Podcasts about Parag

Take the 2026 AI Engineering Survey and get >$2k in credits and AIE WF tickets!On the product side, everyone is getting Computer - Perplexity, Manus, Cursor, and so on. Meanwhile on the research side, agentic evals like TerminalBench and GDPVal are also assuming computer (Harbor). On both ends, the consolidating LLM OS stack has become a standard toolkit, and Daytona is one of a small set of AI Infra companies that are booming because of it.“The end of localhost” has been Ivan Burazin's obsession for more than a decade.Something that is all too familiar…Long before agents became the default way people talked about software development, Ivan was already chasing the idea that development should not depend on a fragile local machine. CodeAnywhere, one of the first browser-based IDEs, was an early attempt at that future: move the development environment into the cloud, make setup reproducible, and free developers from the endless “works on my machine” tax.The thesis was directionally right, but the market wasn't ready yet.However, agents changed that. They do not care about a laptop, desk setup, or favorite editor. They need a computer they can access through an API: something stateful enough to keep working, fast enough to spin up instantly, flexible enough to resize, isolated enough to be safe, and composable enough to run the messy real-world workflows that real software engineering actually requires.Daytona isn't just selling “sandboxes” in the narrow code-execution sense. It is the latest version of Ivan's original localhost thesis.In this episode, Daytona's CEO joins swyx to explain why AI agents need more than code execution boxes: they need composable computers, stateful sandboxes, instant startup, dynamic resources, and infrastructure that can survive workloads going from zero to 100,000 CPUs.We go deep on the new agent compute market: Daytona's hard pivot from human dev environments to AI sandboxes, the New Year's Eve MVP that customers begged for, why Daytona runs on bare metal with its own scheduler, how one customer runs almost 850,000 sandboxes a day, and why RL/eval workloads went from 0% to roughly 50% of usage in just months. Ivan also explains why agents need Windows and macOS machines, why CLI may matter more than MCP, why Kubernetes is painful for this workload, and why the future AI cloud may look more like Stripe than AWS.We discuss:* How Daytona grew out of CodeAnywhere, Shift, and the “end of localhost” thesis* Why Daytona pivoted from human dev environments to AI sandboxes* Why agents need composable computers instead of disposable code execution boxes* The New Year's Eve MVP that customers chased API keys for* Why Daytona chose bare metal, stateful snapshots, and its own scheduler* How Daytona spins up one sandbox in ~60ms and 50,000 sandboxes in ~75 seconds* Why Daytona's biggest customer runs ~850,000 sandboxes a day* How RL/eval workloads create zero-to-100,000 CPU spikes* Why RL workloads went from 0% to roughly 50% of Daytona usage* Why customers compare Daytona against EKS/GKS and say they're “never going back”* Why every AI agent may need a computer, including Windows and macOS environments* The Apple licensing constraints that make macOS sandboxes hard* Why CLI gives agents more power than MCP* How open source helps agents integrate Daytona* Why agent-generated PRs may break today's CI/CD assumptions* Why AI SaaS companies reselling tokens may face a cold shower* Why the AI cloud may look more like Stripe than AWSIvan Burazin* LinkedIn: https://www.linkedin.com/in/ivanburazin* X: https://x.com/ivanburazinDaytona* Website: https://www.daytona.io* X: https://x.com/daytonaioTimestamps* 00:00:00 Hook* 00:01:12 Introduction* 00:03:15 CodeAnywhere, Shift, and the end of localhost* 00:05:58 What Daytona is: composable computers for AI agents* 00:08:07 The pivot from dev environments to AI sandboxes* 00:10:17 The New Year's Eve MVP and customers begging for API keys* 00:12:56 Bare metal, stateful sandboxes, and Daytona's scheduler* 00:17:28 60ms startup, 50,000 sandboxes, and 850K daily runs* 00:21:53 Spiky RL/eval workloads and the new agent infra problem* 00:28:12 RL workloads, Kubernetes pain, and dynamic resizing* 00:33:31 Why every AI agent needs a computer* 00:38:48 macOS sandboxes and Apple's licensing problem* 00:44:28 Why CLI may matter more than MCP* 00:48:11 Open source, GitHub stars, and agent integration* 00:53:11 Git, CI/CD, and agent collaboration bottlenecks* 00:58:15 Founder life and building a 25-person infra company* 01:02:44 AI SaaS, token resale, and API-first business models* 01:06:10 GPU sandboxes, data centers, and compute growth* 01:09:48 Why the AI cloud may look more like Stripe than AWS* 01:11:26 Closing thoughtsTranscriptIntroduction: Daytona, CodeAnywhere, and the End of LocalhostSwyx [00:00:02]: Okay, we're in the studio with Ivan Burazin, CEO of Daytona. Welcome.Ivan [00:00:07]: Thanks for having me, man.Swyx [00:00:08]: Ivan, you and I go back.Ivan [00:00:10]: Way back.Swyx [00:00:11]: How I don't even know how, you found, did you reach out or, for Shift.Ivan [00:00:17]: I reached out to you. The reason was you - we were just - we were thinking about I was one of the co-founders of CodeAnywhere, the first browser-based IDE, and so we were thinking a long time of, localhost should die. And you had this article.Swyx [00:00:29]: End of localhost.Ivan [00:00:30]: Then I reached out to you because of that, and then we talked, and I was actually at a different job and learning about I was the head of, developer experience, and you were quite well-versed in that, and I actually reached out to you, among other people, how do we go about that? What are the key things and whatnot at this point in time? And you were nice enough to take the call, and I remember I was late on your call with you.Swyx [00:00:51]: I don't remember.Ivan [00:00:52]: I remember because I was with my then I'm thinking of a girlfriend or wife at that point in time, I'm not sure. It's the same person, so that's great, and I was late ‘cause we were, in, Italy on, vacation, and then I was late for something. I felt so bad, and you were so nice to be, good about.Swyx [00:01:10]: The reason I'm nice is because I'm also late to other people, so it's like, who's, who's without sin here, yeah, so I have to, for those who don't know, InfoBip Shift, there's this whole thing that, you did in the past, and, and that was basically one of the inspirations for me starting AI Engineer, which is like, I have to thank you for giving me that push to be like, “Oh, you can, you can build and sell conferences?”Ivan [00:01:34]: I remember you asked you asked me at the beginning to give me advisory shares, and I was so focused on what we were doing, I said no, and I should've took the advisory shares. So I'm sorry, dude. But anyway.Swyx [00:01:43]: We're not, we're not venture backed.Ivan [00:01:44]: No, it doesn't matter.Swyx [00:01:45]: It's Yeah, anyway, so I think what's impressive about you is that CodeAnywhere is the thing that you've been trying to build, and, you kind of put it on hold and then came back after InfoBip. Just give us the story, do you - the story and the origin story, going into Daytona.From CodeAnywhere and Shift to DaytonaIvan [00:02:05]: Sure. Like, really way back, me and my co-founder have been together. I say this, I've said this multiple times, it's like we were married and divorced and married. Some people actually ask me is my co-founder my partner. they thought it literally. It's not literally, but we have done multiple companies together, and to your point, we had this shift where we went from the CodeAnywhere to the conference called Shift, and then back to, Daytona. We originally started stacking servers, doing like virtualization in the early 2000s and, routers and doing basically all these things, at a foundational level, and that was a services company which we sold to focus on what my co-founder actually invented, which was the very first browser-based IDE, right, I say the first. Before us was actually Heroku. They did it for a very short time until they became Heroku. But outside of them, we were the only one, and it was called.Swyx [00:02:55]: There was Cloud9.Ivan [00:02:57]: Cloud9 came out slightly after us. There was Replit, which came out when we stopped doing it, Replit came out, and they have been successful since then, which is great. There was Nitrous.io. There was quite a few that existed at the time, but it was like too early. But the interesting part is that we, at that point in time, because there was no VS Code, there was no Kubernetes, and Docker had just started when we Or I'm not sure if it was even public at that point in time. And so we had to build everything to the whole stack ourselves and that was the key learning that we brought into and that we've been using in Daytona today. So it was super early. There's about 3 million people used CodeAnywhere. It was slightly, it was angel-backed more than venture-backed. We ended up paying everyone back because it didn't have that sort of scale. But, three years ago, we started something similar with Daytona, which is not what we are today, but it was automating dev environments for human engineers, the basically the underlying stack of CodeAnywhere. And then we did a hard pivot last January to sandboxes. And so here we are.Swyx [00:04:01]: Historic pivot, yeah, and, it's one of those things where, I had independently invested in CodeAnywhere, but also in E2B, and then both of you pivoted into the same thing, and I'm like, “F**k.”Ivan [00:04:12]: You invested, you invested in Daytona. You invested in Daytona. But you were the first If we had not got your check, we wouldn't have done it.Swyx [00:04:18]: No way.Ivan [00:04:19]: No, it was like, “We have to get him on board first,” and you were that kicker that we, that got us off the ground.Swyx [00:04:23]: No, because you were putting me on your pitch deck, man. I was like, “Man, this is like a good trip if I don't invest.”Ivan [00:04:29]: That's because it was your quote. It's like we.Swyx [00:04:30]: Yeah. It's the end of localhost.Ivan [00:04:31]: Did a bunch of research about end of localhost and who was interested in that,.Swyx [00:04:34]: No, that's like, I put, I wrote that blog post, and every single company in that field reached out to me, and then every VC who was receiving those pitches then also had to call me and, talk it, talk through it with me.Ivan [00:04:47]: It's finally happening though.Swyx [00:04:48]: It was really super interesting.Ivan [00:04:48]: It's finally happening.Swyx [00:04:49]: It's finally happening.Ivan [00:04:49]: Yeah, it's finally.Swyx [00:04:49]: It's finally happening, with maybe sort of non-human users. Yeah, so what is Daytona today? Let's get like a quick description. I'm wearing the shirt.What Daytona Is Today: Composable Computers for AI AgentsIvan [00:04:58]: You're wearing the shirt. Yes,.Swyx [00:04:59]: It says, I think your branding is very good. Like, it's very consistent. It runs AI code. Like, it cannot be simpler.Ivan [00:05:05]: Exactly, but we're gonna probably have to change that.Swyx [00:05:07]: Oh, s**t.Ivan [00:05:07]: It's also a subset of what we do. Unfortunately, we really love this, Run AI Code is super simple. People interpret it different ways. I think we've given out 5,000, 6,000 of these shirts. People wear them with pride because it doesn't really market about us.Swyx [00:05:21]: Yeah, Daytona's on the back.Ivan [00:05:22]: It markets the back. It markets to the person itself, so I think we did a really good job on that one. But it is also a subset of what we do, because people, when they think about Run AI Code, they just think about these small, let's call it isolates, code execution boxes that, you send some code, you get an output. Whereas what Daytona is today is essentially composable computers for AI agents. It is, the market calls them sandboxes which can be misleading.Swyx [00:05:44]: All these things. All these things on.Ivan [00:05:45]: Yeah, exactly, ‘cause it can be misleading ‘cause people usually think about sandboxes as a demo or a test environment versus a production-grade environment. But what Daytona does, if you think of the laptop that you have in front of you or the computer that's over there, or, my wife is an architect, so she has like a Windows with a 3D graphics card inside to do 3D rendering. Like, as humans, we have different computers or different compositions of computers. And our belief is strongly that agents today and going forward will need all these different compositions of computers to do different types of tasks. And so we offer that basically through an API.Swyx [00:06:19]: Yeah, to give people - I'm trying to sort of front-load all the aha moments or the wow moments so that people can, stay engaged and click like and subscribe. the market is exploding, right? Like, you have been reporting 74% month-on-month growth, and it also, it's just been growing for a while. Like, it's been going like this. And every single - It's not just you guys. It's every single.Ivan [00:06:41]: Everyone, yeah.Swyx [00:06:42]: Sort of, compute provider. I don't know if you agree with me saying compute provider or not.Ivan [00:06:48]: It's fine.Swyx [00:06:48]: Yeah. So like organically PLG-driven growth, but also enterprise is doing super well, I think I wanna rewind to January of last year when you did the pivot. Like, so you obviously called this market early, and you were positioned for it, and you are now one of the market leaders. But what was the insight that made you do the pivot?The Pivot: From Human Dev Environments to Agent SandboxesIvan [00:07:06]: The insight that made us do this pivot is the quarter before that, so end of 2024, when we had - Basically, we did a demo with - I don't I think we discussed this as well, Devin was not public. You actually gave me access to Devin at that time. So Devin.Swyx [00:07:25]: I did?Ivan [00:07:26]: Yeah, you gave me access.Swyx [00:07:26]: I don't think I was supposed.Ivan [00:07:27]: Yeah, exactly.Swyx [00:07:28]: Yeah, I.Ivan [00:07:28]: So it doesn't matter. You.Swyx [00:07:29]: Yeah. I gave like three friends access.Ivan [00:07:31]: Yeah, or it was a call and you showed it to me. It doesn't matter. but OpenDevin was available, which is now called OpenHands. And so we're like, “Oh, this seems to be a thing. This is not public. Let's take our for human automation of dev environments and take, OpenDevin and launch that as a SaaS.” And we did that. Not very many people signed up and used it, but a lot of people reached out that were building agents, and they were like, “Hey, my agent needs a compute sandbox runtime,” whatever you wanna call it. I forgot what it was called at that point. And then we were like, “Oh, amazing. This is a new market. Here is our infrastructure. Here's our product, and go.” And what we found really fast, soon, was that people did not like what we had built. It didn't work. And I remember talking to people at the beginning when we're doing this, the sandbox we're building for agents. People were like, “Oh, why is it different? It's the same thing. We have like EC2, we have VMs, we have all these things.” But we saw that everyone we gave it to, it was like 20, 30 people, they all said, “No.” Like, “This is not what we need. This sort of breaks.” And basically, me and my co-founder not knowing a lot about - ‘cause we're infra people. We're not AI people. So I basically took it upon myself to like watch every single podcast that exists, including all of, all of these and all that, and sort of get up to date, read all the blogs, like get, understand what's going on.Swyx [00:08:45]: Do you wanna shout out who else was useful, just in case people are also looking.Ivan [00:08:49]: Generally we -, I looked at There's a few of podcast, different segments and different types. So there's you guys, No Priors, Bill Gurley's was great while.Swyx [00:09:04]: VG2, yeah.Ivan [00:09:05]: Yeah, while it was around. So there's a few. 20VC is interesting from a different dynamic, and some are different dynamic. But there was, also Red Points.Swyx [00:09:14]: We're not really about the compute market.Ivan [00:09:15]: It was also already - Sorry?Swyx [00:09:16]: You're, you want - You're looking at the agent infra market.Ivan [00:09:19]: I was looking at the agent market and the AI market in general and sort of understanding who are the players, what the perception, and how that goes. And like obviously you complement this with like going to conferences, going to events, going to meetups, reading white papers, like doing all the things that you have to do to understand what's happening. And so when we figured, when we sort of had an idea of what we had to build, literally over the New Year's Eve, literally on New Year's Eve, I half vibe coded the first MVP, first minimal viable product of what Daytona is today. And I went to sleep at like 3:00 AM or something like that. I was doing - I just put my like baby daughter and wife to sleep and, Happy New Year's, and go back to just, doing this. And I sent it to my co-founder, my CTO, and he saw it in the morning. He's like, “This is absolute garbage.” “Do not show this to anybody at all, but the idea is good.” And so he took two weeks, and he rebuilt it.Swyx [00:10:09]: Did it like look like that? Listen, I - It was rough idea.Ivan [00:10:12]: Oh, not even, not even close. Like it was it was way worse. But it was like a very - It was a simplistic view of what it should be. Like, it worked, but it was not ideal. And so he went, we went down the whole, which is his job as CTO, to go, and he came back with this version. We then called all the people that had said like, “This is garbage,” a quarter ago. And we set up these calls, and we gave it to - We just demoed it to everyone. And all the calls went long, every single one. They were 15-minute calls, and they all went to like 25, 30 minutes or whatnot. And everyone said, “We need, we want access.” There was no login, just an API key, ‘cause it was just a beta or an alpha. And they said, “Oh, we want access.” And we're like, “Sure, yeah. Okay, thank you very much.” But after like the next day, if we'd not send it, every single one, like every call that we did, everyone came back, “Where is my API key?” Like everyone wanted it. We're like, “S**t.” Like this is it. Like I've never felt So one, the understanding to your point was like most people thought it was the same infrastructure for humans and agents. We understood a quarter ago it's not. We just didn't know what was the right primitive. And then when we came, and we can talk about what that is, and we gave it to these people, I've never seen, I've never experienced - I've done multiple companies in my life. I've never experienced this, that people literally call you if you do not give them access. Like they want access right now. And so it's like, okay, they don't want this. the thing that they want doesn't seem to exist, or they have not found it, and they really want what we want. And then when we understood that we're onto something, and then when you think about the size of the market, like the market for human engineers and enterprise is a very large market, so think GitLab or whatnot. But the market for every single agent that will exist ever in the future is just like, what is that market? How big is that? And we're like, “We are all in on this.” And so that is where we made sort of the cut between the old product and the new one.Bare Metal, Stateful Sandboxes, and the Lambda + EC2 ModelSwyx [00:12:02]: Yeah. But it wasn't composable at the time?Ivan [00:12:05]: It was very - It was basically just a Linux box that you could change, that you could define number of CPUs, disk, and RAM. Like that is what you could do, but you couldn't have multiple operating systems, you couldn't resize it on the fly, you couldn't add a GPU, you couldn't do like all the things. It was just the, just the first sort of variation of that, yeah.Swyx [00:12:22]: Was it bare metal from the start?Ivan [00:12:24]: It was bare metal from the start. And so the interesting thing that we thought about right away, so our.Swyx [00:12:29]: Which, give people the background, what is the normal path?Ivan [00:12:32]: Yeah, so, basically most providers run this on top of VMs. And also.Swyx [00:12:37]: Firecracker.Ivan [00:12:38]: Yeah, they run on Firecracker and VM. And so we also fire - We can get - We have multiple isolation layers and we can do that. But the common way to do it is that they, one, that the state of the machine, or the hard disk is not part of the sandbox itself. And the other thing is they're not meant to last forever. So most of them are preemptible, like they can There's a time that they can live. And so our thought was when we were going into this is, agents will be like humans in the sense of you don't want your laptop to be shut down until you're done with work. Like, and you want to close the lid and open the lid, it's the same state. So you - Agents would want that, like the pause and come back. They want those two things. But also agents really want speed, right? Can they get it? So when we thought about it's like we need something insanely fast, how to make it fast, how to make it long-running, and stateful. And so those two things, it's like combining a Lambda and an EC2, right? Those two things together. And so we didn't have an idea how others did it, ‘cause we didn't know too that there was a market around this. It was more like, okay, this is what we need, what they need. And we looked at Kubernetes, it wasn't wasn't good enough for that. We looked at Nomad, it didn't enable that. And so our history in rewriting our own scheduler at CodeAnywhere is basically what my CTO came up with. Like, he's like, “Oh, the learnings from there,” and he brought it. And the funny thing is, our third co-founder, when he saw it, he's like, “Dude, what is this? This is like 2008.” Like, we went back in time, and he's like, “Exactly.” And so the reason why Daytona is like super fast, and you see this on benchmarks, is we essentially, we run on bare metal. We have our own scheduler, we use the underlying, disk, CPU, and RAM of the underlying machine, which means your IOPS are insanely fast because there's no, there's no network between an EBS or something like that. But also the snapshot, the point in time, the templates, are also preloaded on the bare metal machines. So when you fire off a sandbox from a template or a snapshot, you're essentially directed to the bare metal machine where that snapshot is based on that NVMe drive, and then it literally just turns on that machine, and it's local. There's no network latency, anything on there. And so that is sort of the specificities that we, when we're thinking from first principles, what a computer would look like for an agent, that is what we came up with, and that's what we created.Benchmarks, 60ms Startup, and 50,000 SandboxesSwyx [00:15:02]: Yeah. I should maybe, I don't know if you endorse this, but there's someone that does compute SDK, you guys do very well on there, with like the TTI, right? I. is this a, is this a is this a relevant benchmark for you guys? I don't know.Ivan [00:15:16]: I don't know, and it changes every day. So today RKL is.Swyx [00:15:18]: I don't know what RKL is. Never heard of it.Ivan [00:15:20]: Yeah. RK, yeah, so it is there.Swyx [00:15:22]: You are, at least a third of the next tier of performance, and then, there's a lot of other better-known names that are very slow to start.Ivan [00:15:31]: Yeah. We've been the number one by far for a long time, and now there's different, there's different definitions also of sandboxes, different isolation patterns, different other things. So RKL runs it literally on the S3, the data, so it's very different, and they spin up a sandbox, spin up a container for that, so it's a different type of thing. So the definition of a sandbox is something that we can all, we all need to get along with. But yeah, we're insanely fast on getting these things, up and running. And so you can see even there that it's a zero point 0.10 to 0.11, so.Swyx [00:16:03]: Close enough. Yeah. what else do you need, right?Ivan [00:16:05]: Yeah. So the benchmarks itself, so, in this, in I don't think the benchmarks equate to market ownership or revenue or anything like that. and I've seen this with multiple benchmarks, not just in sandboxes, but in general benchmarks around.Swyx [00:16:20]: It's table stakes. It's just like.Ivan [00:16:21]: Exactly. But it doesn't hurt.Swyx [00:16:22]: Just roughly check.Ivan [00:16:22]: Like you definitely have to be up there and you have to be competing so that people know that, oh, this is definitely one of the top. Because this is only one dimension of what customers look for. There's other things like how many can you spin up consecutively? There's a feature set, there's support, there's like all different things that people look at, but you definitely have to be there, on the benchmarks.Swyx [00:16:40]: How many people do people spin up consecutively?Ivan [00:16:43]: So we have.Swyx [00:16:43]: Or concurrently, is the Concurrency, right?Ivan [00:16:45]: There's three metrics that we look at. And so one is like time to spin up one, and so our time to spin up one is 60 milliseconds with network latency. So request, spin up, reply, 60, the whole thing, 60 milliseconds. That is one. But if you wanna spin up 50,000 at once, we are now at about 75 seconds. So it takes about 75 seconds to spin up concurrently 50,000. Some others, there's public data around this, like take 2,000 seconds, which is 30 minutes. Like there's different variations of that. And then there is the so it is speed of one, speed of like multiple, and then how many can you consistently have up and running. And so we basically have right now no limit to how much we can add because we basically own our own metal. But the biggest customer of ours does like about 850,000 every single day is sort of where they're, where they're just shy of a million every single day that they're running, we do have a request for half a million concurrent, which is literally half a million CPUs somewhere running. So that's an interesting.Swyx [00:17:44]: They pay by like vCPU seconds.Ivan [00:17:47]: By seconds, yeah.Swyx [00:17:47]: Or whatever. Yeah. Okay, and so and then, and the other thing is, the sleeping and the resuming, ‘cause it's all the stateful resumption of all these things, how, what kind of workload are people putting through this, right? Like how is it Do we measure by gigabytes in memory, gigabytes in storage? I don't In like network attached storage. I, what are the costly ones of, out of all these features?Workload Economics: CPU, RAM, Network, and StorageIvan [00:18:15]: The most expensive thing are CPU.Swyx [00:18:18]: Okay. Yeah, of course.Ivan [00:18:18]: The second one, yeah Then it's RAM, then it's disk. We actually don't charge.Swyx [00:18:22]: Which is snapshotting, right?Ivan [00:18:23]: No, it's actually the, snapshotting's part of it, but basically the size of your hard disk, of your machine. So do you have 10 gigabytes, do you have 20, do you have 50, do you have whatever? And then the transference of that. Right now, currently we don't charge for, network at all at Polychron.Swyx [00:18:37]: Oh, you gotta, yeah, you gotta fix.Ivan [00:18:38]: Yeah. It is very much a it's a larger and larger part of our bill, so we're working around, that part there. Obviously, that is the least, expensive, so the hard disk is the least expensive, so it's basically CPU, RAM, for us network, ‘cause we don't charge the customer, and then hard disk, is how it's split up. But there's also different types of workloads, so we basically split it up into two types of workloads in Daytona. One is what we call background agents or long-running agents. and the other is, basically RLs and evals, which I put sort of together. And so they have very different patterns of usage, and if you look at the usage of a background And I'll just name names of companies, not specifically.Background Agents vs. RL/Evals: Two Usage ShapesSwyx [00:19:21]: Yeah, open, all hands.Ivan [00:19:23]: Yeah. So like a background agent's a Cognition, a Lovable, a like all these things are Harvey. These are all long-running, background agents. And so if you look at their usage patterns, their usage patterns are similar to human, which is like follow the sun. Basically, the usage patterns of that is like noon is probably the highest, and the midnight is the lowest, and then weekends are lower. weekday is higher.Swyx [00:19:42]: Yeah, that's a fun question. How global is it? Is it very US-centric or?Ivan [00:19:46]: The US is a large part, but we have currently, we have Asia, Europe, and the US regions.Swyx [00:19:52]: So it's quite global.Ivan [00:19:53]: Yeah, it's quite global. We have it all over. It's interesting that our I talked to you a bit about this. Our number one city by user.Swyx [00:20:01]: Hmm.Ivan [00:20:02]: Is Singapore.Swyx [00:20:04]: Oh, wow. Amazing.Ivan [00:20:05]: Which is an interesting one, right? Not by revenue, just by just like by individual head count.Swyx [00:20:09]: Really?Ivan [00:20:09]: Just like an interesting thing.Swyx [00:20:10]: Singapore is, Singapore is weirdly high in the adoption charts of AI for the population. It's like an, seven, eight million population. And it's like keeps showing up.Ivan [00:20:20]: No, it's quite interesting. We were quite shocked, and I was like, “Oh, this is interesting.” And also one that's up there.Swyx [00:20:24]: There's a reason I'm doing AI using Singapore. it's because I'm from there.Ivan [00:20:27]: We're there. We're gonna, we're gonna be there as well. and it's interesting that Japan is in the top or like Tokyo's in the top, which is in all the tech cycles it has never been. It has never been, so it's quite interesting that they're.Swyx [00:20:39]: I think the Japanese just love AI. Yeah. It's that, and then it's Brazil. That's it.Ivan [00:20:44]: Brazil has always been in.Swyx [00:20:45]: I think.Ivan [00:20:46]: Even when I look, if you look at like GitHub's data and ask historically with CodeAnywhere, it was always like US, Western Europe, and then you'd have like India, Brazil, China, like that would be there. But like Singapore was not in, specifically Japan was never in sort of that top, that top.Swyx [00:21:01]: Yeah. Weird pockets.Ivan [00:21:01]: Weird. Yeah, so it's very global.Swyx [00:21:02]: Okay, so actually that, but that's helps you to distribute your load through, all time?Ivan [00:21:08]: The interesting thing is like we have those kind of loads, but if you look at the researcher loads, they're quite different. So what they are is like if you give them concurrency of 10,000 or 50,000 or 100,000 CPUs at ARMb, when they fire off a run, it's just 100%. And then it just runs, and then it stops. So it's very, the usage pattern is squares basically, right? And it's also not follow the sun, because people will fire it off at midnight before they go to sleep but then wake up and so it's very unpredictable, so you don't know where that is. So the shapes of the usage are quite different than we have had before. And also what's interesting is when it's sort of a follow the sun, even if you have a high growth company, you can sort of predict your usage patterns and have enough capacity for that, because it's sort of, it grows in a, in a way you can project. When you have companies doing sort of like evals and RL, they're super spiky. So they're gonna come in, it's like, “We're gonna use nothing, then can we have 100,000?” Right? And then go back down. And then 100,000, go back down. So it's very different, right? And.Swyx [00:22:09]: Do you want to lock them into commits so.Ivan [00:22:11]: Yeah, we do.Swyx [00:22:12]: Yeah, okay.Ivan [00:22:12]: We so we have to lock them into some sort of commits to have that capacity, because we have to have, basically we have to have the capacity for peak. Right? And so right now, Daytona's mean utilization is 15%, 1-5.Swyx [00:22:25]: Oh my God.Ivan [00:22:26]: So it's very low.Swyx [00:22:27]: Because it's very spiky.Ivan [00:22:27]: It's very spiky, but we get up to 90%. so we have these things. And so what we're, what we're looking at right now as a company is similar to Cloudflare where you can like geo move things around, but that works really well for basically the background agent where it's follow the sun. But this, it's not. Like it's a very different shape. Obviously with scale you figure these things out, but that's an interesting new problem that we have, as a compute provider in the agent space. And when we were doing the conference recently, and so we talked to like Nikita from Neon and.Swyx [00:22:57]: I should bring it up.Ivan [00:22:58]: Parag from Parallel and whatnot, everyone has the same problem. Whereas the usage is super spiky, and this is something that has not happened before, that you have these types of like it was always, it the amplitudes were not this high, right? So it's quite interesting use case and problem solve.Compute Conference and Spiky Agent InfrastructureSwyx [00:23:12]: Yeah, I don't know if we're gonna bring this up again, but let's just talk about the conference, you had like 1,000 something people at the Warriors game, at the Sorry, where is it? What's.Ivan [00:23:22]: Chase Center.Swyx [00:23:23]: Chase Center.Ivan [00:23:23]: Chase Center.Swyx [00:23:24]: I went. It was, it was very impressive. Obviously, you can, how to throw a conference, what did you learn? you put, you pulled together all these impressive names.Ivan [00:23:33]: What I.Swyx [00:23:34]: What were you looking for?Ivan [00:23:35]: My thesis behind the Compute Conference was let's bring together people that are building infrastructure for AI agents. Because when I think of what we're building, it is the agent is the primary user, what are the ergonomics and usage patterns of agents, and so we can do that. And what I found, this was a theory, it wasn't proven, is that we all have these problems, as I touched onto. And I was, as I was talking on stage, it was like we all have the same underlying infra problems, which is this spiky workloads, unpredictable workloads that we've never had before, in human, compute or human infrastructure. And it's, again, it's the same when I was talking to Parag or when I was talking.Swyx [00:24:20]: Lynn. Nikita.Ivan [00:24:21]: Lynn, Nikita. Lynn especially, I was talking to her the other day as well. Like the It is a very interesting type of problem to solve because I can touch on Cloudflare because there's a lot of like talk about that recently as to how they solve that, which is they have a bunch of geos, and basically, as users work in different places, and depending on your tier, they can move you around the geos. And so that how, that's how they get the higher utilization. But you can sort of predict these, and it's If it's something in You'll rarely get a spike that is 10 orders of magnitude. Like you'll get a like let's say one of your customers has some like an exponential curve. What is that to I'm using Cloudflare as an example. 10%, 20%, whatever it is. I don't, I don't have this data, I'm just assessing. It's surely not 10x, right? It's surely not something there. And so how do you go out and solve this problem? And we're all solving this in different ways. So we have.Swyx [00:25:11]: She also has the same thing.Ivan [00:25:12]: Yeah, I know specifically that like Neon had that issue as well. Like how are we solving these spiky loads and things like that ‘cause we talked about it. And so the interesting thing for me to actually internalize was, yes, everyone that's building for agents first is going through this, and we're all solving similar problems, which is quite.Swyx [00:25:28]: Let me let me double-click on this. Okay. So for example, Neon, I happen to know that they're very sort of S3 oriented, right? so they're just like fully bet on S3. And you get to benefit from S3's distribution and infrastructure. So I would imagine that Neon doesn't have to care, whereas Lynn maybe has to care a bit more because obviously she's doing GPU inference. And, for listeners, we did an episode with her, one and a half years ago. And you have to care. But like, right?Ivan [00:25:54]: Parag cares for sure, and Nikita.Swyx [00:25:58]: And Parag is C of, Parallel.Ivan [00:25:59]: Parallel, yeah.Swyx [00:26:00]: Former CTO of Twitter.Ivan [00:26:01]: Twitter, yeah.Swyx [00:26:02]: They are the search.Ivan [00:26:03]: Yeah, they're search, yeah.Swyx [00:26:03]: I You and I know but the listeners don't know.Ivan [00:26:08]: Yeah, we can put it down in the screen, and so ‘cause we, when we were talking.Swyx [00:26:11]: I'll put it up on the, on the screen.Ivan [00:26:12]: Yeah, right.Swyx [00:26:12]: People can look it up if they need.Ivan [00:26:14]: Look it up. And, yes, but they still have CPU and RAM, allocation that you have to have up and running. And so CPU and RAM, you have to allocate that and have that ready. And so there's basically two ways to do it. One is you either over-provision and you can handle the bursts, or two, you basically have, I don't know if this is a term, just-in-time compute, which is like as your load becomes, as your usage comes in, you can fire off requests for VMs or bare metals at other cloud providers and then get them up and running.Swyx [00:26:43]: This is if you go above 100%, right?Ivan [00:26:45]: Yeah, this is.Swyx [00:26:46]: Like your overflow.Ivan [00:26:46]: If your overflow, like spillage or whatever you do.Swyx [00:26:48]: You probably lose money on it, but it doesn't matter, right?Ivan [00:26:50]: It, not Well, you might, you might not That is a more cost-effective way to do it but it's a slower way to do it. Because basically what you have to do is you have to like queue your requests, spin up these just-in-time compute, get it all ready, provision it, and then get your workload there. And so if the time isn't important that much, that's fine, and you can do that. But if your customer, and especially for, let's say, the RL training runs, the reason why a lot of people come to us is because GPUs are more expensive than CPUs, right? So you want your GPU running at, what, 100% the entire time. And so when you're running runs on CPUs, when the when the CPU cycle is like down and spinning up the next one, you want that to be instantaneous so that your GPU doesn't go down, right? And if you then have to like go out and provision machines, you're essentially telling the GPU that it has to wait, and that's incurring our cost. So there's things that you have to try to solve for there.RL Workloads, Declarative Images, and Kubernetes ReplacementSwyx [00:27:43]: Yeah, let's talk about the different workload, right? You said that, what was it? A few months ago, you had zero RL workload and now it's 50%.Ivan [00:27:52]: It will be this one, 50%, yeah.Swyx [00:27:54]: Let's talk about how different it is, right? Like I imagine, for example, a lot less dynamic code generation of like arbitrary code. Like here, it's probably all the same code. You're just doing parallel runs or something, I don't know.Ivan [00:28:05]: Yeah. So you'll have multiple Depends on the like for each run, you'll have a snapshot. And they, for the most part, they actually do use our declarative image builder, which is like, “Oh, we, the agent wants these dependencies, these env vars.”Swyx [00:28:17]: These ones, yeah.Ivan [00:28:18]: Yeah, the declarative image builder, it.Swyx [00:28:20]: Which is a very modal like thing that they.Ivan [00:28:22]: Yeah. And so we build it on the fly and then we propagate that snapshot, and you can spin up as many sandboxes as you want against that snapshot. And then if you have to do changes, the model can, or like it could be also be automated. It's like, “Oh, now for the next run, we need to install these things or remove these things or whatever to get, a task done,” and then it goes off and runs that. So yes, that is something that it seems that they prefer. The number one reason I found, or should I say, let's take a step back. What we are competing against in that environment is essentially managed Kubernetes. So EKS, GKE, whatever. That is what the vast majority run on. And anyone that has tried Daytona versus GKE, EKS is like, “I'm never going back.” That has always been. There's a few reasons. One is the ergonomics. So if you have, if you're using Kubernetes to spin that up, you have to essentially manage the interface interactions with that. Daytona, although as a compute provider, it's more akin to a Twilio and Stripe from a consumption perspective than it is an AWS. Like you have an API, an SDK, it's quite like easy and seamless to get these things up and running, that's one. The other is the speed to which we spin up, which we mentioned earlier, which is much faster, and the scale to which we can go to. We haven't got into features, but an interesting feature is that it's very hard to OOM, or out of memory, our sandboxes, because we can dynamically on the fly.Swyx [00:29:48]: Resize.Ivan [00:29:49]: Resize, which is like impossible on almost any other thing. There are some technologies that enable you to do that, but it's like a very hard thing. And so we actually saw this when, the Terminal Revenge team is, brought us actually. So thank you, Alex and the team, that brought us into this whole space.Swyx [00:30:05]: It's just very rare that, a framework would just say, “Guys, just use Daytona.”Ivan [00:30:11]: Yeah, I think it says it somewhere. Yeah.Swyx [00:30:13]: Yeah. I was like, “What is this?”Ivan [00:30:15]: There's all, there's multiple there, but they also mention a few other places. and so Daytona specifically-We have, the, just jumping on themes here We, I don't know where it says Data Center.Swyx [00:30:27]: I, there.Ivan [00:30:27]: Doesn't matter.Swyx [00:30:28]: There's a very strong recommendation, which is, very unusual. Which is, it's.Ivan [00:30:33]: We do not pay them for this, just.Swyx [00:30:34]: I know, yeah. They just like you.Ivan [00:30:35]: Yeah, they like us. yeah, and also a thing, so, Data Center has multiple isolation sets underneath. The customer doesn't have to know what they are. But basically we have Docker, which is a container, that's hardened with Sysbox. So it's Docker's, isolation that is a security equivalent to a VM, but it's still a container. And that is the default, and they, especially in these training workloads, really like that as an interface to be able to use just a basic Docker container, and we enable Docker and Docker. Which for these RL runs, if you need to do a Docker compose or Kubernetes, you can spin up a K3S inside of these things, which unlocks a huge amount of workloads that you can do that you cannot do on other providers. So just on that part is much more interesting. And so we went that, through that. We showed them that we could do that, and they enjoyed that quite a bit. They being the general venture people.Swyx [00:31:28]: Those people, yeah.Ivan [00:31:29]: And Harbor people.Swyx [00:31:29]: Harbor people, do are they, are they a company yet?Ivan [00:31:33]: As far, I do not know.Customer Pull, Slack Connect, and the Computer Use BetSwyx [00:31:35]: Okay. All right. Yeah. It's like super obvious that like, there's a lot of excitement and success around these things, okay, so yeah, tell us more, right? Like, this is an exploding workload, Harbor adopted you, which helped speed things along. But what are you learning as this new workload comes online?Ivan [00:31:53]: There's a couple things that we learned, which we chat about in the beginning. We, and this has led our story, as we mentioned, we like talked to a lot of customers along the way, and we add more features and more tool sets as we talk to customers. And it's interesting that And I think it's that the ecosystem is so small and/or the models get smarter, where when we see one user come with a request, we know it goes on a roadmap if like three to five customers come with the same request in that week. It's like very bizarre. It happens so many times, which is.Swyx [00:32:27]: Because they're all friends.Ivan [00:32:28]: Sorry?Swyx [00:32:28]: They all, they're all friends. They're all in the same group chat.Ivan [00:32:30]: Yeah, probably, yeah. ‘Cause and they're like, “Oh, can you do this?” And I'm like, “Okay, this is interesting. We'll put it on a feature request.” And then the next one's like, “Oh, can you do this?” “Okay.” It's all the same, right? It's always the same. And so what we try to do, and I personally try to do, I try to be on as many call, quote-unquote “sales calls” I can. I'm in every Slack channel. We literally have about 1,000 Slack Connect channels, something like that. It's an interesting, there's so many interesting things you find out when you have all the Slack channels. You can also see where people, transfer between companies. You see leave Slack channel, enter Slack channel. It's an interesting thing. Also, just I digress, I feel that Slack Connect is literally LinkedIn what it should be. You have a list.Swyx [00:33:08]: LinkedIn charges you to, use your own connections, but Slack doesn't, right? Slack is like, do it for free. It's more lock-in. It's great.Ivan [00:33:15]: Yeah. It's amazing. Yeah. It's one of the reasons.Swyx [00:33:17]: You're gonna pay Slack for life.Ivan [00:33:18]: Exactly. You're there for life. So that's interesting. And so one of the things, the newer things we were talking about earlier is we made a big bet and put a lot of investment on computer use. that is not seen publicly the light of day. We haven't GA'd that yet, but we have.Swyx [00:33:32]: Is there a thing I can pull up?Ivan [00:33:33]: There is computer use there. It's right up a bit.Swyx [00:33:36]: Oh, yeah. Okay.Ivan [00:33:38]: What we have, what we talked about and what we've seen publicly is there's this theme now about, the human emulator where And Elon from XAI has talked about this publicly, and if you think about the models today, they're actually quite sophisticated and they can do a lot of work, but they still don't have access to all the tools. Like, I'm a strong believer that the most efficient way for an agent to work is essentially headless or through, terminal or whatnot. But if we, if we look at knowledge work in general, there's about 100 million knowledge workers in the US, about a billion in the world, and knowledge workers, and the salaries of them aggregate to 10 trillion in the US 50 trillion worldwide.Swyx [00:34:24]: Wow.Ivan [00:34:25]: Something like that. And if we look at, the five most important sectors of that, so like healthcare and government and financial services and whatnot, that's about 56% of that. So let's say it's about half of that. So in the US it's about 25 trillion, and most of them, most of that work is actually still locked into legacy apps inside of Windows, which is not going anywhere for a very long time. Like, people just won't invest in that. How much of it? our assumption is the following: if, in the RPA market, which is similar market, well, not the same 25% of, these white collar, workers', work is automated. If an agent is more sophisticated, can go through more runs, figure stuff out, let's say it's, 40%, right? And so if you take 40% of that, you get to essentially, $10 trillion a year.Swyx [00:35:17]: That's a TAM.Ivan [00:35:18]: That is a that is a TAM. So that's the TAM of the models, right? That's not our, essentially ours. But you get to that size, and to be able to do that, you essentially have to give agents these computers with the legacy. So computer use, either Mac or Windows or Linux. Linux we also obviously have and others have. But Windows specifically is something very new, and the only option right now is an EC2 with, Windows or on Azure. Both of them take anywhere from three to five minutes to spin up. We've created an actual sandbox, so it's a second instead of milliseconds, but you have, point in time snapshots, you have, forking, you have all the things that you have from a sandbox, but essentially enables you to hopefully unlock all this value. And so that's been our big push and bet, but we've sort of, kept our ear to the ground. What is sort of the next things in the market?RPA Returns: Why Agents Still Need ComputersSwyx [00:36:06]: Yeah, knowledge work, and building, and sort of RPA, the next wave of RPA. I got very excited about RPA kind of during COVID times. The UI path was IPO-ing. And it was, a very hot Isn't it, Eastern European?Ivan [00:36:20]: It is, Romanian.Swyx [00:36:21]: Romanian?Yeah, it might be the only Romanian, big unicorn okay, yeah. This I don't I don't, I don't have like a I think there's, I think there's a stage being set for the resurgence of RPA, ‘cause everyone understands that, yeah, no one wants to deal with these shitty apps and no one's gonna rewrite them. Like, you just have to do, a remote operation and programmatic operation of them.Ivan [00:36:45]: If you wanna unlock it, my own setup was basically the following. So I was doing a board deck recently, last month, whatever, and I'm like, “Okay, let's just, let's just do automated.” So, all our data's in, ClickHouse and PostHog and QuickBooks, where everyone else's is, and I'm basically, connected that all to, my Cloud code, like go off and go Cloud code whatever. Go off and, here's the integrations, go do that. It pulled out the first report, which was great. It connected to Brex and all these things, pulled it, which was great, and then I say, “Okay, now pull out this, and this,” and I kept getting, really well McKinsey-style design reports, but the data said partial data. all the missing data, partial data. Like, it can't access all the things, and I got so frustrated, and so I got, I got, my Mac Mini virtual sandbox with OpenClaw. I gave it its own account in our company, and then I went to all these services and created a read-only account, so literally like an intern in your company. And so I would say, “Now go and do this report,” and it would get the same, or like, “I can't via the MCP or the API or whatever. I can't get all the information.” I'm like, “Go log in.” And it will log into the website, then go in, export the data. It'll export the data and do the thing end to end. So even for things that have today APIs, not all of it is exposed, and I to get value, I get immense value right now, but it has to be a computer usage, unfortunately, and so I spend a bunch of tokens just on that, but I get the job done. And so if even a startup like ours, and using all the hottest tools, still needs a computer agent what hope does, Goldman have to have a headless, right?Swyx [00:38:22]: Yeah, what a - Why isn't Microsoft doing this?Ivan [00:38:27]: I'm pretty sure, Satya had a post yesterday.Swyx [00:38:29]: Oh, okay. I see.Ivan [00:38:29]: Which was like, “Every agent needs a computer.”Swyx [00:38:31]: I see, I see.Ivan [00:38:32]: So they have launched something recently.Swyx [00:38:34]: Yeah, they have Microsoft Power Automate, I'm sure, I'm sure, they're gonna have their version.macOS Sandboxes, Apple Constraints, and the Windows OpportunityIvan [00:38:39]: Version of that, yeah.Swyx [00:38:39]: You're gonna try to do yours, and it - I always know there's always demand for Mac, but I know it's, tricky to host, macOS sandboxes.Ivan [00:38:49]: We will have macOS sandboxes fairly soon. The problem with macOS, OS sandboxes is, I'm deep in this, I don't know how much interesting is.Swyx [00:38:55]: No, it's.Ivan [00:38:56]: MacOS has this problem.Swyx [00:38:57]: It's a licensing thing, right?Ivan [00:38:58]: Licensing thing. So one, you're allowed to run only two parallel VMs per machine, so that's one. Two, you can only license to a different user every 24 hours. So if you come in and theoretically, if I wanna charge you per second and I charge you one second, I have to have it idle for the rest of the day. I can't have anyone else doing that. So the pricing will be different in the sense that I will have to - we would have to charge for 24 hours, and that's not even, that's not even the most difficult thing. But the, thing above that is, from a security perspective, they enable you to do memory snapshot, pause, resume, but only on the same physical drive, physical machine. And so what you can do in, Windows world or Linux world is that I can move in the background, your snapshot from one to the other and manage load, right? Here, if you wanna do that, you essentially have to have your.Swyx [00:39:49]: Yeah, snapshots. Yeah.Ivan [00:39:50]: Your.Swyx [00:39:51]: It's like.Ivan [00:39:51]: Physical machine.Swyx [00:39:52]: You can't break it up.Ivan [00:39:53]: You can't, you can't move things around that, and all of that is, that part is, from a security standpoint, if it is written. Like, I understand the security aspect of that, but it disables you from doing these agentic, like really scalable agentic workloads.Swyx [00:40:08]: You need to do a vibe-coded, clean room implementation on macOS that you can then - That's like Clean OS or something. I don't know.Ivan [00:40:17]: So. We have.Swyx [00:40:18]: ‘cause like Linux was originally like a clean room rewrite of Unix.Ivan [00:40:21]: Okay. Yeah.Swyx [00:40:21]: Or something like that, right? Like same thing to macOS. Someone needs to do it.Ivan [00:40:25]: Someone will do that, and someone will have some long-running agents for a few days to figure this stuff out. But yeah. So definitely we - we're really close to offering something ‘cause people do want it, but the pricing will be different, and the feature set will be sort of stringent.Swyx [00:40:38]: Yeah, nobody's gonna use this. like, the labs, the labs will because they want to automate macOS.Ivan [00:40:42]: They have to do RL. They have to do RL again. But even if you The - So the point is with the RL part, if you, if you do RL on macOS, then the next iteration of the model comes out, it will be able to use these tools significantly. Then you actually need to run those, that somewhere. So you're gonna have to have that, later on. And from, if anyone at Apple is listening, I very much feel that they are shooting themselves in the foot of the scale of the revenue of compute or licensing they could get if they would just enable a concurrency model similar to what you can get on a Windows and a, and Linux.Swyx [00:41:17]: Yeah. Yeah. And I'm sure they've heard this before. They just don't care. Yeah, it's And maybe they will change their mind with the new CEO.Ivan [00:41:24]: Yeah. We'll see.Swyx [00:41:25]: We'll see.Ivan [00:41:25]: High hopes.Swyx [00:41:26]: High hopes.Ivan [00:41:26]: High hopes.Swyx [00:41:27]: Okay. But I, it's very clear the market opportunity is huge in Windows, and you can go for a long time on just Windows, but your customers are gonna want both. and I think, it is interesting to me that, this is the sort of God application of agents, right? Like, I don't It was - How big was OpenClaw for you guys? Like, was it, was there, a significant bump.OpenClaw, Agent Labs, and the B2B2C Sandbox MarketIvan [00:41:54]: Not for us because we.Swyx [00:41:54]: Because you already.Ivan [00:41:55]: We're kind of positioned differently. Whereas although it's completely PLG and we have individual developers that use it, most of the users that use Daytona are sort of a B2B2C. Sort of it's either B2B or B2B2C. So, in the researcher world, it's B2B, so you're selling to, labs and neo labs and things like that. But on the long-running agents, it's mostly, from a scale revenue perspective, it's mostly B2B2C, where you have a app layer agent that uses you at a big scale.Swyx [00:42:26]: Like a Manus. Yeah.Ivan [00:42:28]: Like a Manus Lovable type of thing.Swyx [00:42:31]: Yeah. I think that's the question of, well how, um-Uh, yeah, B2B to C is basically to me what I've been calling an agent lab, which is kind of like you're not in a model lab, but you're making a very good wrapper that is a platform that other people can sign up so they don't have to code those things. Yeah, it sound, it sounds like a much better market than the direct OpenClaw market.Ivan [00:42:56]: I've like - We I've done multiple things. So the CodeAnywhere's part of our career path R in the calendar, was very much an end user developer product. And so that is great. It You can get a lot of developer love, and I feel that we do as a company have a bunch of developer love. But it's a different type, where it's people building these things. Again, it's more akin to a Twilio because you don't really run - As a person, you wouldn't run Twilio. I don't know how many people remember. It was like ask your developer billboard and whatnot. And people really love Twilio, but they only used it inside of like, “Oh, I'm building this app or service for thing.” And so we're very much directly to that. And you also know that I used to work for a competitor for Twilio, so it's kind of ingrained, in my DNA.Swyx [00:43:35]: People don't know InfoBip is that big.Ivan [00:43:38]: Yeah, it's.Swyx [00:43:39]: Because.Ivan [00:43:40]: It's a billion euro.Swyx [00:43:40]: They're all American. They're like, “Whatever's in Europe doesn't matter to me.” But like it's the, it's the same size or bigger? Same size?Ivan [00:43:46]: It's about half the size.Swyx [00:43:47]: Half the size?Ivan [00:43:48]: Yeah, about half the size.Swyx [00:43:48]: It's like, yeah.Ivan [00:43:48]: Still huge. Multiple billions a year. Yes.Swyx [00:43:51]: That's crazy.Ivan [00:43:51]: Exactly, and so that - These are like really interesting and large revenue-generating, very sticky businesses. Whereas when you're selling to the - When your focus is the end developer, it is a very hard sell because they're very price sensitive, very price conscious, very around that. And there's very It's very hard to scale. Your cap is the number of people that are willing to spin up - First of all, wanna spin that up, and then spin up multiple of these. Whereas if you're in the enterprise one, like we know everyone's talking about like how many tokens they're spending, I'm spending. Like a lot of companies today are like, “If this is our company, spend as much as you can.” Like basically that is where we're going. And so if you think about that paradigm, where you're selling to companies that say, “Spend as much as you can to generate, productivity,” versus, “Oh, I'm a single person. I have this much budget, and I'm doing this thing because it's fun or it's helping me out or whatever.” Like it is a different, it's a different go-to-market, I think, strategy.MCP, CLIs, and Sandboxes as the Agent RuntimeSwyx [00:44:50]: Yeah, there's a lot of discussion. I'm just kind of going through like the mental list of things that are in your favor, which is, for example, MCP versus CLI. Like obviously you want CLI. It's been very good for you. I feel like it's maybe a drop in the bucket or maybe it's huge. I'm just checking whether it's like these are big trends.Ivan [00:45:10]: Those things you - work well in our favor, to your point just because every.Swyx [00:45:13]: They're kind of drop in the bucket, right?Ivan [00:45:15]: I think it's like sort of all the things come together. And so there's so many things that impact that. To your point, like OpenClaw wasn't huge for us, but like having the agent SDK, from Anthropic, so or Cloud Claude Code was very interesting. The reason why it was interesting is that a lot of, let's call them app I don't know what to call them, app layer agent companies, essentially they are like, “Oh, I can create this new app, this new agent. All I need, I just use Claude Code, and I throw it into a sandbox, and then I have my interface to the human to that.” And so that enabled so many more companies to actually offer this, and then they would pull on sandbox. So that was, that was interesting. And to your point, like MCP, versus the CLI, the MCP is an interface against an API, whereas the CLI is like you can actually go do things. Like this is it. The difference between integrations and actually running scripts or data or analysis against a thing. So being able to use a CLI very well enables the agent to do more things, and it's because that people will invoke a sandbox, they'll run it in the CLI, and but it'll do anal-analysis on that data and then give you an actual result versus just, pulling data from an API source.Swyx [00:46:29]: Yeah, it's a layer of indirection basically, it's the same thing as agentic search versus RAG, which where you're.Ivan [00:46:34]: Exactly, yeah.Swyx [00:46:34]: Just like you just win whenever people put more agents into their workflow. And so like it doesn't really matter, but I'm just kinda teasing out like what else have people heard about that like it's sort of, “Oh yeah, this is another sandbox use case. Oh yeah, that's another one.” Am I, am I missing any big ones?Ivan [00:46:51]: The thing, the thing that people, which is the computer use stuff, which I think is probably the most interesting one, is, and to your point, we've talked to so many people over the last year. It's like, “Oh, like why do you need a sandbox? Why do you need this? Why this?” And to your point, it's like, “Oh, I need sandbox for this. I need sandbox for that. I need sandbox-” It's like, “Oh, I need it for every single thing.” And so basically what I, what I - and it sounds like a broken record, it's like you use a laptop every single day, right? And you are n of one. It's just you. But now imagine how And by the way, the laptop, the computer PC market, the PC market is about equal to the cloud market in total. So it's about 150, 180 billion a year. Something like that. It's about roughly the three cloud hyperscalers is about equal to like Apple, HP, Lenovo, whatever, It's a little bit less, but it's sort of like that. And now imagine And that's just like, so how big is the addressable market? What, how many people are there in the world now? What's the last data?Swyx [00:47:45]: Let's call it eight billion.Ivan [00:47:46]: Eight billion. And so let's say you can have two computer, like you have one personal and one business, whatever. Like so it's double that, right? and so that's 16 billion, right? How many agents are gonna be running in two years, in 10 years, in 100 years? Like And for every single task, they will need one of these. And so how big is that? That market is essentially quote unquote “infinite”. You will get to the point, and Dylan Patel was at the conference talking about, from SemiAnalysis, that talks usually about GPUs, was also talking about how CPUs will now be a bottleneck because it will be the constraint. You won't be able to grow, or we won't be able to have enough of these because there won't be enough CPUs to basically do.Swyx [00:48:23]: Yeah. Well, I actually had a really good podcast with Doug Oliphant, who, which was his president at SemiAnalysis, where they've basically been like, yeah, it's been a GPU shortage first, but then it's cascaded down to memory and now to CPUs.Ivan [00:48:35]: CPU, yeah.Swyx [00:48:35]: It-What's next? So networking. So, networking actually has been in shortage for a while if you're looking at, just GPU networking. But, yeah, it's really crazy the amount of computer use that's going on, yeah, cool. I, other questions are, just the one very big part is the open sourceness which you didn't have to do, your competitors don't do, like it's not, a lot of people are worried about keeping their projects open source because some competitor can just slot fork it. I don't know if there's any reflections on just being an open source company.Open Source, Trust, and Enterprise ProcurementIvan [00:49:15]: Yeah. There's a bunch. So we the original product that we did was open source.Swyx [00:49:19]: Yeah. CodeAnywhere.Ivan [00:49:20]: So doing that was actually very good for us. There's basically a saying of, What's the saying? Like, companies that are, that are doing really well, measure themselves against, free cashflow, that are kinda okay, it's EBITDA, then, it's, it goes all the way down.Swyx [00:49:36]: The worst is like GitHub stars.Ivan [00:49:37]: GitHub stars. GitHub stars are the worst, yeah. So you go all the way down to GitHub stars. And so our original one was GitHub stars. That's what we talked about, we're at the point we're talking about revenue, so we're we've gone up the stack on that. And so we started.Swyx [00:49:47]: No, profit.Ivan [00:49:48]: Yeah. We haven't, we're, we'll get there. We'll get there. But basically at that point we did stars and GitHub and it was useful, and the original variation that we did, it we split the core into its own repo and it was Apache 2.0, so very, permissive. And then we basically would bundl

In this episode of the CPQ Podcast, Frank Sohn speaks with Parag Jagdale, Co-Founder and CEO of Unific, about the continued evolution of Quotific, Unific's CPQ and quoting solution for eCommerce-driven businesses. Parag explains how Quotific has developed since his last appearance on the podcast, including deeper integration with Shopify, support for customer-specific price lists, location-based inventory visibility, and improved product catalog search capabilities. He also discusses why Shopify's recent B2B-related enhancements are creating new opportunities for companies that need a more connected quote-to-order process. A major theme of the conversation is the growing need to reduce fragmentation between eCommerce, CRM, quoting, pricing, approval, and order management processes. Parag shares why many customers want sales teams to work primarily inside HubSpot, while still connecting quoting and ordering activity with Shopify. He also explains why Unific has chosen to focus more deeply on Shopify and HubSpot before expanding its integration efforts with platforms such as Salesforce or Microsoft Dynamics. The discussion also covers common challenges in B2B eCommerce and high-ticket B2C selling, including pricing complexity, discount approvals, fragmented workflows, and the difficulty of changing sales rep behavior. Parag shares examples from customer conversations and explains why time savings, easier quote management, and a smoother buyer experience are key adoption drivers. Toward the end of the episode, Frank and Parag discuss the role of AI in CPQ, including product recommendations, customer segmentation, and the potential for AI to improve the buying experience in eCommerce-focused CPQ scenarios. This episode is especially relevant for anyone interested in CPQ, eCommerce CPQ, Shopify CPQ, HubSpot quoting, B2B eCommerce, quote-to-order automation, and the future of AI in CPQ.

In Episode 3 of The Insight Edge Podcast with Sanjay Manjrekar and Shachi Pai, we explore the controversies enveloping Rajasthan Royals, Suryakumar Yadav's frustrating lean patch, why Sanjay has temporarily stepped back from IPL commentary duties and much more. #CricketPodcast #InsightEdge #SanjayManjrekar

What happens when AI agents — not humans — become your primary customer? That's not a hypothetical. It's already happening, and the founders who recognize it earliest are rebuilding their entire infrastructure stacks from scratch. In this live episode of Founded & Funded from our IA Summit in Seattle, Madrona Venture Partner Jon Turow sits down with Parag Agrawal, former CEO of Twitter and founder of Parallel Web Systems, and Nikita Shamgunov, who led Neon through a rapid AI pivot before its acquisition by Databricks. What they cover: Why Parag is building a new search index from the ground up — and why existing ones weren't designed for AI agents The moment Nikita realized Replit agents were spinning up databases 4x faster than all human developers combined — and what that forced him to do How to pivot an established company in weeks, not months, when your customer base suddenly changes The "pagers vs. iPhones" framework for knowing when to lean into disruption vs. protect what you have Parag's two-person hiring rubric for teams operating in deep uncertainty Why Nikita added the head of product for ChatGPT to Neon's board — and what that signaled to the market The "two-way door" model for giving agents real autonomy without catastrophic downside Whether you're building infrastructure, running an AI-native startup, or trying to figure out where your product fits in an agent-first world — this conversation will sharpen your thinking. Full Transcript: https://www.madrona.com/twitter-ex-ceo-web-built-for-humans-make-it-work-for-ai-agents-nikita-Shamgunov-parag-agrawal Chapters (00:00) – Introduction (01:52) – Parag Agrawal: Why Parallel Was Built for AI Agents From Day One (03:22) – Why Existing Search Indexes Don't Work for AI Agents (05:08) – Nikita Shamgunov: How Replit Agents Outpaced the Entire World on Neon (08:27) – The Pager-to-iPhone Decision: Lean Into Disruption or Get Left Behind (11:13) – How Neon Built an AI Team in Two Weeks and Launched MCP Before Anyone Else (13:41) – Firing Bullets: Why a 4-Out-of-9 Batting Average Was Good Enough (15:37) – Parag on the Two Types of People You Need to Take Concentrated Risk (21:08) – Building Trust in Agents: Evals, Confidence Scores, and Read-Only Infrastructure (23:32) – Nikita's Two-Way Door Framework for Agent Autonomy (25:35) – Parallel Execution: Fork Environments and Let Agents Compete

What does it take to build companies from the ground in a novel sector in India?In this conversation, Parag Sharma, Chief Executive Officer at Resolven (formerly Zelestra), reflects on a three-decade journey from growing up in a thermal power plant campus to building gigawatt-scale renewable businesses.Drawing from his experience across engineering, consulting, and entrepreneurship, he explains how India's renewable energy market matured into one of the world's largest investment destinations. The discussion explores the forces shaping the sector today, from global investor confidence and competitive bidding to the evolving balance between solar, wind, and battery storage.As India races toward ambitious clean energy targets, the conversation also looks ahead: what will define the next generation of renewable companies? From disciplined bidding and smart project development to hybrid energy solutions and emerging opportunities in green hydrogen, data centers, and AI-driven energy demand.Mr. Sharma is the former Founder and CEO of O2 Power, previously served as COO at ReNew Power, and currently holds leadership roles as President of the Wind Independent Power Producers Association (WIPPA) and Chairperson of the Confederation of Indian Industry (CII), Northern Region. Full transcript of the episode is available in English.Presented by 101ReportersParag Sharma is on LinkedInFollow TIEH podcast on Twitter, Linkedin & YouTubeOur hosts, Shreya Jai on Twitter, Linkedin & Dr. Sandeep Pai on Twitter, Linkedin

Professor Olga Vitek has a deep understanding of statistics, machine learning, and computational biology. She puts her know-how to work to develop computational tools enabling high-quality proteomic analysis and systems biology approaches. She hopes to apply these tools to the quantitative analysis of large-scale mass spectrometry-based investigations and thereby advance our understanding of organismal function. In this episode, Parag and Professor Vitek discuss:Why statistics is important for experimental designHow statistics and AI can help researchers understand biologyGaps keeping us from using AI and statistics to their maximum potential in biologyResourcesStatistical methods for studies of biomolecular systems websiteOlga's personal lab websiteBeyond protein lists: AI-assisted interpretation of proteomic investigations in the context of evolving scientific knowledgeGyori and Vitek, 2024 discuss how AI can be used to interpret proteomics data and its biological meaning.A Bayesian Active Learning Experimental Design for Inferring Signaling NetworksNess et al., 2018 show how statistical methods can guide the selection of experiments that optimally enhance understanding

The CPG Guys are joined in this episode by Parag Shah, CEO & Co-Founder of ThinkBlue Consulting.We decompose what happened at the 2026 FMI Midwinter Executive Conference.Learn more about FMI Midwinter here: https://www.fmi.org/midwinter-conferenceFollow Parag on LinkedIn at: https://www.linkedin.com/in/omnigrowthparag/CPG Guys Website: http://CPGguys.comFMCG Guys Website: http://FMCGguys.comSheCOMMERCE Website: https://shecommercepodcast.com/Rhea Raj's Website: http://rhearaj.comLara Raj in Katseye: https://www.katseye.world/DISCLAIMER: The content in this podcast episode is provided for general informational purposes only. By listening to our episode, you understand that no information contained in this episode should be construed as advice from CPGGUYS, LLC or the individual author, hosts, or guests, nor is it intended to be a substitute for research on any subject matter. Reference to any specific product or entity does not constitute an endorsement or recommendation by CPGGUYS, LLC. The views expressed by guests are their own and their appearance on the program does not imply an endorsement of them or any entity they represent.CPGGUYS LLC expressly disclaims any and all liability or responsibility for any direct, indirect, incidental, special, consequential or other damages arising out of any individual's use of, reference to, or inability to use this podcast or the information we presented in this podcast.

Italia, uno de los países cuyas reticencias impidieron la firma en diciembre del acuerdo comercial entre la Unión Europea y el bloque Mercosur, parece dispuesta a dar luz verde a la firma en la votación prevista este viernes. La Comisión Europea ha presentado hoy a los ministros de Agricultura en una reunión extraordinaria una serie de medidas para apoyar la firma del acuerdo que contemplan: Un incremento potencial de 45.000 millones de euros para agricultura, mediante el adelanto de márgenes presupuestarios del futuro MFP; la apertura de 48.700 millones de euros del Fondo Rural para medidas agrícolas y dos medidas adicionales relativas a fertilizantes (CBAM o antidumping) y a la reciprocidad comercial frente a terceros países. De alcanzarse el acuerdo, la firma tendría lugar el próximo 12 de enero en Paragüay.

Parag Amin is the founder and principal attorney of the Law Office of Parag L. Amin, P.C. (LawPLA), a Los Angeles-based boutique litigation firm. With practice areas spanning personal injury, business litigation, and consumer class actions, Parag has built a reputation for selectivity, complex case handling, and high-touch service. A former startup operator with an MBA from USC, he brings business acumen to the courtroom — combining trial skill with a focus on client experience, trust, and top-tier talent. In this episode, Parag reveals how he turned a single client request into nationally recognized PI results, and what most firms overlook when they try to add injury work. From building a personal brand that wins cases before intake to hiring trial lawyers who can actually deliver, this quick start guide shows you what it really takes to succeed in PI. Listen to the full episode with David Craig on Personal Injury Mastermind, powered by Rankings.io below: Spotify Apple Podcasts Watch the Episodes On YouTube Parag Amin: Law Office of Parag L. Amin, P.C If you like what you hear, hit subscribe. We do this every week. Get Social! Personal Injury Mastermind (PIM) powered by Rankings.io is on Instagram | YouTube | TikTok

On this episode of Translating Proteomics, Parag and Andreas share their reflections on proteomics developments in 2025 largely inspired by their observations at the World HUPO 2025 conference in Toronto. Whether you agree, disagree, or simply want to share some of your own observations on proteomics, please post your thoughts in the comments.We look forward to even more exciting developments in 2026!Chapters00:00 - 00:35 – Intro00:36 – 07:00 - Increased focus on applications of proteomics and less on method developmentLearn more about One Health from our conversation with Professor Jennifer Geddes-McAlisterhttps://youtu.be/JFwvTdkb5bw07:01 – 12:47 - Increase in people talking about the importance of proteoformsLearn more about proteoforms in our episode featuring proteoform pioneer Professor Neil Kelleherhttps://youtu.be/3pPuxVrMxpw12:47 – 17:26 - An increase in multiomics studies17:27 – 20:03 - A shift to larger scale proteomics studiesFor a great example of a multi-platform comparison study, check out Kirsher et al., 2025https://www.nature.com/articles/s42004-025-01665-120:03 – 25:07 - Increased integration of AI into proteomics workflowsFor an example of how proteomics workflows can be modified with multiomic data, check out Suhre et al., 2025https://www.nature.com/articles/s41588-025-02413-w25:08 – 30:05 – Recognition of the need to assess quality across proteomics workflows30:06 – 32:19 – Less of a focus on spatial proteomics this year than in past years32:20 – 35: 13 - Parag and Andreas share their predictions for 202635:14 – End – Outro

Mumbai taxi driver Parag Patil recently secured five medals in track and field events at the Australian Masters Games held in Canberra from October 18 to 25. The 46-year-old began running by sprinting after buses, but has since competed in multiple international competitions and earned numerous medals. Now, he hopes to build on his latest success and continues to proudly represent India on the veteran and masters athletics stage.

In this episode, Parag Shah of Nationwide breaks down what ethical leadership looks like in everyday practice, from making clear, values-aligned decisions to fostering trust and psychological safety across teams. He offers practical guidance on how leaders can stay grounded, navigate gray areas, and create workplaces where people feel respected, supported, and able to do […]

On this episode of Translating Proteomics, Parag speaks with Professor Jennifer Geddes-McAlister from the University of Guelph. Professor Geddes-McAlister is an expert at using proteomics to study host-microbe interactions from a systems biology perspective. Her exciting work spans studies of pathogenic fungi all the way to engineering plants to produce pharmaceutics (so-called “molecular pharming"). On top of all that, Professor Geddes-McAlister also founded “Moms in Proteomics” to support and encourage an intentional focus on the inherently unique physical, emotional, and biological commitments of Mothers, and the ensuing balance required to excel within the diverse STEM fields encompassing Mass-Spectrometry-based proteomics. Dive into this episode to:Learn why it's critical to study hosts, pathogens, and molecular pharming from a systems point of viewDiscover what Professor Geddes-McAlister is excited about for the upcoming Human Proteome Organization (HUPO) conferenceFind out what “Moms in Proteomics” has planned for HUPOChapters00:00 - Intro01:39 - Professor Geddes-McAlister's initial interest in host-microbe interactions06:13 - Why it's important to study host-microbe interactions08:10 - Pathogens vs helpful microbes10:06 - Thinking about microbes through the lens of "One Health" 14:34 - Why Professor Geddes-McAlister works primarily in proteomics as opposed to other omes19:44 - Professor Geddes-McAlister's favorite thing that she's learned from the proteome and couldn't learn from the other omes24:56 - Molecular pharming29:35 - The need for accessibility in proteomics34:09 - The need for all-in-one workflows in proteomics36:08 - HUPO 202539:56 - Moms in Proteomics42:36 - The future of proteomics43:59 - OutroResourcesGeddes et al., 2015. Secretome profiling of Cryptococcus neoformans reveals regulation of a subset of virulence-associated proteins and potential biomarkers by protein kinase Ahttps://pubmed.ncbi.nlm.nih.gov/26453029/Some of Professor Geddes-McAlister's early work using proteomics to study pathogenic fungiPrudhomme et al., 2024. Bacterial growth-mediated systems remodelling of Nicotiana benthamiana defines unique signatures of target protein production in molecular pharminghttps://onlinelibrary.wiley.com/doi/10.1111/pbi.14342Researchers from Professor Geddes-McAlister's lab use multiomic techniques to discover factors impacting the production of a pharmaceutical in an engineered plantWoods et al., 2023. A One Health approach to overcoming fungal disease and antifungal resistancehttps://wires.onlinelibrary.wiley.com/doi/full/10.1002/wsbm.1610Review on the importance of incorporating “One Health” principals into efforts to fight pathogenic fungiMoms in Proteomics websitehttps://momsinproteomics.caLearn all about the Moms in Proteomics initiative and its international community

Breaking into personal injury isn't about luck — it's about trust, strategy, and talent. Parag Amin, founder and principal attorney of the Law Office of Parag L. Amin, P.C. (LawPLA), reveals how he turned a single client request into nationally recognized PI results, and what most firms overlook when they try to add injury work. From building a personal brand that wins cases before intake to hiring trial lawyers who can actually deliver, this quick start guide shows you what it really takes to succeed in PI. You'll learn:  The first move every firm should make before adding PI How to turn personal brand into a client-winning engine The intake standards that protect your reputation from day one The difference between mercenary hires and loyal team players Why moving from tactician to leader is critical for growth If you like what you hear, hit subscribe. We do this every week. Get Social! Personal Injury Mastermind (PIM) is on Instagram | YouTube | TikTok

Parag Agrawal is the co-founder and CEO of Parallel, a startup building search infrastructure for the web's second user: AIs. Before launching Parallel, Parag spent over a decade at Twitter, where he served as CTO and later CEO during a period of intense transformation, as well as public scrutiny. In this episode, Parag shares what he learned from his time at Twitter, why the web must evolve to serve AI at massive scale, how Parallel is tackling “deep research” challenges by prioritizing accuracy over speed, and the design choices that make their APIs uniquely agent-friendly. We also discuss: Why Parallel designs for AI as the primary customer Lessons from 11 years at Twitter and applying them to a startup Potential business models to keep the web open for AI Hiring philosophy: balancing high potential and experienced talent The evolving role of engineers in an AI-assisted world Why “agents” are finally becoming useful in production And much more… References: Bloomberg launch coverage: https://www.bloomberg.com/news/articles/2025-08-14/twitter-ex-ceo-parag-agrawal-is-moving-past-his-elon-musk-drama Clay: https://www.clay.com/ Index Ventures: https://www.indexventures.com/ Josh Kopelman: https://www.linkedin.com/in/jkopelman/ KLA: https://www.kla.com/ OpenAI: https://openai.com/ Parallel: https://parallel.ai/ Patrick Collison: https://www.linkedin.com/in/patrickcollison/ Stripe: https://stripe.com/ Where to find Parag: LinkedIn: https://www.linkedin.com/in/paragagr/ X/Twitter: https://x.com/paraga Where to find Todd: LinkedIn: https://www.linkedin.com/in/toddj0/ X/Twitter: https://x.com/tjack Where to find First Round Capital: Website: https://firstround.com/ First Round Review: https://review.firstround.com/ X/Twitter: https://twitter.com/firstround YouTube: https://www.youtube.com/@FirstRoundCapital This podcast on all platforms: https://review.firstround.com/podcast Timestamps: (1:26) Founding Parallel with an AI-first mission (3:23) From Twitter CTO/CEO to startup founder (6:20) What the AI era spells for companies (7:58) The CEO to founder pipeline (11:18) Reflections on Twitter's transformation (17:48) How Parallel was born (22:31) Early use cases for Parallel (31:42) How has Parallel's ICP changed? (34:37) AI's impact on competitor dynamics (36:06) When should founders launch? (37:43) Parag's fundraising framework (40:14) Building a high-impact engineering team (44:49) Counterproductive uses of AI (47:35) How will the software engineer role evolve? (49:10) How are Parallel's customers using AI? (53:27) Defining agents in 2025 (55:02) Parallel's long-term vision (1:03:43) Parag's growth as a founder

Dr. Parag Khanna, global strategist and founder of AlphaGeo, joins Edelman's Sat Dayal to explore how climate change, migration, and emerging technologies are redrawing the global map, and reshaping public trust. Parag breaks down his concept of “programmable geography,” and shares how data, design, and local adaptation can build resilience in an age of disruption. 

Michael Ferrari is Chief Scientific and Investment Officer at AlphaGeo. We focused on how resilience varies across geographies and what this means for long term regional investability. Accompanying this discussion is their web app. This is confronting. If you change the time slider to "End of Century", most of the world is red, indicating significant physical climate risk.Particularly alarming is when you change the toggle to "Resilience Adjusted Risk". This intensifies the red color in some parts of the world - Sub Saharan Africa, India, Pakistan, Yemen, Papua New Guinea and along the coast from French Guiana to Venezuela. This indicates that these countries have low resilience and limited capacity to combat the effects of climate change. There are implications here for population migrations, as illustrated by AlphaGeo here with regard to Africa. The conversation then turned to another app, produced in collaboration with Washington Post. Here one can input your location in the US and you will be given useful information from the perspective of a property investor on long term risk and resilience. Parag Khanna is the CEO. He has given several interesting TED talks such as how megacities are changing the map of the world.Perhaps the most fascinating idea of all though from Parag is Periodic Table of States, details here. For this analysis it all comes down to stability and they rank Eritrea as worst with a score of 2.36. They rank Switzerland best at 21.77. Overall, a fascinating crash course from Michael on the kind of spatial finance I like - using geography to inform investment decisions. It was a case of meeting my idols. I am glad we were able to hit it off and am keen to see what develops.

On this episode of Translating Proteomics, Parag, Andreas, and special guest Don Kirkpatrick answer questions submitted by the Translating Proteomics community. They cover:Needs in plasma proteomicsHow proteomics impacts drug development – with special guest Don Kirkpatrick Ph.D.!How lifestyle impacts the proteomeHow the Nautilus Proteome Analysis Platform is impacting tau and Alzheimer's disease researchReferencesShome et al., 2022 - Serum autoantibodyome reveals that healthy individuals share common autoantibodieshttps://www.sciencedirect.com/science/article/pii/S2211124722006489LaBaer Lab paper investigating autoantibody levels in plasma and their relationship to health.Sylman et al., 2018 - A Temporal Examination of Platelet Counts as a Predictor of Prognosis in Lung, Prostate, and Colon Cancer Patientshttps://www.nature.com/articles/s41598-018-25019-1Mallick lab paper investigating temporal changes in platelets and their associations with cancer biology.Krönke et al., 2014 - Lenalidomide causes selective degradation of IKZF1 and IKZF3 in multiple myeloma cellshttps://www.science.org/doi/10.1126/science.1244851Seminal paper describing selective protein degradation caused by lenalidomide.Fink and Ebert 2015 - The novel mechanism of lenalidomide activityhttps://ashpublications.org/blood/article/126/21/2366/34644/The-novel-mechanism-of-lenalidomide-activityReview of research elucidating the mechanisms of lenalidomide activityNdoja et al., 2025 - COP1 Deficiency in BRAFV600E Melanomas Confers Resistance to Inhibitors of the MAPK Pathwayhttps://www.mdpi.com/2073-4409/14/13/975Describe links between kinase inhibitor vemurafenib and changes in ETV transcription factor degradationSong et al., 2022 - RTK-Dependent Inducible Degradation of Mutant PI3Kα Drives GDC-0077 (Inavolisib) Efficacyhttps://aacrjournals.org/cancerdiscovery/article/12/1/204/675622/RTK-Dependent-Inducible-Degradation-of-Mutant-PI3KUse proteomics to discover that inavolisib acts through selective degradation of mutant PI3KαCanon et al., 2019 - The clinical KRAS(G12C) inhibitor AMG 510 drives anti-tumour immunityhttps://www.nature.com/articles/s41586-019-1694-1Covers the development of an inhibitor of KRAS mutant KRAS (G12C).Schneider et al., 2024 - Feeding gut microbes to nourish the brain: unravelling the diet-microbiota-gut-brain axishttps://www.nature.com/articles/s42255-024-01108-6Review on the gut-brain axisWebpage for Johanna Lampe's Lab at Fred Hutch Cancer Center

Kerry Lutz and Parag El-Amin dive into rising tensions between Donald Trump and Fed Chair Jerome Powell. They explore Trump's corporate-style push for control over monetary policy and float the provocative idea of a “shadow Fed chair.” Parag critiques government dysfunction and resistance to innovation, while Lutz introduces the concept of “Trump GPT”—suggesting AI may be driving rapid-fire decisions inside Trump's camp. The conversation also touches on the Impoundment Control Act, runaway spending, and whether Powell's days at the Fed are numbered. Find Parag here: http://www.lawpla.com/ Find Kerry here: http://financialsurvivalnetwork.com/ and here: https://inflation.cafe Kerry's New Book “The World According to Martin Armstrong – Conversations with the Master Forecaster” is now a #1 Best Seller on Amazon. . Get your copy here: https://amzn.to/4kuC5p5  

Changes in the ways the U.S. harnesses energy shifted supply in favor of demand. Parag Sanghani points to data centers as a driving force that will shift that perspective as technology evolves. Parag talks about the ways his firm uses energy companies through ETFs and how they navigate energy volatility.======== Schwab Network ========Empowering every investor and trader, every market day. Subscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/ About Schwab Network - https://schwabnetwork.com/about

Fishing Boat – Parag'autaq (N), Parag'uutaq (S) Kugyasigciqukut parag'uutakun. – We are going to go fishing (seining) on the boat.

  Thrift Shops & Online Hustles Are Booming On this week's Trending Tuesday on The Debbie Nigro Show, we talked tariffs, thrift shops, and thriving through turbulence. Whether you're bargain hunting or business-minded, there's never been a better time to think secondhand—or second income! According to the 2024 Thrift Industry Report by Savers Value Village 16-18% of Americans shop at thrift stores each year: 12 to 15% shop at consignment or resale stores. Nearly 90% of consumers have shopped or donated at a Thrift Store up from 83% in 2022. It's The Ultimate Treasure Hunt Personally, I will donate through one door and then go back in and shop through another door. LOL I love the treasure hunt fun and get excited when I find something unique! It could be anything!  Meanwhile the report went on to say…   *Among the many incredible changes the thrift industry has seen in recent years, one of the most significant is the mainstreaming of this once-niche retail segment.  *Long seen as serving those on a limited budget, secondhand has emerged as a symbol of creativity and individuality and now appeals to a wide range of shoppers who are increasingly seeking value—and style.  *Another notable trend is the growing environmental awareness of consumers who are putting the planet first by choosing secondhand.   I was joined by Parag Amin, a savvy Los Angeles business attorney who helps entrepreneurs avoid costly mistakes (like the one that derailed his father's American dream). Parag shared how rising prices from tariffs are pushing more people toward secondhand shopping—and why that shift is also sparking big-time opportunity. From consignment goldmines to online stores, more people are flipping used goods and making real money. Think resale clothing, Amazon brands, and influencer-fueled product lines. It's all about low overhead, smart sourcing, and even smarter risk management. And yes, Parag's seen clients go from leggings to luxury lifestyles—literally! Pro tip from Parag: Want to test a resale biz? Start with consignment. No upfront cost, no inventory headaches, and way less risk. Tune in for insights, laughs, and inspiration— Listen now to this short podcast of my conversation with Parag Amin and get the full scoop on from The Debbie Nigro Show.

On this special episode of Translating Proteomics, Parag and Andreas break down the basics of proteomics — perfect for anyone with a background in molecular biology looking to get started in the field.Seasoned experts: We hope you can share this episode as a teaching tool or to inspire others to explore proteomics.Parag and Andreas cover the following questions in the episode, and links to additional Nautilus resources can be found below each question.What is proteomics?Blog post – What is proteomics? Techniques, applications, and methodsWhat are key questions proteomics can answer?Blog category – Applications of proteomicsWhy is it important to measure the proteome?FAQ on the Nautilus Resources pageBlog post – Genomics vs. proteomics: Two complementary perspectives on lifeWhat can and can't you do with proteomics?Translating Proteomics episode – Plasma Proteomics: The Dream and the NightmareLearn how the Nautilus Platform is designed to enable comprehensive broadscale proteomics and targeted proteoform studiesWhat are key proteomics methods and techniques?Blog series – Traditional protein analysis methodsBlog series – Next-generation proteomics technologiesWhat are the major pitfalls when doing proteomics?What are the challenges in proteomic data analysis?Translating Proteomics episode – Biology in Space and TimeBlog post – What is multiomics?What are people excited about in proteomics?Translating Proteomics episode – Poised for a Proteomics BreakthroughTranslating Proteomics episode - US HUPO 2025 – Key Takeaways, Trends, and Future Directions for ProteomicsTranslating Proteomics episode –

If you listened to our episode focused on science communication featuring proteomics leaders Ben Orsburn Ph.D. and Ben Neely Ph.D., then you've already heard about their excellent podcast, The Proteomics Show. On The Proteomics Show, they interview researchers in the proteomics community to learn about their motivations, their backstories, and their work. Today, we're sharing an episode of The Proteomics Show where the Bens interview Translating Proteomics host Parag Mallick. Check it out to learn about Parag's journey to proteomics, his efforts advocating for open data sharing, and his work as a professional magician.After listening, be sure to check out more episodes of The Proteomics Show on their feed where you'll find over 70 interviews with many, many interesting people in the proteomics community. Find their feed here:https://us-hupo.org/Podcasts

We have been hearing about in-office (or in-clinic) surgery suites where we can perform intra-ocular surgery such as cataract surgery without having to go to an ASC (ambulatory surgery center). Decades ago we shifted from performing ocular surgery in hospitals to out-patient surgery centers and today that is where we perform most of our cases. Some surgeons are now predicting that we will make another move, from the ASC to an in-office/in-clinic surgery suite. Our podcast guest today is Dr Parag Majmudar who runs the Chicago Cornea practice and is a Professor at Rush University. He has started Syt Surgical to help ophthalmologists start doing OBS: Office Based Surgery. This is something you must learn about. We feature a new podcast every week on Sundays and they are uploaded to all major podcast services (click links here: Apple, Google, Spotify) for enjoying as you drive to work or exercise. The full video of the podcast is here on CataractCoach as well as on our YouTube channel. Starting now we have sponsorship opportunities available for the top podcast in all of ophthalmology. Please contact us to inquire.

Which countries are best positioned to thrive in the 21st century? No, it's not Denmark. Nor China. According to Parag Khanna, the Singapore based geo-strategist, the three countries that top what he calls The Periodic Table of States are Germany, Japan and Switzerland. And the United States of America, Khanna says, going against conventional wisdom, isn't far behind. Khanna's analysis describes a "post-Westphalian world" where non-state actors like corporations and diasporas hold significant influence. Khanna challenges the more conventional rankings of countries by incorporating climate resilience, governance quality, and economic stability alongside traditional metrics into his Periodic Table.The 5 KEEN ON AMERICA takeaways from our conversation with Khanna* Traditional power metrics are insufficient for measuring state stability - Khanna's "Periodic Table of States" incorporates factors like climate resilience, governance quality, and institutional effectiveness alongside conventional metrics.* Small states often outperform large powers in stability - Switzerland, Germany, and Japan top the rankings while large nations like India, Brazil, and Russia fall into the second tier.* We live in a "post-Westphalian" world where non-state actors (corporations like Google, diaspora networks, and even organized crime) wield significant power beyond traditional nation-state frameworks.* Migration management varies significantly across governance systems - Khanna notes that non-democratic states like UAE and Singapore have effectively managed high immigration rates while democratic nations have struggled politically with migration issues.* A "neo-Hanseatic league" of small, innovative states (like Estonia, Singapore, and Israel) is emerging as a powerful network outside traditional alliance structures, forming their own connections through academic exchanges, free labor mobility, and economic partnerships.Parag Khanna is Founder & CEO of AlphaGeo, the leading AI-powered geospatial analytics platform. He is the internationally bestselling author of seven books including MOVE: Where People Are Going for a Better Future (2021), preceded by The Future is Asian: Commerce, Conflict & Culture in the 21st Century (2019), as well as a trilogy of books on the future of world order beginning with The Second World: Empires and Influence in the New Global Order (2008), followed by How to Run the World: Charting a Course to the Next Renaissance (2011), and concluding with Connectography: Mapping the Future of Global Civilization (2016). He is also the author of Technocracy in America: Rise of the Info-State (2017) and co-author of Hybrid Reality: Thriving in the Emerging Human-Technology Civilization (2012). Parag was named one of Esquire's “75 Most Influential People of the 21st Century,” and featured in WIRED magazine's “Smart List.” He holds a Ph.D. from the London School of Economics, and Bachelors and Masters degrees from the School of Foreign Service at Georgetown University. Born in India and raised in the UAE, New York and Germany, he has traveled to more than 150 countries and is a Young Global Leader of the World Economic Forum.Named as one of the "100 most connected men" by GQ magazine, Andrew Keen is amongst the world's best known broadcasters and commentators. In addition to presenting the daily KEEN ON show, he is the host of the long-running How To Fix Democracy interview series. He is also the author of four prescient books about digital technology: CULT OF THE AMATEUR, DIGITAL VERTIGO, THE INTERNET IS NOT THE ANSWER and HOW TO FIX THE FUTURE. Andrew lives in San Francisco, is married to Cassandra Knight, Google's VP of Litigation & Discovery, and has two grown children.Keen On America is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit keenon.substack.com/subscribe

As part of the non-sponsored sporadic "B-sides" series*, Ben and Ben sit down with Parag Mallick, Nautilus Biotechnology. Actually this is a crossover from February where Parag had us on his podcast, Translating Proteomics. Find the original here.(* this series is where we put guests we want to talk to but who do not fit within any sponsored series, but is still proteomics.... mostly)

In this conversation, Anthony and Parag Khanna discuss the concept of the 'Periodic Table of States,' which categorizes countries based on their stability and governance. Parag emphasizes the need for a balance between democracy and effective governance. They explore the philosophical debate surrounding democracy and authoritarianism, the role of technology in governance, and the potential of blockchain to enhance global mobility and economic growth. Read Parag's latest thoughts in Foreign Policy: https://foreignpolicy.com/2025/03/13/periodic-table-states-rankings-strength-stability-stateness/?utm_content=gifting&tpcc=gifting_article&gifting_article=cGVyaW9kaWMtdGFibGUtc3RhdGVzLXJhbmtpbmdzLXN0cmVuZ3RoLXN0YWJpbGl0eS1zdGF0ZW5lc3M=&pid=OC20506955 Learn more about your ad choices. Visit megaphone.fm/adchoices

The Second London Baptist Confession of Faith 1689 Chapter 2, Paragraph 1

Ever wondered how top dental educators and world-renowned lecturers got their start? Or are you looking for career opportunities beyond chairside dentistry? This week on Dentistry Unmasked, David and Pam chat with Dr. Parag Kachalia—practicing dentist, international lecturer, and tech expert. Parag shares his journey, from his passion for technology to becoming an AI expert, and reveals which innovations are worth your attention (and investment). Whether you're exploring new career paths or curious about the future of dental tech, this episode is a must-listen! Parag's IG: @techdds

Keith Coleman, the VP of product at Twitter/X, and Jay Baxter, the founding ML engineer, are the minds behind Community Notes. Here they reveal how a small, scrappy team built the most trusted crowdsourced information system on the internet—one that's changing the way we understand truth online. What you'll learn:1. How Community Notes actually works—a deep dive into the groundbreaking algorithm that rewards “bridging agreement” instead of majority rule2. The seemingly crazy yet brilliant way this idea survived multiple CEO changes—from Jack to Parag to Elon3. How this project started with a dumpster fire GIF (literally)—the untold backstory of its early launch4. The secret to running ultra-fast, high-impact product teams—no OKRs, no Jira; just one Google Doc5. What Meta's adoption of Community Notes means for the future of online (mis)information—why this open source system is becoming the industry standard—Brought to you by:• WorkOS—Modern identity platform for B2B SaaS, free up to 1 million MAUs• Productboard—Make products that matter• Wix Studio—The web creation platform built for agencies—Find the transcript at: https://www.lennysnewsletter.com/p/how-x-built-the-best-fact-checking-system-on-the-internet—Where to find Keith Coleman:• X: https://x.com/kcoleman• LinkedIn: https://www.linkedin.com/in/keith-coleman-19b12b46/—Where to find Jay Baxter:• X: https://x.com/_jaybaxter_• LinkedIn: https://www.linkedin.com/in/jaybaxter/• Website: http://jaybaxter.net/—In this episode, we cover:(00:00) Introduction to Community Notes(06:56) How the “bridging-based” algorithm works(13:33) The impact and scale of Community Notes(17:24) Understanding the note publishing threshold(21:32) Challenges and philosophies(26:26) The effect of notes on re-sharing content(29:41) Origin story(35:46) Embracing small teams for big impact(40:23) The thermal project approach(47:47) Algorithm development and internal competitions(50:34) An inside look at how the team operates(58:56) Working with Elon(01:05:30) Launching Birdwatch(01:10:48) The core principles behind Community Notes(01:26:15) Anonymity and pseudonymity in contributions(01:32:17) Sustaining the project through leadership changes(01:37:57) Future directions for Community Notes(01:42:12) Final thoughts and optimism for the future—Referenced:• Community Notes on X: https://x.com/CommunityNotes• Sign up to be a Community Notes contributor: https://communitynotes.x.com/guide/en/contributing/signing-up• The Making of Community Notes: https://asteriskmag.com/issues/08/the-making-of-community-notes• “Readers added a Community Note to this Tweet”: https://x.com/HelpfulNotes/status/1718103364792205704• Note-ranking algorithm: https://communitynotes.x.com/guide/en/under-the-hood/ranking-notes#matrix-factorization• Study: Community Notes on X could be key to curbing misinformation: https://giesbusiness.illinois.edu/news/2024/11/18/study--community-notes-on-x-could-be-key-to-curbing-misinformation• Study Finds X's (Formerly Twitter's) Community Notes Provide Accurate, Credible Answers to Vaccine Misinformation: https://qi.ucsd.edu/study-finds-xs-formerly-twitters-community-notes-provide-accurate-credible-answers-to-vaccine-misinformation/• Did the Roll-Out of Community Notes Reduce Engagement with Misinformation on X/Twitter?: https://dl.acm.org/doi/10.1145/3686967• Kayvon Beykpour on LinkedIn: https://www.linkedin.com/in/kayvz/• Jack Dorsey on X: https://x.com/jack• “Birdwatch gives me the creeps” tweet: https://x.com/elonmusk/status/1589454464611540992• Blake Scholl on LinkedIn: https://www.linkedin.com/in/blakescholl/• Creating Truthtelling Incentives with the Bayesian Truth Serum: https://www.eecs.harvard.edu/cs286r/courses/fall12/papers/DW08.pdf• Asana: https://asana.com/• Spaces: https://blog.x.com/en_us/topics/product/2021/spaces-is-here• Amazon MTurk: https://www.mturk.com/• Community notes on GitHub: https://github.com/twitter/communitynotes• What do I think about Community Notes?: https://vitalik.eth.limo/general/2023/08/16/communitynotes.html• X's community-led approach: tackling inaccurate and misleading information: https://blog.x.com/en_us/topics/company/2023/xs-community-led-approach-tackling-inaccurate-and-misleading-information• Linda Yaccarino on LinkedIn: https://www.linkedin.com/in/lindayaccarino/• Messi-Ronaldo rivalry: https://en.wikipedia.org/wiki/Messi%E2%80%93Ronaldo_rivalry• Supernotes paper: https://arxiv.org/pdf/2411.06116v1—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. Get full access to Lenny's Newsletter at www.lennysnewsletter.com/subscribe

Part 2 of 2: Our guest today is Parag Shah, CEO and Founding Managing Director of K2 HealthVentures. K2 HealthVentures is an alternative investment firm that provides flexible, long-term financing solutions to innovative private and public companies in the life sciences and healthcare industries. Committed to making a broader impact, K2 also donates a percentage of its profits to support underserved areas in healthcare. Before founding K2, Parag was Senior Managing Director & Group Head of the Life Sciences practice at Hercules Capital, where he led the fund's public offering and managed over $2 billion in investments. His deep expertise in life science and healthcare financing was further shaped through key leadership roles at Comerica, Imperial Bank, and BankBoston.Parag's academic background includes a Masters in Environmental Policy & Planning and a Bachelors in Molecular Biology from MIT, where he conducted research at the Whitehead Institute. With 25+ years of experience at the intersection of science and finance, Parag brings invaluable insights for first-time founders, investors, scientists, and industry leaders navigating the complexities of biotech funding.

Part 1 of 2: Our guest today is Parag Shah, CEO and Founding Managing Director of K2 HealthVentures. K2 HealthVentures is an alternative investment firm that provides flexible, long-term financing solutions to innovative private and public companies in the life sciences and healthcare industries. Committed to making a broader impact, K2 also donates a percentage of its profits to support underserved areas in healthcare. Before founding K2, Parag was Senior Managing Director & Group Head of the Life Sciences practice at Hercules Capital, where he led the fund's public offering and managed over $2 billion in investments. His deep expertise in life science and healthcare financing was further shaped through key leadership roles at Comerica, Imperial Bank, and BankBoston.Parag's academic background includes a Masters in Environmental Policy & Planning and a Bachelors in Molecular Biology from MIT, where he conducted research at the Whitehead Institute. With 25+ years of experience at the intersection of science and finance, Parag brings invaluable insights for first-time founders, investors, scientists, and industry leaders navigating the complexities of biotech funding.

On this episode of Translating Proteomics, co-hosts Parag Mallick and Andreas Huhmer of Nautilus Biotechnology discuss the reproducibility crisis in biology and specifically focus on how we can enhance reproducibility in computational proteomics. Key topics they cover include:• What the reproducibility crisis is• Factors that make it difficult to replicate multiomics research• Steps we can take to make biology research more reproducibleChapters 00:00 – 01:20 – Introduction01:20– 03:10 – What is reproducibility in research and why is it important?03:10 – 05:42 – Recent work from the Mallick Lab focused on computational proteomics reproducibility05:42 – 09:32 – Ways to help improve reproducibility in computational proteomics – More detailed documentation, moving beyond papers as our main form of documentation, and ensuring computational workflows are available,09:32 – 11:30 – Why Parag got interested reproducibility – Attempts to build AI layers on top of current workflows11:30 – 14:00 – The need to create repositories of analytical workflows codified in a structured way that AI can learn from14:00 – 15:24 – A role for dedicated data curators15:24 – 18:31 – Moving beyond the idea of study endpoints and recognizing data as part of a larger whole18:31 – 21:32 – How does AI fit into the continuous analysis and incorporation of new datasets21:32 – 23:36 – The role of AI in helping researchers design experiments23:36 – 27:25 – Three things we can do today to increase the reproducibility of computational proteomics experiments:· Be clear about the stated hypothesis· Document analyses through workflow engines and containerized workflows· Advocate for support for funding for reproducibility and reproducibility tools27:25 – End – OutroResourcesParag's Gilbert S. Omenn Computational Proteomics Award Lectureo In this lecture, Parag describes his vision for a more reproducible future in proteomicsNature Special on “Challenges in irreproducible research”o A list of articles and perspective pieces discussing the “reproducibility crisis” in researchWhy Most Published Research Findings Are False (Ioannidis 2005)o Article outlining many of the issues that make it difficult to reproduce research findingsReproducibility Project: Cancer Biologyo eLife initiative investigating reproducibility in preclinical cancer researchCenter for Open Science Preregistration Initiativeo Resources for preregistering a hypothesis as part of a studyNational Institute of Standards and Technology (NIST)o US government agency that aims to...

Kerry Lutz welcomed attorney Parag Amin to discuss the legal implications of failing to pay minimum wage in California, emphasizing the severe financial repercussions for employers, including back pay, interest, and attorney fees, which can accumulate rapidly with multiple employees. Parag highlighted the role of the Private Attorney General Act, which enables private attorneys to sue on behalf of the state, leading to significant penalties for non-compliant employers and financial recovery for affected employees. He noted California's economic strengths but acknowledged that its regulatory policies have prompted a business exodus, contrasting its growth with that of states like Texas and Florida, which offer more favorable conditions. Lutz raised concerns about wage compliance risks, to which Parag responded that paying above minimum wage does not exempt employers from liability for unpaid hours. He also discussed the challenges posed by Assembly Bill 5 regarding worker classification, warning that misclassification can lead to serious financial consequences, including ongoing liabilities even after bankruptcy.  Find Parag here: www.lawpla.com Find Kerry here: https://financialsurvivalnetwork.com and here: https://inflation.cafe

Simon Conway's interview with Parag Amin during Tuesday's second hour.

In this episode of the eCommerce Marketing Podcast, host Arlen Robinson speaks with Parag Mamnani, founder and CEO of WebGility, about the transformative role of AI in eCommerce for small and medium-sized businesses. They discuss the myths surrounding AI, the advantages small businesses have in adopting AI technologies, and practical ways to leverage AI for automation in operations and marketing. Parag shares insights from his extensive experience in the tech and eCommerce space, emphasizing the importance of embracing AI to stay competitive in a rapidly evolving market. Key Episode Takeaways: AI is not as complicated as many believe. Small businesses can leverage AI for research, content creation, and analysis. The fear of data privacy should be balanced with the opportunities AI presents. Small businesses have the agility to adopt AI tools faster than larger companies. AI can automate inventory management and improve operational efficiency. Setting clear goals can help businesses effectively implement AI solutions. AI technologies are being integrated into tools that cater specifically to small businesses. The future of AI will involve more conversational interfaces for business operations. AI is transforming marketing by enabling more personalized and efficient strategies. The investment in AI is unprecedented, signaling a major shift in technology.  If you feel Parag and his team at WebGility can help your business, you may visit: https://www.webgility.com/  For show transcript and past guests, please visit https://www.ecommercemarketingpodcast.com Or on YouTube at: https://www.youtube.com/@ecommercemarketingpodcast  Twitter: https://x.com/emarketpodcast  Facebook:  https://www.facebook.com/ecommercemarktingpodcast  Instagram:  https://www.instagram.com/emarketingpodcast/  Past guests on the ecommerce marketing podcast include Neil Patel, Nemo Chu, Luke Lintz, Luke Carthy, Amber Armstrong, Kris Ruby and many more. Thanks for listening. Be sure to subscribe and leave a review.  

Parag Amin is the Founder, Principal and Managing Attorney at Law Office of Parag L Amin, PC - providing legal assistance and services for Business Litigation & Partnership Disputes. He is an 8-time SuperLawyers Rising Star awardee. Parag is alum of University of Southern California and University of Maryland. --- Support this podcast: https://podcasters.spotify.com/pod/show/theindustryshow/support

Episode Summary:Discover the secrets of e-commerce mastery with Parag Mamnani, founder and CEO of WebGility, as he shares his journey from a computer science graduate during the dot-com bust to a leading figure in e-commerce automation. Parag opens up about the critical challenges e-commerce businesses face today, such as financial reconciliation across multiple platforms and cash flow management, and how WebGility is revolutionizing the way businesses operate. Learn how to harness the power of data-driven decision-making and customer feedback, strategies Parag honed during his time at Amazon, to improve operational excellence and achieve sustainable business growth.Explore the nuances of selling on platforms like Amazon, understanding deductions and fees, and how these elements can impact your revenue. We unpack the intricacies of expanding to new markets, including the challenges of currency fluctuations and the importance of mastering one sales channel before venturing into others. Whether you're looking to leverage marketplaces or build an independent brand, automation emerges as the key to efficiently managing multiple sales channels and uncovering hidden growth opportunities. Through insightful discussions, we highlight how e-commerce entrepreneurs can streamline operations and enhance profitability.The episode also delves into the transformative potential of AI in e-commerce, exploring how emerging technologies are set to change the landscape. From AI-driven interactions to the challenges faced by small businesses in maintaining financial clarity amidst evolving fee structures, we cover it all. Parag's story is a testament to resilience and innovation in entrepreneurship, offering listeners invaluable lessons on the attributes that distinguish successful entrepreneurs. This episode promises to equip you with the tools and insights to optimize your e-commerce operations and pave the way to success in the digital marketplace.Resources Mentioned:Webgility – E-commerce automation platformBook: The Art of Living by EpictetusConnect with Parag Mamnani:Website: https://www.webgility.com/Linkedin: https://www.linkedin.com/company/webgility/Instagram: https://www.instagram.com/webgilityinc/YouTube: https://www.youtube.com/channel/UC0hLo8JM9BAOeLGK_aVWqFATikTok: https://www.tiktok.com/@webgilityFacebook: https://www.facebook.com/webgility Support the show

Kerry Lutz and attorney Parag Amin discussed the critical importance of disaster preparedness for businesses in the wake of hurricanes in Florida, emphasizing the need for proactive planning and adequate insurance coverage, particularly business interruption and flood insurance. Amin highlighted the ongoing insurance crisis in the state, driven by the increasing frequency of hurricanes, which has led many insurers to exit the market. He expressed concern over recent legal changes that hinder homeowners from recovering attorney's fees in disputes with insurance companies, arguing that this creates an unfair disadvantage for policyholders. The conversation also touched on the balance between regulation and capitalism in the insurance sector, with Amin advocating for more regulation to ensure accountability and consumer protection, while Lutz shared positive experiences with certain insurance providers. Additionally, Amin stressed the importance of thorough documentation for insurance claims, including maintaining organized records and a clear timeline of communications, and provided resources for further assistance. The meeting concluded with a reminder of the unpredictability of disasters and the necessity of being prepared. Find Parag here: lawpla.com Find Kerry here: FSN and here: Inflation.Cafe

When treating heart failure, how do we distinguish between the expanding list of medications recommended for “Guideline Directed Medical Therapy” (GDMT) and what might be considered runaway polypharmacy? In this week's podcast, we'll tackle this crucial question, thanks to a fantastic suggestion from GeriPal listener Matthew Shuster, who will join us as a guest host. We've also invited two amazing cardiologists, Parag Goyal and Nicole Superville, to join us about GDMT in heart failure with reduced ejection fraction (HFrEF) and in Heart Failure with preserved EF (HFpEF).  We talk about what is heart failure, particularly HFpEF, how we treat it (including the use of sodium–glucose cotransporter-2 inhibitors (SGLT2's), and how we should apply guidelines to individual patients, especially those with multimorbidity who are taking a lot of other medications. I'd also like to give a shout out to a recent ACP article on HFpEF with an outstanding contribution from Ariela Orkaby, geriatrician extraordinaire (we also just did a podcast with her on frailty).  

Ever get frustrated by all those endless spreadsheets, PDFs, and emails cluttering up your workflow?   This week, I'm exploring the world of data automation in commercial real estate with tech mastermind Parag Goswami, CEO of Clik.ai.   Parag's got an incredible backstory — from building credit risk systems to founding a firm that revolutionizes the way CRE pros tackle back-office work.   Now, he's all about Clik.ai, a tool that does the heavy lifting for you with data consolidation, underwriting, and reporting, leaving you with more time to focus on actually running your business (with less stress).   If you're bogged down by endless Excel sheets or spending hours on financial reviews, this episode is just what you need.   Parag breaks down how Clik.ai helps you stay on top of your portfolio quickly, efficiently, and accurately.   You'll discover how their “human-assisted AI” integrates seamlessly into your existing systems (no need to reinvent the wheel here) and can even handle messy scans and data formats from multiple sources.   Here's what you'll learn: How AI can streamline financial modeling and speed up your deal analysis. Ways Clik.ai automates those mind-numbing manual processes and saves hours on reporting. What "human-assisted AI" really means and how it adds precision to Clik.ai's automation. The potential of Clik.ai's new "deal dashboard" for effortless deal comparisons and portfolio analysis. Why even small shops can gain huge benefits by automating their back-office tasks. Listen in, level up, and get ready to work smarter, not harder! ***** The only Podcast you need on real estate and AI.   Learn how other real estate pros are using AI to get ahead of their competition.   Get early notice of hot new game-changing AI real estate apps.   Walk away with something you can actually use in every episode.   PLUS, subscribe to my free newsletter and get: • practical guides, • how-to's, and • news updates   All exclusively for real estate investors that make learning AI fun and easy and insanely productive, for free.   EasyWin.AI

The CPG Guys are joined in this episode by Mark Edwards, founder & CEO of 345 Global, which markets store planning, merchandising, sales & marketing into one cloud-based platform. Also, Parag Shah Chief Growth Officer at Think Blue.Follow Mark Edward on LinkedIn at: https://www.linkedin.com/in/mark-edwards-51713b4/Follow 345 Global on LinkedIn at: https://www.linkedin.com/company/345global/Follow 345 Global Online at: https://www.345.global/Follow Parag Shah online at: https://www.linkedin.com/in/omnigrowthparag/Follow Think Blue on LinedIn at: https://www.linkedin.com/in/omnigrowthparag/Follow Think Blue online at: https://thethinkblue.com/Mark & Parag answer these questions:Mark - you've been in stealth mode for a while from what I know, who is Mark, what is 345 and how does one come up with a name such as 345?Parag - tell us about all things going on with space planning. Why do you feel the world is changing in retail and why does retail need transformation in this space?Mark - why were you in stealth mode for so long? What have you been building? What's the vision of 345?Parag - what is the partnership between you and 345? What do you aim to launch?Mark - what is the 345 tech platform? Why is it revolutionary?Mark - take us through the various pieces of 345 - believe those are VQ, SQ, IQ, EQ?Parag - The omnichannel world is 24-7 and 360 in terms of how she connects, how she shops, where she discovers and where she browses - shopping baskets are very fragmented. How can 345 help retailers chase this with these capabilities? Is it data is it something else?Parag - how does 345 empower merchants to win everyday? Why should they pay attention?Mark - Looking forward, what are you focused on, where can we find you? CPG Guys Website: http://CPGguys.comFMCG Guys Website: http://FMCGguys.comCPG Scoop Website: http://CPGscoop.comRhea Raj's Website: http://rhearaj.comLara Raj on PopStar Academy: https://www.netflix.com/us/title/81587828?s=i&trkid=258593161&vlang=enDISCLAIMER: The content in this podcast episode is provided for general informational purposes only. By listening to our episode, you understand that no information contained in this episode should be construed as advice from CPGGUYS, LLC or the individual author, hosts, or guests, nor is it intended to be a substitute for research on any subject matter. Reference to any specific product or entity does not constitute an endorsement or recommendation by CPGGUYS, LLC. The views expressed by guests are their own and their appearance on the program does not imply an endorsement of them or any entity they represent.CPGGUYS LLC expressly disclaims any and all liability or responsibility for any direct, indirect, incidental, special, consequential or other damages arising out of any individual's use of, reference to, or inability to use this podcast or the information we presented in this podcast.

Welcome to another episode of Mastering eCommerce Marketing! Today, our host Eitan Koter is joined by Parag Mamnani, the founder and CEO of Webgility. Webgility is a leading platform helping e-commerce businesses streamline their operations, especially in accounting and inventory management.In this episode, Parag talks about how the focus for businesses has shifted from rapid revenue growth to sustainable profitability. He shares insights into the challenges smaller brands face in a world where big players, like Shopify and major marketplaces, are dominating the space. We also dive into how AI is playing a role in optimizing operations beyond just content creation and marketing, with a focus on improving efficiency and reducing costs.If you're an e-commerce brand navigating today's landscape, you'll find real, straightforward tips on how to optimize your business, manage costs, and grow smartly in a competitive market. Enjoy the conversation!Website: https://www.vimmi.netEmail us: info@vimmi.netPodcast website: https://vimmi.net/mastering-ecommerce-marketing/Talk to us on Social:LinkedIn Eitan Koter: https://www.linkedin.com/in/eitankoter/LinkedIn Vimmi: https://il.linkedin.com/company/vimmiYouTube: https://www.youtube.com/@VimmiCommunicationsGuest: Parag Mamnani, the founder and CEO of Webgility.LinkedIn: https://www.linkedin.com/in/paragmamnani/Webgility: http://www.webgility.com/Watch the full Youtube video here:https://youtu.be/NHuA47Ihf9kTakeaways:There has been a shift in the e-commerce industry from focusing solely on revenue growth to prioritizing profitability.Small businesses face challenges in competing with large marketplaces and need to be thoughtful about their channels and customer acquisition strategies.The order management system (OMS) industry is evolving with the rise of platforms like Shopify and the addition of more capabilities.AI has the potential to optimize business operations and finance by leveraging data and providing predictive insights.Webgility offers free onboarding and support to help businesses streamline their accounting operations.Maintaining a work-life balance is important for business owners.Chapters:00:00 The Shift from Revenue Growth to Profitability in E-commerce02:34 The Evolution of the Order Management System (OMS) Industry05:48 Challenges Faced by Small Businesses in the E-commerce Industry08:19 The Importance of Data and Predictive Insights in AI10:56 The Role of AI in Business Operations and Finance15:19 The Onboarding Process and Support Provided by Webgility20:37 The Significance of Work-Life Balance for Business Owners

Check out this episode wherever you like to listen or watch podcasts! Episode Page: https://vinneychopra.com/podcast/ Youtube: https://youtu.be/JwmBLkstMRQ Spotify: https://spoti.fi/423B4fz iTunes: https://apple.co/3tQ9Tsf       ——   To learn more about how Vinney can help you, click here - https://linktr.ee/VinneySmileChopra   Smile Always and Be Happy!   -----  

Check out this episode wherever you like to listen or watch podcasts! Episode Page: https://vinneychopra.com/podcast/ Youtube: https://youtu.be/JwmBLkstMRQ Spotify: https://spoti.fi/423B4fz iTunes: https://apple.co/3tQ9Tsf       ——     To learn more about how Vinney can help you, click here - https://linktr.ee/VinneySmileChopra   Smile Always and Be Happy!   -----  

Check out this episode wherever you like to listen or watch podcasts! Episode Page: https://vinneychopra.com/podcast/ Youtube: https://youtu.be/JwmBLkstMRQ Spotify: https://spoti.fi/423B4fz iTunes: https://apple.co/3tQ9Tsf     ----     To learn more about how Vinney can help you, click here - https://linktr.ee/VinneySmileChopra   Smile Always and Be Happy!   -----  

Unlock the secrets to navigating the treacherous waters of high-stakes business litigation in our conversation with Parag Amin, a top litigation attorney from Los Angeles, California. Hear Parag's heartfelt story about how his family's financial woes led him to a career in law, shedding light on the complex and emotional nature of "business divorces." You'll gain invaluable insights into the world of partnership disputes, discovering how financial disagreements can escalate and why no business is immune from such challenges. Dive into the nitty-gritty of financial disputes within business partnerships as we discuss intentional overspending, unlawful fund withdrawals, and the critical role of clear written agreements. Parag brings these issues to life with real-world examples and a thorough explanation of the business judgment rule, which grants business owners some leeway in decision-making. Learn why legally sound contracts are indispensable for defining financial boundaries and protecting all parties involved. Prepare for business partnership success by understanding the essential steps to take before problems arise. We emphasize the importance of having difficult yet necessary conversations about roles, responsibilities, and exit strategies early on. Topics such as the implications of death on business ownership and the transfer of ownership are discussed to ensure you're well-prepared for any eventuality. Don't miss our encouragement for proactive engagement and learning, with tips on how to connect with Parag for further consultation, ensuring you tackle potential issues head-on with expert advice. (00:01) Navigating High-Stakes Partnership Litigation Parag Amin shares his personal story of becoming a high-stakes litigation attorney, discussing partnership disputes and the emotional nature of business divorces. (07:13) Navigating Partnership Disputes and Legal Issues Partnership financial disputes stem from overspending and withdrawal of funds, emphasizing the importance of written agreements. (20:26) Preparing for Business Partnership Success Nature's role in business partnerships, including discussions on roles, responsibilities, exit strategies, and ownership transfer. (27:08) Engaging With the Audience and Partners Proactive engagement and learning through social media, consulting with experienced individuals, and addressing business issues before they arise. https://www.lawpla.com/ https://www.linkedin.com/in/parag-l-amin-5504449 https://www.instagram.com/paragaminesq/?hl=en --- Support this podcast: https://podcasters.spotify.com/pod/show/themattphiferexperience/support

Discussions about the impacts of dams around the world are often focused on the displacement of communities due to the creation of reservoirs and the submergence of towns and cities. What happens when a dam affects more people downstream than it displaces upstream? How does a dam impact humans living downstream?In this episode, Parag Jyoti Saikia shares how the Subansiri Lower Hydroelectric Project, one of India's largest dams under construction, will impact the lifeways of Indigenous communities living downstream of the dam. The dam will not displace them. Instead, it will change the ways in which the river currently flows. Delving into people's relationship with the river and their understanding of its flows, Parag describes the dam's environmental, sociocultural, and political consequences for communities living downstream.Parag Jyoti Saikia is studying the construction of a hydropower dam in India to understand how infrastructures in the making shape everyday life, the environment, and geopolitics. He is a Ph.D. candidate in anthropology at the University of North Carolina, Chapel Hill. His research is supported by the Wenner-Gren Foundation's Dissertation Fieldwork Grant and the Social Science Research Council's International Dissertation Research Fellowship. For nearly a decade, Parag has been associated with grassroots organizations working on dams, rivers, and the environment. He has been writing about these issues in English and Assamese, his mother tongue.Check out these related resources: “Writing Indigenous Oral Tradition to Fight a Dam” “The UNESCO Site That Never Was” “Damming the Northeast” “Arunachal's Unfinished Lower Subansiri Dam Could Be Tomb for India's Giant Hydropower Projects” “Bhupen Hazarika Setu and the Politics of Infrastructure”