Name: Samar Abbas, Temporal
Uploaded: 2026-08-02T07:00:00.000Z
Duration: 28 min 24 s

More from theCUBE + NYSE Wired: C-Suite Business Transformation

Samar Abbas

Co-Founder & CEO

Temporal

John Furrier

Co-Founder & Co-CEO

SiliconANGLE Media, Inc.

Info

Samar Abbas, Temporal

Samar Abbas

Co-Founder & CEO Temporal

John Furrier

Co-Founder & Co-CEO SiliconANGLE Media, Inc.

HOST

(INTRO)

John Furrier

>> For your host of theCUBE, we're here in theCUBE's NYSE studio, of course, we have our Palo Alto studio on the West Coast connecting Silicon Valley to Wall Street. This is our Transformation Edge series where we talk to the leaders who are building technologies and are part of the massive transformation that's being enabled by AI and AI infrastructure infrastructure, but more importantly, the software that's being generated to run the AI will change our lives for the better, to be safe, reliable. That's the focus today is to talk more about not just the productivity, but the safety. Samar Abbas is here. He's the co -founder and CEO of Temporal Technologies. Temporal just recently announced some big news, big funding. Thanks for coming on, Samar. Great to see you.

>> Yeah, thanks a lot, John, for having me. Like, excited to be here.

John Furrier

>> We were just talking a little history lesson down memory lane almost almost a decade and a half ago, about Amazon Web Services and the rise of the cloud. Now we have the rise of AI infrastructure, which is helping everybody. The rising tide floats all boats. The hyperscale is AWS, Azure all winning, more revenue there. You've got the rise of the NeoClouds, now called AI Clouds. They don't like the NeoCloud name, something called NeoCloud Labs. Now you have the enterprises eyeing in kind of this next wave where they saw the value of coding. Agents are coming right along fast in the enterprise. So they're leaning into deployment strategies strategies for CapEx, seeing that clearly. I mean, they're not going to spend billions of dollars like a NeoCloud, but they will connect to and put on -premises AI factories. That'll spawn new applications, create new user expectations that everybody wants to AI. You guys are in the middle of it. Yep. Your valuation is really a significant, I think, template and a sign of what's coming. Explain the news and why that happened.

>> Yeah. Yeah, so before I go into the news, let me give you a high -level intro about what we are, because then it will explain things. So Temporal is an open -source platform which ensures durable execution of your code. What that means is today, if you woke up and published a Snap story, or ordered a Taco Bell, or used OpenAI as a coding agent, all of that was powered by Temporal. And so this is where what we've been trying to do is, like, especially software, when it runs for a longer period of time, it interacts with the outside world. Our outside world has lots of failures, failure modes there. And during the execution of that software, people can lose their... Software has always been losing their place, essentially, when those failures happen. So now what we do with temporal is if that software is built on top of us, they will never lose their place.

John Furrier

>> Explain what people are buying because I think this is a good point. So we'll get to the news. I think the momentum and the value proposition justifies why the big numbers. What is the reason? What is actually being powered? Are you powering the app? Are you powering the infrastructure? What specifically are you guys enabling and accelerating for your customers?

>> So, especially if you look at in the last 18 months, what has fundamentally happened, AI has stopped talking and started doing stuff. And this is exactly where temporal is super differentiated, is as these models get smarter smarter and smarter. When we talk to an organization, you always hear that. That when an agent runs longer, takes more action, does more stuff, it creates more value. It's super clear to those enterprises. And guess what? Temporal is the layer which is making sure that these agents can do that reliably, and most importantly, securely take those actions to make sure they don't cause any harms. So, and this is exactly the reason why we have seen an amazing growth of those actions on top of our platform. Even in the month of August alone, we have processed over 1 .9 trillion actions, which is a 350 % increase compared to a year ago.

John Furrier

>> So you're talking about the talking, meaning the chatbots. We know AI when we first used it. Hey, you know, tell me about this, write the story for me, give me some marketing material, search for things. That's search. You're getting more at work. Like, okay, go figure this out, complex problem, organize my email, call my friend, book a flight, more multi -step activities that require touching more resource.

>> 100%. A very good example is, for example, coding agents. As these models are getting smarter, what we are seeing is these coding agents are now taking on more and more complex tasks, which runs for hours. And during those hours, all sorts of failures can happen. Machines can restart, or downstream tools can fail or time out. Or even models can return an error. These models have a pretty high error rate. So how do you remember all of that state? This is exactly where temporal comes in to manage all of that state for your agent So they don't lose track of it and don't don't redo your stuff and it actually helps out the saving tokens also You know, I was talking to an engineer who works at stripe recently and was not on cameras

John Furrier

>> like a off -the -record conversation So I won't say his name. He said these agents are great. People are deploying them like crazy They're seeing value as you pointed out. He says but there's a big problem I go, what? He goes, well, they're basically calling the main models and paying for the tokens, and they're running it like in a production environment. That's like us building a payment gateway and running it in production. Yeah. The sandbox, the test dev environment. So he's like, it's all broken. It's exciting. People are deploying and are leaning into it. They're enthusiastic. But they have to use production -like resource and costs to do the test dev. that kind of brings up the IT transformation kind of connection, which is, hey, I want to just build this app and I want to automate a lot of these things. I want to create that value. But I got to like observe it. I got to have telemetry. I need to do all these, you know, tech things under the covers. Sounds like that's what you guys are doing. Explain what that means for you guys, because that's the problem that everyone's trying to solve right now.

>> And I hope so, by the way, that everyone starts to solving, because this is becoming the problem. If the industry does not get it right, we might screw up the entire AI platform shift that we are seeing. And by the way, this is not a new problem. This is like when the cloud platform shift happened, we saw the exact same excitement with the cloud platform shift, but then industry came around and, to your point, made all of those infrastructure to make sure you can run an application in a cloud with all of the necessary guardrails and protections which won't cause any harm. And I think the AI industry, as the AI is now moving from just providing you answers to actually taking real actions on the behalf of a user, they absolutely need to start putting in all of those guardrails.

John Furrier

>> The press loves to talk about, oh, it's off the rails, agents gone rogue, I've heard that, we need to kill switch, We don't need a kill switch. So there's a lot of negativity around some of the failures in agents. But there's a lot of positive examples happening. What's your reaction to that? Because you're seeing a bifurcation of people going, well, I am scared or doom and gloom. And then you have another half saying this is the best thing we've ever seen. It's a life -changing experiences. Societal benefits are off the charts. What's your reaction when you see this kind of polarization?

>> So let me first address the negativity comment that you mentioned. I think a lot of fear which is coming in is, I completely understand where it's coming from. But if you double click on especially, let's say the last few months, all of the incidents which have been coming out in the news. For instance, the hugging phase, like hack, which happened during an open AI testing, which is all over the place now. Yeah, everyone uses that one. Yeah. So if you kind of dig into it, one thing becomes absolutely clear. There is a pattern emerging. That when these AI agents takes actions, pretty, one of the things which we don't have in place is auditability of what that agent is doing. And in my opinion, that's one of the biggest gaps which is out there right now. So this is exactly the place where temporal is differentiated, is when you build an agent using temporal as an underlying platform, each and every step or action an agent takes, it's durably recorded in what we call as a execution history of that agent and nothing there is no way anyone can come in and interfere with it because that's how with the platform works in natively basically nothing is of the books everything is recorded durably and every time that agent is taking an action before it takes an action it's durably recorded there and then you have an audit log which you can use by any auditors to actually chase what that agent was doing when it goes rogue. And then the second capability, temporal ads, is all of those actions are recorded before they happen, which means it gives an opportunity to that organization to put on their own guardrails, which could be a human kind of approving that action or a business rule executed somewhere which might reject it. And so that's how you have this chain of who did what.

John Furrier

>> And this is the role that - It's like rules of engagement too. You have everything laid out. What's interesting about when I hear you talking, I get excited because there's a lot of parallels and it's kind of a history lesson to be learned here. If you look at AWS early days of cloud where you have history, a lot of the higher level services that Amazon ended up coming out with weren't even invented yet. I mean, the basic building blocks of AWS were a dream scenario for a startup that didn't have any cash, put their credit card down. Everyone knows that story. Shadow IT emerged. You could actually get stuff done with those simple things, but then higher level services came out. I mean, when you're talking about ages, I could see new things emerge like agents for agents. I mean, I talked with Jensen and NVIDIA team all the time about how they're using simulations simulations and synthetic data, you can almost predict things. So you're starting to see, as it gets out there and more adopted, what's your vision on that? What do you see that's possible to make things more reliable, more predictable, more safe?

>> Yeah, that's exactly the direction that we are headed. We have some customers who are already running over 5 ,000 namespaces on top of Temporal Cloud. We are kind of basically, namespace is our unit of isolation where people, they run their own workloads. So, what that means is we are already starting to become the API boundaries on how those organizations talk to each other. We have a project called Project Nexus, which is trying to create an industry -wide standard how asynchronous communications happens in those larger enterprises. So, as these agents get more and more long -lived, this is exactly where our investment on Project access will be super differentiated because it becomes the backbone how agents talk to each other.

John Furrier

>> I think you're the first interview guest I've had on theCUBE that used the word namespace so congratulations. You get the award for namespace. Namespace is for the folks watching is very simple definitions think of it like an address book like the man your address at home and knows things knows what things are and and that's important I want to just click on that because I think it's a nuanced tech point yeah but it's the science behind the computer science where if you understand the domains and the addressing system, discovery, reliability, paths, efficiency, explain the importance of having a good namespace system or addressing system and why is that super important?

>> Think of namespace as an envelope where we give you an envelope and use that envelope to run your specific application within that envelope. And it gives you complete isolation from anything else. And especially important because Temporal Cloud is a multi -tenant cloud service. What that means is today we are completely hiding all of the infrastructure from you. What you come in and create an account on Temporal Cloud and then when you want to build an application, the first thing you build is a namespace, which gives you a box where you can now start running your workload and activities inside. The reason it's important is how do you guarantee one namespace does not interfere with the workload or performance characteristics of another namespace? And that's where this envelope becomes really, really interesting because it gives you complete isolation from performance standpoint. And you get things delivered.

John Furrier

>> It gets to the endpoint. It gives outcome. I want to talk about your history you and your co -founder have. I think what I love about this era, it's not talked about a lot in the media, is the history of the computer industry. And specifically, open source has a saying, standing on the shoulders of giants, meaning because it's open source code, you can build on top of code. Great. We love open source. But you start to see the giants' shoulders, like Uber, like AWS. You worked at Uber. A lot of this stuff has been solved for these early first movers that had to build their own system. Let's take Uber, for example. I mean, they literally had to build the app that we all love and use, lifted the same thing. I mean, it's basically you log in to the cloud, multi -tandem cloud. You actually have to hail a driver who's not even works for the company. You've got to track that person with GPS. You have an account, a database for all your stuff. You've got to bring all these things in real time. Now, that's a state -of -the -art problem. Go back when the original found it. That was really hard. But that was also a marker. trail marker for what would be coming to the mainstream. So in a way, a lot of the innovation that you're doing and others have been there and the market just hasn't evolved yet. And now it has explained the importance of this. You just wake up one day and say, Hey, I'm going to start temporal. Yeah. Talk about the importance of the trajectory of the industry and why those other advancements were and what it means for the world. What what happens next?

>> 100%. So very good question. So, by the way, there are kind of founders who sometimes wake up one day, they have an idea and then they build a company around it. Both me and my co -founder, Maxime, we've been iterating over this problem for at least 20 plus years now. It started actually at Amazon AWS. So where we saw the transformation of an Amazon from a monolith into a service -oriented architecture. And this is where we build simple workflow as the underlying kind of application platform to help with those massive service -oriented architecture to become the reliability layer for building those applications. Then I continued that at Azure, where I was part of a team at Azure called Azure Service Bus, which kind of owns the messaging stack. And I really quickly see similarities on how engineers are using messaging as a core underlying lying primitive to build essentially reliability or resiliency into their apps. So I kind of continued my same journey and built durable task framework at Azure. And then out of coincidence, both me and Max actually ended up at Uber. Where we, and among other things. Randomly at Uber, or did they call each other up? Are you gonna Uber, or did you go together as a pair? Random? It was complete luck, essentially, like yeah. And we didn't actually stay in touch after AWS and it was just a coincidence essentially. So among other things, we build an open source platform there by the name of Cadence. With the whole idea of Cadence is engineers who are composing low level primitive like queues, databases, retry mechanisms, and durable timers to build resiliency into their applications. And 80 % of the engineering was actually going, composing or stretching those things together rather than focusing on the actual problem that you are talking about which Uber needs to solve to provide a best ride sharing experience. And this is where both me and Max looked at that and said, I think we can fix this problem.

John Furrier

>> And I think the service -oriented architecture is a great way to talk about AI now because AI is essentially a bunch of services. These agents are services. And a lot of the microservices stuff in cloud native actually map nicely to how agents need to behave. What resource am I touching? Is it the right resource? These are like big questions. 100%. You have to think these through. So let's talk about the success. You got $550 million, over a half a billion dollars in capital raised at a $12 .55 billion valuation. Great success. Obviously, you guys have the track record. You're solving a big problem. What was that funding round like? Did people lean in? Did they understand it? What was the pitch? What was the pitch when you were doing the funding? Because there's a transformation story here. There's kind of an IT on steroids story. There's an agent story. There's a lot of things happening. in your world.

>> Yeah. So actually, let's take a step back, look at what has happened in the last seven months since our previous round. We have crossed over $250 million of ARR. Our NDR, like net dollar retention, is over 200%, which means our customers running on top of a cloud is doubling their spend on us. They're using you and putting more in. They're expanding. They are expanding. And then we have over 4 ,300 now customers running as cloud customers, essentially. So I like, and by the way, we don't get paid for AI enthusiasm. The thing we make money on is when these AI agents essentially or applications take real actions in the outside world. And this is where August alone, we processed over 1 .9 trillion actions in a single month, which is up 350 % compared to a year ago. So I think that is...

John Furrier

>> I mean, the pitch is you're the connective tissue for reliable, resilient applications running on enterprise or an application.

>> And basically, and this is exactly is what drove a lot of interest in these investors. At this point, temporal has kind of become the default durable execution engine for powering the AI wave.

John Furrier

>> Yeah, also I will say that in 17 years of doing theCUBE, the word resilience was also either a backup and recovery discussion or security. Resilience now is built into all applications as a standard feature because like you mentioned, these agents can't go rogue. They gotta be resilient, they gotta react, they gotta make good decisions. It's not a search paradigm, it's a work paradigm. time. And so the word resilient has kind of been moved into the mainstream, cyber resilience, AI resilience. How would you define the word resilience if someone says, hey, I need AI resilience? What would be your response to that? If you had to explain that.

>> So you have made an interesting point. Like as an engineer, this is the struggle I've seen I've been in the industry for 26 plus years. Every engineer, when they are tasked with a challenge, this concept of resilience that you are talking about has always been bolted in afterwards. And I think what this AI wave or platform shift is showing us, the world cannot operate in that world. Especially what's been happening in the last few months is people have to think about reliability of their systems from grounds up when they are building it rather than bolting it later because otherwise that's how you see all of the incidents that you are seeing in the industry right now.

John Furrier

>> It's exciting because a lot of the old terms come back in vogue. Grid computing, now that's energy. Resilience, now that's embedded into everything. You're starting to see self -healing come up. I heard that a few times. I'm self -healing networks member back in the day. These agents have to heal and react on their own and make decisions. Repair, oh, I don't do that, but roll back, do this, talk to this agent on that namespace. So a lot of the computer science has moved up the stack. What's your vision on how you take this funding and go forward on the build side and your customer side? What's the focus?

>> Yeah. Yeah, first of all, a lot of funding is going to go into R &D, which is we need to keep on doubling down on durable execution, although we are clearly the leader in that space, but we are very aggressively investing into more and more primitives and durable execution so people can use it for wider and wider class of applications. What's the constraint there?

John Furrier

>> What's the constraint on durability? Just more primitives?

>> So let me give you an example. We just shipped a feature called standalone activities. Because now people see the power of durable execution, and it is a no -brainer when you are working on it for a workload which is highly critical or high value. But then people love the programming model. They want to use it for low -value use cases also. But sometimes cost comes in the way, so we are creating more lighter -weight primitives, So people should be able to adopt durable execution from pretty much every workload.

John Furrier

>> Yeah, I mean, durable execution, that's an easy sell. When you come and say, hey, we provide durable execution, like, sign me up. That's like, who doesn't want better durability? Explain what it means. What does durable execution actually mean? Amazing.

>> So the way I would describe durable execution is today when an engineer writes code, I write a function, and during an execution of a function, if a failure happens, you lose all your state. And what durable execution does is if you now implement the same function using temporal execution capabilities, that function can never fail. Which means if you run a money transfer application, which is a debit from an account and then credit into a target account, what happens if the transaction fails? A machine restarts when it's in the middle. That money just simply disappeared in thin air. What durable execution gives you a guarantee is that function can never fail, which means your transfers can never fail. We will guarantee that your transfer runs to your completion.

John Furrier

>> If people aren't technical, it means that you have to start over. Yeah. Or it just doesn't work. It fails, basically.

>> Start over in this money transfer case is not even an option because you have already lost that money in train air because you did debit it from the...

John Furrier

>> We could probably put you in our mixture of expert series that we have, too, because we're getting in the weeds here in a good way. Talk about the importance of durable execution as it relates to agents and compare the importance of what APIs meant on the cloud era. Because, you know, APIs didn't really have a lot of state. They were critical for the cloud growth, for the services. Now you've got state and agents as you cross these namespaces. It's like preserving the envelope. Talk about the importance of the data state and having that durability. And is it as big of an impact as APIs were for the cloud?

>> I think it will be even bigger impact. Because in the agent world, especially as I mentioned earlier, the agents are now graduating from just giving you answers to taking actions on your behalf. You give examples like, oh, booking your next reservation or your vacation. or canceling an order, or making a money transfer. These are actions agents have started to take on a person's behalf. And when these agents are taking actions, you want this durability layer backing those agents because you want each and every one of those agents to make sure they don't lose their threat while they are middle of running a really critical task for you.

John Furrier

>> You know, this transformation series, to wrap up, it's really originally started around CFOs and business model transformation. It's evolved to essentially all transformation competitive edge because when you get into tokens and agents, you're talking about money. I mean, not just money, transactions. Like there's now value lines of sight into the economics of the results. It's not an IT project. People aren't just getting their apps loaded faster on the screen or some other IT benefit in the past. This is actual real money. And so this is a big transformation story. What's your advice to a CFO out there when they say, say, well, just bottom line me, do I make more money with you guys or not? What would be your answer? So is it like, sorry, making money?

>> No, because if the system's running, it's going to produce revenue. Oh, 100%. Yeah, yeah, yeah. And by the way, for instance, last year in October, there's a bunch of cloud provider outages happened. And this is where the impact of not having a reliable system was so clear. year because then, for example, Alaska runs their bookings on top of us. While their systems were down, they were not taking any bookings. Taco Bell, every order that you place at a Taco Bell is a temporal workflow. While if you have a system which is down, you are not bringing in new revenue, essentially. So this is exactly - And they can stay up with you guys. And this is where we have invested into features like multi -region namespaces, which allows a user from just like a click of a button, completely migrate their workload to be powered out of a completely different region, and actually we support it across different cloud providers also. So if, depending on the availability requirements of whatever underlying workload you are powering and how critical it is, we give you all sorts of availability options to run the workload with the right level of nines that you are looking for.

John Furrier

>> Smart, congratulations on the big funding, 5 .5, 50 million, half a billion, over half a billion. Validation, really, valuation shows validation. Congratulations, thanks for sharing on theCUBE. Thanks a lot. Talking namespaces, agents, really the connective tissue is powering the agents. Everyone wants agents, they want that automation, but you have to have reliability. You need the resilience, you need the safety. That's the top conversation we're seeing today in the AI and it will come in. It'll come in through the entrepreneurs and the engineers working hard. This is theCUBE's TransformationEd series. Thanks for watching.

Samar Abbas, Temporal

(INTRO)

John Furrier

>> Yeah, thanks a lot, John, for having me. Like, excited to be here.

John Furrier

>> I mean, the pitch is you're the connective tissue for reliable, resilient applications running on enterprise or an application.

>> And basically, and this is exactly is what drove a lot of interest in these investors. At this point, temporal has kind of become the default durable execution engine for powering the AI wave.

John Furrier

>> What's the constraint on durability? Just more primitives?

John Furrier

>> If people aren't technical, it means that you have to start over. Yeah. Or it just doesn't work. It fails, basically.

>> Start over in this money transfer case is not even an option because you have already lost that money in train air because you did debit it from the...

John Furrier