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This episode of The Sean Spicer Show features a panel of three Democrat strategists discussing primary day and the 2028 election. The discussion touches on the frontrunner for 2028 and which Senate race is generating the most excitement, offering essential news analysis on current us politics. https://www.seanspicer.com subscribe for an ad free version of this podcast https://www.Firecracker.Farm - use code spicer for a discount https://www.shopbeam.com/SPICER to receive 40% off your order https://www.MarketInstitute.org - Check them out today My latest book Trump 2.0: The Revolution That Will Permanently Transform America is available for preorder, just click the link: https://a.co/d/67kKgje Learn more about your ad choices. Visit megaphone.fm/adchoices

Homelander doesn't just want power anymore. He wants worship. And the final season of The Boys takes that idea to its logical extreme, where politics, celebrity, and faith blur into one terrifying machine that can crown a supe as a living god. We walk through the whole run, from the early chaos and sudden deaths to the final White House confrontation that forces everyone to pick a side and pay for it. We break down the season's core engine: the supe-killing virus, the V1 variant, and the way it turns The Boys into the very thing they claim to fight. Along the way we dig into A-Train's last stand, Soldier Boy's complicated return, Firecracker's loyalty test, and how the Seven collapses under jealousy, sabotage, and raw fear. We also talk about the “church of Homelander” plot, why it fits the show's satire so well, and how the god complex becomes a public performance that finally spins out on live TV. The endgame hits hard. Frenchie's sacrifice reshapes the team, Kimiko's power-erasing ability becomes the key to the final fight, and Ryan's choices add a painful family layer to an already violent war. We spend time on the finale's biggest question: when you have a weapon that could wipe out every supe, where do you draw the line before you become the villain? If you enjoy The Boys season 5 recap, finale breakdowns, and character-driven debates about power and consequences, you'll feel right at home here. If this review helped you see the season differently, subscribe, share it with a friend who watches The Boys, and leave us a rating or review. What part of the ending worked for you, and what would you change?Text us for feedback and recommendations for future episodes!Support the showWe thank everyone for listening to our podcast! We hope to grow even bigger to make great things happen, such as new equipment for higher-quality podcasts, a merch store & more! If you're interested in supporting us, giving us feedback and staying in the loop with updates, then follow our ZONE Social Media Portal to access our website, our Discord server, our Patreon page, and other social media platforms!DISCLAIMER: The thoughts and opinions shared within are those of the speaker. We encourage everyone to do their own research and to experience the content mentioned at your own volition. We try not to reveal spoilers to those who are not up to speed, but in case some slips out, please be sure to check out the source material before you continue listening!Stay nerdy and stay faithful,- J.B.Subscribe to "Content for Creators" on YouTube to listen to some of the music used for these episodes!

The new AIEWF website is live! CFPs close in 2 days and we will run our first New Engineer Orientation this weekend, get your tickets booked ASAP as they -will- sell out. Take the AI Engineering Survey and get >$2k in credits and free AIE WF tickets!One of the central tensions in the agents industry is that even while there are major decacorn agent labs like Sierra, Decagon, Notion and Cursor being built up, it is also true that it has never been easier to DIY agents, with a plethora of agent frameworks like LangGraph and Pydantic and Flue, and managed agents from Anthropic and Gemini and Amazon. There has been a wave of companies building their own background agents from Shopify to Stripe to Paradigm to Razorpay, and even Cognition's friends Ramp have built their own coding agent with other friend Modal.You'd think Cognition might feel a bit threatened, but they're not - even after all this, they were way oversubscribed for the $1B Series D they just announced:Walden Yan, coiner of context engineering and Chief Product Officer/Cofounder of Cognition, invited OpenInspect's Cole Murray to talk about why the Devin is in the Details.Full conversation live on the pod today: In retrospect, async agents were the most AGI pilled bet you could make in 2024 - the models weren't good enough yet to vibecode, and people didn't trust AI enough to let it rip, nobody (including early Cognition) was sure about the form factors. Now it is obvious:* The first wave of AI coding tools made the developer faster but remain heavily in the loop. Copilor and Cursor's tab autocomplete are prime examples However, the workflow was still heavily centered around and bottlenecked by the developer's local workflow: a developer in an IDE, watching the model, accepting or rejecting changes, and pushing code one interaction at a time.* The second wave was local agents: Claude Code, Windsurf, Cursor's agents pane: first one and increasingly many terminals all running concurrently.* The current Age of Async Agents points to a different future focused more on agent orchestration which drives end-to-end development.According to previous guest Steve Yegge, there are finer-grained 8 levels to agent adoption, but we have collapsed it into three.As Cursor's Michael Truell put it in The third era of AI software development:Cursor is no longer primarily about writing code. It is about helping developers build the factory that creates their software. This factory is made up of fleets of agents that they interact with as teammates: providing initial direction, equipping them with the tools to work independently, and reviewing their work.The agent should not sit solely inside the developer's flow. It should be setup to work in the background so that you can give it a task, a repo, a machine, a shell, a browser, tests, memory, and review loops to go do the work somewhere else.In less than a year, the sentiment has shifted from avoiding multi-agent systems:to suggesting approaches that actually work:From coining “context engineering” to building the infrastructure behind Devin's 7x PR growth and jump from 16% to 80% of commits across Cognition repos, Walden Yan has had a front-row seat to the background-agent shift. In this episode, Cognition co-founder and CPO Walden Yan joins swyx alongside Cole Murray, creator of OpenInspect, to unpack why everyone is building their own Devin, what changed after the December 2025 model inflection, and why “spec to pull request” is now becoming a real production workflow.We go deep on the architecture of background agents: harness-in-the-box vs out-of-the-box, why Devin separates the “brain” from the machine, why repo setup is still one of the hardest problems, why Docker is not always enough, and how full VMs, snapshots, scoped secrets, GitHub bots, Slack integrations, and video-based testing all fit together. Walden and Cole also dig into memory, MCP limitations, multi-agent orchestration, AI code review, SRE auto-triage, PMs shipping code from Slack, Windsurf 2.0, hybrid frontier/sub-frontier systems, and the real failure mode of uncontrolled vibe coding: your codebase regressing to your worst engineer.And as agents eat software… and software eats the world… you can draw the conclusion on what is next:We discuss:* Why the engineering world is waking up to background agents and cloud agents* The December 2025 model inflection that made spec-to-PR workflows practical* Devin's 7x merged PR growth and rise from 16% to 80% of commits* Why Cole built OpenInspect as an open-source background-agent system* The economics of $20/seat agent products and why monetization is tricky* What Cognition actually sells beyond Devin: infra, onboarding, integrations, and adoption* Harness in the box vs out of the box, and why architecture matters* Why Devin separates the brain from the machine for security and permissions* Repo setup, scoped secrets, Docker Compose, and agent-ready dev environments* Why full VMs matter when agents need to run real applications and test them* Android, macOS, Windows, nested virtualization, and machine-specific agent work* Why testing is much harder than “computer use”* Screenshots, video verification, and the “I know it works” merge moment* GitHub UX, Devin Review, AI reviewers, and agents responding to PR comments* Why MCP alone is not enough for first-class Slack and enterprise integrations* Memory, Knowledge, skills, Claude.md, and why retrieval is still unsolved* Devin's auto-generated memories and the challenge of memory pruning* Always-on agents as permanent PMs for issues, tickets, and product areas* Sub-agents, meta-Devin management, and what multi-agent systems actually add* Why pure auto-merge vibe coding breaks down after about two weeks* AI code smells, lint rules, reward hacking, and Semgrep for agent-written code* GitAI, inline context, and preserving the “why” behind code changes* Local testing, mock servers, older codebases, and preparing companies for agents* Windsurf 2.0 and the handoff between local foreground agents and cloud background agents* SRE auto-triage, support workflows, and agents as first responders* PMs, marketing, and non-engineers creating pull requests from Slack* AI agent budgets, $1k-$5k per engineer spend, and hybrid frontier/sub-frontier systems* The rise of autonomous coding factories and who Cognition is hiringWalden Yan* X: https://x.com/walden_yan* LinkedIn: https://www.linkedin.com/in/waldenyan/Cole Murray* X: https://x.com/_colemurray* LinkedIn: https://www.linkedin.com/in/colemurray/* OpenInspect / Background Agents: https://github.com/ColeMurray/background-agentsTimestamps00:00:00 Introduction00:00:43 Why Everyone Is Building Their Own Devin00:01:57 Devin's 2025 Ramp: 7x PR Growth and 80% of Commits00:03:49 OpenInspect and the Rise of Open-Source Background Agents00:07:59 What Cognition Actually Sells Beyond Devin00:09:56 Background Agent Architecture: Harness In vs Out of the Box00:12:08 Separating the Brain from the Machine00:14:07 Repo Setup, Secrets, Docker, and Full VMs00:19:13 Why Testing Is Harder Than Computer Use00:22:40 Video Verification and the “I Know It Works” Merge Moment00:23:19 GitHub UX, Devin Review, and AI Code Review00:25:42 MCP, Slack, and Enterprise Agent Integrations00:28:59 Memory, Knowledge, and Always-On Agents00:36:16 Sub-Agents, Multi-Agent Orchestration, and Meta-Devin00:43:55 Vibe Coding, Auto-Merge, and Codebase Decay00:48:38 Agent Infra, VPCs, Cloud Providers, and Fast VM Restore00:52:25 AI Code Smells, Reward Hacking, and Code Review Systems00:56:10 Making Codebases Agent-Ready00:58:30 Windsurf 2.0 and the Local-to-Cloud Agent Handoff01:01:15 SRE Auto-Triage, PMs Shipping Code, and Agent Use Cases01:04:32 Agent Budgets, Hybrid Models, and Autonomous Coding Factories01:06:51 Hiring at Cognition and OpenInspect Consulting01:07:45 OutroTranscriptIntroduction: Walden Yan, Cole Murray, and Context EngineeringSwyx [00:00:00]: All right, we're in the studio with Walden Yan, co-founder of Cognition, CPO.Walden [00:00:08]: Happy to be here.Swyx [00:00:09]: Which is a cool title. And coiner of context engineering.Walden [00:00:15]: Although I think there are many people who'd used the terms in various ways beforehand, but I did find that people, both internally and externally, enjoyed the upgrade from prompt engineering or model wrapping into maybe a more thoughtful way to build agents.Swyx [00:00:33]: For those who haven't caught up on that, I have on screen the Don't Build Multi-Agents post, which you should go read on and we might refer to, and Cole Murray, who created OpenInspect.Cole [00:00:43]: Great to be here.Swyx [00:00:43]: So let's talk about it. Everyone is building their own Devins. What's going on?The December Shift: From Handholding Models to Autonomous PRsCole [00:00:51]: So I think the engineering world is waking up to this idea of background agents, cloud agents, whatever you'd like to call it. And I think we saw a shift around the December timeframe of 2025, where the models Opus 4.5 and GPT 5.2, they reached a capability where we moved away from handholding the model and being able to actually more or less autonomously drive the model. And what I mean by that is that we could pretty much go from a specification to a completed pull request, assuming the spec was good enough, with very little friction. And that paradigm alone, I think, changed a lot of how we interact with agents, and opened this world where background agents became more practical.Swyx [00:01:41]: I think for Cole, everyone experienced this in December, but I feel like there was just this increasing ramp, right? There was this moment which was, I think, Sonnet 3.7, where, You guys rewrote Devin in one night or something. So describe 2025 or how it felt from your side.Walden [00:02:01]: In retrospect, we always thought it was ramping up, but then even now, over the last three, four months from today, it's been ramping up even faster. So it's almost funny to be talking about how, big of a leap Sonnet 3.7 was, and honestly, a lot of it was stripping out parts of Devin that were no longer needed with that jump in of intelligence. But I also just think that a lot of the recent leaps, especially, you look at, models like Opus and the latest GPT models, they are reaching levels of autonomy where people are actually finding that they actually can just be hands-off. And people who were once debating, “Oh, do I need to be in the weeds with my model in the IDE? Can I just completely move it off into the cloud?” That's a more serious conversation, and we've seen that in all of our growth charts. Internally there's this funny graph where our usage has, of PRs, our merged PRs, has grown 7X since I forget what it was called.Swyx [00:02:57]: I think Dev, maybe tweeted that. Yes.Walden [00:03:01]: it grew like 7X over, the last, I think it was, two months, three months, something like that. And then you see our engineering headcount growth. It's, gone up by, 10% or something.Swyx [00:03:11]: We were, we were afraid To release this. So this is Devin commit percentages on all Devin repos, was 16% in January and now 80% in March.Walden [00:03:25]: It's a big shift right now. And so it makes sense that a lot of people are now thinking about, buying Devin, but also maybe, trying to build their own and there's Lots of I have a lot of fun building Devin, so I can see why other people would want to build their own cloud agents as well. Matt, well, maybe it's good to hear, what initially inspired you to try to build OpenInspect?OpenInspect: Ramp, Cloud Agents, and Open SourceCole [00:03:49]: OpenInspect came about, through primarily my clients observing how they were using tools like Claude, OpenAI's Codex at the time, and seeing some of the friction that they were having with it. Primarily the Claude was being used through Slack, and a big issue they ran into was that the sessions that were launched were specific to whoever called it via Slack. And so if a PM was the one who invoked the session and they would then go to pass context to engineering can't see the session. And that in itself was a deal breaker because the PM, “Hey, engineering, can you jump in?” But there's nothing to jump in on unless they're copy-pasting out or the single response that came back. And so seeing some of these problems, I had built a similar architecture internally, just to experiment with, test out different ideas as this trend of moving off of localhost was starting to become, And as Ramp released their blog post, I had a lot of the pieces for this already in place, and just thought it would be funny to, see what Claude could do just purely from the blog post. And on my X account, there's actually a thread of where I live tweeted, going through thisCole [00:05:14]: comparing GPT and Claude as both of them are going through it.Swyx [00:05:17]: On the announcement thing or something else?Cole [00:05:19]: right after it got released. We can put it in the show notes. Yeah, it was helpful that I had already knew how to verify the system. I knew what I was looking for. I think Ramp did a great job of really illustrating, the technical aspects of how to build something. It was much more than just like, “Hey, we built a great system.” It was, “And here's how you can build it too.” And so, I resonated a lot with that, just with the problems that I was already seeing, and I thought that, looking around, I didn't really see anything in the open source community that, met this type of system. I think there's a lot that run, in localhost like Superset, Conductor, and many others.But nothing that was actually running in the cloud. And so, I built it, and I thought it was interesting to just open source it and allow anyone to then have a foundation that they can mix and match on top of.The Business of Background Agents: Open Source vs. DevinSwyx [00:06:16]: So literally after Devin was launched was, there was OpenDevin Which became All Hands. I don't know if you tried that orWalden [00:06:22]: I was going to say, one of the things that interested me a lot with OpenInspect was, you didn't try to go make it then something you monetize. There are a lot of, I think, these open source projects would then go and really try to, raise VSwyx [00:06:36]: That's why no OpenDevin. Yeah.Walden [00:06:38]: yeah, and how did you think about that? I thought that was very interesting.Cole [00:06:44]: I thought, and just what I had seen across my clients, was that having a background agent system is going to become a critical infrastructure within their company. And so because of that, I think that I wanted to open source it so that they could fork it and put in whatever customization they wanted. To that question though, I get asked all, “Oh, are you going to raise? Are you going to turn this into a service?”Walden [00:07:08]: I'm sure you've gotten offers.Cole [00:07:09]: but primarily I don't want to do that for a few reasons. One, I think that I don't want to compete for, $20 a seat. I think that is just a really difficult business. I think it's very easy to copy the main pieces of it. Again, I built this fairly quickly. And I think because you are not owning, I guess, the entire stack, it's hard to monetize. You have money being made at the sandbox layer with Daytona, E2b, many other players. You have money being made at the model layer. And you sit in this weird in-between gray area where what are you actually selling? You're selling, I guess, the infrastructure. You're selling, the integrations maybe.Swyx [00:07:55]: let's ask the guy. What are you What are you selling?Walden [00:07:59]: Well, yeah, there's multiple layers to this in practice, and actually it's funny you mentioned the infrastructure, ‘cause when we got started building Devin as well, we had to go figure out how to make the infrastructure as well because,Swyx [00:08:10]: You had to build this two years before everyone else,?Swyx [00:08:15]: Including, the model sideWalden [00:08:17]: It was not, it was not very polished at the start, when we just built it off of raw VMs from cloud providers like EC2, the boot up time was so slow, I think, And especially then, turning off the machines, saving them, and then to be able to bring them back up again when the, when you want Devin to wake up again later. It would just be out cold for like 10 minutes because that's just how long these systems took. They were not built for this repeated down and up usage. And so we actually had to go do all of that. And as a result now, one thing we offer when we go and sell Devin to people is, you don't have to worry about all the compute side of things. We'll make it work. We'll make it work in your cloud if you want it to. But aside from the product, and I want to go into the agents and the tuning of the intelligence part later, but I think a big part of what we do at Cognition as well is to just make sure that your company learns and uses and adopts these coding agents. ‘Cause I think for especially the largest enterprises in the world, you find that there is a lot of people who want to move over to using AI for their day-to-day workloads. But because of the way projects are planned, because, not everyone is literate in using AI in these ways, having a team of engineers who can actually go in and onboard you, set up all the integrations you need, the automations you need to really get to that level of, leverage with AI, is super helpful. And so We do that. We show thought partners to the customers that we work with as well.Swyx [00:09:56]: So let's talk about, architectural stuff. I think that's always, that is something that was the topic of conversation between the two of you. Is this, the mental model that you want to start with or something else? I'll just leave the floor open to you guys.Agent Architecture: Harness in the Box vs. Out of the BoxCole [00:10:11]: I think, maybe we can start here as just a general what are the pieces of a background agent system. And then maybe we can go into some of the nuances of, Decisions that you can make.Swyx [00:10:22]: But I guess I also Like, what, maybe what Walden is saying is the agent is like in this open code box, I guess. Right? This is infra, and then there's, that's the agent. And you had this discussion about whether you put the agent in here or in Out externally. Can you tease that out?Cole [00:10:39]: In a background agent systems, you have a decision to make of where the agent is actually going to run. This is typically described as the harness in the box or out of the box. With running the agent in the box, you're making some trade-offs by doing that. The negative trade-off you're making is primarily security. Because the agent is running in that box, unless you otherwise design it, all of your secrets need to go into that box as well. And given the nature of AI, it can be unpredictable, and you could very easily end up accidentally exfilling your secrets, or other unintended behavior. Now, the out of the box is the idea that we are going to have the actual agent running not directly in the sandbox, and we will have, quote-unquote, the brain of the agent running in some type of worker, control plane. That sandbox then is going to serve as the hands where the brain is basically operating and making tool calls into that environment to manipulate it. I guess other trade-off that you're making between the two systems is that, in my opinion, running it out of the box is much more complex because, you have state that has to be managed, whereas if you're running it in the box, all of the state of that agent is actually in the box, and yes, it's you could persist it elsewhere, but it's all localized and you have less concerns to worry about.Walden [00:12:08]: I think a lot of that, what you mentioned, is why we actually from the start built Devin to what we called separate the brain from the machine. The other thing that this allows you to do is reuse any existing infrastructure you have for dev boxes Perhaps. And so you don't have to worry as much about making a new type of dev box that has all the dependencies the brain needs, as you mentioned, the secrets the brain needs as well. One thing that we've seen some customers run into is, you have a GitHub app and you want Devin, your agent, whatever, be able to interact with GitHub through this application, but then you have different users with different actual permissions. If they are all interacting through the same GitHub app and there's no actual, separation between the system that decides, what it does and the actual secrets on the machine, then you run into an issue where, okay, it's hard to do the separation. But in practice, with Devin, it's much easier because we just say whatever you put on the machine, that is, the scope of basically what the user is free to do, what the agent is free to do. So only put the most scoped secrets on that machine, and then the brain is fully not accessible from the machine. So you don't have to worry about messing with the, any of the most secure parts of the brain if the user is free to do whatever they want with the machine.Swyx [00:13:31]: I was going to just bring, I have this, chart from OpenAI, where I don't know if this is, in the box, out of the box. That is something that they do use to describe it. And then also recently Anthropic did, managed agentsSwyx [00:13:44]: Which is, this is their thing. I don't know. It's all, it's all variations of the same pattern, right?Cole [00:13:49]: So this would be out of the box.Swyx [00:13:51]: Which, is preferable for them because it's less work?Cole [00:13:56]: I would say it's more work.Swyx [00:13:58]: It's more work?Cole [00:13:58]: But it, in my opinion, it is the better architecture of the two. It's just, you're taking on a bit of complexity by doing that.Repo Setup, Docker, and VM-Based Development EnvironmentsWalden [00:14:07]: One thing I've not seen a lot of other players do well is how do you manage what's actually on the box? And this can be complex for many reasons. Let's say you have a big repository that's changing and updating a lot with changing dependencies. How do you make sure that the working environment of the agent actually stays up to date, has all the credentials it needs to, let's say, run the app and test it, and all the things you want your autonomousSwyx [00:14:34]: So a repo setup.Walden [00:14:35]: Exactly. So in, internally At Cognition, we call this repo setup.Cole [00:14:39]: The hardest part ofWalden [00:14:40]: It's been a perennial problem since the start of the company, of how do we help people get this set up? Because not everyone just has, working cloud environments working out of the box. And do you find this to be a common problem withSwyx [00:14:53]: How do you solve it?Walden [00:14:53]: Your clients?Cole [00:14:54]: This is a very common problem, and through my consulting, this is a lot of what I help teams do. A lot of teams don't really have great developer environment setups, if any. A lot of the times it's, “Go talk to Bob and get the secrets,” and that obviously doesn't work when the agent needs to actually set this up. And so a lot of that, most teams are using Docker Compose or some type of microservices. And so for theSwyx [00:15:19]: Even in prod?Cole [00:15:20]: Not in prod. With the OpenInspect, you are using this primarily to interact, and make code changes. There is other use cases, but you can hook, whether through CLI, MCPs, other tools, you can then hook that into your production systems primarily for, SRE type use cases. But you are not, necessarily, trying to test your prod internal microservice through the system.Walden [00:15:48]: And you mentioned Docker Compose. I think one direction we saw some of our friends take early on was, using Docker containers as the level of abstraction for their models. There's lots of reasons, I think, why Docker containers are not great. One thing is, Docker container's not really a true security boundary, for one. But the other is, if you are running real applications, a lot of times those applications use Docker, and then you have to think about Docker in Docker, which is, really weird. And so I think part of, the really hard challenge of getting VMs to work, why did we do that? Well, it was because we realized that you actually needed, full VMs to be able to do these types of things. And especially nowadays where there's actually value in running the application and clicking around and sending you screen recordings of these things. The value just, keeps adding on top of that. But it is a decision I see people run into when they try to build their own systems, is, “Oh, do we, in addition to this, do we put the agent in the machine or out of the machine? Do we use Docker? Do we use something else?” What do you recommend people nowadays?Cole [00:16:57]: I think Docker is a good solution for maybe not running the agent, but running your infrastructure, because that is more or less the same setup your engineers are probably already using. If they're not, then I don't know what they're using. But they're probably already using Docker Compose.Swyx [00:17:14]: I've always had a small candle for web containers. I don't know if you guys have tried them before.Swyx [00:17:19]: To me, they were, supposed to be like Docker Light.Cole [00:17:22]: Is it?Swyx [00:17:22]: I don't know.Cole [00:17:22]: No, I haven't tried it. But yeah, I think any environment that you've set up that is a good experience for your developer naturally lends itself to being easy to set up for the agent. And once you figure out that local developer story, you've more or less solved the agent in a sandbox, environment setup. OpenInspect does have hooks as well, where you can, run a setup SH script that will pre-install everything. You can then pre-snapshot that build so it starts instantly, and then there is a second hook to actually then, restore the state of the sandbox when it comes back. And so you can already have all of those microservices running and basically get the same experience that you would on your machine within the sandbox.Testing Agents: Computer Use, Screenshots, and Real App WorkflowsWalden [00:18:08]: Another thing that we've been thinking a lot about is like Different VM service offerings. Have you had customers where they needed like macOS specific VMs or like Windows specificWalden [00:18:20]: VMs?Walden [00:18:22]: There are like many technologies in the world that only work on specific types of machines, right? If you're building a.NET application that has to run on Windows or like, maybe more commonly if you want to build iOS or macOS Does that workSwyx [00:18:32]: Does Commission supportSwyx [00:18:33]: Choices like that?Walden [00:18:35]: The fundamental architecture we do, because we do the separation, it does support, but the actual work in progress is happening right now on these. Another thing that we've actually recently added support now for, it's in beta, is doing Android development. To do that, we needed to support, I think, nested virtualization within our machines because the VM itself is like a, is a virtualized Firecracker instance, and then you had to then run another Android emulator inside. And there's like weird performance issues that like, it, which is why it's like still in beta. We have to think through these problems, but it unlocks a lot for anyone who wants to do Android development.Swyx [00:19:13]: I was trying to find like a reference video for the testing thing. I couldn't find it, but I think you worked on the testing, capability. Why call it testing and not like computer use or I don't know, it's, what's the general Category of problem?Walden [00:19:26]: I think that when people think about the ability of an AI to run your app and test it, I think they actually over-index on the computer use part of it because computer use in my mind is the literal, okay, you want what button you want to click. Can you emit the right coordinates to go click that button? I think testing is actually a really interesting likeWalden [00:19:48]: Problem-solving, challenge for these AIs because if you wanted to do arbitrary testing, imagine you make a change that spans the frontend and the backend, maybe, even some other like even more deeply nested service. To actually test that change, we have to reason through what-- how do you first run these applications to orchestrate with each other with the right version of the code? Then, okay, how do I trigger the feature or how do I make the thing actually happen? And this can get arbitrarily hard, maybe you have to be an admin. Maybe a certain thing has to be feature flagged on. Maybe, you have to like run two sessions and then send us a very specific word into one of them to trigger a specific behavior. And figuring out how do you do that requires a lot of code base context, requires, a lot of orchestration that we've specifically done. And in some cases, we found that you actually, no one frontier model can actually do this full end-to-end task itself.Walden [00:20:42]: We've seen cases where we actually had to orchestrate different frontier models together to solve this problem together. That is where we spend most of our time when we think about this testing problem, not so much the computer use part. Computer use for what it's worth has gotten a lot better with recent models and it's made that part of the job certainly easier.Swyx [00:20:58]: Especially with like even 4.7, that they released yesterday, apparently like way better in terms of the vision stuff, which is going to be encompassing computer use.Walden [00:21:08]: Having evals for all these as well is something that like takes a while to build up. And having the evals be right is tricky as well. Do you ever see like, clients who are building their own agents have to start standing up evals to make sure things don't regress?Swyx [00:21:25]: Not so much evals in the traditional sense, but specific to the testing part that has just gone in. I just added support for screenshots And in theory you can also do video. I need to put in a plugin to do that. But they do show up natively, and it was a very heavily requested feature, especially after Cursor's recording came out. I think that was very enlightening for everyone of like, “Oh, this is a very good feature to actually have.”, I think with Devin you guys have had this for a while.Swyx [00:21:57]: Oh, yeah. See how screenshots work. Yeah, I don't know if there's anything, super and not obvious. It's like once what feature to build, you can just prompt it and it Will mostly work.Walden [00:22:09]: I think to Walden's point, though, the computer use is a subset of the larger testing problem, and I think that's very specific to the code base that you're working and it's not something that, out of the box that you could just solve it. The-- you do need the code base context to actually know how to test it. And I think in the case of a background agent system, you fortunately do have that code base locally that what is changing and could then inspect it and use that to drive the model.Swyx [00:22:40]: For those who haven't seen it before, this is an example of how it works. You, after the PR is done, you click testing approved, and then it sends you back a video. What I really like is that it labels, It's very small here, but it actually labels what it's testing. And then it-- and then you actually see the cursor and everything. So I don't know, yeah, the engineering in this, just Whatever you want to show. ‘cause this is like, this is one of those like, oh, few of the AGI moments, right? ‘cause Once I look at this, I actually don't I wish I can just merge inside Of Slack instead of going to GitHub ‘cause I don't need to see the code. I know it works.Walden [00:23:19]: Maybe a new feature in Cursor. Yeah, the annotations at the bottom was also a big difference for me when I, when I added those.Swyx [00:23:27]: It's just like, what am I looking at? What are you trying to demonstrate?Walden [00:23:30]: Exactly. There's a surprisingly long tail of small details that ends up making a big difference for this end metric of like how fast do you actually merge the code in. One experience that we spent a lot of time tuning early on was what is the right experience on GitHub for these tools. Because I think, most tools out there when you build the agent, you'll think about, oh, it'll create the PR for you. We try to take that a step further and say, “Oh, what if we actually made sure you could interact Devin, with direct Devin directly on GitHub?” And so we made sure that you can comment on GitHub, and Devin would actually receive those comments and address them back. But there's actually quite a bit of tuning you have to do here because you can imagine that actually like-We recently have Devin Review, for example. Devin Review will post comments on his own PR And then Devin has to then goGitHub Workflows: Devin Review, Comments, and PR AutomationSwyx [00:24:23]: He answers his own comments, which is Really loopy. So like, yeah, I like that it just updates here that it's, that I have commented But usually it's just me saying like, “Hey, merged, fix any merge conflicts.”Walden [00:24:37]: The, so when Devin fixes his own comments, you might be scared that, oh, maybe I'll infinite loop. But we've put a lot of work into making sure it doesn't, both by making sure that the comments are high signal, but also that the agent is thoughtful about what comments it immediately goes and tries to fix, and what comments it's like, “Wait a second, I think you're wrong.” Actually, that's one of my favorite moments is when Devin tells me that I'm wrong, when I try to get it to do something different. But tuning that behavior, actually makes a big difference in terms of how useful the actual GitHub experience is.Cole [00:25:06]: I think to touch on that as well, I think having the AI reviewer integrated into the system is a critical part of this background system. OpenInspect does have that. It has a GitHub code reviewer that you can control the prompt. It does do comments as well. It doesn't do them automatically yet. The capability is there, but it's not fully used.Swyx [00:25:27]: So you have to ask for it?Cole [00:25:28]: you do, yeah. You can tag it on GitHub, and then whatever you named your, GitHub bot, it will then follow up on it. It will then, if you have merge conflicts or whatever you have asked it to resolve, it will then resolve it, but it doesn't do it automatically yet.Integrations: Slack, MCP, and First-Party Agent InterfacesWalden [00:25:42]: Well, I'm curious, what is, the most common thing that people end up requesting, that they still need on top of OpenInspect when you help them go implement it?Cole [00:25:52]: I think a lot of it comes down to actually integrating it into the company. It's one thing to have the background agent system set up, but if it isn't actually integrated into your larger ecosystem, it isn't that useful. It is useful to be able to kick off sessions, but what we really want to be able to do is hook it into all of our other systems, whether that is the production database with read-only credentials, the logs, a Confluence or internal knowledge-based system. I think that is where I see the huge leap for companies, and that can be a challenge for companies as well who are maybe not familiar with exactly how to approach it, especially if they're in environments that have more compliance type things where, access control can be pretty big and how do you deliberately think about these problems, I find to be, one of the problems that comes with a system like this.Walden [00:26:46]: The thing we found is So, MCPs, obviously it has been like this, really big explosion of, oh, you can go, integrate it with all these different things. But to actually get the integration right and the and get the right experience, oftentimes we found that we had to go build our own ad hoc things. I think Slack is a great example of this. You could give your agent a Slack MCP and okay, it can post messages back to you on Slack. But we actually use Devin like a coworker in Slack, and that's how it's been built from the ground up. But to do that, you actually need to, support webhooks that come back, right? And then Devin has to respond in a natural way and then hopefully don't spam your threads too much and annoy the people in your company. So you got to tune that experience just right. Especially when there's a lot of back and forths, we find that we actually have to go beyond the simple MCP integrations in these places.Swyx [00:27:39]: I just pulled up the MCP marketplace. I know this is a Fair amount of work. Is the answer to eventually take first party control of all the top MCPs? Is that theWalden [00:27:48]: I would love a world where you could have something that's more expressive than MCP. That, goes both ways, not just a set of tools, but a proper system that interacts back and lets it Have the right experience with all these interfaces.Swyx [00:28:03]: So there actually is sampling in the MCP spec, but nobody Uses it, right?Walden [00:28:07]: And so I think that's the other part is, actually we found that when the MCP spec starts to get too complicated, it starts to lose its original promise of Being like a simple one-step connect. Now then we have to go figure out how to support all these different variations of things and It starts to look a lot like just building the first party integrations in a lot of these cases now.Cole [00:28:29]: I think it matters, too, how critical it is to your company, right? If this is something that nearly every session is going through, it probably makes sense to own it so that you can make optimizations on top of it Versus just whatever is off the shelf.Swyx [00:28:43]: Awesome. Other than MCPs, what else, sorry, well, I don't know if that's Narrowing in too much on, integrations. But what else? What other elements of building OpenInspect or Devin that you guys really sink on?Memory and Knowledge: What Agents Should RememberCole [00:28:59]: I think, a problem that comes up very frequently is this idea of memories or knowledge base.Swyx [00:29:05]: Oh, boy. How do you solve it?Cole [00:29:08]: so not solved yet, is the short answer.Cole [00:29:11]: it's something, there's a open issue for it, someone asking about it.Swyx [00:29:16]: There's, I, D Wiki hasn't indexed anything about memory yet.Cole [00:29:20]: how I'm seeing it solved across my clients is primarily through skills. I find that skills can be a good gap within that or updating Claude MD, but I think memory as a whole is a pretty unsolved problem, and it is why I've been hesitant to add it. I think there is parts of memory and that can be addressed, but I think as a whole it's a very difficult retrieval problem.Swyx [00:29:44]: Oh my God. RAMP didn't write anything about memory? I see zero search results.Walden [00:29:50]: No. Memory can be quite tricky to get right because it's the retrieval, but also the generation of the memories that can be really tricky. You don't want it to just like Remember very specific details.Swyx [00:29:59]: Walk us through the Devin memory journey because I know there's been a journey.Walden [00:30:03]: the first version of memory that like stuck around for a while was A system we have called Knowledge. And the idea was we wanted it to pick up things over time and not need the user to be proactive about teaching Devin things. So, okay, any time you remind Devin, “Wait, no, that's not quite the way you're supposed to use Git”Like, we actually want Devin to say, “Hey, do you want me to actually just remember this for the future?” And for you to just basically quickly approve or reject and for it to build up over time. ‘Cause I find that, 95%, I think, or some crazy stat like that of the memories that Devin has are all through these auto-generated things. Very few people actually just want to sit down and write big docs on Here's how you're supposed to work with the technology, et cetera. The generation and the retrieval has been something that we've been trying to tune a lot over the years. Generation, you don't want it to remember something like, if you asked one time to like, “Oh, please open as a draft PR,” you don't want to be like, “Oh, everyone forever now should get their PRs as draft PRs.” But you do want some, conveyor. Maybe you want to say like, “Oh, Cole generally likes, things to be created as draft PRs.” Same with retrieval, if you have thousands of these memories, how do you actually make sure they're retrieved at the right time? And that can be quite tricky to do right without exploding the context with a bunch of useful yeah, useless information. Surprising amount of just, eval work to just make sure that, memory is, remains a reliable system as new models come and go.Cole [00:31:31]: Do you have anything that you could share on, memory pruning? And like the temporal aspect of memory?Swyx [00:31:36]: Deleting and forgetting?Walden [00:31:39]: The, today, the, So the things they could do is it could edit memories. And so if your memory used to say like, “Oh, Cole likes to open everything as like a draft PR,” then you can imagine, “No, don't do that.” And then it'll say, “Oh, do you want me to update the memory to be Cole now want everything as, open PRs?” I think that at the same time we don't know if this is going to be the final version of the system. Whatever we have here will probably, translate into the new system that we'll be coming up with. But I think one big difference between two years ago and today is these agents are really good at using anything that resembles a file system natively. And so part of us are, is thinking, “Oh, should we rebuild memories to feel more like a file system that we let the agent navigate on its own?” That's been an interesting exploration. Also similar ideas in the scale space.Swyx [00:32:35]: I am pulling up OpenClaude's memory thing right now. So memory, OpenClaude has like this like daily memory journal thing, right? And you can I mean, that is a file system you can grep through and is a source of truth. I don't know if it's the best. It's probably super noisy, but at least, if you lose something you can discover it or you can apply some, forgetting algorithm to, more ancient memories that don't get recalled again or something. I don't know.Walden [00:33:01]: One thing we've been trying to do to push the boundaries of how you use agents at your company is letting an agent basically have a very similar file, a memory.md or something, and just like be your permanent PM for a specific set of issues maybe. So we have like some Slack channels internally, maybe a Slack channel dedicated to, a specific product like DeepWiki maybe. And you can imagine that, or you want a Devin that never stops, it's just always awake, but it has this like memory dock that it can just maintain for itself about, okay, what are like the number one priorities of what we have to fix and prioritize? Who is responsible for some upcoming work? Maybe they'll even Devin will even tag you on some recurring basis. And so it's been an interesting move to see, okay, how can we actually use Devin for more than just engineering? Can we actually upstream above the engineering process and maybe it's just Devin creating tickets, which then maybe some humans do, but then maybe other Devins do.Swyx [00:34:00]: One of my more fun automations is go research competitors and just suggest stuff to me on a weekly basis. That's the automation. I can't find it right now, but basically it just like, “Look at competitors and suggest things.” “And here are three things that you've suggested that I don't want any more of,” and you just stick that in the prompts. But like I wish actually So for like when I, for example, when I reject a PR, I wish that it updated memory so that I can then just not have to go up, go back and update the scheduled, sync, but anyway, feature request.Walden [00:34:31]: what? We might change it soon. I guess OpenInspect, in the time you've been around, has there been anything you tried to implement but then you had to like undo and like do a different way?OpenInspect Architecture: Webhooks, Control Planes, and Agent StateCole [00:34:41]: Nothing yet, but something that is on my mind. The initial way that I built it was that each of the integrations lives as its own package. And so you have The Slack bot, which is what's handling the webhooks, and then is basically interacting with the control plane. As I'm seeing the system starting to be more integrated, specifically with the GitHub bot integration, I'm considering bringing that all into the central control plane because especially now I want to start, And a request that I'm getting is the ability to monitor, the actual, pull requests being merged, as well as just tracking ofSwyx [00:35:19]: What do I have open?Cole [00:35:21]: What do I have open? How many of these are getting merged? How many comments are showing up? To just understand the health of the system. And so in the case of a GitHub app, you only have one webhook. And so then it's a question of do I put that webhook in that GitHub bot package? That's weird. It doesn't really make sense to live there because that package is more for like the code reviewer. Or do I like centralize it? So that's something that's on my mind of, making that decision. I think the other one we touched on earlier is the harness in the box versus out of the box. I think long term the architecture will eventually come back out of the box. Some of the newer tools that I've added are calling back into the control plane so that you don't have the secrets in the sandbox. And so I think long term I probably will pull the actual, agent out of the box, but I think for now it's fine.Subagents and Multi-Agent Systems: When Parallelism Helps or HurtsSwyx [00:36:16]: Just, a quick question on pulling the agent out of the box. I'm One thing I'm very bullish on this year is agents calling other agents or spawning sub-agents or Whatever you want to call it. Does that make it harder or easier? I can't tell. Because if the harness is in the box, you can just spin up more boxes. If the harness is outside the box, then you're, it's less easy because you are, you have a unicorn pet of a, of a harness that's, living outside the box.Cole [00:36:45]: In theory it would be the same way, right? Whether, one agent has launched many, sub-sessions within it, OpenInspect, for example, can launch sub-sessions and actually create other environments and then monitor them. In the case where it is out of the box, that would basically just be an additional session that's running. And so that session is also running outside of the box. It's running in your worker plane, wherever you're running this. And then you really just have to think about how does your top level agent then interact with it. I do think it can be more complex, just ‘cause again, you have now a more difficult architecture. But I think if you figured it out once, it's probably fine.Swyx [00:37:26]: Well, then I'm just, throwing it open to you in terms of, I call this like meta Devin management. Which is like the, Devin's calling Devins or Devin scheduling Devins or querying trajectories or anything like that. What have you built or unshipped, anything?Cole [00:37:46]: I think one of the surprising things we've seen is that a lot of the ways that, these, separate agents work with each other, and you want them to, parallelize their work, has still mostly followed the same manager sub-agents regime. And a lot of people I think are excited about this world where you have swarms of agents that, talk with each other all over the place. We've actually given Devin an MCP so they can just go arbitrarily message other Devins And create new Devins, et cetera. But I guess, it somehow creates, a really chaotic world in that sense. And so we've still found that most practical use on a day-to-day basis has been one single Devin.Cole [00:38:33]: Figuring out how to segregate the work and get, have other Devins work on it in, a relatively isolated sense, each with their own boxes Not sharing machines, so there's, a very little room for conflict is the regime that you have to create today.Swyx [00:38:50]: I'll call out, the experiments from Cursor, right? This is Wilson Lin's work on Single agent to multi-agent, and you're obviously famously on the side of don't build multi-agent. But they went through the whole thing, only to arrive at, this Which is exactly what Devin has, I think.Cole [00:39:08]: I think there will be a revision to that post at some point AboutSwyx [00:39:12]: Tell us about itCole [00:39:12]: I think multi-agents were very much not at all possible a year ago. You do see more multi-agent experiments today, but you can argue, are they really multi-agents, or are they just just, tool calls,? There are people who, will create sub-agents to go look for XYZ file, XYZ implementation. Has really nice context management benefits because all of the tool calls and tokens that it spends then get collapsed back to just the answer for the main agent. There's a lot of benefits to doing this. We basically have Devin do this with Deep Bookie, make a call out to Deep Bookie, give you back the results, but that feels like a tool call,? It's not like these, two collaborators actually talking back with each, back and forth with each other. But I think the thing that gives me the most bullishness that multi-agents might actually be possible is actually what I said earlier about Devin will actually sometimes tell me I'm wrong and push back, and I think that demonstrates a level of maturity and communication today that makes a multi-agent world possible. One, can two agents who have seen different information come back to each other and actually figure out who is right, what is the correct implementation? They're not just, yes men. Claude, I guess is like, used to just say, what is it? “You're right,” or,Swyx [00:40:25]: “You're absolutely right.”Cole [00:40:26]: “You're absolutely right.” Yeah.Swyx [00:40:28]: The Have you seen, did you seeCole [00:40:29]: The age is overSwyx [00:40:30]: The Codex app troll in Topic? This is the Codex app. Inside of Settings, there's a little, there's a little Easter egg, right? So if you go to, the Themes or Appearance, right? There's all these, color codes, and the top is absolutely, and it's the Topic's colors. Which is such a troll. Anyway.Model Behavior: Pushback, Adversarial Prompts, and Agent SkepticismCole [00:40:53]: I love that Easter egg. Did you discover that yourself?Swyx [00:40:54]: No, it was, someone was, tweeting about it And I was like, I was like, “Is this true?” Because, sometimes people just tweet stuff to, get a rise out of you. But yeah, there you go, in Topic colors.Cole [00:41:06]: Yeah. So yeah, we're out of this regime where, it just says you're absolutely right, and they can have real conversations and real back and forths.Swyx [00:41:13]: You can prompt it as well to be more adversarial or whatever. Yeah. Okay. Yeah, that, I mean, to me, that is more intelligence, right? That is not just something that's, a dumb tool, it's actually pushing back on you I think. Yeah.Cole [00:41:24]: when you mentioned, of course, the blog posts. There was one blog they had where they fed a swarm of agents together and built a browser.Swyx [00:41:34]: That was I think that was the one.Cole [00:41:36]: You can have, likeSwyx [00:41:37]: I think it's the same oneCole [00:41:37]: Creation of it. We found a surprising success of, don't do a swarm or anything, just have one Devin, it does its own context management. Just let it keep running for a while and give it some crazy tasks. I think we asked it to, rebuild, a Windows OS system. And it managed to do it just like, going on for long enough. It'sSwyx [00:41:55]: Was this Andrew's thing?Cole [00:41:58]: there were lots of demos that we ended up not posting, ‘cause at some point we'd just be posting way too much a bunch of, Demos. But I love that because it shows that I think the multi-agent thing still has, a bit of exciting sexiness to it, which is maybe still beyond still, the actual delta it adds to the capabilities of these systems. But it's absolutely the future. I think we're heading in that direction and we can see the progress being made there already.Swyx [00:42:25]: If I were to, make one super minor pushback because I don't feel that confident about it yetCole [00:42:33]: Go for itSwyx [00:42:33]: But I've had Ryan Lopopolo from OpenAI on the pod And he's a super slop cannon, right? Oh my God, that's my coding agent being done. I downloaded this, Peon Ping. I don't know if you guys have heard this. It takes like-, sound packs from popular games like, Command and Conquer and Warcraft, and then it plays it whenever it's done. And so it's like, “Work,” or whatever, “At your command,” or something. Anyway, what I got from the Cursor code base and from Ryan's thing was that there's a slop cannon approach where you try to loosen the single agent's, bottleneck, and I feel like that is, probably an, a very important thing to try to figure out. I don't think anyone's, really solved it. Because then you just have more reviewer slop on top of the agent slop To try to wrangle it all. Ryan will probably very strongly object that I say that he hasn't solved it, but he thinks he's He thinks he's completely solved it. But I think it's still I think it's, very important, ‘cause, that is a bottleneck, right? I feel Devin is slow sometimes Because I'm like, well, yeah, this is very readable and very sensible, but also it is slower than it could be if I just, I want a button to just say, “Just ramp this up 1,000 next parallel, in parallel and just, see what happens,”? And I don't know if that's, feasible at some point in the future.Code Review, Entropy, and AI SlopWalden [00:43:55]: I And we've also run experiments internally where we've basically tried to build entire products, true products that we knew we would eventually ship, but for now, let's try to see if we can do it just by purely, vibe coding on top of each other, auto merge, no code review at all. And then there's this benchmark of how many weeks can you go onto this for Before you say, “We have the trashiest code base.”Walden [00:44:18]: “Let's actually rewrite it from scratch.”Swyx [00:44:19]: Start a new factory, yeah. What'd you find?Walden [00:44:21]: I think we found that the state-of-the-art in December was you can probably, run this for about two weeks. By the end of those two weeks, you'd find that, hey, you want to, change the color of a button. Well, it turns out this button is implemented in, 10 different places, and they, have All these different variations, and oh, you forgot one of them, and actually it's a slightly different color in one spot. And you're like, “Okay, this is too much to work with. Let's actually try to do code review at the same time.” And make sure that we're on top of our software, actually cleaning it up a bit And making sure it's done in a scalable way.Cole [00:44:54]: I think building on that, the idea of, you don't have to look at code, I think is generally a bad idea. And the meme that I have for thatWalden [00:45:03]: What timeline, all right, is Do you think that statement will be true on?Cole [00:45:06]: I think probably for a while it'll be true that you should continue to look at your code. A problem that I see a lot of teams run into that I work with who are embracing AI native, AI first coding, is The meme that I have is that your code base regresses to your worst engineer, because that engineer who is, very gung-ho about AI and is not auditing their code, their pattern starts cementing into the code, and now the AI is referencing their patterns. And so now their if/else block that, is 20 if/elses back and forth, the AI is seeing that as the pattern of how things are done and starts to then exponentially grow this slop. And I find to your point, a pretty good approach to that is having scheduled cleanup, whether by humans or through systems, that are looking for duplication. They then address that. You'll end up with like 12 helpers for how to format a date. And you need to address that, because otherwise it will continue to sprawl.Swyx [00:46:09]: Within balance, I think it's fine to have some duplication, and then sometimes To have garbage collection, right? Yeah. The What I've been, talking about with a lot of engineering leaders is that you want to be very strict about the boundaries between modules, and it's your job as an architect, as a CTO, whatever, to say like, “Okay, here's the hard contract between you guys and you guys. Whatever you do inside this black box is your business. You do whatever. But between these guys, let's be, really damn clear, and any movement must be signed off by a human or me,” or. Then, and like that's that. I don't know if you have any other modifications or advice.Walden [00:46:44]: Well, I guess generally on the topic of, where humans can be useful, I found that ‘cause, some of these, really deep infra problems, sometimes just having a human that just has, really deep expertise can make a big difference. I've actually seen this come into play when actually building agents. So we've had a few friends now, try building their own coding agents, and I think one same problem that I recurringly heard a lot of them run into was this problem of like, “Oh, Grep is really slow on our agents' machines.” And so a lot of them, I assume because they're using AI and they themselves don't have, super deep infra background knowledge, say, “Okay, we're going to go build our own custom Grep index. It's going to be really fast,” and use that as a way around this problem. When we ran into this problem About like, maybe like a year and a half ago when we were, in the early days of building Devin, we obviously didn't have AI then. We just asked our, how to, how to do this. You can just swap out a new Grep index, so.Infrastructure Details: Grep, File Systems, and SandboxesSwyx [00:47:45]: What do you mean you hand-coded Devin? What?Walden [00:47:48]: It's like, can you believe we hand-wrote this code? And we had, our infra people who are really amazing, they were looking into it and they're like, “Oh, what? We realized that actually the root cause of this problem is actually super simple, but like fine-grain detail,” which is that a lot of these virtual machines actually underlying them don't use real file systems. They use these, network file systems where things are actually cached over the network actually in S3. So when you're Grepping, you're actually making network calls Every time you're doing these things, and that's why Grep is extremely slow on these machines. And so again, goes back to, what is all of the crazy infra work that we had to do to actually get these machines working. If you try to do this yourself, there are tons of small details like this, and so we had to eventually go swap out that network file system. ButSwyx [00:48:35]: I think there's a write-up about it, right? Silas did one about the virtual file system.Walden [00:48:38]: Oh, that was a whole other thing. TheSwyx [00:48:39]: Oh, that's a different thingWalden [00:48:40]: The BlockDev file storage formatSwyx [00:48:42]: I'll bring it upWalden [00:48:42]: Which is, a file system format that we built so that the VMs could be spun up and down very quickly. Basically, the intuition behind this is-Imagine you have, a terabyte of disk, and your agent only, wrote, a hundred lines of code on top of that disk. How long does it, say, take to, save and re-bring up that disk? And most systems, because you're not optimizing for this case, it's just, on the order of a terabyte of work because you have to Save all of that and bring it back up. In our system, we try to build a file system that incrementally builds on top of each other. So every time you save and bring the machine back up, you're only doing work that is proportional to effectively the diff in the file system. And so this, shaves off a lot of time in the boot-up process of Devin. I think we This is actually now outdated. We have a newer system inside of Devin. But yeah, there's a lot of tiny details you have to get right here to actually get the day-to-day experience of Devin to be good.Swyx [00:49:39]: It's, not technically agents, but it is agent infra, and when you sell an agent as a company, you sell agent plus agent infra.Walden [00:49:46]: At least the way we do it be And the other The nice thing about having the agent infra being done together is, you We get to deploy Devin in whatever environment we want now. We don't need to wait for some underlying infra provider to also go and support VPC or on-prem or FedGovCloud, for instance. So we can actually go and figure out, okay, since we own the infrastructure, how can we get that set up for you?Cloud Providers: Modal, Daytona, and Enterprise SandboxesSwyx [00:50:12]: Whereas you're Cloudflare dependent.Cole [00:50:15]: so Cloudflare runs the control plane. The sandboxes, Modal is supported. A contributor just added Daytona. E2B is on the roadmap, and I think there's an abstraction in place that if any contributor wants to add a new provider, they can add that in.Walden [00:50:32]: Well, what are, How are the customers you work with Do they generally try to then go set up a contract with another one of these third-party providers? Do they try to do the VMs in-house?Cole [00:50:44]: most of them I see using Modal. I think Modal has a greatWalden [00:50:48]: Shout out Modal.Swyx [00:50:48]: Shout out Modal.Cole [00:50:50]: I think Modal has a great offering. It captures all of the sandbox pieces you need, snapshots being a pretty big piece of that, and given that they also offer GPUs, I think it's a pretty nice offering as a whole.Swyx [00:51:04]: no debate there.Walden [00:51:07]: Modal is great, especially, I think their container offering is, the most natural, and so especially if you are willing to, forego, the full VM requirements Modal is, a really vast place you can spin something up on.Swyx [00:51:20]: Is there a point So Modal's very Python, and I feel like most workload, has really shifted to JavaScript. I don't know if you guys Get the same feeling. So, okay, when I started Landspace and IE and all these things, I was like 50/50 Python and JS, right? That's roughly. I think that's wrong now. I think JS has won. I don't know if you guys Like, I Maybe I'm overstating it, and maybe for cognition, there's, C# and Java and what have you. But for, new greenfield apps, do you feel that Do you get that sense? Does it matter?Cole [00:51:52]: I think that most of the libraries that I see in this space are Python native first, especially in theCole [00:51:58]: Observability space. That said, I think that there is a pretty big appeal of having your entire system in one language. Especially when you have both your frontend and backend communicating, you can have one central type Which is very nice.Swyx [00:52:11]: That's my case against Modal, which is Then you have to run JS. You can run JS inside Modal. It's just, one extra step That, isn't native to the runtime. I don't know ifWalden [00:52:22]: I don't knowSwyx [00:52:23]: Reviews. Do you have numbers? I don't know.Walden [00:52:25]: the one thing I don't like about Python is whenever AI, whenever it writes Python, it always does, the weirdest patterns, andSwyx [00:52:32]: Oh, because it's, mixing two and three or what?Walden [00:52:34]: I think it's something mixing two and three, yeah. The I don't know if you see this. It always tries to do, has attribute on objects as likeCole [00:52:41]: Oh, my God.Walden [00:52:41]: But it's like But that you shouldn't be doing that. It should error if there wasSwyx [00:52:45]: Because it's training on library code?Cole [00:52:47]: I think it's more of, likeCole [00:52:48]: From what I've seen, it's more of, a reward hacking mechanism where it doesn't want to basicallyWalden [00:52:54]: It'll never error.Cole [00:52:54]: It doesn't want the code to fail. And so it Even when it knows it has the attribute, it'll call getattr on a, and for a lot of my clients who have moved towards more autonomous coding, we've put that in as a lint rule That if you do getattr, your pull request is going to fail.Slop Signatures: Comments, Backwards Compatibility, and TypesSwyx [00:53:12]: Ooh, this is a fun topic. Can you tell me more about this? What else is a sign of AI coding that you have to put guards in?Walden [00:53:21]: So we were talking just before this about Opus 4.7. One of the things this new model likes to do is it writes lots of comments. Not like, it'll, comment every line, but it'll write, paragraph, PRDs, on top of every function. But I will say, to its credit, these aren't slop, descriptions like they were before. “Oh, here's what this function does.” It's like, “Oh, here's actually the r

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

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If AI agents are the new digital knowledge workers, where exactly do they do their work? In this episode of the MAD Podcast, Ivan Burazin joins us to unpack the emerging infrastructure stack for AI agents and explain why every agent needs its own secure, stateful "computer." We explore the technical realities of sandboxes, dive into why legacy, stateless hyperscalers weren't built for these new workloads, and break down the mechanics of microVMs and custom schedulers alongside a contrarian prediction on an impending CPU shortage. Finally, Ivan delivers an absolute masterclass on product-led growth, community building, and go-to-market strategy for technical founders.(00:40) Intro(02:13) What is an AI agent sandbox?(03:17) Security risks of running agents locally(05:17) Stateful vs. stateless hyperscalers(07:04) The history of cloud IDEs and the end of localhost(09:45) Do all AI agents need a sandbox?(12:26) Sandbox use cases: RL evals & background agents(14:10) Unpacking the emerging AI Agent Stack(16:20) The unsolved problem of agent memory and learning(19:37) Where sandboxes fit in the agent harness(21:35) OpenAI, Anthropic, and agent SDKs(23:06) Ivan's founder journey: From CodeAnywhere to Daytona(26:59) GTM strategies and building developer communities(33:48) Why customer support is your best GTM strategy(35:34) Leveraging Twitter during the AI super cycle(40:50) The technical anatomy of a sandbox(41:53) Why fast spin-up speeds maximize GPU efficiency(46:09) Firecracker, QEMU, and isolation primitives(49:58) Why sandbox snapshots and state forking matter(51:40) Why Daytona built a custom scheduler from scratch(55:24) The challenge of long-running stateful sandboxes(58:10) The build your own sandbox trap(1:01:03) Why AI agents might trigger a global CPU shortage(1:02:46) The future of the AI Agent Stack

Today we learn that the U.S. Clarity Act, a crucial legislation governing stablecoins, is about to reach its decisive moment. They desperately want the Clarity Act to pass, providing the industry with clear rules, so that USDC can reach $200 billion. The real, fierce opposition comes from retail and community banks that heavily rely on deposits for lending. 00:00 Intro 03:11 Gold Backed Treasury 04:48 Coins / Paper to Digital 08:02 Clarity Act 17:45 Bankers 20:46 Firecrackers

Today we learn that the U.S. Clarity Act, a crucial legislation governing stablecoins, is about to reach its decisive moment. They desperately want the Clarity Act to pass, providing the industry with clear rules, so that USDC can reach $200 billion. The real, fierce opposition comes from retail and community banks that heavily rely on deposits for lending. 00:00 Intro 03:11 Gold Backed Treasury 04:48 Coins / Paper to Digital 08:02 Clarity Act 17:45 Bankers 20:46 Firecrackers

Today we learn that the U.S. Clarity Act, a crucial legislation governing stablecoins, is about to reach its decisive moment. They desperately want the Clarity Act to pass, providing the industry with clear rules, so that USDC can reach $200 billion. The real, fierce opposition comes from retail and community banks that heavily rely on deposits for lending. 00:00 Intro 03:11 Gold Backed Treasury 04:48 Coins / Paper to Digital 08:02 Clarity Act 17:45 Bankers 20:46 Firecrackers

The host explains why the general public is easily manipulated, citing the "Truth Default Theory" where individuals automatically assume honesty from trusted sources. He proposes a "Lie Default" operating system for processing information.Auto-Believers: Most people are "auto-believers" who lack the situational awareness to recognize systemic, collusive media fakery.The Veracity Effect: Humans are generally better at judging truth than detecting lies, which the media exploits.Situational Awareness: Once a consumer is informed about "news bending," their frame of reference updates to treat the source as a "pathological liar".Cognitive Inoculation: Sitting and listening to these deconstructions allows for a form of "osmosis" that inoculates the mind against future psyops.The "Non" Position: Instead of being "pro" or "anti" (both of which are reactive), the host suggests being "non"—a conscientious objector to the mind war.Quote: "You should be lie default they're lying unless the evidence supports otherwise you could say fake until proven real... so you should be suspending your judgment until you get more facts."The host analyzes the eerie synchronization between the TV show The Boys and real-world political events, arguing that this "Concurrent Programming" proves collusion between the government and mass entertainment.Homelander/Trump Parallels: Recent scenes in The Boys involving golden statues, Bibles, and fist-raising mirror Donald Trump's real-world activities.Assassination Narratives: The host notes that the show's assassination subplots tracked with real events, leading to emergency title changes for episodes.Entrainment: This phenomenon is defined as "entrainment between entertainment and psyops," where scripts written years ago perfectly coordinate with current news.The Simulation "Stop-Gap": People use the "simulation" theory to explain these coincidences because they cannot process the idea of a pre-scripted, intelligently planned reality.Propaganda Conduit: The host views popular media like The Boys as a "propaganda conduit for PSYOP reinforcement".Quote: "The Homelander is Trump... Firecracker is MTG... My point is... the show was recorded years ago So how did a show recorded years ago perfectly coordinate with what's happening right now? It's because there's entrainment between entertainment and psyops."This topic dives into the idea that history is not just edited or censored, but "fabricated entirely" and "pre-written" into the future.Systemic Fakery: Major events like the moon landing, 9/11, and COVID-19 are described as chapters in the same "script" that shares a singular backstory.History as Prefabrication: The host argues that history for the last 60+ years has been a "prefabricated historical timeline" rather than a record of organic events.Worldview Warfare: Media has replaced the "holy book" with a "closed system of ideas" that tells the public about their past, present, and future.Subplots in Alt-Media: Conspiracy theories within alternative media (like the "J-pill" or "Mud Flood") are dismissed as "subplots" that keep truthers tethered to the fake timeline. Closed Systems: Using a cruise ship as "Ground Zero" creates a controlled environment for media narratives to flourish, similar to the Diamond Princess in 2020.Crisis Actors: The host points to individuals in the news cycles as "crisis thespians" who reappear across different staged events.Symbolism on Currency: He references the appearance of "bats" and "Mayflower" imagery on quarters as evidence of long-term symbolic planning for these events.The "Odyssey" Reference: Headlines describing a "33-day Atlantic Odyssey" are cited as proof of the "Meta Script" using coded language.Fear as a Mind Virus: The host emphasizes that the real threat is the "infectious mind virus" of fear, which causes psychosomatic reactions like "mind AIDS".

How much does Firecracker believe in the Democratic Church of America and can Bombsight be found? Who is on who'e side? Izzi joins Adam and Neil to share thoughts, theories and talking points from The Boys season 5 episode 5, One Shots and episode 6, Though the Heavens Fall.You can subscribe to the Exclusive Strand of TV DNA to get bonus content here - https://creators.spotify.com/pod/profile/tv-dna-podcast/subscribe We can't wait for you to hear our thoughts on the latest episodes and for you to give us yours too. You can find and follow us on all the socials @tvdnapodYou can also email us on tvdnapod@gmail.com  We have recent specials on Heated Rivalry, The Traitors and A Knight of the Seven Kingdoms, weekly, spoiler-free watchlist episodes and our back catalogue includes Severance, MAFS UK and Blue Lights. Listen here https://open.spotify.com/show/7eh93AAcO5y1m5jdEcTqAk?si=7l1do-YcQNS-eQ1YMIdCHAWe're on Apple Podcasts, Spotify, Google Podcasts, Pocket Casts, Podcast Addict, Breaker and Radio Public so be sure to subscribe to the pod and please leave us a review. Thanks as always to JComp for our logo and Roman Senyk Music for our theme. Adam, Grace, Neil, Damian and Isabel

The Boys Season 5 Episode 5 “One-Shots” finally delivers the long-awaited Supernatural reunion with Jensen Ackles and Jared Padalecki, but does the episode actually move the story forward? We break down Black Noir's bizarre theater storyline, what's going on with Firecracker, and why The Boys are doing nothing. Full recap, review, spoilers, easter eggs, and ending explained for The Boys Season 5 Episode 5.#TheBoys #TheBoysSeason5 #Supernatural #JensenAckles #JaredPadalecki #SoldierBoy-------------------Support Us:https://www.patreon.com/c/sceneitebeforecast/membershipFollow Us:Instagram - https://www.instagram.com/sceneitbeforecast/TikTok - https://www.tiktok.com/@sceneitbeforecast/Follow Danny:Instagram - https://www.instagram.com/danny_wosLetterboxd - https://letterboxd.com/DJWosYouTube - https://www.youtube.com/channel/UCbXsBr-nJUqhcnC5YzCa3VQFollow Dan:Instagram - https://www.instagram.com/danthedonutman_1Letterboxd - https://letterboxd.com/donutman96/Listen to the Podcast:https://linktr.ee/sceneitbeforeSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

It's a Nintendo-heavy installment of Hardly Focused! In one corner, Becky is deep into collecting Pokémon cards, while learning from Jack the ins and outs of the franchise. In the other corner, Nate and Jack are cautiously optimistic about the newly-announced Star Fox game on Switch 2. How many times can a single game be reimagined? Also discussed in this episode of Hardly Focused: Nate is indulging in Firecracker Pop Oreos, the filling of which resembles toothpaste. Where can one find better peanuts - Fenway Park, or Texas Roadhouse? (Dead) Dad Jokes, a free show happening at the Hotel Vernon in Worcester, MA on Sunday, May 17. Nate is opening! Strike Force Five will reunite on The Late Show with Stephen Colbert. FOLLOW and SUBSCRIBE! https://hardlyfocused.com/subscribe Learn more about your ad choices. Visit megaphone.fm/adchoices

Star Jam Ft. Savin SA | RJ RafiIn this candid Star Jam conversation, director Savin SA opens up about his journey from a small-town movie lover and assistant director to becoming the blockbuster filmmaker behind Vaazha 2. He talks about the pressure of being trusted with a huge project by Vipin Das, building an energetic young team, and how their freedom and friendship shaped the film on and off setSavin breaks down the now-iconic theatre fight sequence, why he was scared it might not work, and how it became crucial for the bonding between the four leads and the audience. He reveals how Biju Kuttan's Vishu firecracker scene was originally planned as pure comedy but unexpectedly turned into one of the most emotional moments in the film, deeply connected to a painful chapter in the actor's real life

Naughtsie and Cam run through Casey's loss to Sydney, with Tommy Matthews starring again and pushing his case for senior selection. Hosted on Acast. See acast.com/privacy for more information.

The Boys Season 5 Episode 5 - INSTANT REACTION - One-Shots In this episode of The Prestige-ish Media Podcast - Craig Lake and Dan McNair give their INSTANT REACTION to the Amazon Prime show The Boys Season Five Episode Five - One-ShotsIn this episode we discuss Firecracker, Black Noir 2, Terror, Seth Rogan, McLovin and more. SPOILER WARNING: The Boys Seasons 1-4 and Season 5 episodes 1-5. Also potential Gen V Season 1-2 spoilers. Please continue to join us for our coverage of The Boys Season 5 on Amazon Prime Video. Also please join us for our continuing coverage of the HBO Max show Euphoria Season 3.Please check out our website at http://prestigeish.com, follow our podcasts on all your favorite podcast platforms, and leave us positive reviews if you enjoy our show. X @prestige_ish Instagram @prestigeishmedia TikTok @prestigeish YouTube @prestigeishmedia X/Instagram @realrealbatman @danmcnair1017  http://prestigeish.com

We're back with Episode 5 of The Boys for our Side quest Reviews. This episode brings a noticeably different tone compared to the rest of the season. There's a strong focus on character development and we might've even found ourselves feeling a little sympathy for a certain Firecracker. We get into which character needs to take The Deep out for good, who we think will actually make it out alive, and we also share our thoughts on the cancellation of Gen V. Be sure to follow, subscribe, and drop your thoughts in the comments.

In this thought-provoking episode of Scene N Nerd, Sarah and Will tackle the latest developments in the world of superhero television, starting with the bittersweet news of the cancellation of Gen V. They discuss the implications of this decision for the future of The Boys universe and reflect on how it affects the characters' trajectories. As they dive into the viewership drop for Daredevil: Born Again, they analyze the factors contributing to the decline and share their thoughts on the show's evolving narrative and character dynamics. The dynamic duo then shifts gears to review The Boys Season 5, Episode 5, "One Shots." They break down the episode's unique storytelling format, exploring the one-shots of various characters, including Firecracker, Black Noir, and Sister Sage. With a mix of humor and insightful commentary, they discuss the moral complexities faced by these characters and how their relationships with power and loyalty are portrayed. The episode culminates in a deeper understanding of the characters' motivations and the consequences of their choices, all while maintaining the show's signature style. Wrapping up, Sarah and Will transition to Daredevil: Born Again, discussing Episodes 3 and 4. They reflect on the series' pacing, the courtroom drama, and the impact of Vanessa's fate on Fisk's character. As they analyze the juxtaposition of power dynamics and personal relationships, they ponder the show's direction and what lies ahead for the characters. With a blend of humor and critical analysis, this episode is a must-listen for fans of both series. 0:00 - Welcome & News Roundup: Gen V Cancellation & Daredevil Viewership Drop 12:55 - The Boys Season 5, Episode 5 "One Shots" Review 54:00 - Daredevil: Born Again Season 2, Episodes 3-4 Discussion 1:10:00 - Outro Want to keep the conversation going? Hit us up on X (formerly Twitter) @SceneNNerd, Bluesky @SceneNNerd.bsky.social, Facebook, Instagram @scene_n_nerd, and Threads @scene_n_nerd. Don't forget to check out our website at www.scenennerdpodcast.com. If you enjoyed this episode, drop us a rating and a shout-out on Apple Podcasts, Spotify, or wherever you get your podcast fix!

This episode has five parts therefore we're allowed to do at least two. So for part one we're ranting about Firecracker's faltering faith, Noir takong to the stage, Terror's incredible dreams, saying bye bye to Bourke and passionately kissing Jesus figurines. #TheBoys #Season5 #Vought #V1 #Homelander #SoldierBoy #TheBoysS5 #VoughtRising #GenV Follow us on our YouTube channel:https://youtube.com/@monorants?si=b7zLmCZWSxbW-FsXAnd also BlueSky @monorants, Twitter @rantsmono, Instagram: MonoRants_The_Boys or send your own rants to monorantspodcast@gmail.com

Monarch’s Tim is LARPing as the MAN This week on the podcast, Brian and Darryl dive into another packed week of prestige chaos, Sith trauma, kaiju family therapy, Hell's Kitchen courtroom warfare, and The Boys reminding everyone that celebrity cameos are just meat with better agents. Episode Index Intro: 0:07 Maul: 8:27 Monarch: 15:51 Daredevil: 29:40 The Boys: 44:14 Star Wars: Maul – Shadow Lord, Episode 7 Title: Chapter 7: Call to Oblivion Air date: April 27, 2026 Director: Nathaniel Villanueva Writer: Julia Cooperman Summary: Maul brings Devon and Rylee to his hideout as the Empire closes in, but Devon refuses to follow him and tries to get Rylee away. Things go sideways fast when Imperial forces capture Rylee, forcing Devon back toward Lawson and Daki. Meanwhile, Maul's attempt to escape Janix collapses into a brutal fight with Marrok and the Eleventh Brother, leaving his followers scattered, his ship destroyed, and his already damaged leg becoming a very real problem. Maul survives because of course he does, but this is the Empire turning the screws hard. Star Wars: Maul – Shadow Lord, Episode 8 Title: Chapter 8: The Creeping Fear Air date: April 27, 2026 Director: Saul Ruiz Writer: Jennifer Corbett Summary: With Maul separated from his crew and physically breaking down, the episode digs into his past through hallucinations of Sidious, Savage Opress, and the trauma that shaped him into the walking red flag he is today. Two-Boots finally gets his moral compass rebooted after learning what the Empire really did to Klyce, helping Rylee escape before the group walks into yet another trap. Sul sacrifices herself to stop Blake, and Maul's surviving crew regroups just in time for a message from Dryden Vos, because apparently the galaxy's criminal LinkedIn is still very active. Rating Out of 10 Help Me Darryl-Wan Kneobi, Brian Stopped Watching Darryl: 6.8/10 Brian: DNW Monarch: Legacy of Monsters, Season 2, Episode 9 Title: Ends of the Earth Air date: April 24, 2026 Director: Lawrence Trilling Writer: Tanner Hansinger Summary: Outpost 18 tracks Godzilla and Titan X toward Skull Island, where Godzilla backs off and Isabel reveals the full flavor of her Apex-branded madness. Her plan is not just about Axis Mundi. It is about using Titan X, its egg, and Skull Island itself as pieces on a very expensive monster chessboard. Meanwhile, Tim, Shaw, Keiko, May, and Monarch forces follow Titan X onto the island, Shaw and Keiko get separated, Cate escapes, and Kentaro drops the emotional trap card by claiming they can save Hiroshi. In the 1958 storyline, Keiko and Bill marry, while Bill's later obsession with rifts shows how this family has been getting emotionally nuked by monster science for decades. Rating Out of 5 When Godzilla and Titan X Stop to Have a Chat Brian: 4.01/5 Darryl: 3/5 Daredevil: Born Again, Season 2, Episode 7 Title: The Hateful Darkness Air date: April 28, 2026 Director: Iain B. MacDonald Writer: Heather Bellson Summary: Karen Page finally gets her day in court, and Matt comes out of hiding to help defend her alongside Kirsten McDuffie. The trial puts the AVTF under pressure, but Fisk's machine responds the only way it knows how: violence, intimidation, and ugly backroom damage control. Jessica Jones confronts Mr. Charles and learns Luke Cage is working overseas with the CIA, while Dex interrupts an assassination attempt on Governor McCaffrey. The emotional gut punch lands with Daniel Blake, who nearly gives BB Urich up to Cashman before finding his spine at the worst possible time. He lets her escape, refuses to reveal her location, and pays for it with his life. Rating Out of 5, Matthew Murdock for the Defense is Straight Fire Brian: 4.22/5 Darryl: 3.5/5 The Boys, Season 5, Episode 5 Title: One-Shots Air date: April 29, 2026 Director: Phil Sgriccia Writer: Judalina Neira Summary: The Boys keeps pushing the virus and chasing V1 while Homelander and Soldier Boy go hunting for answers through Stan Edgar and Mister Marathon. In Los Angeles, Mister Marathon and Malchemical try to pull Soldier Boy away from Homelander, but Soldier Boy chooses Team Daddy Issues and kills Malchemical instead. Marathon's escape turns into a blood-soaked celebrity disaster before Homelander finishes him off. Back at Vought, Sage warns Ashley that Homelander can't get V1, Noir spirals through theater-kid identity crisis hell, The Deep does Deep things, and Firecracker finally starts doubting Homelander, which goes about as well as expected. He kills her. Because apparently loyalty programs at Vought end with murder. Rating Out of 5 If Only Moose Could Do Such a Thing Brian: 1/5 Darryl: 1/5 Contact Us The Infamous Podcast can be found wherever podcasts are found on the Interwebs, feel free to subscribe and follow along on social media. And don't be shy about helping out the show with a 5-star review on Apple Podcasts to help us move up in the ratings. @infamouspodcast facebook/infamouspodcast instagram/infamouspodcast stitcher Apple Podcasts Spotify Google Play iHeart Radio contact@infamouspodcast.com Our theme music is ‘Skate Beat’ provided by Michael Henry, with additional music provided by Michael Henry. Find more at MeetMichaelHenry.com. The Infamous Podcast is hosted by Brian Tudor and Darryl Jasper, is recorded in Cincinnati, Ohio. The show is produced and edited by Brian Tudor. Subscribe today!

Jenna is joined by Stanford sophomore pitcher, National Pitcher of the Week honoree, and ACC strikeout leader, Zoe Prystajko! They talk about why Jenna nicknamed her ‘Zoe Prystrikeout', how leaning on her teammates helped build confidence in year two, Cardinal bullpens, developing a drop ball in the offseason, why she pitches lefty and throws righty, the brand new Stanford Softball Stadium, Head Coach Jessica Allister's leadership, Stanford Athletics' 50 year streak of NCAA championships, the postseason mindset, majoring in bioengineering, her recruiting process, playing travel ball for Tony Rico's Firecrackers, and more. 00:00:00-00:07:19 Intro/Covering Our Bases 00:07:19-00:45:48 Interview 00:45:48-00:46:58 Bring It Home/Outro IG: @bleavinsoftball X: @BleavInSoftball Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

It's Hollywood bloodbaths, dog dreams and fighting with your faith on another wholesome episode of 'The Boys'. Bankole, Chiagoziem and Oseghale return to get into it all, investigate just what makes our favourite superheroes tick and ponder the cost of a soul.(8:30) - Firecracker's Faustian Bargain(25:10) - The Boys' Humanity(34:35) - LA Field TripYou can support us here.Also available on YouTube.Host: Bankole ImoukhuedeGuests: Chiagoziem & OseghaleProduction by: Bankole Imoukhuede

It's time for a road trip to the ironically named Fort Harmony where no one has any. The Boys hunt for V1 nearly tears them apart, Annie gets some answers from her past, Homelander wants Firecracker to sell him as God and we question Frenchies continued survival #TheBoys #Season5 #Vought #V1 #Homelander #SoldierBoy #TheBoysS5 #VoughtRising #GenV Follow us on our YouTube channel:https://youtube.com/@monorants?si=b7zLmCZWSxbW-FsXAnd also BlueSky @monorants, Twitter @rantsmono, Instagram: MonoRants_The_Boys or send your own rants to monorantspodcast@gmail.com

It is a full plate of body slams, Sith drama, Titan trouble, Hell's Kitchen violence, Vought insanity, and superhero trauma. This week on the podcast, Brian and Darryl recover from the two-night chaos of WrestleMania 42, then dive into a stacked TV lineup with Maul: Shadow Lord Episodes 5 and 6, the Invincible Season 4 finale, Monarch: Legacy of Monsters Season 2 Episode 8, Daredevil: Born Again Season 2 Episode 6, and The Boys Season 5 Episode 4. Episode Index Intro: 0:07 WrestleMania: 7:17 Maul Shadow Lord: 35:48 Monarch: 39:20 Daredevil: 45:35 The Boys: 52:23 Invincible: 01:02:15 WrestleMania 42 WrestleMania 42 took place across two nights on Saturday, April 18 and Sunday, April 19, 2026, at Allegiant Stadium in Las Vegas. The weekend featured major title matches, big returns, title changes, and a few “is this a retirement tease?” moments. Night 1 was built around Cody Rhodes defending the Undisputed WWE Championship against Randy Orton, with Cody retaining in the main event before Orton attacked him after the match. The night also featured Paige returning to team with Brie Bella, Gunther defeating Seth Rollins after Bron Breakker got involved, and Liv Morgan retaining the Women's World Championship. Night 2 leaned even harder into big WrestleMania moments, with Oba Femi defeating Brock Lesnar, Penta surviving a chaotic ladder match to retain the Intercontinental Championship, Trick Williams winning the United States Championship, Rhea Ripley defeating Jade Cargill, and Roman Reigns closing the weekend by beating CM Punk for the World Heavyweight Championship. WrestleMania 42: Night 1 Date: Saturday, April 18, 2026 Location: Allegiant Stadium, Las Vegas, Nevada Match 1: LA Knight, Jey Uso, and Jimmy Uso vs. Logan Paul, Austin Theory, and IShowSpeed Winner: LA Knight, Jey Uso, and Jimmy Uso Match 2: Jacob Fatu vs. Drew McIntyre Winner: Jacob Fatu Match 3: Brie Bella and Paige vs. Alexa Bliss and Charlotte Flair vs. Bayley and Lyra Valkyria vs. Nia Jax and Lash Legend Stipulation: Fatal 4-Way Match for the WWE Women's Tag Team Championship Winner: Brie Bella and Paige Match 4: Becky Lynch vs. AJ Lee Stipulation: Women's Intercontinental Championship Match Winner: Becky Lynch Match 5: Gunther vs. Seth Rollins Winner: Gunther Match 6: Liv Morgan vs. Stephanie Vaquer Stipulation: Women's World Championship Match Winner: Liv Morgan Match 7: Cody Rhodes vs. Randy Orton Stipulation: Undisputed WWE Championship Match Winner: Cody Rhodes WrestleMania 42: Night 2 Date: Sunday, April 19, 2026 Location: Allegiant Stadium, Las Vegas, Nevada Match 1: Oba Femi vs. Brock Lesnar Winner: Oba Femi Match 2: Penta vs. Je'Von Evans vs. Dragon Lee vs. Rusev vs. JD McDonagh vs. Rey Mysterio Stipulation: Ladder Match for the Intercontinental Championship Winner: Penta Match 3: Trick Williams vs. Sami Zayn Stipulation: United States Championship Match Winner: Trick Williams Match 4: Finn Bálor vs. Dominik Mysterio Winner: Finn Bálor Match 5: Rhea Ripley vs. Jade Cargill Stipulation: WWE Women's Championship Match Winner: Rhea Ripley Match 6: Roman Reigns vs. CM Punk Stipulation: World Heavyweight Championship Match Winner: Roman Reigns Night 1 Rating Out of 10 Oh What The Hell Was That Brian: 3/10 Darryl: 2.5/10 Night 2 Rating Out of 10 Brian: 7/10 Darryl: 7.35/10 Maul: Shadow Lord (Disney+) Maul: Shadow Lord, Episode 5 Title: Chapter 5: Inquisition Air date: April 20, 2026 Director: Saul Ruiz and Tatyana Drewry Carvin Writer: Jennifer Corbett Summary: The Empire tightens its grip on Janix as Maul's operation starts drawing the kind of attention even he cannot simply murder his way out of. With the Imperial occupation escalating, Rook Kast warns Maul that the situation is getting worse, while Looti Vario begins questioning whether staying with the Shadow Collective is safer than running. Meanwhile, Brander Lawson finds himself caught between Imperial pressure, local chaos, and Maul's growing influence, as the arrival of the Inquisitors turns Janix into a hunting ground. Maul: Shadow Lord, Episode 6 Title: Chapter 6: Night of the Hunted Air date: April 20, 2026 Director: Steward Lee Writer: Nicolas Anastassiou Summary: Maul, Devon Izara, Brander Lawson, and the others are forced into survival mode as Marrok and the Inquisitors close in. What started as Maul rebuilding his criminal empire becomes something much more dangerous as the Empire realizes there are Force users hiding on Janix. Marrok's pursuit pushes the group into desperate choices, and when he fails to bring Maul down, he makes a mysterious call to an unseen figure he addresses as “my lord,” setting up a much larger threat for Maul, Devon, and anyone standing between them and the Empire. Rating Out of 10 Whatever Darryl Thinks Darryl: 7.9/10 Brian: DNW Monarch: Legacy of Monsters (Apple TV) Monarch: Legacy of Monsters, Season 2, Episode 8 Title: Separate Ways Air date: April 17, 2026 Director: Gandja Monteiro Writer: Mariko Tamaki Summary: Titan X makes landfall in Australia, forcing Monarch into another high-stakes monster crisis as Shaw attempts to lure Godzilla into a direct showdown. While the Titans dominate the battlefield, Isabel uses the chaos as cover for a secret operation, because apparently one giant monster fight was not enough drama for the week. The episode also pushes Cate closer to the truth about Titan X, including the discovery that the creature may not be the threat everyone assumed. Out of 5 Finally Godzilla! Brian: 3.8/5 Darry: 3.2/5 Daredevil: Born Again (Disney Plus) Daredevil: Born Again, Season 2, Episode 6 Title: Requiem Air date: April 21, 2026 Director: Angela Barnes Writers: Devon Kliger and Jesse Wigutow Summary: “Requiem” keeps the pressure on Hell's Kitchen as Fisk's grip starts to show cracks and Matt tries to make an impossible move by seeking a truce with Wilson Fisk. Around them, everyone seems to be making destructive choices: Mr. Charles makes his move, Daniel confronts BB, Powell's violence escalates, Heather snaps, and Karen nearly makes a devastating decision. The episode also brings Jessica Jones back into the mix, raising the stakes for Matt's growing resistance against Fisk and the AVTF. Out of 5 How Was Matt’s Back Not Destroyed When He Went Through the Wall Painting Brian: 3.4/5 Darryl: 3/5 The Boys (Amazon Prime) The Boys, Season 5, Episode 4 Title: King of Hell Air date: April 22, 2026 Director: Karen Gaviola Writer: Geoff Aull Summary: Homelander takes another step toward declaring himself America's new god, with Firecracker and the Vought propaganda machine helping turn his messianic delusions into a full-blown movement. Meanwhile, The Boys investigate Fort Harmony in search of V1, an early and extremely dangerous version of Compound V. The mission gets weird fast when they encounter Quinn, a scientist fused into the base itself, whose powers trigger violent aggression and infighting. Soldier Boy and Homelander clash again, Annie searches for answers about her father, Ryan walks away from Butcher, and the episode ends with Vought pushing Homelander further into cult-leader territory. Rating Out of 5 Stuck in a Uranium Filled Room Bleeding Out Your **** Brian: 4.1/5 Darryl: 3.43/5 Invincible (Amazon Prime) Invincible, Season 4, Episode 8 Title: Don't Leave Me Hanging Here Air date: April 22, 2026 Director: Ian Abando Writer: Simon Racioppa Summary: The Season 4 finale shifts away from one last giant battle and instead deals with the emotional fallout of the Viltrumite War. Mark returns to Earth shaken, haunted by visions of the people he loves being slaughtered, while Thragg reveals that the surviving Viltrumites are now hiding on Earth and gives Mark a brutal ultimatum: let them live among humans or risk Earth being destroyed. Mark reluctantly agrees, hoping to buy time. Meanwhile, Eve reveals she had an abortion while Mark was gone, Nolan and Debbie leave for Telescria to care for Oliver, and Allen is left with a terrifying choice after learning about a perfected Scourge Virus that could wipe out Viltrumites, and possibly humanity too. Rating out of 5 Mark See Thragg Everywehre Brian: 4.25/5 Darryl: 3.77/ 5 Rating out of 10 Season 5 Was So Close to Being Perfect Brian: 8.3/10 Darryl: 7.4/10 Contact Us The Infamous Podcast can be found wherever podcasts are found on the Interwebs, feel free to subscribe and follow along on social media. And don't be shy about helping out the show with a 5-star review on Apple Podcasts to help us move up in the ratings. @infamouspodcast facebook/infamouspodcast instagram/infamouspodcast stitcher Apple Podcasts Spotify Google Play iHeart Radio contact@infamouspodcast.com Our theme music is ‘Skate Beat’ provided by Michael Henry, with additional music provided by Michael Henry. Find more at MeetMichaelHenry.com. The Infamous Podcast is hosted by Brian Tudor and Darryl Jasper, is recorded in Cincinnati, Ohio. The show is produced and edited by Brian Tudor. Subscribe today!

Homelander has officially lost it… and it might be too late to stop him.The Boys Season 5 Episode 3 delivers one of the most disturbing moments of the entire series — as Homelander has a full mental breakdown, embraces his god complex, and brutally attacks his own son.Yeah… it's THAT episode.Brandon & Chanel break down everything from Homelander's terrifying transformation to the chaos with The Boys and the confusing twists around the supe virus.

AWS Morning Brief for the week of April 20th, with Corey Quinn. Links:Amazon CloudWatch now supports cross-region telemetry auditing and enablement rulesIntroducing Amazon EC2 C8in and C8ib instancesAmazon Quick now supports multi-account sign-in within the same browserAmazon WorkSpaces Personal and Amazon WorkSpaces Core are now available in two additional AWS RegionsAWS announces general availability of AWS Interconnect - multicloudAutomate AWS Cost Reporting with Scheduled Dashboard Email DeliveryIntroducing Anthropic's Claude Opus 4.7 model in Amazon BedrockIntroducing Amazon Bio DiscoveryCVE-2026-5429 - Kiro IDE Webview Cross-Site Scripting via Workspace Color ThemeIssues with Amazon Athena ODBC DriverIssues with AWS Research and Engineering Studio (RES)CVE-2026-5747 - Out-of-bounds Write in Firecracker virtio-pci Transport

Peter watches Mad Max: Fury Road for the first time in decades, and Eden — who has seen it at least a dozen times — watches the black-and-chrome edition alongside him. Peter finds the opening act almost too uncomfortable to watch, given its uncomfortable parallels to the current political moment, but gets fully on board the moment the sandstorm hits. They dig into what makes the film a masterpiece of practical filmmaking, why Furiosa holds up better than the prequel, and what it means that George Miller also made Babe: Pig in the City and Happy Feet.SHOW NOTESCheck-in / What we've been up to — Eden is riding their cargo bike in 35mph Iowa wind gusts; Peter is heading to Austin for an Intuitive Surgical robotics event. Eden vents about 18 months of accessibility compliance work being ignored by faculty who don't read their emails.Peter's picks — Finishing Dungeon Crawler Carl Book 6 (fun but disposable, and the online fandom's intensity baffles him); finished Season 2 of A Man on the Inside (Ted Danson and his real-life wife Mary Steenburgen falling for each other on screen — highly recommended); Taskmaster Series 21 has started, featuring Kumail Nanjiani. Big metal week — Peter covers a stack of new releases: Slave Machine by Nervosa (vicious all-female death-thrash from Brazil); Too Fast to Die by ArchSpire (potential album of the year if not for Neurosis); new Inferi album featuring departing drummer Spencer Moore; Descent by Immolation; and Master Boot Record's first live album Realtime Execution. Eden's picks — Eden is scrobbling again on Last.fm and shares a chaotic top-four week: Portishead, Rebecca Black (Salvation EP praised as a stone-cold classic), Neurosis, and new discovery Javiera Mena, a Chilean electro-pop artist. Also watched two bad movies with the bad movie crew: Firecracker (notable for a truly unhinged sex scene) and American Cyborg: Steel Warrior ("Children of Men with a $13 budget"). Currently reading a 3,500-page Chinese web novel called Long Awaited Feelings / My Feelings Can Wait.Why Peter struggled with the opening act — Peter found Immortan Joe's cult of worship uncomfortably familiar, given current events, describing it as George Miller predicting how "stupid and gullible people can be." He warmed to the film as it progressed, with the sandstorm sequence being the turning point."A perfect action film" — Eden's framing: not their favorite action film, but possibly a perfect one — no wasted frame, no wasted scene. They've seen it at least a dozen times, and this watch was the black-and-chrome edition, which Miller originally intended before the studio overruled him.Practical effects deep dive — 80–90% of the stunts were practical, shot on location in Namibia under miserable conditions. They highlight the pole-cat war boys actually swinging on moving vehicles, and the real flamethrower guitarist who was instructed not to hold the guitar too high.On the cast — Charlize Theron gets full credit for owning the film as Furiosa. Tom Hardy's near-silent, physically understated performance is praised. Nicholas Hoult's arc as Nux — going from zealot to sacrifice — is called out as the emotional hinge of the film.Frame rate trivia — Eden flags that 50–60% of the film was shot below 24fps, with Miller manipulating frame rates shot-by-shot to control tension and legibility.Furiosa comparison — Eden recommends the prequel but notes its heavy CGI and green screen make it feel cheaper and less embodied than Fury Road. Peter says he's now interested to watch it.The Babe 2 revelation — The episode ends on Eden's genuine disbelief that the director of Fury Road also made Babe: Pig in the City and Happy Feet, and a fun piece of trivia: Immortan Joe's actor, Hugh Keays-Byrne, also played Toecutter, the villain of the original Mad Max.

We all know the big names of prog rock -- they're mentioned numerous time in this episode -- and we all know the music of many other names from all over the world, especially the Italian and Scandinavian progressive gods. And Holland's Supersister! But do you know Babylon, Yezda Urfa or Ethos? Perhaps not. The US prog movement of the '70s happened mid-/late decade, well past the prime/peak of 1972 (ish)...but we haven't forgotten these excellent American contributors to our favorite subset of rock music. Dive in with us as we unearth five of our US prog favorites from that glorious decade... Note I: Wow, sorry about the quality of Jeff's transmission in the first three-quarters of the episode…we're back to the dark ages of early RR episodes there. Our apologies! Note II: Jeff's Voivod book, ‘Always Moving: The Strange Multiverse of Voivod,' is now available. You can purchase a copy of the 540-page, 3-pound behemoth HERE: radicalresearch.org/voivod Note III: The Radical Research Patreon page is now set up and ready for your patronage. We are offering tiered subscription levels for those who want a set-it-and-forget-it donation option. As ever, if you choose to support us, we are humbled and grateful! patreon.com/RadicalResearchPodcast Music cited in order of appearance: Babylon, “The Mote in God's Eye” (Babylon, 1978) Babylon, “Dreamfish” (Babylon, 1978) Cathedral, “Introspect” (Stained Glass Stories, 1978) Cathedral, “The Search” (Stained Glass Stories, 1978) Ethos, “Atlanteans” (Ardour, 1976) Ethos, “Long Dancer” (Ardour, 1976) Yezda Urfa, “Boris and His Three Verses (Including Flow Guides Aren't My Bag)” (Boris, 1975) Yezda Urfa, “The Basis of Dubenglazy (While Dirk Does the Dance)” (Boris, 1975) Starcastle, “Elliptical Seasons” (Starcastle, 1976) Happy the Man, “Stumpy Meets the Firecracker in Stencil Forest” (Happy the Man, 1977) Happy the Man, “Steaming Pipes” (Crafty Hands, 1978) Radical Research is a conversation about the inner- and outer-reaches of rock and metal music. This podcast is conceived and conducted by Jeff Wagner and Hunter Ginn. Though we consume music in a variety of ways, we give particular privilege to the immersive, full-album listening experience. Likewise, we believe that tangible music formats help provide the richest, most rewarding immersions and that music, artwork, and song titles cooperate to produce a singular effect on the listener. Great music is worth more than we ever pay for it.

-Brigitte Gabriel (ActForAmerica.org) joins and brings enough energy to power the studio while predicting the Iranian regime's collapse and urging Americans to stand behind the military. The pair discuss Iranian protests, regime instability, and why winning a war “is not a Starbucks drive-through” despite what impatient critics might think. Today's podcast is sponsored by : GHOSTBED : I used to think a mattress was just furniture, until I got my GhostBed! GhostBed is offering my audience their lowest prices of the season, plus an extra 10% off. Go to http://GhostBed.com/CARSON and use promo code CARSON SHOPIFY - Stop waiting and start selling! Sign up now for your $1/month trial at http://shopify.com/newsmax BIRCH GOLD - Protect and grow your retirement savings with gold. Text ROB to 98 98 98 for your FREE information kit! To call in and speak with Rob Carson live on the show, dial 1-800-922-6680 between the hours of 12 Noon and 3:00 pm Eastern Time Monday through Friday…E-mail Rob Carson at : RobCarsonShow@gmail.com Musical parodies provided by Jim Gossett (http://patreon.com/JimGossettComedy) Listen to Newsmax LIVE and see our entire podcast lineup at http://Newsmax.com/Listen Make the switch to NEWSMAX today! Get your 15 day free trial of NEWSMAX+ at http://NewsmaxPlus.com Looking for NEWSMAX caps, tees, mugs & more? Check out the Newsmax merchandise shop at : http://nws.mx/shop Follow NEWSMAX on Social Media:  -Facebook: http://nws.mx/FB  -X/Twitter: http://nws.mx/twitter -Instagram: http://nws.mx/IG -YouTube: https://youtube.com/NewsmaxTV -Rumble: https://rumble.com/c/NewsmaxTV -TRUTH Social: https://truthsocial.com/@NEWSMAX -GETTR: https://gettr.com/user/newsmax -Threads: http://threads.net/@NEWSMAX  -Telegram: http://t.me/newsmax  -BlueSky: https://bsky.app/profile/newsmax.com -Parler: http://app.parler.com/newsmax Learn more about your ad choices. Visit megaphone.fm/adchoices

On Friday's Football Daily, Phil Egan has news of the Premier League, the Champions and the League of Ireland.Dublin derby preview as Bohemians host fierce rivals Shamrock Rovers at Dalymount Park, with live commentary coverage.Full breakdown of tonight's crucial fixtures across the League of Ireland Premier and First Divisions.Major sanctions handed to Drogheda United following supporter damage to facilities during their clash with Dundalk.Government update as Patrick O'Donovan confirms funding pause on artificial pitches has been lifted.Key early-season pressure building on several clubs as title hopefuls look to find form.Connacht derby preview and squad updates as western rivals prepare for a crucial showdown.Six English clubs discover their knockout path in the UEFA Champions League last-16 draw.Injury concerns grow around Evan Ferguson ahead of Ireland's vital World Cup playoff against Czechia.Contract boost for Brentford as head coach Keith Andrews commits his long-term future.European roundup as Celtic secure a historic win in Germany but exit Europe on aggregate.Progress in continental competition for Nottingham Forest despite a nervy second-leg defeat to Fenerbahce.Team news concerns for Liverpool as Florian Wirtz faces time on the sidelines.Relegation fears intensify for Wolves as they prepare for a must-win clash.Top-four ambitions continue for Aston Villa as they aim to strengthen their Premier League position.Expert analysis, manager reactions, and everything you need ahead of a packed weekend of football at home and abroad.Become a member and sign up at offtheball.com/join

On Prime Time Episode 367, Oliver Nivaud is tonight's special guest. There is always a lot of things happening at United Cigars and Selected Tobacco, and we will cover them tonight. Most recently there are some announcements around Nelson Alfonso's new facility in Spain plus some new Firecrackers are on the horizon. We will also have our FSG Beef, Alec Bradley Live True, Espinosa, and Dunbarton Tobacco & Trust Industry Deliberation segments.

On Prime Time Episode 367, Oliver Nivaud is tonight's special guest. There is always a lot of things happening at United Cigars and Selected Tobacco, and we will cover them tonight. Most recently there are some announcements around Nelson Alfonso's new facility in Spain plus some new Firecrackers are on the horizon. We will also have our FSG Beef, Alec Bradley Live True, Espinosa, and Dunbarton Tobacco & Trust Industry Deliberation segments.

Episode: 3266 Fireworks, Firecrackers, and Lunar New Year.  Today, we ring the new year in with a bang.

Season 4, Episode 8: Tarnesha Nickens is a firecracker! That is said probably ten times on this episode of The Front Porch. After hearing her story and all the ways she is giving back in Melissa, Texas, you understand how fitting that title truly is. She gets stuff done, and her driving force revolves around legacy. During our conversation, she said: "Sometimes your legacy is not always with the next generation - with your children - it's what your handprint has left in the community that you're in." That one was one of many "drop the mic" moments on this episode. #frontporchLinks:City of Melissa: WebsiteMusic: https://www.purple-planet.com

Festivals reveal a society's values. In China, few moments do so like Spring Festival, especially from the second day onward, when private rituals become public celebration. Welcoming the son-in-law and worshipping ancestors and gods once reflected an agrarian world of kinship and survival. Today, these same customs sit alongside malls, livestreamed fairs, and global audiences. What happens when tradition meets urbanization and technology? On the show: Niu Honglin, Steve & Yangyang

Author : Angela Liu Narrator : Rebecca Wei Hsieh Host : Katherine Inskip Audio Producer : Jeremy Carter First published in Worlds of Possibility in February 2024. Image by Pfeilgiftfeder from Pixabay Firecrackers on 28 Mott Street by Angela Liu The children wield firecrackers as they enter the old shop on Mott Street. Copper wind […] Source

Discover all of the podcasts in our network, search for specific episodes, get the Optimal Living Daily workbook, and learn more at: OLDPodcast.com. Episode 3459: FIRECracker challenges the myth that homeownership is the key to financial security by showing how renting can lead to greater career freedom, lifestyle flexibility, and investment growth. Drawing from personal experience, she reveals how avoiding the hidden costs of buying property helped her retire early and live on her own terms. Read along with the original article(s) here: https://www.millennial-revolution.com/rent/renting-will-make-you-rich/ Quotes to ponder: "You are renting a place for free. Let me repeat that. You are renting FOR FREE." "Renting is NOT throwing your money away, and buying a house comes with WAY more hidden costs than you think." "You don't fall into the trap of having all your money locked in ONE asset, whose price you CAN'T control." Episode references: Quit Like a Millionaire: https://www.amazon.com/Quit-Like-Millionaire-No-Gimmicks/dp/0525538690 Learn more about your ad choices. Visit megaphone.fm/adchoices

Discover all of the podcasts in our network, search for specific episodes, get the Optimal Living Daily workbook, and learn more at: OLDPodcast.com. Episode 3459: FIRECracker challenges the myth that homeownership is the key to financial security by showing how renting can lead to greater career freedom, lifestyle flexibility, and investment growth. Drawing from personal experience, she reveals how avoiding the hidden costs of buying property helped her retire early and live on her own terms. Read along with the original article(s) here: https://www.millennial-revolution.com/rent/renting-will-make-you-rich/ Quotes to ponder: "You are renting a place for free. Let me repeat that. You are renting FOR FREE." "Renting is NOT throwing your money away, and buying a house comes with WAY more hidden costs than you think." "You don't fall into the trap of having all your money locked in ONE asset, whose price you CAN'T control." Episode references: Quit Like a Millionaire: https://www.amazon.com/Quit-Like-Millionaire-No-Gimmicks/dp/0525538690 Learn more about your ad choices. Visit megaphone.fm/adchoices

Discover all of the podcasts in our network, search for specific episodes, get the Optimal Living Daily workbook, and learn more at: OLDPodcast.com. Episode 3459: FIRECracker challenges the myth that homeownership is the key to financial security by showing how renting can lead to greater career freedom, lifestyle flexibility, and investment growth. Drawing from personal experience, she reveals how avoiding the hidden costs of buying property helped her retire early and live on her own terms. Read along with the original article(s) here: https://www.millennial-revolution.com/rent/renting-will-make-you-rich/ Quotes to ponder: "You are renting a place for free. Let me repeat that. You are renting FOR FREE." "Renting is NOT throwing your money away, and buying a house comes with WAY more hidden costs than you think." "You don't fall into the trap of having all your money locked in ONE asset, whose price you CAN'T control." Episode references: Quit Like a Millionaire: https://www.amazon.com/Quit-Like-Millionaire-No-Gimmicks/dp/0525538690 Learn more about your ad choices. Visit megaphone.fm/adchoices

以農曆新年為主題的藝術展覽 "Echoes of the Firecracker"《爆竹的回聲》，正在雪梨 Chatswood 的 The Concourse 舉行。

listen without ads at www.patreon.com/dopeypodcastThis week on Dopey's Greatest Hits!This replay episode features host David Manheim reflecting on personal chaos, gratitude amid frustration, powerful listener emails/stories (including a harrowing crack/coke seizure tale from Minnesota Matt), and a full classic interview with his partner Linda. They share their raw, unfiltered relationship story—from meeting via mutual friend Todd, early partying (coke, Ativan, drinking), pregnancy amid hidden heroin relapse, family destruction during active addiction, separation, supervised visitations, Dave's bottoming out, eventual sobriety, reconciliation, and rebuilding a family with two kids. Interspersed with intros, emails, Spotify comments, voicemails, and musical interludes (Firecracker rap, song snippets), it captures Dopey's signature mix of dark humor, brutal honesty, recovery insights, and "dumb shit" war stories.The episode opens with Dave navigating recent frustrations—dealing with a guest pulling an episode due to cold feet, sponsor issues, and everyday life stressors—while emphasizing core recovery principles like acceptance, gratitude, and service over resentment. He reflects on childhood influences like Popeye's "I am what I am" mantra as a metaphor for self-acceptance in sobriety, and teases upcoming substantive guests while reading heartfelt (and critical) listener feedback. The heart of the show is the replay of a classic episode featuring Dave and Linda's candid conversation, detailing the highs and lows of their relationship: from initial attraction and drug-fueled early days, through the pregnancy discovery and Dave's escalating heroin use (including nodding out during birthing classes and missing key moments post-birth), to the devastating confrontation when Linda discovered the paraphernalia and the subsequent separation.The story doesn't shy away from the pain—Linda's isolation during a complicated delivery, Dave's rock-bottom spiral involving heavy daily use, arrests, and black eyes during supervised visits with their daughter Nora—but it ultimately lands on hope and redemption. Dave credits their daughter as a major motivator for sobriety, and the couple discusses the hard work of rebuilding trust, family life, and even welcoming a second child. Reflections on the losses of close friends Todd and Chris add emotional weight, underscoring how addiction's toll extends beyond the individual. All that and More, more, more on this weeks new new new episode of dopey!  Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Fluent Fiction - Mandarin Chinese: Snowy Meditations: Finding Peace Among the Firecrackers Find the full episode transcript, vocabulary words, and more:fluentfiction.com/zh/episode/2026-01-22-08-38-20-zh Story Transcript:Zh: 在杭州的冬季，灵隐寺被皑皑白雪覆盖，En: In the winter of Hangzhou, Lingyin Temple was covered in a blanket of white snow.Zh: 寺院四周是古老的森林，它们在淡淡的雾气下显得神秘而宁静。En: The surrounding ancient forest appeared mysterious and tranquil under the light mist.Zh: 正值春节期间，寺庙里挂满了鲜红的灯笼，金色的横幅在风中轻轻飘舞。En: It was the Spring Festival period, and the temple was adorned with bright red lanterns, with golden banners gently waving in the wind.Zh: 尽管冷风刺骨，这里显得异常热闹。En: Despite the biting cold wind, the place felt unusually lively.Zh: 黎亮，一个向往安静与顿悟的青年，决定在春节期间来到灵隐寺进行冥想。En: Li Liang, a young man who yearned for peace and enlightenment, decided to visit Lingyin Temple during the Spring Festival for meditation.Zh: 他渴望在新年到来之际寻求内心的平和。En: He longed to seek inner peace as the new year approached.Zh: 他的朋友周和梅陪同前来。En: His friends Zhou and Mei accompanied him.Zh: 周是个心地善良但总是笨手笨脚的人，而梅则是个活泼风趣的人，她总能在任何境地中找到乐趣。En: Zhou was a kind-hearted but often clumsy person, while Mei was lively and witty, always able to find joy in any situation.Zh: 黎亮找到寺中一个安静的角落，打算开始他的重要冥想。En: Li Liang found a quiet corner in the temple to begin his important meditation.Zh: "我只需要一刻的宁静，"他对自己说。En: "I just need a moment of silence," he told himself.Zh: 闭上眼睛，他开始进入冥想状态。En: Closing his eyes, he began to enter a meditative state.Zh: 可是，寺庙里正在为春节做准备，四处都是喧闹声。En: However, preparations for the Spring Festival were underway in the temple, and there was noise everywhere.Zh: 首先，周不小心踢翻了一个装满小铜铃的篮子，叮当作响。En: First, Zhou accidentally kicked over a basket full of small copper bells, which rang out loudly.Zh: 这声音打断了黎亮的冥想，En: This sound interrupted Li Liang's meditation.Zh: 他皱了皱眉，但还是继续努力集中注意力。En: He frowned but continued to concentrate.Zh: 接着，梅嬉笑着模仿寺庙里的钟声，笑声不断传入黎亮的耳中。En: Next, Mei giggled as she imitated the temple's bell sounds, her laughter continuously reaching Li Liang's ears.Zh: "真不凑巧，"他想，但他并没有生气。En: "Such bad timing," he thought, but he didn't get angry.Zh: 随着时间的推移，庙里的准备更加繁忙。En: As time went by, the preparations in the temple became even busier.Zh: 到了高潮时刻，就在黎亮几乎达到完美的冥想状态时，寺庙门外忽然有人点燃了一串巨大的炮竹声，巨响冲天而起。En: At the climax, just as Li Liang was almost reaching a perfect meditative state, someone suddenly set off a string of giant firecrackers outside the temple door, with a thunderous noise rising into the sky.Zh: 黎亮张开眼，显得极为震惊，但当他看向身边的周和梅，他们正捂着耳朵笑得前仰后合。En: Li Liang opened his eyes, looking extremely startled, but when he looked at Zhou and Mei beside him, they were covering their ears, laughing uproariously.Zh: 黎亮再次闭上眼，这一次，他不再强求完美的宁静。En: Li Liang closed his eyes again, this time no longer striving for perfect peace.Zh: 慢慢地，他意识到了周围的热闹和快乐，也感到了那份暖意。En: Slowly, he became aware of the liveliness and joy around him, and he also felt a sense of warmth.Zh: 他放下了执念，脸上露出释然的笑容，和朋友们一起开怀大笑。En: He let go of his obsessions, a relieved smile appearing on his face, as he laughed heartily with his friends.Zh: 黎亮终于明白，顿悟不在于绝对的静谧，而在于欣然接受生活的变化与无常。En: Li Liang finally understood that enlightenment is not about absolute tranquility, but about gladly accepting the changes and impermanence of life.Zh: 他找到了内心的宁静，虽然不是在他所预想的方式里。En: He found inner peace, although not in the way he had envisioned.Zh: 春节的烟花照亮了半边天，灵隐寺在热闹与宁静之间找到了平衡，而黎亮，也找到了心灵的启迪。En: The fireworks of the Spring Festival lit up half the sky, with Lingyin Temple finding balance between liveliness and tranquility, and Li Liang finding enlightenment in his soul. Vocabulary Words:blanket: 覆盖biting: 刺骨yearned: 向往enlightenment: 顿悟adorned: 挂满concentrate: 集中tranquility: 宁静obstructions: 障碍imitation: 模仿uproariously: 开怀大笑meditative: 冥想striving: 强求obsessions: 执念relieved: 释然impermanence: 无常giggled: 嬉笑thunderous: 巨响exuberant: 热闹liveliness: 活泼firecrackers: 炮竹gently: 轻轻climax: 高潮perfect: 完美startled: 震惊tranquil: 神秘accompany: 陪同appeared: 显得preparations: 准备meditation: 冥想banners: 横幅

This week on The Cigar Authority, it's the 2026 Firecracker Announcement with Oliver Nivaud of United Cigars! Oliver is back for his annual unveiling of the Limited Edition Firecracker coming out this summer! What will be this year's limited edition firecracker!? Tune in this week to find out while we smoke Firecracker Maduro! Join Mr. Jonathan, David Garofalo and Ed Sullivan as we light up cigars and talk about them. The Cigar Authority is a member of the United Podcast Network and is recorded live in front of a studio audience at Studio 21 Podcast Cafe upstairs at Two Guys Smoke Shop in Salem, NH.

This episode features the stories "Firecracker," "Banished," "Tough" and "After the Attack," as well as the poem "Have A Heart." Stories and poem used by permission of the author. Learn more about your ad choices. Visit megaphone.fm/adchoices

#227 The Chemistry Behind Firecrackers and Christmas Crackers Melissa and Jam delve into the chemistry behind firecrackers and Christmas crackers. They discuss the key component, silver fulminate, explaining its unstable nature and how it reacts to create the explosive effects. The discussion also touches on the octet rule, formal charges, and isomers. Along with sharing personal experiences and pranks involving firecrackers, they also recount historical debates between chemists over the discovery of isomers and their eventual agreement. The episode highlights the importance of chemistry in understanding everyday phenomena and ensuring safety. 00:00 Introduction and Firecracker Anecdotes 00:58 Chemistry of Firecrackers 04:53 Explosive Chemistry Explained 19:55 Historical Discoveries and Isomers 24:20 The Origins of a Scientific Discovery 24:48 Friendship and Scientific Collaboration 25:24 Understanding Isotopes and Isomers 27:20 Chemistry Behind Christmas Crackers 30:26 Fireworks and Safety Concerns 35:52 Fire Alarms and Home Safety 42:33 Supporting the Show and Community Shoutouts Support this podcast on Patreon Buy Podcast Merch and Apparel Check out our website at chemforyourlife.com Watch our episodes on YouTube Find us on Instagram, Twitter, and Facebook @ChemForYourLife References from the Episode:   Thanks to our monthly supporters Amanda Raymond Emily Morrison Kyle McCray Justine Emily Hardy Ash Vince W Julie S. Heather Ragusa Autoclave Dorien VD Scott Beyer Jessie Reder J0HNTR0Y Jeannette Napoleon Cullyn R Erica Bee Elizabeth P Rachel Reina Letila Katrina Barnum-Huckins Suzanne Phillips Venus Rebholz Jacob Taber Brian Kimball Kristina Gotfredsen Timothy Parker Steven Boyles Chris Skupien Chelsea B Avishai Barnoy Hunter Reardon Support this podcast on Patreon Buy Podcast Merch and Apparel Check out our website at chemforyourlife.com Watch our episodes on YouTube Find us on Instagram, Twitter, and Facebook @ChemForYourLife Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Firecracker Comedy!  Welcome to the first THREE-GUEST EPISODE of Broccoli and Ice Cream! Because... Firecracker Comedy is a comedy 'supergroup' composed of Gabby Gutierrez-Reed, Kate Strobel and Salma Zaky. Forged in the grade-A comedy incubator of Denver, CO, Firecracker Comedy has been putting on killer shows for years.  The Firecracker Comedy album celebrates this trio of badass women who center their comedy, and everything they do around their deep and undying friendship, love, and appreciation for each other: "We started running Firecracker Comedy as a standup show in a tattoo shop in Denver years ago, when we all were in a bit of a dark place and at a crossroads in our lives. The show is a celebration of finding joy, building community, and being silly with your pals when the world around you is spiraling out of control. We even have matching firecracker tattoos!" Firecracker Comedy consists of 20 minute sets from Gabby, Kate and Salma, following an introduction from all three to welcome the audience to the group's delightful chemistry. Each of the three comedians have distinct styles: Kate's heartfelt storytelling, Gabby's hilarious impressions, and Salma's perfectly crafted one-liners. These differences compliment each other, much like in a friendship (or three)!   Salma and Kate are now based in Brooklyn where they regularly bring the Firecracker vibes to Union Hall. The album is a culmination of material from their collective time in Denver - running that sold-out indie comedy show in the tattoo studio, hauling chairs across town, hanging flyers in every Denver coffee shop, stressing about if the broken sound system would work that night - as well as Salma and Kate's early experiences in the Big Apple. The album shows how no matter where they find themselves, the three always come back together as friends. Gabby, Kate and Salma of course want their listeners to belly laugh for an hour straight, but they also want listeners to feel connected to them as a group, and be inspired to create silly little things with their friends too. What else is life really about besides deepening our relationships and collaborating with the ones you love? We have a great chat! You have a great listen! And this is only the first HALF of our chat! For part two, subscribe via Apple Podcasts OR merely click on over here to Patreon!

www.patreon.com/dopeypodcastDave opens the Tuesday teaser alone in his house, loving the rare quiet and recording next to Susan the snake's terrarium. He complains about his fancy Rogan-style mic breaking, says he hates stands, and talks about launching “fake meditation shit” because he likes the sound of his own voice.He previews this week's Patreon episode: him and Doug in the Honda Pilot “by the bay,” where Dave had a full sneezing meltdown and wound up blowing his nose into his sock for the entire show because he had no tissues.Dave announces a possible new Dopey schedule:Monday: standalone interviewTuesday: teaserWednesday: Secret DopeyThursday: archived interviews or mailbagFriday: DopeyHe announces a Patreon Zoom at 9pm.He then reads an email from a listener named Dave, who realized his sponsor is the guy who made the Firecracker rap for DopeyCon. Dave plays the Firecracker rap and riffs on how good it is, how white recovery rap can be weird, and how much he loves the shout-out to Artie Lange and Chris.The emailer says he's 18 months sober and thanks Dave. Dave tells him to send more rap.Then the teaser cuts to Dave and Doug in the Honda Pilot, roasting each other. Doug calls Dave a homeless person for blowing his nose in a sock. They argue about Rich Roll, Doug's critiques of Dave's interviews, Doug's surgery, Dave's voice, meditation, and a guy on Soft White Underbelly. Doug claims Dave was needy and weak on his second Rich Roll appearance. Dave pushes back.All that and not much more on the all new patreon teaser for the good old dopey show. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Heather Lynn and Caleb Francis are joined by Solomonica. From trying Taco Bell's new Baja Blast Pie to designing their own action figures (complete with milk, swords, lettuce heads, and skull accessories), this episode spirals beautifully into chaos. They cover everything from serial killer M.O.s to bounty hunting, Dutch winter food, hunting conservation, and Mad Dog cocktailsGet Exclusive NordVPN deal here → https://nordvpn.com/timeforpie It's risk-free with Nord's 30-day money-back guarantee! EVERYTHING tastes better with Firecracker farm HOT SALTExplore their selection and use code MILK to save 10%https://shop.firecracker.farm/pages/pieLet's level up your pouch routine with Lucy. Go to Lucy.co/PIE and use promo code (PIE) to get 20% off your first order. Lucy has a 30-day refund policy if you change your mind.

Discover all of the podcasts in our network, search for specific episodes, get the Optimal Living Daily workbook, and learn more at: OLDPodcast.com. Episode 3331: FIRECracker challenges the conventional wisdom that owning is always better than renting by sharing a personal story of how car-sharing saved thousands and reduced stress after a nasty accident with a white van. With sharp humor and financial insight, she makes a compelling case that renting both cars and homes can lead to greater freedom, fewer surprises, and accelerated wealth building, especially in high-cost cities. Read along with the original article(s) here: https://jlcollinsnh.com/2016/10/21/buy-your-freedom-rent-the-rest/ Quotes to ponder: "Renting lets you get ahead, because you don't need to take the financial risk to maintain a physical asset." "The costs of owning are WAY higher than people think, and the worst part of these expenses are they are often unexpected." "Stress free and predictable. That's the key to freedom." Episode references: Enterprise CarShare: https://www.enterprisecarshare.com Learn more about your ad choices. Visit megaphone.fm/adchoices