I use Apple Numbers which is like a obscure spreadsheet program but the model still knocks it out.
25:00I don't think I've ever heard someone use Apple Numbers.
25:03It's a surprisingly great spreadsheet software. Um and then I think there's a third category of thing which I'm kind of the most excited about which is just starting and I think you know on the horizon you know um which is really just having a different way to use your entire computer or interface with software. I think you saw in our Astra ad uh really cool examples of people just talk to their computer with their voice. It's such a natural way to use your computer and I think over time we're going to see the form factor of
25:32software itself change due to this technology and I'm I'm really excited about that on that point. Okay, form factor of software changing. Um if imagine if you're an enterprise user or you've used you're used to using whatever clunky ERP from you know 30 years ago. Um there's a world in which you now, you know, unleash uh a set of agents that just operate that software and you don't really care. Um there's another world in
25:59which um folks are a new like AI native player is using computer using agent and I'm curious if do you think the world is going to go more in the direction of like keep the legacy folks um and just have this layer on top or do you think you know computer using agents can absolutely be part of uh new software players and this is something I think a lot about so I'm curious to get get your guys' thoughts. It is such an interesting moment where simultaneously the cost and complexity of creating new
26:29software is so much lower. So you can't imagine software changing so much but also there exists so much legacy software in the world. The computer use is so well suited to interact with. So I expect both of those things to continue for a long time. You know if you look at the software that's in production today a lot of it was written 10 20 30 40 years ago and I I I don't think that that stuff's going to go away overnight.
26:49I do think that in some way the existence of computer use um uh puts may put more pressure on companies to make software work better with agents because all the software is going to work with agents by default and I think webc is a great example of this and I think we'll see more stuff like that.
27:06Um so yeah, I I sort of expect both to be to be super important. Um but I I do think it'll like kind of shift over time. Um what do you think, James?
27:15Yeah, I I I agree with you. I think it's like um the there the the way there's like a lot of arts and craft and you understand this because Ari built beautiful product with his team. the cursor was all in. Um, and so the uh um I think there's like a lot of art and craft into building like great products that people can hold in their hand. And um I don't know like for me if we go if the internet becomes just this like faceless, you know, thing that is just agents
27:44talking to each other and and people are not using anything anymore. I would be very sad. Um, and and I I don't think it will be like that because like there's like something about craftsmanship and art artisan software that's like just feels nice to use because the person who designed it really really understands um like the experience that the customer wants to have. So like my wife loves is recently got into playing this like uh you know board game. I I forgot the name of it. It's where you connect like five pebbles to like win. I think it's like
28:13Omach is the name of it. And so anyway, uh so she's trying to get good at it because she's playing online with friends and it's getting her ass kicked and so I was like, "All right, I'm going to build you like a tactical trainer for um you know, going through different gambits so you can like get better at it." Like that's for example something that like I you know created a first version. I was like, "Oh, I know like she likes to do it in a certain way. She likes these type of uh ways to learn more than others." And so I was able to like, you know, craft the software to be something that feels really good for
28:42her. And like these kind of personalized software, I I know it's like a thing maybe today still feels like only really tech people will do. But I think if you like think about this a few years out, it's like if anybody can build anything and they can build these really craft software in a very short amount of time for like niche use cases that are like so well tailored for people, I think that's a beautiful world. Um, and again, you know, at the end of her training,
29:10the lessons and mistakes she made, that could be an agent that summarizes it and gives her in text format, but when she's actually playing with the with the AI and and and and trying to get better, that's something that the person has to do. So I do think it's it's um I I'm more I'm bullish that I I don't think UI is going away and and uh and I think kind of a little tangent to your original question, but I I do think that um the pressure of cheap software will make it so that software has to be better. Um but I don't think it will just be like yeah everything will have
29:39an MCP and an API and you know comput will never be useful.
29:43I love this point so much. I think that like humans are so hardwired for direct manipulation. you really want to be able to, you know, move and and and do things with your own hands. Um, and I I think that it's really exciting to think about how software in the past was so oneizefits-all and had to be, you know, often uh a lot of the software we interact with every day is designed for millions, tens of millions, hundreds of millions, billions of people to use. And I think we will enter an era where any piece of software could be designed for
30:11a hundred people or one person and um just how much more uh personal and and and unique that kind of software will be.
30:20Yeah. I my mental model is I think there's probably two buckets. One is on the consumer side you've got um either something you just get you you get joy out of you enjoy using or you learn from. There is this it's not the utility of it. It's the joy of interacting or learning or whatever it is and you want to spend time on the on the B2B side.
30:41You you may want your agent to complete a bunch of the tedious work, but you also there's this concept of like the audit log like and you that could be personalized in how you want to interact, but the product really is me as the human user setting the goal and then being able to like understand the logic but not necessarily need to run through like the entire chain of command of how it happened. And so like any B2B user still needs to figure out okay like why did that payment get made and go back in and get a summary of what happened and be able to say okay pay
31:10this person at this time um yeah at 30 days this this much um discount should be applied etc. They want the agent to take care of like the execution of it but they want to be able to at some level like some level of control still needs to be put put in there and I think that's like something that does require a UI of some sort. Um and it has to be I think if our it if we're moving more towards believing that um AI will do more of this that part has to be enjoyable to use too, right? Like why
31:39not? Like why should we settle for shitty software?
31:42You know, it's I do think it'll be really interesting to see if we and I I'm optimistic that we will see new kinds of software where it has traditional user interfaces but is also using agents under the hood. And then maybe sometimes those agents are themselves using computer use to automate legacy software by giving you some much nicer more purpose-built experience. I'm like really excited for for that class.
32:05Yeah, it's kind of like the one where we like to use internally like the shared intelligence layer, right? Like you have your agent using legacy software somewhere else and doing things other places. You like if you're using an application, the application wants to get access to that context so it's able to deliver a better experience. It's like I think if we had every website has its own agent that doesn't talk to your agent, it's it's a very fragmented world. And so figuring out like how that plays together where the agent can plug in and and use your other software, I
32:34think it's going to be like a really um interesting thing to play out over the next few months.
32:38I love that you guys Yeah. talk about this because I I think it's so underappreciated the importance of like human AI interaction, especially if you want like a product to be successful. So like being thoughtful of like how can I kind of like humans are used to collaborate. So you want any agent to be able to like kind of fit into the team.
32:56I'm just curious like if you apply that to a new startup let's say you're like I don't know starting a company tomorrow and you want to use computer use to like um solve a workflow within the enterprise. How would you think about it? And uh would you be kind of what would be the things that jump to mind in terms of like oh I want to know when it fails well. I want it to be able to communicate with people or I want it to be like a I don't know a black box just like maybe if you had to talk to founders right now what advice would you
33:25give them as they try to use your models and capabilities to just solve problems for enterprises. In my mind, it depends on it depends so much on the modality of you know are you trying to are you a small team and you want sort of individual on the team to be able to use some piece of software that that you're um that that your team is using but in a more efficient way. Um or are you maybe
33:54building something that itself wants to interact with existing software in which case maybe you have some you know machine in the cloud somewhere that's uh doing computer use in the background I think that will really affect the modality of how you want the human agent collaboration to be right um and um yeah you know in the former case I think a lot of our products are serving this use case um you know where you sit down at chatbt and uh you know there's a lot of great uh you collaboration you can have
34:21there. Um and in the other case, you know, maybe you're building something with with the API. Um you're you're um uh doing doing your own computer use implementation. And then uh yeah, then it really is interesting to figure out when when do you want the human to be in the loop? Is the agent telling you when something's wrong? Is it telling you when something went right? Uh you know, is something summarizing that so that you don't get bombarded with notifications saying, "Hey, this happened. This happened. This happened."
34:46Which actually you're going to ignore.
34:48Um um I don't know. What do you think, James?
34:50Yeah, I mean I I you know, both Ari and I were startup founders before we joined OpenAI and so you know I'm I'm still very bullish on startups. You know I think the question right kind of comes down to like what is there still a mo right? Is there something that startups can still tackle while labs are are doing things? I mean in general I just think there's like like two two things like one is like I think there's so many things to build right and like even though we're quite big now thousands of people we are still feeling very stretched thin internally and like you know it's like the teams are not very big for all the problems and so if you
35:20have a problem that you really deeply understand you have industry expertise you understand how regulatory works the go to market motion how to service the those customers um it it is still I think a very green field out there and um the the tools that that you have through our APIs like Ari mentioned with computer use. Um I think I think we'll still let you accelerate and speed really I think at the end of the day speed and pay is kind of the mode that that exists today. Um I think the other thing I think about a lot is like there are in my opinion still a lot of like
35:49vertical industries where um the diffusion of AI is like much slower. And so um you know uh I was talking to a company the other day who uh uses computer use to help restaurant groups to you know take pictures of like their back storage you know and then using that the the vision looks at kind of like what is going to be missing based on a projection of tomorrow's traffic and then it takes that to then use computer use to go to like a shopppee or
36:18some kind of like procurement software to then order your groceries for the next day. Um and then based on that it will go into your ERP to adjust like the timetable for your like employees who are um who we might need more people to help because in the last year at this time of the day um there was a lot more traffic coming in from like like a holiday or something like that. And so like you know those restaurant groups are probably not like tech companies that are um super you know familiar with
36:47all the tools are available. And so I think like you know living in San Francisco we see a lot of thinking wow like you know labs can do everything the codecs and like you know why doesn't everybody just install codecs and just have it do stuff but like for the average American and the average small mid medium business owner the average enterprise um even understanding what the tools are capable is one connecting tools in a way that makes sense is two deploying it is three servicing is four and so there's still a lot in my opinion where if there there are complex workflows that require a lot of disparate software computer use is a
37:16great way to join them complete the entire intend flow and then building it in a format and UI that is feels good to hold um for those customers feels still like a really really big opportunity that um you know we I think is still open right tell us about what's next what's what are you excited about um that's on the frontier that you can share around uh around computer using agents well I' I've sort of gestured towards it already but we're really excited about speed we're really excited about making
37:45computer use superhuman and Um, we're really excited about things that blend together different kinds of interfaces that bring together sort of multimodal inputs and outputs. Um, so you can have more kind of fluid experiences with your computer. I think right now a lot of our computer use product is very background focused. It's very much like um, let me give the agent a task. So it can do that while I do something else, which is actually a tremendous strength, right, of the product. But I think that in the future we'll also see more of this like real time collaboration between you and
38:14the agent. Um, so I'm I'm really excited about this area. Um, and um um and other otherwise just uh sort of better, cheaper, more more available, easier to use, more Yeah, exactly. Being able to actually access everything. Yeah. I think I think there is, you know, we with DOTS, right, we're we're giving folks these like computer in the cloud. Tragic work also has a browser in the cloud. I think honestly like for for me like one thing I'm excited about is just making the experience feel a little bit more more
38:42coherent. Like you know today you can install the Chrome extension and it that uses your like password manager and everything in Chrome and then we have an inapp browser in the desktop app which has a different set of cookies and different passwords. Your computer in the cloud also has different things and for the average consumer it's confusing.
38:59It's like why do I have these four different browsers that all don't talk to each other? If I open up a tab in one does it like show up in the other? And so like I think a lot of um what I'm excited about is how do we make computer use go from this product that is used by like enterprises and like really hardcore tip of the spear kind of users to something that's actually understandable for for people. It's kind of like an oxymoron because I think computer use is actually the most easy to understand AI product because right it's an AI using your computer but then
39:28because of the like uh complexities of like the different like states you have to manage and the different places you're using it the implementation details sometimes seep through and then it becomes kind of hard to gro and so um being able to kind of make that consumer grade and easier to understand more more coherent um is something I'm really excited about next quarter yeah and I think it it comes back to the point that there is still a human that's setting off the agent right and they have to the the the better the UI and controls and the easier and more
39:56enjoyable it is to use, the more they're going to get out of it. And that's absolutely principle. On that point, one other thing I want to gesture towards is um I think another challenge of the product today is you you have to put some thought into how you're going to use it and you have to remember to use it and you have to um convince yourself to do things that are different from how you're used to doing them. Um, and I do think, um, dots, like James was talking about earlier, um, have this really powerful proactivity where they can sort
40:26of come to you and identify situations and and and and, um, and and help you solve problems. I think we'll also see a lot more proactivity. I'm really excited about a world where the agent can sort of adapt to you instead of you adapting to it. Um, and I think that we're going to see a lot of that and I think it will um make it a lot easier for people to actually like relate to and u and and understand and incorporate this technology while also um still being the ones sort of setting and searing the the the goals if that makes sense.
40:56One of the things we haven't talked about yet is the momentum behind computer use and how much has changed and Fitzi and I chatted a little bit about this in in our piece. would love for you to just kind of talk about where it's, you know, how it's the trajectories so far and where things are headed.
41:11Yeah, I mean James and I have been working on computer use for some time now um at OpenAI and it's been an incredibly exciting past like six to nine months, right? Because we started working on these computer use products and um very few people were using them. um the models um all of a sudden it felt to me became great at these kinds of tasks um earlier this year because of amazing work the research team did and then we've been working super hard with a bunch of teams internally on how to
41:40create actually good product experiences around this and then just in the past couple of months all of a sudden you know the product's growing like crazy and and people are really seeing the value in it um but I think it's still so early you know it's still the case that only um some you know portion of our user face is using computer use and um I think we're going to see it uh grow quite a bit.
42:02Yeah, totally. I mean, you know, I joined OpenAI in January and I was I joined working on the Atlas product and love love Atlas, RIP Atlas, but the uh the I think you know, one of the things that we realized was um in the Atlas product, the agentic experience, I think for a few reasons, wasn't actually like a big selling point. Not many people used it, partly because I think most people treated it like a normal browser.
42:26Um, and over kind of the last few months because the model capabilities have gotten better. We've now incorporated browser and browser use into kind of all of our existing products where there was already a gentic usage, we've we've just seen, you know, it's like YC level of growth week over week and then always surprised by how fast it can go. And I think this next like big inflection point is like cloud, right? Like how do we like desktop is still very much a power user thing. I know we probably use our desktop all the time, but like most
42:54most consumers are on their phones, right? And so um how do you give every single chat user, how do you give everybody who's just using their phone for their day-to-day life um a powerful computer that they don't even need to understand how to use that it just kind of makes things work for them. And so really excited about how that kind of brings it to, you know, billion users.
43:14It feels like computer using agents have had a ton of momentum behind them and now it's the moment of like, okay, how do we get it into more people's hands?
43:21they trust it, they feel like they can really use it. And your experience your point earlier about coherent experiences like that's that's a real I think once as that gets a lot better, I think consumers will feel more comfortable using it and and it'll feel more natural.
43:35I think that's right. I think I think we're at the scaling moment of computer use both for consumer and enterprise. Yeah. At the same time. Um and I'm Yeah. really excited to see where it goes and what people build with it.
43:48Well, thank you so much for joining us. This was awesome. Um, we love talking about this topic and it was really fun to hear it from you guys directly.
43:55Thank you. A lot of fun as well.