Samar Abbas, Temporal | theCUBE + NYSE Wired: Business Transformation Edge

Palo Alto studio connection Silicon Valley and Wall Street. I'm John F co here with Dave Volante my co-host. [music] Hello, I'm John Furry your host of the cube. We here in the cub's NYC 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 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 basis here is the co-founder and CEO of temporal technologies temporal just recently announced some big news big funding thanks for coming on Great to see you. >> Yeah, thanks a lot, John, for having me. Like excited to be here. >> We were just talking a little history lesson down memory lane 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. Yeah. The hyperscalers, AWS, Azure all winning more revenue there. You got the rise of the Neoclouds now called AI clouds that like the NeoCloud name something called Neocloud Labs. Now you have the enterprises eyeing in kind of the this next wave where they saw the value of coding. Agents are coming right along fast in the enterprise. So they're going leaning into deployment strategies for capex. We're seeing that clearly and they're not going to spend billions of dollars like a neo cloud, but they will connect to and put on premises AI factories that'll spawn new applications, create new user expectations. Everybody wants the AI. You guys are in the middle of it. >> Yep. your valuation is really a significant I think template and and a sign of what's coming. Explain the news and why that happened. >> Yeah. So before I go into the news, let me give you like 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 coding agent all of that was powered by temporal and um so this is where what we have been trying to do is like as especially uh software when it runs for longer period of time it interacts with the outside world There 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. >> Explain what people are buying because I think this is points we'll get to the news. I think the momentum and the value proposition justifies why the big numbers. What is the reason? What's 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, um 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 um as these models get 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 uh take those actions to make sure they don't cause any harms. So um and this is exactly the reason why um 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 uh which is a 350% increase uh compared to a year ago. >> So you're talking about the talking meaning the chat bots. 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. >> Yeah. >> You're getting more at work like, okay, go figure this out. Complex problem, organize my email, call my friend, book a flight, more more multi-step activities that require touching more resources. >> 100%. Um 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 task which runs for hours and during those hours all sorts of failures can happen. Machines can restart like or downstream tools can fail or time out or even model 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 do don't redo your stuff and it actually helps us with saving tokens also. You know I was talking to an engineer who works at Stripe recently and was not on camera was like a off thereord 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. What? is where 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 it's he's like it's all broken. It's exciting. People are deploying and 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 how what that means for you guys because that's the problem that everyone's trying to solve right now. And um 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. Uh this is like whenever the 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 uh infrastructure to make sure you can run an application in a cloud with all of the necessary guard rails 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. >> The press loves to talk about, oh, it's off the rails. Agents gone rogue. I've heard that we need a kill switch. We don't need a kill switch. Um, so there's a lot of negativity around some of the failures in agents, but there's a lot of positive examples um happening. Um, what's your reaction to that? because you you're seeing a bifurcation of people going well AI I'm 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 um let me first address like the negativity comment that you mentioned I think a lot of fear which is coming in is uh I completely understand where uh it's coming from But if you double click on especially let's say the last uh few months all of the incidents which have been coming out in the news uh for instance the hugging phase uh 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 uh 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 um 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 off 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 go it goes rogue. And then the second capability temporal ads is all of those actions are recorded before they happen which means it gives a uh 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 uh so that's how you have this chain of who did what >> and uh 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. 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 and um 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? >> I think that's Yeah, that's exactly the direction that we are we are headed. Uh 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 industrywide standard how asynchronous communications happens in those larger enterprises. So as uh these agents get more and more longived this is exactly where our investment on project access will be super differentiated because it becomes the backbone how agents talk to each other. I think you're the first uh interview guest I've had on the cube that used the word namespace. So congratulations. You [laughter] you get the award for namespace. Namespace is for the folks watching is a very simple definition. Think of like an address book like the man your address at home. It knows things knows where things are and and that's important. I want to just click on that because I think it's a nuance tech point. Yeah. >> But it's the science behind the computer science where if you understand the domains Yeah. and the addressing system discovery, reliability, paths, efficiency. Explain the importance of having a good name space system that or addressing system and why why is that super important? It's uh so 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 it's 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 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 an namespace which gives you a box where you can now start running your workloads 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 like you can >> and you get things delivered >> it gets to the end point outcome >> um I want to talk about your history you and your co-founder have I think it's what I love about this era it's not talked about a in the media is the history of the computer industry and specifically open source has a 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're starting to see the giants shoulders like Uber like AWS you work at Uber a lot of this stuff has been solved 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 lift did the same thing. I mean it's basically you log in to the cloud multi-tenant cloud. You actually have to hail a driver who's not even works for the company. >> Yeah. >> You got to track that person with GPS. You have an account, a database for all your stuff. You got to bring all these things in real time. Now that's a state-of-the-art problem. Go back when the original founding that was really hard. But that was also a marker trail marker for what would be coming to the mainstream. 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. Explain the importance of this. You didn't 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 um those other advancements were and what it means for the AI world. What what happens next? >> 100%. So, uh very good question. So um 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 Maxim uh we've been iterating over this problem for at least 20 plus years now. It started actually at Amazon AWS. So uh where we saw the transformation of an Amazon from a monolith into a serviceoriented architecture and this is where we build simple workflow as underlying kind of application platform to help with those massive serviceoriented architecture to become the reliability layer for building those applications. Then I continued that at Azure where uh I was part of an uh a team at Azure called Azure Service Bus which kind of owns the messaging stack and I very quickly see similarities on how engineers are using messaging as a core underlying 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 uh we uh and among other things >> randomly at Uber or you did they call each other up going to go to Uber go together as a pair random >> it was complete luck essentially like yeah and we didn't we didn't actually stay in touch after AWS and it was just a coincidence essentially so among other things we build um an open-source platform there by the name of Cadence which the whole idea of Cadence is engineers who are composing low-level primitives like cues, 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 problems that you are talking about which Uber needs to solve to provide a best uh ride sharing experience. And this is where both me and Max looked at that and said I think we can we can fix this problem. >> And I think the service 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 microer stuff in cloud native actually map nicely to how agents need to behave. What resource am I touching? Is it the right resource? I mean these are like big questions and you got 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. Um, great success. Obviously, you guys have the track record. You're solving a big problem. What was that that funding round like? Was was did people lean in? Did they understand it? They had what was the what was the pitch? What was the pitch when you were doing the funding? Because, you know, 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, um actually uh let's take a step back. Um look at what has happened in the last 7 months since our previous round. Um we uh we have crossed over 250 million of ARR. Our NDR like net dollar retention is over 200%. Which means uh our customers running on top of our cloud is doubling their spend on us. They're using you and and putting more in. >> Yeah, >> 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 uh 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 uh 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 >> I mean the pitch is you're the connective tissue for reliable resilient applications running on on enterprise or an application >> and basically and this is exactly is what drove a lot of interest in uh these investors at this point emporal is kind of become the default durable execution engine for powering the AI wave. Yeah, it's also I will say that you know in 17 years of doing the cube 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. You got to they got to be resilient. They got to react. They got to make good decisions. It's not a search paradigm. It's like a re it's a work paradigm. And so res 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 someone if you had to explain that >> so uh you have made an interesting point like as an engineer this is the struggle I have seen throughout my I've been in the industry for 26 plus years every engineer when they are tasked with a challenge the this concept of resilience that you are talking about has always been bolted in afterwards. And I think what this AI uh 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 uh in the industry right now. It's exciting because a lot of the old terms come back in vogue. Grid computing, now that's energy. Um, resilience, now that's embedded into everything. You're starting to see self-healing come up. I heard that a few times. Self-healing networks. Remember back in the day, you 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 name space. So, a lot of like the computer science has moved up the stack. what what's your vision on how you take this funding and go forward on the build side uh and uh your customer side what's the focus 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 primitive in durable execution so people can use it for wider and wider class of applications and like for example >> what's the constraint there? What's the constraint on durable durability just more primitives? >> So uh let me give you uh 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 high 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. >> Yeah. I mean durable execution that's an easy cell when you come say hey we provide durable execution like sign me up. I'll that's like who doesn't want better durability? Explain what it means. What does durable execution actually mean? >> Amazing. So um the way I would describe durable execution is today when an engineer writes code or 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's durable 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 [snorts] 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 are we will guarantee that your run your transfer runs to your completion. If people aren't technical, it means that you have to start over. >> Yeah. >> And or it just doesn't work. It fails. Basically, >> start over in this money transfer uh case is not even an option because you you have already lost that money in thin air because you did debited from the >> We could probably put you in our mixture of expert series that we have too because you're we're getting in the weeds here in a good way. um talk about the importance of durable execution as it relates to agents and compare the the importance of what APIs meant on the cloud error because you know APIs didn't really have a lot of state um they were critical for the cloud growth for the services now you got state and agents as you cross these name spaces it's like preserving the envelope talk about the importance of the the data state and having that durability and And and is it is it as big of an impact as APIs were for the cloud? >> I think it will be even bigger impact. Um 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 gave examples like oh booking your next reservation or your vacation or cancelling an order or making a money transfer. These are actions agents have started to take on a person's behalf. And when like 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 thread while they are middle of running a very critical task for you. >> You know, this transformation series uh 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 in you're you talk about money and not just money trans 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. Um what's your advice to a CFO out there when they say, "Well, just bottom line me. Do I make more money with with you guys or not? What would be your answer? >> Uh so is it like sorry making money? Uh >> no because if the system's running it's going to produce revenue. >> Oh 100%. Yeah. Yeah. Yeah. And by the way for instance uh last year in October we there's a bunch of cloud provider outages happen. And this is where the impact of not having a reliable system was so clear because then like for example Alaska runs their bookings on top of us. While their systems were down they were not taking any bookings. Uh 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 taking uh bringing in new revenue essentially. So uh this is exactly >> and they can stay up with you guys >> and this is where we have invested into uh features like multi-reion name spaces 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 n uh level of nines that you are looking for. Mark, congratulations on the big funding 5.550 million half a billion over half a billion uh validation really valuation shows validation. Congratulations. Thanks for sharing on the cube. Thanks >> talking name spaces agents really the connective tissue that's 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 has to will come in. It'll come in through the entrepreneurs and the engineers working hard. This is the Cub's Transformation Ed series. Thanks for watching.