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Take the 2026 AI Engineering Survey and get >$2k in credits and AIE WF tickets!This was recorded before Railway suffered a major GCP outage on May 19, despite being a multi-AZ, multi-zone mesh ring, with HA fiber interconnects between their Metal GCP AWS, because workload discoverability was unintentionally still tied to GCP. All has been resolved with a post-mortem.Railway did not start as an AI infrastructure company.It was founded in 2020 years before agents became the default way people thought about deploying software. Jake Cooper, formerly at Bloomberg and Uber, started Railway with a simple obsession: the activation energy to ship something to production should be near zero. Push code, get a URL, iterate. No Docker files, no Kubernetes manifests, no Ansible scripts stacked on Ansible scripts.For years, this was a slow grind. Railway spent its first 18 months hand-acquiring its first 100 users with Jake personally greeting every Discord signup on a second monitor.Today, Railway has raised $124m and is growing very fast. A 35-person team supports 3 million users, adding roughly 100,000 signups a week. Their bare metal data centers have a 3-month payback period vs. renting in the cloud, with 70% margins funding aggressive cloud bursting when needed. The servers they own have actually appreciated in value as RAM prices have climbed basically meaning the value of their hardware now exceeds the capital they've raised.From rebuilding Railway's network overlay over a weekend to moving the vast majority of workloads onto its own bare metal data centers, Jake Cooper is trying to build a new cloud for an agent-native world. In this episode, Railway's founder and “conductor” joins swyx and Alessio to unpack why the next era of software infrastructure is not just “Heroku but newer,” what agents need that humans did not, and why the old deployment loop of Git, PRs, CI/CD, and static cloud resources may be heading for a rewrite.We go deep on Railway's infrastructure stack: own-metal data centers, three-month cloud payback periods, cloud bursting, data center debt, Railpack, Nixpacks, Temporal, feature flags, Central Station, content-addressable filesystems, agent-safe production forks, and why the CLI may become more important than the canvas in an agent world. Jake also shares the founder journey behind Railway, how the company survived losing $500K/month, why it now serves millions of users with only 35 people, and why he believes the pull request is dying.We discuss:* How Railway went from a slow six-year grind to adding 100,000 users a week* How Railway thinks about agents as the next dominant software species* Why agents need version control, observability, compute, storage, and orchestration at 1000x scale* The economics of Railway's own-metal data centers and three-month payback* How Railway uses cloud bursting while scaling its own infrastructure* Why data center debt can be a better tool than venture debt for infra startups* Central Station, Railway's internal system for clustering customer feedback and incidents* Why responsible disclosure and over-communication matter for platforms* Why feature flags, progressive rollouts, and shadow traffic are essential for agents* Temporal's strengths, pain points, and why workflows matter for agents* Railpack, Nixpacks, Nix, and lazy-loaded content-addressable filesystems* Why “cattle, not pets” may change if you can clone the pets* Why Railway is building a new cloud from scratch instead of copying hyperscalers* The solo founder path, focus, writing, and how Jake thinks about company buildingRailway:* Website: https://railway.com/* X: https://x.com/RailwayJake Cooper:* LinkedIn: https://www.linkedin.com/in/thejakecooper/* X: https://x.com/JustJakeTimestamps00:00:00 Introduction: What Is Railway?00:02:07 Jake's Path to Railway00:06:13 Railway's Six-Year Growth Story00:08:52 Rebuilding the Business After the Free Tier00:11:17 Agents as the Next Software Platform00:13:29 Railway's Infrastructure Philosophy00:15:42 Bare Metal, Cloud Economics, and the Compute Crunch00:17:22 Cloud Bursting and Five-Cloud Networking00:20:20 Data Center Debt and Infra Financing00:23:31 Data Centers in Space00:25:24 What Agents Need From Infrastructure00:28:24 CLIs, Canvas, and Agent-Native UX00:35:15 Central Station, Incidents, and Responsible Disclosure00:40:30 Safe Rollouts, SRE Agents, and Production Forks00:45:00 AI SRE, Specs, Code, and Tests00:48:24 Self-Replicating Infrastructure and the New Serverless00:53:18 Heroku, Temporal, and Workflow Engines01:04:07 Railpack, Nixpacks, and Lazy-Loaded Filesystems01:06:01 Coding Agents, Token Spend, and Roadmap Acceleration01:10:56 The Pull Request Is Dying01:12:28 Feature Flags and the Agent-Era SDLC01:16:15 Cattle, Pets, and Cloning Machines01:19:29 Solo Founder Lessons01:24:12 Focus, GPUs, and Building a New Cloud01:28:20 Closing ThoughtsTranscriptAlessio [00:00:00]: Hey, everyone. Welcome to the Latent Space Podcast. This is Alessio, founder of Kernel Labs, and I'm joined by Swyx, editor of Latent Space.Swyx [00:00:10]: Hey, hey, hey. Today we're in the studio with Jake Cooper of Railway.Alessio [00:00:14]: Conductor of Railway.Swyx [00:00:15]: Conductor at Railway. Yeah.Alessio [00:00:16]: Choo-choo.Swyx [00:00:17]: Do you actually have that anywhere, like on your business card?Jake [00:00:20]: We call some of our volunteer moderators conductors. I don't have a business card. We're not that big yet. At some point I will. I got handed a nice business card from the Supermicro folks, and I was like, “Damn, this is pretty official.”Swyx [00:00:30]: Business cards are coming back.Jake [00:00:32]: They're cool. They're hip. The conductor thing is good. We're trying to figure out what we want to call each other internally. Some people think it's super cringe and say, “You don't need a name for people internally.” Some people want to call each other something. We still don't have a really good one.Jake [00:00:55]: We've got New Railcrews, Trainiacs. Nothing has stuck yet.Swyx [00:01:00]: I like Trainiac. Trainiac sounds good. Railwayians. For those who don't know, what is Railway? Let's give people a crisp definition up front.Jake [00:01:09]: Railway is the easiest way to ship anything. You go to the canvas, or you talk with Claude, and you say, “Deploy a Postgres instance, deploy my GitHub repository, run this code,” and you're off to the races.Swyx [00:01:22]: You've got a nice animation on the landing page.Jake [00:01:24]: Thank you. None of my work, by the way. They don't let me touch the design stuff anymore.Jake [00:01:25]: We want to make it trivially easy not just to deploy things, but to evolve applications over time. Most tooling right now stacks entropy on top of entropy: Docker, Kubernetes, Ansible scripts, and all these other things. If we can version all of your software and keep track of all the changes, then we can make it trivial to clone environments, fork into a parallel universe, get copies of production data, get copies of any services, make changes, validate them, and collapse them back in without reproducing everything across a staging environment.The Railway Origin Story: From Uber Systems to a New CloudSwyx [00:02:07]: I was looking at your background: Bloomberg, Uber. Nothing immediately stands out as, “This guy is going to found the next great platform as a service.” What prepared you for Railway?Jake [00:02:21]: It was curiosity to keep going deeper. I started out on front-end stuff, working on Wolfram Mathematica and porting it over. Then I briefly moved to Bloomberg, then toward Uber and distributed systems, taking the Jump Bikes systems and moving them to a distributed system built on top of Cadence, the pre-Temporal Temporal.Swyx [00:02:44]: Which, by the way, I'm happy to talk about, pros and cons.Jake [00:02:48]: Totally.Swyx [00:02:51]: But let's do the Railway story.Jake [00:02:52]: It has been a continual step of wanting an experience. Whether it's walking up to a bike, unlocking it, and having it work frictionlessly, or something else, the depth required to make that happen follows from the experience. A lot of the work I do, and a lot of the team does, is in service of that experience. We fundamentally don't care how deep we have to go. We will swim to the bottom of the swimming pool to get the experience.Jake [00:03:17]: I don't have a physics PhD. I did an EECS degree. It has always been about figuring out the next step: how do we get there? That's what led to starting Railway for that experience and then moving all the way to bare metal data centers. I was adding patches to the kernel this week to get the experience there because I can see how much better it can be.Swyx [00:03:49]: Other patches to the Linux kernel this week?Jake [00:03:51]: Yeah. Not upstream. Our fork.Swyx [00:03:52]: That's a flex. Railpack? No, this is different. This is the OS on top of Railpack?Jake [00:03:57]: No, this is an actual kernel patch. It's always literally: what do we have to do to get that experience? Then figure it out. Anything is figureoutable.Swyx [00:04:10]: Would you send the patch upstream, or does it not fit other use cases?Jake [00:04:13]: Maybe. We have to work out the experience internally. It has to do with the storage layer we're building for some of the agentic stuff. Maybe it'll be useful upstream, but it's deeply useful for us internally.Open Source, Forks, and Non-Deterministic VersioningSwyx [00:04:29]: You mentioned open source before. How do you think about starting from open source, and then coding agents letting you do a lot more from forks of it?Jake [00:04:38]: GitHub's original sin is that it's almost a series of broken pointers. You have this thing, then you clone it, and now you've lost the whole upstream. How do we make it trivial for people to modify really small pieces of it?Jake [00:04:51]: We think of Git in a discrete sense: I've either made a change and merged upstream, or I haven't. What would it look like if it were percentage-based, a little more non-deterministic, or a stream of changes that users traverse as a percentage rolled out in general and then rolled all the way up?Jake [00:05:13]: We have the open-source kickback program and let you deploy templates because we want to make it trivial for people to version these shards over time. It solves a large problem around authentication, authorization, and security. NPM has a way to define, “Don't take any new packages.” The ideal end state is that you roll out progressively to users with the minimum impact zone and continue rolling up. JPMorgan should probably be the last one on the patch line, for all our sakes, because our money and livelihoods are there.Jake [00:05:53]: It's okay if Johnny Vibe Coder gets a broken patch because there's so much entropy in the system that the rubber has to meet the road at some point. You have to test at varying levels.The Long Grind: First Users, Free Tier, and Making the Business WorkSwyx [00:06:13]: I wanted to pull up this glorious chart, which is your usage or number of daily signups?Jake [00:06:22]: Daily signups, I think.Swyx [00:06:24]: You started six years ago. It was a slow grind, and now you're on a rocket ship. You say, “Don't doubt your fight and don't quit.” Maybe pick out certain points that were key inflections for the company.Jake [00:06:40]: At the start, it's about getting your first 100 users, hell or high water. We had a website and a support link. The support link was the Discord channel. I had notifications on with two monitors: the monitor I was working on and the other monitor with Discord. If anybody came in, I was immediately like, “Hey, how's it going?” It was rare, so getting those first 100 users to come back was the start.Jake [00:07:14]: Then you build a consultancy factory because users want all these things. You have to go back to the board and ask, “What is the actual product offering I want to build on top of this?”Jake [00:07:28]: VCs want charts that always go up and to the right, but in reality you don't necessarily want charts that look like that. For us, there have been periods of expansion where we add features to test use cases, and periods of compaction where we ask, “If the experience we have is good, how do we make it significantly better?” Maybe we strip out features that don't fit our ICP anymore.Jake [00:07:57]: The boom from 2022 to 2023 came from the free tier. Everybody under the sun was using it.Swyx [00:08:09]: A lot of Reddit bots and Discord bots.Jake [00:08:12]: And crypto miners. When you build an open product on the internet where anybody can sign up, the internet is a horrible place with so many things. You go through periods of asking, “How do I reach as many people as possible?” Then, “How do I fit the exact use case for the people who really matter and are really excited about this specific thing?”Jake [00:08:39]: Then there was a two-year period of making the actual business work. During the free-tier era, we were losing about half a million dollars a month.Swyx [00:08:59]: On a $20 million bank account.Jake [00:09:02]: On a $20 million bank account with maybe $50,000 a month in revenue. That's a horrible business. I don't know how anybody invested. But you have to go through it and say, “We have an experience people love, but the business has to work.”Jake [00:09:17]: There are two schools of thought. You can run the horrible business all the way up with bad margins, or you can go back and make it work. We've always wanted a super lean team. We're 35 people right now. It's very small.Swyx [00:09:36]: Supporting three million already?Jake [00:09:38]: Yeah. We're adding 100,000 users a week right now, so it's growing fast. We don't want to add headcount for the sake of headcount or throw bodies at problems. We want to build systems. It's hard to build systems during expansion because you're adding things to the system because people are asking for them or things are breaking.Jake [00:10:00]: We had to cut off the free users for a little while, rebuild the business, and make sure it worked. We want to reach as many people as possible because software is important. It's become difficult to create things in the physical world, so it's important to make it easy for people to build in the virtual world and have access to creation. But there are legs to that journey.Jake [00:10:30]: You can see divots in the charts. If you follow between 2025 and 2026, it's either summer or winter. People go on holiday with family.Swyx [00:10:50]: It affects that much?Jake [00:10:51]: Yeah. It's kind of B2C and kind of B2B. People are shipping constantly, then they stop. Our activation curve now shows more people activating on weekdays because we have more business users, so it smooths out over time.Agents as the New Interface to DeploymentSwyx [00:11:17]: Was there a point where you started prioritizing AI development or agent development?Jake [00:11:24]: We've prioritized agentic as a top-of-funnel thing. Over the last six months, we've deeply prioritized agentic as a mechanism to build and deploy things because we believe the curve is so steep and that is how people will build and deploy software.Jake [00:11:42]: It almost fundamentally doesn't matter whether this is dot-com or not because we're all on the internet anyway. If agents are going to deploy a bunch of things and we hit an inference wall at some point, we'll fix those problems. The dominant species over the next 10 years is that we've moved from assembly to C to C++ to JavaScript to words. You're going to need to close that loop.Swyx [00:12:13]: When you say this is dot-com, did you mean buying the domain, or the general case?Jake [00:12:17]: I mean the dot-com era, when companies had a huge run-up because people understood the internet was important. Then they hit bottlenecks, fundamental laws of physics, math didn't work, and everybody came back down to earth. But it didn't matter because the internet became so impactful. If you operate on a long enough time horizon, you should build these things anyway because you can see where it's going.Jake [00:12:45]: That's where I think a lot of agent stuff is. You get to a point where you're running thousands of agents in parallel. What is the inference cost? What is the compute cost? How do you make that efficient? How do you coordinate all this? We have issues coordinating humans; we don't even have good tooling for that. Now we have to figure out how to get agents to coordinate, safely version changes, and know when to raise their hand for someone to intervene. Otherwise it becomes an interrupt factory.Railway's Infrastructure Thesis: Network, Compute, Storage, and MetalSwyx [00:13:19]: Let's go right into the technical side. What are the core infrastructure or architectural beliefs of Railway that allow you to do what you do?Jake [00:13:29]: The primitives matter a lot for us. We need network, compute, storage, and orchestration around it. You need control over a lot of those things. We've talked a lot about how we don't really use Kubernetes because we want higher-order control to place workloads in very specific places.Jake [00:13:48]: The reason is that you have to be very efficient with agents: memory reuse and all these other things, or you're going to massively blow up your cost structure. Being able to rack and stack your own servers and build your own metal unlocks performance and cost. Experiences where you're running 1,000 agents in parallel are not massively cost prohibitive.Jake [00:14:13]: Token use and compute use are blowing up. Over time, those things have to get a lot more efficient. You can get a lot of margin to make those experiences solid by building your own metal. That's all in service of offering a differentiated experience to as many people as humanly possible.Swyx [00:14:51]: You have a data center in Singapore.Jake [00:14:53]: Yeah. We have two in every other region now. In Singapore, we're adding a second one in Q3.Swyx [00:14:58]: What's it like? I've never built a data center. Do you go to Equinix and say, “I want some slots?”Jake [00:15:05]: Yeah. Equinix. You basically go and say, “I want power and I want a cage.” They say, “Great, here's what it's going to be.” You rent the cage for a period of time, fill it with racks and servers, and hook up internet to it. That's all the pieces.Swyx [00:15:36]: Then you handle everything else.Jake [00:15:37]: You handle everything else.Swyx [00:15:39]: What's the math versus clouds doing it for you?Jake [00:15:43]: If we rented in the cloud, our payback period when we go to metal is about three months.Swyx [00:15:50]: Which is crazy.Jake [00:15:51]: It's nuts. That's four years of depreciated hardware. You're going to see a lot of this compute crunch because hyperscalers are buying up a lot of stuff. We're working directly with OEMs, resellers, and people building these machines: Supermicro, Dell, and others.Jake [00:16:11]: Upstream, there's a bunch of supply pressure. When we raised our last round, between deploying capital for servers and now, the amount of money we've raised is less than the amount of money we have in the bank plus the value of the servers because the servers have appreciated as RAM has gone up. It's nuts how valuable hardware has become.Jake [00:16:50]: If you look at hyperscalers, they deployed around $80 billion of capital expenditures this year, and next year will be more. That's a massive infrastructure build-out. You look at that and think it's crazy that they're spending way more than the Manhattan Project. But if every person is going to run dozens or hundreds of agents in parallel, you have no conceptual idea how much compute is required to make that experience happen, even if you're deeply efficient and sharing resources. And that doesn't even count inference.Swyx [00:17:22]: How do you plan the build-out? The growth chart is so vertical. Are you usually at 100% utilization as soon as racks are live? How far ahead are you planning?Jake [00:17:33]: We still maintain cloud presence for bursting. We work with AWS, GCP, and a few other clouds. We can rent, and then the moment we get space or power, we compact those workloads off the cloud. We started on the clouds, then built a system to migrate to our own metal. There's nothing that says you can't continually do that again, and that's exactly what we do. We never want to be compute constrained.Jake [00:18:09]: At the start of the year, we actually became compute constrained because one upstream provider wasn't able to give us quota at the rate we needed, and the hardware was slower. I spent a weekend rebuilding our entire network overlay so we could straddle five clouds: Oracle, AWS, ourselves, GCP, and one other one. We can do more than that now.Jake [00:18:38]: We got into a spot where we were trying to pack instances tight because we couldn't get enough compute. That led to a few reliability issues, which are now past us. I made a tweet pointing out that it's becoming harder and harder to acquire compute at the rate these models need to acquire compute. We got bit by it.Swyx [00:19:15]: How do you think about pricing knowing you might not have your own metal available at all times? Are you pricing assuming you need extra margin if you end up going into the cloud?Jake [00:19:26]: Because we've built out our metal data centers, our margins on metal are around 70%. We can deeply subsidize the cloud business if we want to scale at a reasonable rate. We have a few levers: metal, which makes the margins; cloud burst; debt to buy servers; and venture capital. It's an interesting operational problem: how much cash do we have, how much should we raise, how quickly can we deploy it, and can we scale revenue as quickly as we scale compute?Jake [00:20:05]: If we continue making it trivially easy for people to build and deploy, then the faster we close that loop and the more operationally excellent we are with capital, the faster the business can scale. It's almost a straight linear deployment rate.Financing Infrastructure: Hardware Debt, VC, and Operational LeverageSwyx [00:20:20]: I think infra startups raising debt is a tool people don't utilize enough or know enough about. What can you tell us about that? Is it secured against your CPUs?Jake [00:20:32]: It's secured against our hardware.Swyx [00:20:37]: What rates do you get? Who are the lenders?Jake [00:20:39]: We pay prime plus a spread, and we can refinance any of the debt as rates go down. The terms are pretty good. The unfortunate thing is that Twitter has no nuance, so people say, “Venture debt bad.” But as with all things, there are specific tools and areas where you can be deliberate instead of using one tool as a hammer. Venture capital is not the hammer for everything. You have to explore and figure out what works.Swyx [00:21:12]: VC is usually the most expensive financing you can get.Jake [00:21:15]: Yeah. I also think people think about VC incorrectly from a capital-raising perspective. Most people think, “How do I raise as much money as possible from whoever is probably the best I can get at that time?” That's close to right, but what we've tried to do is figure out what unfair advantage we can buy with that equity.Jake [00:21:34]: It's the most expensive equity you're going to give away at that point in time, assuming the company keeps getting better. How do you use it to work with someone stellar who complements you? In the seed stage, I had never started a company. Ray Tonsing had good advice, and I could text him all the time. He was really fast. Awesome.Jake [00:22:01]: Then with John and Erica at Unusual, they said, “You roughly know what you're doing building a product. We'll mostly leave you alone and be available for advice.” Amazing. Then we got to Series A and the business was an operational tire fire because we didn't know how to scale a business. Work with Erica, and Jordan is over at Redpoint, so bonus.Jake [00:22:28]: Now we've raised from TQ and FPV as we're moving into enterprises. Every step of the way, we've asked: who can we partner with at this specific time to unlock the next section of the journey? I don't know enterprise sales. As an engineer, I can eyeball what features we might need, and we have wonderful people internally who can help. But you want boardroom dynamics where everyone is aligned and asking, “How do we win this?” instead of bickering about strategy.Data Centers in Space and the Physics of ComputeSwyx [00:23:31]: You had a tweet about data centers in space. Why no data centers in space?Jake [00:23:37]: It's not “no data centers in space.” My hot take is that I think it is solvable. I've just never seen anybody solve it.Swyx [00:23:49]: You said, “How are you going to dissipate that much heat in a vacuum?” You're making a physics claim.Jake [00:23:55]: I haven't seen anybody prove how you're going to dissipate that much heat in a vacuum. It doesn't mean it's not possible. It just means nobody has brought it up yet.Swyx [00:24:05]: Astrophage.Jake [00:24:06]: I don't know what that is.Swyx [00:24:07]: The Martian thing. Okay, you're very logical.Jake [00:24:09]: It could work. A lot of people are putting the cart before the horse. They say, “We're going to put data centers in space.” Okay, but how? “We have time to figure it out.” It's like in The Martian where they ask how they're going to intercept something and say, “We'll figure it out.”Swyx [00:24:36]: Making a bet on human invention is weird because you blind trust that it can be solved. But with physics, there are first-principles bounds you can put on it. Maybe not. Maybe you're asking to travel time or break a fundamental thermodynamic law.Jake [00:24:57]: I don't know how VCs do this either. How do you know what's not possible and a grift versus what's possible but sounds completely insane? “We're going to put data centers in space.” Coin flip as to which it is, and I guess you'll know in 10 years. That's one cycle.What Agents Need: Versioning, Observability, and 1,000x ScaleSwyx [00:25:23]: Moving back to agents. The branching, fast spin-up, and orchestration you do feels like pre-work that happened to be exactly what agents want. What do agents want differently than humans?Jake [00:25:37]: They want the ability to version things. It's not that different; it materializes slightly differently. Agents want a way to test changes incrementally. Engineers have feature flags. Is there a reason agents can't use feature flags? I don't think so.Jake [00:25:54]: They want version control. Can we use Git or not Git? That one is up in the air. I think something outside Git will emerge for how we version these things over time. They need observability. You need to query what happened, when it happened, which steps failed, traces, logs, metrics, and all the rest. They need network, compute, and storage. They need to write files, save files, iterate on files, and snapshot file systems.Jake [00:26:25]: A lot of what humans needed is in line with what agents need. Branching and forking are not different; we're just moving 1,000 times quicker. It can look like you need something massively different, but what you need is something massively better than what existed. You need orchestration massively better than Kubernetes. You need networking probably better than Envoy. It goes all the way down the stack.Jake [00:26:55]: If the workload profile doesn't change so much as it gets massively compressed because you need thousands of these things, what assumptions change? etcd is going to melt. You need to replace it with something. You can go all the way down the stack and say, “That part has to change, that part has to change, and that part has to change.”Jake [00:27:19]: The interesting thing about the super-exponential curve is that you have to build systems where you can rip out those parts at any time because a new bottleneck might emerge. You get good at parallel agents, and a different part of the system breaks. So it's similar to what humans needed, but at 1,000x scale.Jake [00:27:55]: How do you do code review in the age of agents?Swyx [00:28:00]: You throw more agents at it.Jake [00:28:01]: You don't. But then who reviews for CVEs and all these other things?Swyx [00:28:07]: More agents.Jake [00:28:08]: And that's how we hit the inference wall. You can continually throw agents at the problem, but I think there's a limit to the number of agents you can throw at a problem.CLI, Agent Handles, and Closing the LoopSwyx [00:28:24]: You already had a CLI before it was cool. How is the shape of what you're exposing changing, if at all?Jake [00:28:28]: CLIs have always been cool. The CLI changes because we think about how to give Claude, Codex, ChatGPT, or any model a handhold.Jake [00:28:50]: A CLI is a single command: deploy, get logs, and so on. Things that were prohibitively annoying to humans are not annoying to agents. They're nice. If I handed you a CLI with 40 arguments and 600 flags, you'd think, “I'm never going to use all of this.” But if you hand it to an agent, it says, “This is excellent. I have so many handles to work with.”Jake [00:29:24]: If you're going to expose things to agents that way, you want as many handles as possible where they can get information, query dynamic information, and close the loop quickly. Most problems right now are about how to close the loop as quickly as possible. Where does the agent get stuck, and how can you remove that?Jake [00:29:49]: Telemetry is important. If you can tell where the agent gets stuck from the CLI and say, “12% of people deviate from the happy path because of this, and now I add this argument and drive it down to 2%,” you massively increase the rate of loop closure.Jake [00:30:03]: That's how we think about not just the CLI, but every point in the dashboard. It's a user journey: I hear about Railway. I get something deployed. I get my first green build or aha moment. I see an endpoint, logs, whatever. Then I iterate. The iteration loop is indefinite. The user wants to deploy a new thing, a Postgres instance, change code, and keep iterating.Jake [00:30:36]: If you focus on the iteration loops and what's blocking them from closing quickly, one thing we say internally is: you never want to be waiting on compute anymore. You always want to be waiting on intelligence. If you're waiting on compute, there's a bottleneck that needs to be destroyed because eventually that bottleneck becomes so large that another workflow emerges to change it.Jake [00:31:04]: We've built a product where you push code, build it, and so on. But I fundamentally believe the push-pull loop is going away. We'll get to a point where you make a small change in production, that change is versioned across your infrastructure, you're working alongside copy-on-write versions of your database and infrastructure, and then you merge it in and it's instantaneously live. That's the holy grail of loops. The push-pull-rebuild thing is a point of friction that we're removing entirely.Canvas as Output: Dashboards, Context Anchors, and HyperstructuresSwyx [00:31:43]: It's incredibly fast. If anyone hasn't tried it, that fast feedback is great. My hot take is that Railway was famous for its canvas, which visualizes your infrastructure and lets you manipulate it visually. But that was for humans. For the next phase of growth, Railway CLI is more important than canvas.Jake [00:32:05]: The canvas is funny because it's a mechanism to show changes over time. You're right that previously we used it a lot as an input. Moving forward, its goal is more like an output. You would go to the canvas, make changes, see them, and watch your infrastructure evolve. Now agents have access to the CLI and can make those changes. So the canvas becomes an output: what information does the human need at this moment to make suitable decisions about control requests? Do I approve this or not?Jake [00:32:57]: It also has to be an anchor for your context, a port in the storm. Think of it like layers in a file system. You start with a project, then drill down into services, then into a function or code, because you want to represent the entire thing not just in your head, but in the canvas. Other people can share that representation, think on the same wavelength, and move quickly.Jake [00:33:33]: A lot of organizations get in trouble as they scale because all the context lives in someone's head. “How does this microservice work?” “I have no idea; go ask this person.” Then you have whole categories of products built around context discovery. A lot of that melts away if you have a solid hierarchy and can infinitely nest services, code, context, and everything else all the way down. That's what lets you build these structures over time.Jake [00:34:18]: It's also what lets us build what I've called hyperstructures: things that are way bigger. You look at the Golden Gate Bridge and ask, “How did we build that?” There's a meme that we lost the technology. To some extent, yes, because the coordination that built those things evolved and changed. We lost some of the art of building structure as we jammed everything into Slack.Swyx [00:34:52]: But you jam everything in Discord.Jake [00:34:53]: Same point. It doesn't matter. It's message passing and interrupts, message passing and interrupts.Swyx [00:35:00]: So you're arguing there should be something better and more structured than Slack?Jake [00:35:04]: Yeah. For sure. I think Slack is awful, and Discord is awful too.Central Station: Context Routing, Support, and Incident ClustersSwyx [00:35:09]: This is the equivalent of my mom test. What have you done that has your solution to this?Jake [00:35:15]: Internally, we've built a tool called Central Station that aggregates all the context from our users. Every piece of feedback, every customer support item, everything gets aggregated into clusters. If an incident is brewing, we can determine how many users are affected and break off a discussion based on that.Jake [00:35:40]: That is more helpful than long-running channels where you're trying to decide which channel to put something in. If you can dynamically aggregate information and dynamically route it to the right person based on context, it works better. We know internally that these four people are close to networking. If we see a networking thing, we can drill it down to those four people. If it's with this part, we can look at the commits. This is no longer a manual process internally.Jake [00:36:13]: If you go to station or help.railway.com, that's why we built it. We wanted to scale with a massive amount of leverage by aggregating feedback.Swyx [00:36:27]: This is built in-house?Jake [00:36:28]: Yep.Swyx [00:36:29]: I remember helping out on this one with Angelo in 2023. You scale a lot with a very small team.Jake [00:36:38]: Yeah. We're about 10 times bigger now.Swyx [00:36:40]: You have your full developer code here? Very cool.Jake [00:36:44]: If you go to railway.com/stats, we expose this as a pub-sub-able thing. It's all real-time metrics. There's a way to get it as JSON somewhere if you care.Jake [00:37:01]: We're big on trying to build everything in public and talk about what we're working on. We've had issues in the past, and we'll say, “Here's how we're fixing these things.” We've gotten compliments and flak for incident reports. We're always trying to make them better and talk with people.Incidents, Disclosure, and Progressive RolloutsSwyx [00:37:20]: You had a big one recently. I liked that it was scoped to 3,000. You presumably used Central Station. Talk through what happened and how you address it internally as a team.Jake [00:37:38]: Internally, this one really sucked. It had to do with an upstream provider that didn't do the behavior it said it documented, which is unfortunate given they wrote the RFC for how the behavior should work. We rolled those things out, and Central Station caught it initially when a couple users said caches weren't invalidating. We turned it off immediately.Jake [00:38:03]: When you roll out to a large user base of three million people, you get a lot of disparate behaviors. We tested in staging and had tests, but we hit an edge case. We've hardened those systems, and now we can make that better. But it was a tough one.Swyx [00:38:39]: I always wonder how private disclosure is supposed to work if people find an issue. Are they supposed to contact you first? When you run a platform, these things will happen. What channels should people pursue to quietly resolve it before it becomes a bigger incident?Jake [00:38:59]: There's responsible disclosure. We err on the side of over-disclosing and letting you know something is wrong versus having your provider gaslight you. We've erred on sharing those things more publicly, even if they impact a small subset of users. That's a decision we've made internally. We have four values. One is honor. The honorable thing is to notify people to the widest degree at which they may have been affected or there was an issue, and then confront it head-on: why did it happen, what can we do better?Swyx [00:39:45]: Not the whole user base. That's because of incremental rollouts and other things?Jake [00:39:50]: Yeah. Progressive rollouts.Swyx [00:39:54]: That should be the norm at all large platforms.Jake [00:39:58]: It should. A variety of companies do this. There's the quote that Meta runs 10,000 different versions of Meta. To our earlier point about agents, they need the same thing. They need shadow traffic and all these other things. We've built so much ceremony around production being sacred that we need to make it trivially easy to test different behaviors in a safe environment. Then you can make mistakes in a safe environment.Safe AI SRE: Customer Agents, Forked Environments, and Production ParityAlessio [00:40:30]: Do you see a world where these things get automatically caught, not necessarily by your agent, but by your customer's agent? The cache invalidation issue seems easy to check if you know to look for it.Jake [00:40:44]: It's hard because to determine it, we almost need to hook into your observability infrastructure. That's why we have the template loop on the platform: so you can roll things out progressively. You can roll out to Johnny Vibe Coder initially, or push a shard that someone consumes at their own leisure. Or you can roll it out over weeks: 0.1% of people, 1% of people, early adopters, then all the way up. That's the non-deterministic version control we talked about earlier.Jake [00:41:30]: I believe that's where most things should go, because most companies end up building staged rollout systems in-house. It's the same thing built again and again at every company. There's a massive opportunity to consolidate developer debt.Alessio [00:41:45]: You should have a free tier. Model providers give free tokens if you let them use the data. You could give free compute if someone is the number-one shard that goes out and lets you plug into their observability.Jake [00:41:55]: We do that. That's why we talked about the impact on 3,000 people. We start with lower-impact people. Larger companies on the platform are last to receive those rollouts so they have a version of the platform that's deeply stable.Alessio [00:42:16]: I have three services, so I'm sure I get the first rollout. You can nuke my thing at any time. There are all these SRE agent companies. Observability people also want agents that fix upstream problems. You have your own agent in the canvas now. How do you see that playing out?Jake [00:42:39]: It's the stacking entropy problem. If you don't have primitives to make iteration in production safe, it becomes difficult. If you're an observability provider saying, “Here's the fix to this error,” assume 80% are good and make sense. But in the last 20% long tail of complex issues, if you let somebody stamp it, you create an opportunity for an incident.Jake [00:43:08]: That's why forked environments are important. People have staging, but it always drifts from production. You need primitives, workflows, and experience built first-party on the platform so you can fork any service at any point in time.Jake [00:43:33]: I think of the canvas as a sheet of transparency paper. The agent is a little guy you push up into the canvas. It should say, “I need to copy that service and that service so I can test these two things.” It gets a read-only copy of production. Anything that's PII gets marked as a transform when we clone the database, create a copy-on-write version, or read from it. Then the agent makes changes and asks, “Does this actually work?” as close to production as possible.Jake [00:44:22]: That's how close you have to be, or you get massive drift. The system becomes unstable. You see this with massive systems built on Docker for local, Kubernetes for production, and a specific thing for something else. That complexity slows developers and becomes unstable at scale, making it hard to iterate. We want to compress that way down and say, “As close to prod as possible is where we want to be.”From AISRE Skeptic to Agent BelieverSwyx [00:45:00]: I was texting Erica for questions, and she says you were originally not a believer in AISRE. Have you come around on it?Jake [00:45:10]: I flipped, but I'm still not a believer in AISRE if you don't have the primitives to make it safe. If you unleash AISRE on production infrastructure without safe primitives for copying volumes and making sure things are fine, it's going to nuke your production database. It's not a matter of if, but when. I'm a big believer in making those loops safe.Jake [00:45:33]: I was a deep AI skeptic until 2023. In 2024, I thought, “Maybe I can roughly make this thing do it.” In 2025, I thought, “Now I can hold this.” Over winter break, everybody came back saying, “It's almost impossible to hold this.”Swyx [00:46:01]: Did you see this on the Claude docs? CloudBot? OpenCloud?Jake [00:46:06]: It's gotten to a point where it's harder to hold it wrong than to hold it right. There's a scene in Avengers where Vision picks up Thor's hammer and says it's terribly well-balanced. It self-balances and works well. I'm a deep believer at this point that this will be the dominant species: assembly, C, C++, JavaScript, words.Swyx [00:46:35]: It feels like a big jump.Jake [00:46:37]: It is. But it's not like you abandon CPU-based discrete logic and move straight to fuzzy logic. You need both. Your skills should call code or applications or some static structure. You can use skills to distill what the procedure should be or how the code should act.Jake [00:47:02]: I'm coming to a thesis: you need three points. You need a clear spec defining the system, the code, and the tests. When you say it out loud, if you've been in engineering long enough, you're like, “Of course. That's an RFC, tests, and code.” But they all matter. Having them together lets them reinforce each other: the spec and tests match, but the code doesn't, so reconcile it. Or the tests and code match but the spec doesn't, so reconcile that. That's the iteration loop.Jake [00:47:41]: That's why you're seeing people talk about software factories, docs, and reconciliation. Some of that is architectural astronomy if you don't implement it, but that loop is where most things will end up.Swyx [00:48:07]: For listeners, we've been talking about this on the pod for three years: the holy trinity of specs and tests. Itamar Friedman from Qodo is the reference if people want to look it up.Self-Modifying Infrastructure and the End of Push-Pull-RebuildSwyx [00:48:18]: One thing I want to mention on the OpenCloud idea is self-modification. I don't know how Railway would support it, but I have my OpenClaw, and I just tell it it has the Railway CLI and can do whatever. In theory, whatever capabilities or new infra it needs, it can call the Railway CLI, provision it, and add it to itself. The agent can modify its own infra.Jake [00:48:45]: It's nuts. I have a loop set up where you put the Railway CLI on top of something that runs on Railway. You're authenticated as whatever the current box is, and you can make any changes to it. Then you call Railway deploy, and it deploys itself.Jake [00:49:04]: It's like: “I need to spin up this instance of this environment. I already exist in this environment. Excellent, I have access to a Postgres instance now.” That's where we want to go with agentic, self-replicating infrastructure. That's your loop: iterate in production. You continue making changes. If it works, merge it upstream. If it doesn't, throw it away.Jake [00:49:37]: How do you make throwaway copies trivial to spin up and super cheap? The era of “I have an AWS instance with four vCPU and 16 gigs of RAM” is going to get destroyed. If you do that for agents, you need a thousand of those machines. It's prohibitively expensive compared with what we've spent a ton of time figuring out: the atomic unit of deploy, whether you call it isolates, sandboxes, or something else. Only pay for what you use, spin up instantaneously, and close the loop as quickly as possible.Jake [00:50:15]: If the system can self-replicate safely and say, “This is my environment, I'm making these changes,” it can come back with, “Does this look good? This is a new state of infrastructure given this prompt. I think I've solved it.” Then you go back and say, “Actually, it looks different.” It does the loop again. Then you say, “Cool. Apply.”Swyx [00:50:38]: That's retroactively obvious, which is the most useful kind. Any other comments on agent deployment on Railway?Jake [00:50:51]: It's getting better every day. I'm on X or Twitter. You can always yell at me about the parts not working as well as they should, because plenty of things should work way better.The New Serverless: Stateful, Long-Running, Pay-for-What-You-Use LinuxSwyx [00:51:04]: At this stage, when people want massively or embarrassingly parallel compute, they usually talk serverless. I feel like there's a new serverless compared to the previous five years of serverless. You're in that new bucket. Do you have comparisons or philosophical differences you want to call out?Jake [00:51:31]: It's somewhere in between. It's the ability to run stateful, long-running workflows or executions.Swyx [00:51:42]: Vercel has Fluid Compute, Cloudflare has some container thing, Google has App Runner and others.Jake [00:51:55]: That's where everything is roughly going, and it's why we've been working on this for six years. We believe users need access to a computer: a box that speaks Linux. They need to deploy what they want. Other systems change the surface area of what you can build. For us, users need a computer and need to deploy anything they truly want. That's why we've focused on the primitives: network, compute, storage. If we give you those and expose them so you can run things indefinitely, that's where we believe it's going.Jake [00:52:43]: Twitter has no nuance, so everyone says “servers” or “serverless.” It's always somewhere in the middle: I want to run it for a long time, but I don't want to provision the resource statically or pay for things I'm not using. That's been our thesis from day one: pay only for what you use, run it indefinitely, and it is full Linux.Swyx [00:53:12]: That's why I like the naming of Fluid. It's fluid. Flexible.Heroku, Focus, and Carrying the Torch Without Becoming the PastSwyx [00:53:18]: Another milestone is the Heroku official deprecation. You're one of the presumptive new Herokus. “New Heroku” has been a category for as long as I've been in developer tooling. It's finally happening. What was that like? Any behind-the-scenes of, “This is the moment”?Jake [00:53:42]: You have people where you're like, “You were running stuff on here? You, as this company?” It's crazy that names you would know are running on it and now coming to us saying, “We want to move a lot of this off.”Swyx [00:54:00]: Any behind-the-scenes on why Salesforce let Heroku stagnate?Jake [00:54:05]: I can only guess. It's hard when it's not your business. Salesforce's business is to build a great CRM. That's their focus. Then you acquire a compute business as an offshoot. A lot of early Meta people talk about focus. Boz has a write-up about how in the early days of Meta they had no money, so they were forced to focus. Then they turned on the money tree and had no reason not to split their focus.Jake [00:54:52]: But that dilutes your product. You get offshoots where you ask, “Is this the focus of the business?” If it's not core, it languishes. A lot of companies get in trouble when they split focus because they're fighting a multi-front war, not just externally but internally for alignment. Where are we going? What are we doing? What is our purpose?Jake [00:55:24]: If you're Salesforce-built and mission-driven, you want to work on Salesforce. Heroku is off to the side. It's not core to the business. Getting resources, budget, focus, and alignment internally becomes hard. It was a matter of time.Swyx [00:56:06]: Kudos for them to call it out instead of leaving it unknown.Jake [00:56:12]: Their release was a little odd. They called it out, but they didn't say they were shutting it down. Behind the scenes, I think they issued messages to people saying they should close accounts and that they were going to deprecate and remove things over time.Jake [00:56:30]: It's crazy because some of my first deployment experiences were on Heroku. You start with dragging things into an FTP server, then you try to get a deploy working, and then it's Heroku. It was the on-ramp for us. But the wheel turns. New things emerge. We're happy to carry the torch for a lot of that. But we don't want to be the new Heroku. We want to be the way people build and deploy software, and ultimately the way people monetize software over time.Swyx [00:57:19]: It's still a big crown to be the new Heroku. There are 50 companies that fought for that.Jake [00:57:23]: Everybody is holding some portion of it. We're happy to support people and companies. The platform works differently. The game loop is similar, but we've been dogmatic about where these things are going: primitives, agents, fan-out. Some things fit; some workflows need to change. We have an approximation of Heroku pipelines with the environment system. It's exciting. We've got a ton of people we can support, and it's growing a lot.Temporal, Workflow Engines, and State MachinesSwyx [00:58:12]: I have one more technical question about Temporal. I've sold my shares. You're a power user and one of our earliest customers. I met you through Temporal. You built on Temporal. You have complaints. This may be the most neutral and informed conversation anyone will hear about Temporal without someone working at the company.Jake [00:58:39]: That's fair. I've used Temporal for almost 10 years because of Cadence at Uber.Swyx [00:58:52]: Give people a sense of what Cadence was at Uber.Jake [00:58:57]: Cadence was the precursor to Temporal. It powers trip actions, rides, when you rent a Jump bike or scooter or car. You're running workflows for a period of time and saying, “This ride will run indefinitely until it finishes.” You attach information: you paused in this zone, so add this charge to the bill. When you end the trip, the workflow is done. That experience was powered by Cadence at the time.Swyx [00:59:34]: I used to say it's like programming the entire user journey top-down as one function.Jake [00:59:39]: It's a powerful idea and important. It's also important for the next phase of the agentic journey. You want an agent to do a specific task, be complete or incomplete on that task, and move on to the next thing. You need a way to manage workflows dynamically.Jake [00:59:59]: Temporal was always great in theory, and great when you got it working the way you wanted in production. But it required you to model the entire journey in your head. If you didn't, you could cause issues where replaying the state of the workflow causes non-determinism.Swyx [01:00:25]: Because it works on deterministic workflow history.Jake [01:00:28]: Exactly. I describe it as a jet engine. If you know how to operate it and run it, it's great. But you can't hand it to people trying to build complicated things if they don't have the whole state in their head.Jake [01:00:48]: We run our whole deployment pipeline on top of it. That's a reasonably complicated workflow: pre-commit hooks, signaling, queuing, and all the rest. We ran into the same thing at Uber. As you express a large workflow, it gets more complicated, with more states in the state machine that you have to map back to the workflow.Swyx [01:01:15]: It's a lot of ifs.Jake [01:01:16]: Exactly. At Uber, we built a system for doing the state machine and testing it. We've started to build some of those things here because it's grown heavily. It's not quite love-hate. When it works well, it works super well. But if someone who doesn't have full context puts something into the system that invalidates state or causes non-determinism, or spins off a ton of activities, you have to keep track of underlying SRE knobs like activity slots. Those should scale with memory, vCPU, and so on. It becomes a bear to scale.Swyx [01:02:10]: You need a capable sysadmin running things behind the scenes. If you moved off, what would you do?Jake [01:02:19]: We'd build our own workflow engine. We have a few internally that we've worked on.Swyx [01:02:27]: This is one of those classes of things you typically wouldn't vibe code, but I'm wondering if you can.Jake [01:02:33]: I still don't think you should vibe code it. You still want to run decent tests to make sure it works.Swyx [01:02:39]: Timo didn't invent that from scratch either. There are libraries you can run. On top of that, it's just a state machine that you have to map out. Ultimately, you define the instructions you want and run them through a state machine.Jake [01:03:00]: It's very doable. Workflow stuff is interesting. Restate is doing neat stuff here.Swyx [01:03:10]: You're tied into JavaScript. Are you a JavaScript maxi?Jake [01:03:13]: Internally, we have TypeScript, Rust, and Go. We don't add more languages. Actually, we have a little C because we write BPF code and hooks. But those are the languages.Swyx [01:03:28]: Is this for sidecars?Jake [01:03:32]: No. It's for the networking stack, volumes, and things like that. We use TypeScript a lot because it powers the dashboard, but we're moving a lot of workflow stuff off the dashboard stack and into the infrastructure stack.Railpack, Nixpacks, and Content-Addressable FilesystemsSwyx [01:04:00]: Cool. Any other technical infrastructure stuff? Railpacks?Jake [01:04:07]: We built an engine for determining dependencies based on source code. It's called Railpack. We built the first version, Nixpacks, on top of Nix, and then we moved.Swyx [01:04:17]: People have been trying to get me to adopt Nix and NixOS for four years. Is it ever going to be a thing?Jake [01:04:23]: I don't know. We're excited about it, but it has pain points. Think of it as a stack of versioned binaries at specific slices in time. If you want version X and version Y, you bloat the package space, which blows up image size and makes real-world workloads difficult.Swyx [01:04:53]: But you content-address it and cache it. In theory, there are optimizations.Jake [01:05:00]: In theory, yes. But with a large enough user base and disparate enough machines, you run into a problem Meta described in the XFAAS paper, their internal serverless system. It becomes difficult at scale unless you break out specific runtimes.Jake [01:05:24]: We didn't want to do that because we wanted to truly allow you to deploy anything. That was our initial thing with Nix. But we've moved toward interesting work around content-addressable file systems that can lazy-load anything from any point and page it into memory.Swyx [01:05:48]: Amazing.Jake [01:05:49]: The future is very bright. It's crazy, and it's going to be nuts.Coding Agent Spend, Roadmaps, and Token ROISwyx [01:05:54]: Founder journey stuff?Alessio [01:05:56]: Your cloud usage: you tweeted you're going to spend $300K this month?Jake [01:06:01]: I think we got to $200K.Alessio [01:06:02]: Coding agents?Jake [01:06:03]: Yeah.Swyx [01:06:04]: Across the company?Alessio [01:06:05]: You only have 35 people, so I'm sure they're not all spending $10K a month. What's the distribution?Jake [01:06:10]: I think I'm at about $25K. We have power users all the way down. We came back from winter break, and I basically said, “If you're writing code by hand, you're doing this wrong.” The tools are good enough now that you can move extremely quickly. There are issues and pain points, but you should be reviewing the code you are writing instead of writing it by hand.Jake [01:06:40]: Architectural patterns matter more now than ever, but you shouldn't spend your time generating code you would write. If you know how to write it, ask the agent to write it and reconcile it until it looks like you would have written it yourself.Jake [01:06:58]: People misconstrue my propensity to push people toward agents as connected to our growth and some reliability bumps. They're not necessarily related. The tools are good enough to move extremely quickly and build things way larger than you could before.Jake [01:07:19]: To the earlier point about cooling data centers in space: I don't know. But with software, you can ask, “How would I build block storage from scratch? How would I do these things?” I have ideas because I have history and have read papers. Let me work them out and build massive test benches with thousands of tests, because those are now free to author. If you're not using AI systems to speed-run your roadmap and reconcile your existing system onto the future, you're missing a large point of what's happening.Alessio [01:08:12]: What's the path to spending $3 million a month? Is it bound by ideas and things customers can absorb?Jake [01:08:19]: For most companies, it's bound by deployment at this point. That's why we've seen a massive boom in users and companies, from Fortune 50s down, asking how to get developers to move faster. You'll probably hit your CFO before any technical limits because they'll look at the eye-watering amount of money spent on tokens. Inference costs have to come down, but we're inference constrained now. There will be price discovery around what makes sense for an org to adopt.Jake [01:09:06]: I think you'll end up with the F1 driver concept. If someone is really adept at these things, it makes sense to put them in a $3 million car. If they're not, it probably doesn't make sense. You'll take a few people and say, “You can drive the F1 car. We need to go in this direction. Figure out if it works and prototype it.”Jake [01:09:33]: We've done some of that and vastly accelerated our roadmap. We thought we'd ship something in a few years; now we can probably ship it in a few months because we validated it and don't have to build it incrementally. We can skip steps and move toward our vision.Alessio [01:09:58]: A lot of people are realizing the roadmap doesn't always have a business impact, so they say tokens are too expensive. But if your roadmap were built to make more money by the time you built it, you'd have token pricing for it, the same way you do with sales. You'd spend a billion dollars on sales if you knew you would get $2 billion of revenue.Jake [01:10:19]: Exactly. A naive way to measure this is the percentage of tokens that end up in production. If you can measure impact because those tokens end up in production, that's awesome. But the burden of proof will rise. Internally, we have a growing number of pull requests that haven't merged. The question becomes: how do you get this into production? It's about how quickly you can build and deploy software, which is exciting because that's our whole thing.The SDLC Shift: Prompt Requests, Feature Flags, and Safe RolloutsSwyx [01:10:56]: The SDLC is changing. One thesis is that the pull request is dying. It's going to be the prompt request. Beyond that, code review is also kind of dying if you have all the other systems in place. What else is changing about the SDLC?Jake [01:11:19]: The AISRE and the tools to make it happen. AISRE is pie-in-the-sky aspirational. What does it take to get an AISRE? What tools do you need to build?Swyx [01:11:32]: You should expose your tooling to customers at some point. The Central Station command center.Jake [01:11:39]: We have it for template maintainers. Template maintainers can deploy and maintain templates, and they get feedback. We're going to expose those things incrementally.Swyx [01:11:51]: Clustering around incidents. Everyone has a version of that, but I don't think anyone has solved it.Jake [01:11:56]: I won't say we've solved it internally, but it's gotten so good that we can see incidents forming pretty quickly. At some point, those will be things either someone else builds or we build. We've always built things purpose-built for us. If it makes sense to make it useful for users, monetize it, or turn that loop into a profit center instead of a cost center, we want to do that.Jake [01:12:28]: Pull request is definitely dying.Swyx [01:12:29]: Do you do first-party feature flagging and incremental rollout stuff?Jake [01:12:34]: We have a feature-flagging engine we built internally and will eventually roll out.Swyx [01:12:38]: I don't see it as a user. How come you didn't give us what you have?Jake [01:12:43]: We have to beta test it. We care a lot about the quality of the things. There's plenty we've used internally that doesn't make it all the way through the journey because it fails. It works for one service but not multiple services. We'd have to build it for multiple services and know that if we released it, we'd rebuild it again and again. Some things are worth that, but many inform the roadmap.Jake [01:13:18]: We don't want to dilute the experience by saying, “This works, but only for this service,” unless it's a core initiative. Over the next few months, we'll roll out things that work for a single service, then multiple services, then multiple services across the environment. You have to be deliberate. Otherwise you create broken disparate experiences and support load because people ask how to use the feature.Jake [01:13:52]: It's the earlier expansion and compaction pattern. You expand the company to get features, then compact and smooth them out so the experience is stellar. You told me in the hallway, “It's gotten so much better.” Internally we're saying, “This part really sucks. We need to make it significantly better.”Swyx [01:14:11]: I can attest to that over the last three years watching you build Railway. For listeners, feature flagging is a huge part of Uber culture. So much so that they have too many feature flags and another thing to remove feature flags. Facebook has Gatekeeper. Agents are going to need this. It's fundamental to incremental rollouts. OpenAI acquired Statsig. GPT-5 is routing and flagging through different models.Jake [01:14:56]: It's super important. If the software development lifecycle is going to change because we're doing things 1,000 times faster and 1,000 times more concurrently, what becomes important at scale?Jake [01:15:16]: Before I started Railway, I built a feature-flagging product and tried to sell it. It was an easier version of LaunchDarkly. I ran into a problem: anyone small enough to adopt your technology doesn't care about feature flags, and anyone large enough to need feature flags needs so much scale that you have to build out all the infrastructure. I scrapped it.Jake [01:15:42]: But what is old is new again. Companies are trying to move quickly, but you can't YOLO a vibe-coded thing straight into production. You need to say, “Here's my blast radius, my impact, and I want to shadow it for these users.” Feature flags. You're going to need the tools larger companies built to maintain their structures. Everything gets compressed by 1,000x so everybody can build those structures quickly.Jake [01:16:07]: That's exactly where we are: compressing the software development lifecycle, then expanding it and adding more new things.Cattle, Pets, and Clonable InfrastructureSwyx [01:16:15]: Another term that comes to mind for newer developers is “cattle, not pets.” People treat production like a pet. It has a name. You baby it and keep it alive. With cattle, you can mass farm, roll out, portion parts out, and kill them.Jake [01:16:37]: I think that might change. You can move toward having pets as long as you have a cloning machine for your pets.Swyx [01:16:52]: Yeah.Jake [01:16:52]: If you can snapshot every single thing at every frame, it doesn't matter if something gets obliterated because you have a snapshot of it. The things we've built right now are designed to block changes from the hermetically sealed DevOps line. You have to write a Dockerfile because you nee

In this episode, Ray Cochrane breaks down a reversible conductive glue from Newcastle University that could replace solder and finally make electronics recycling work. Additional stories cover China widening its clean energy lead, DeepMind’s AlphaEvolve scoring wins from genomics to Google’s database, Anthropic’s $200 million partnership with the Gates Foundation, Intel teaming up with McLaren Racing, and end-to-end encrypted RCS rolling out in beta. – Want to start a podcast? Its easy to get started! Sign-up at Blubrry – Thinking of buying a Starlink? Use my link to support the show. Subscribe to the Newsletter. Email Ray if you want to get in touch! Like and Follow Geek News Central’s Facebook Page. Support my Show Sponsor: Best Godaddy Promo Codes Get 1Password Full Summary Cochrane opens the show with a deep dive into Newcastle University’s reversible conductive glue, a water-based adhesive that could finally make electronics recycling economically viable. He frames the e-waste problem first: 62 billion kilos a year, with less than a quarter ever recycled. Then he walks through the silver nanoparticle chemistry, the lead-free angle on traditional solder, and the geopolitical stakes of critical mineral recovery. From there the episode pivots through energy, AI, hardware, open source, data research, space, science, and consumer privacy. A Reversible Conductive Glue That Could Replace Solder A team at Newcastle University has developed a water-based glue that conducts electricity well enough to replace solder. Unlike solder, however, the glue releases cleanly with a quick rinse of acetone or an alkaline bath. The breakthrough relies on silver nanoparticles suspended in a water-based binder. Consequently, components can be recovered intact, opening a viable path to electronics recycling at scale. Co-investigator Volker Pickert framed the second prize directly: solder has the best conductivity, but the best formulations contain lead. China Widens Its Clean Energy Lead A new Atlas Public Policy report shows Chinese firms accounted for 55 percent of $1.1 trillion in global clean energy manufacturing investment between 2019 and 2025. Battery manufacturing alone pulled in nearly half of that money. Meanwhile, U.S. companies have actively retreated from those same industries. With the Strait of Hormuz currently closed, supply chain ownership in solar, wind, and batteries matters more than ever. A separate Ember analysis showed Chinese solar panel exports doubled in March alone. DeepMind’s AlphaEvolve Scores Real Wins DeepMind published an update on AlphaEvolve, its Gemini-powered AI coding agent. The system cut genomic variant detection errors by 30 percent. Additionally, it lifted AC Optimal Power Flow feasibility from 14 to over 88 percent on the electrical grid. AlphaEvolve also found a better cache replacement policy in two days that would have taken human engineers months. Furthermore, it reduced write amplification in Google’s Spanner database by 20 percent. The pattern shows applied AI sticking, not as a chatbot but as a quiet optimizer. Anthropic and Gates Foundation Commit $200 Million Anthropic announced a four-year, $200 million partnership with the Gates Foundation across three pillars. The biggest pillar targets global health and life sciences in low and middle-income countries. Notably, the research scope includes polio, HPV, and preeclampsia. A second pillar covers AI in education across the U.S., sub-Saharan Africa, and India, in partnership with the Global AI for Learning Alliance. Finally, an economic mobility pillar focuses on agricultural productivity and crop benchmarks. Google’s AI Educator Series Launches Free Google rolled out the first 20-plus sessions of its AI Educator Series this week. The free AI literacy training targets the roughly 6 million K-12 and higher education teachers across the U.S. Modules are designed as short, snackable trainings teachers can finish in a prep period or a lunch break. Additionally, stackable workshops let educators build credentials over time. Importantly, the program requires no institutional subscription. Amazon Bedrock Prompt Optimization Goes GA Amazon Bedrock dropped its Advanced Prompt Optimization tool, now generally available across most major regions. The feature rewrites prompts to perform better on specific models and automates prompt migration when switching between models. Furthermore, a built-in evaluation feedback loop lets users benchmark against up to five models side by side. The default judge model is Claude Sonnet 4.6. Consequently, teams can stop hand-tuning string templates and focus on product work. Sponsor: GoDaddy Economy hosting $6.99/month, WordPress hosting $12.99/month, domains $11.99. Website builder trial available. Use codes at geeknewscentral.com/godaddy to support the show. Arm AGI CPU and Red Hat Go Production-Ready on Agentic AI Arm and Red Hat expanded their collaboration around Arm’s AGI CPU, which is Arm’s branding for its agentic AI chip family. The deal brings Red Hat Enterprise Linux and OpenShift to the chip as a production-ready stack. Hardware specifications include 136 Neoverse V3 cores, 96 PCIe Gen6 lanes, and 12 channels of DDR5-8800 memory in a 300-watt thermal envelope. Availability lands in Q4 through Supermicro, Lenovo, and ASRock Rack. Intel Becomes McLaren Racing’s Official Compute Partner Intel announced a multi-year deal as the official compute partner for McLaren Racing. The agreement covers the McLaren Mastercard Formula 1 team, Arrow McLaren IndyCar, and McLaren F1 Sim Racing. Trackside edge compute will power real-time race decisions, while Xeon and Core Ultra silicon drive Computational Fluid Dynamics and digital twin work. Consequently, design iterations that once took weeks now collapse to days. The deal puts Intel silicon in front of every CTO watching a Grand Prix. Rust Lands 13 Google Summer of Code Projects The Rust Project landed 13 accepted projects in Google Summer of Code 2026. Out of 96 proposals, a 50 percent jump from last year, the project selected 13. Notably, three returning contributors from prior years are back. Mentors flagged a noticeable share of AI-generated submissions as a growing challenge. Furthermore, the real bottleneck remains mentor capacity rather than funding. GitHub Innovation Graph Maps Digital Complexity Researchers used GitHub Innovation Graph data to predict GDP, inequality, and emissions through the Economic Complexity Index, or ECI. Countries are compared to kitchens; the more variety and sophistication in software output, the higher the score. Germany ranks first, followed by Australia and Canada. The U.S. lands at sixth. However, the dataset only captures public GitHub activity, leaving most proprietary software invisible. NASA and Eta Space Prepare Cryogenic Fuel Demo NASA is teaming with Eta Space on an in-orbit demonstration called LOXSAT, short for Liquid Oxygen Flight Demonstration. The nine-month mission tests cryogenic fluid management techniques required for in-space propellant depots. Launch is no earlier than July 17 aboard a Rocket Lab Electron from the Mahia Peninsula in New Zealand. Successful refueling in orbit could reshape what is possible for deep-space missions to the Moon and Mars. Stealth Magma Surge Under São Jorge Surprises Researchers Researchers in the UK and Spain published in Nature Communications on a 2022 magma surge under São Jorge Island in the Azores. The surge climbed from more than 20 kilometers underground to 1.6 kilometers below the surface. Surprisingly, most of the thousands of earthquakes happened after the magma stalled, not during the climb. Consequently, scientists are calling it a stealth surge and a failed eruption. A primed magma chamber now sits closer to the surface than before. End-to-End Encrypted RCS Begins Rolling Out Apple and Google led a cross-industry effort to roll out end-to-end encryption for RCS messaging. As of May 11, the feature is rolling out in beta on both platforms. Importantly, encryption is on by default and auto-applies to new and existing conversations. A lock icon in the chat indicates active end-to-end encryption. This quietly raises baseline privacy for billions of cross-platform messages. Cochrane signs off with the usual ecosystem mentions: GNC Insider at geeknewscentral.com/insider, the show newsletter, and modern podcast app recommendations at podcastapps.com. The post A Reversible Glue that could Replace Solder #1865 appeared first on Geek News Central.

Unser Partner Scalable Capital ist der einzige Broker, den deine Familie zum Traden braucht. Bei Scalable Capital gibt's nämlich auch Kinderdepots. Alle weiteren Infos gibt's hier: scalable.capital/oaws. Iran-Deal-Hoffnung treibt Airlines und Touristik. Nvidia steckt 500 Mio. $ in Glasfaser-Firma Corning. AMD und Super Micro springen 15%. Samsung knackt 1 Bio. $. Disney+ erstmals zweistellig profitabel. Uber wächst so schnell wie seit 2022 nicht. Novo erholt sich weiter. Über 50% operative Marge und Kurs verzehnfacht in zehn Jahren. Keyence (WKN: 874827) baut Sensoren für Fabrikautomatisierung und ist dabei profitabler als Apple. Jetzt kommt der erste Aktienrückkauf ever. Hyperliquid ist die Krypto-Success-Story der letzten zwei Jahre. 900 Mio. Umsatz mit 15 Leuten. Jetzt kommen Aktien, Rohstoffe und Pre-IPO-Märkte dazu. Julius Nagel erklärt was dahintersteckt. Diesen Podcast vom 07.05.2026, 3:00 Uhr stellt dir die Podstars GmbH (Noah Leidinger) zur Verfügung. Learn more about your ad choices. Visit megaphone.fm/adchoices

7/5 Usa-Iran, accordo più vicino? Trump: Epic Fury verso la fine se Iran accetterà accordo con riapertura Hormuz. Altrimenti bombarderà di nuovo. NBC: Project Freedom fermata dopo che AS e Kuwait hanno sospeso acceso  alle basi americane e spazio aereo. Brent e Wti (sotto 100$)stabili dopo forti cali della vigilia. 14 minuti prima dell'annuncio di Axios aperta una posizione short sul petrolio da 920milioni di dollari. Dollaro e rendimento Treasury in calo. Su oro e argento, Bitcoin debole. Le trimestrali spingono un rally epico dei chip: aria di bolla? L'indice dei semiconduttori segna +64% da inizio anno. Nuovi record storici per: Intel, AMD, Broadcom, Micron, Sandisk. Super Micro vola del 24%. Nvidia miglior seduta in un mese su accordo Corning. ARM batte le attese, prevede vendite raddoppiate per le nuove CPUs. In after market passa da +12% a -6%: non ha ancora assicurato le forniture. Anthropic: accordo con SpaceX per 300megawatt potenza computazionale e datacenter nello spazio. Amodei: cresciamo a un ritmo di 80 volte superiore alle attese.  *** Questo episodio è offerto da Scalable Capital   Investire comporta rischi  Interesse p.a. lordo variabile su liquidità illimitata. Condizioni e distribuzione della liquidità su scalable.capital/conto-deposito-non-vincolato*** In Asia: Nikkei record sale del 6% e supera 62.000 per la prima volta (Softbank +18%). Yen, aria di intervento: settimana prossima Bessent incontra Takaichi e Ueda. Kospi ha superato anche il Canada: adesso è la settima borsa globale. WSJ: dialogo tra Washington e Pechino su guardrail AI per rischio crisi. Deepseek verso valutazione 45 mld di dollari. In Europa futures in verde. Milano punta ai 50mila. Leonardo batte le attese. L'eredità Cingolani: la capitalizzazione è passata da 4,6 a 34 miliardi. Focus su Campari e Tim dopo i conti.  Learn more about your ad choices. Visit megaphone.fm/adchoices

Super Micro Computer es la protagonista de nuestro Radar de hoy. La firma tecnológica, al igual que AMD, publicó sus resultados tras el cierre del mercado y sus acciones se dispararon cerca de un 20% en el mercado fuera de hora. Entre las cifras más destacadas sobresale el rendimiento de su negocio de centros de datos, junto con unos ingresos que crecieron un 123% interanual, superando los 10.000 millones de dólares. Aunque los ingresos quedaron ligeramente por debajo de lo previsto, su consejero delegado, Charles Liang, atribuyó este desfase a la “falta de preparación de los clientes”, lo que habría retrasado el reconocimiento de ingresos durante el trimestre. En contraste, el beneficio por acción alcanzó los 84 centavos, superando en 22 centavos las previsiones del mercado. Además, la empresa anticipa unas ganancias ajustadas por acción de entre 65 y 79 centavos, con ingresos estimados entre 11.000 y 12.500 millones de dólares, también por encima del consenso. La compañía también informó de un margen bruto del 10,1%, superando claramente el 6,75% esperado por los analistas. Liang subrayó la solidez de los resultados, en especial del área de centros de datos, que según sus previsiones podría representar el 25% de los beneficios en los próximos años. Sin embargo, no todo ha sido positivo en torno a la empresa en los últimos meses, ya que han surgido controversias legales que han afectado su cotización. En concreto, la Fiscalía del Distrito Sur de Nueva York implicó a varios socios de la empresa en un presunto desvío ilegal de servidores con tecnología de Nvidia hacia China. Entre los implicados estaría el cofundador Yih-Shyan "Wally" Liam, quien posteriormente dimitió. A pesar del impacto inicial, que provocó una caída del 33% en bolsa, la empresa asegura mantener la confianza de sus clientes y prevé alcanzar ingresos de hasta 40.000 millones en 2026, reforzando su apuesta por la inteligencia artificial con nuevas instalaciones en Silicon Valley.

Die Wall Street startet nach der gestrigen Rally schwächer in den Tag, belastet durch steigende Ölpreise und geopolitische Unsicherheiten , während die Berichtssaison eine klare Sektor-Rotation zeigt: Halbleiter bleiben das Zugpferd mit starken Zahlen und angehobenen Ausblicken bei Unternehmen wie Texas Instruments und Lam Research, getragen vom anhaltenden AI-Boom, allerdings mehren sich nach der außergewöhnlich starken Rally Überhitzungssignale und das Chance-Risiko-Verhältnis verschlechtert sich deutlich ; im Gegensatz dazu steht der Software-Sektor unter Druck, mit Gewinnmitnahmen bei ServiceNow und IBM, wo sich eine leicht schwächere Wachstumsdynamik, Margendruck und durch den Nahost-Konflikt verzögerte Deals bemerkbar machen ; zusätzlich sorgt im AI-Infrastruktur-Bereich die Schwäche von Supermicro für Aufmerksamkeit, nachdem Berichte über einen verlorenen Milliardenauftrag von Oracle sowie hohe Lagerbestände bei älteren GPUs kursieren, was auf eine Verschiebung der Nachfrage hindeutet und die Aktie belastet; auch Tesla steht trotz solider Zahlen unter Druck, da die massiv steigenden Investitionen von über 25 Milliarden Dollar die freien Cashflows belasten und Zweifel nähren, ob das Bewertungsniveau gerechtfertigt ist – insgesamt zeigt sich ein Markt, der zwar weiterhin vom AI-Boom getragen wird, aber zunehmend selektiver wird und erste Ermüdungserscheinungen in den heiß gelaufenen Segmenten signalisiert. Abonniere den Podcast, um keine Folge zu verpassen! ____ Folge uns, um auf dem Laufenden zu bleiben: • X: http://fal.cn/SQtwitter • LinkedIn: http://fal.cn/SQlinkedin • Instagram: http://fal.cn/SQInstagram

Die Wall Street startet nach der gestrigen Rally schwächer in den Tag, belastet durch steigende Ölpreise und geopolitische Unsicherheiten , während die Berichtssaison eine klare Sektor-Rotation zeigt: Halbleiter bleiben das Zugpferd mit starken Zahlen und angehobenen Ausblicken bei Unternehmen wie Texas Instruments und Lam Research, getragen vom anhaltenden AI-Boom, allerdings mehren sich nach der außergewöhnlich starken Rally Überhitzungssignale und das Chance-Risiko-Verhältnis verschlechtert sich deutlich ; im Gegensatz dazu steht der Software-Sektor unter Druck, mit Gewinnmitnahmen bei ServiceNow und IBM, wo sich eine leicht schwächere Wachstumsdynamik, Margendruck und durch den Nahost-Konflikt verzögerte Deals bemerkbar machen ; zusätzlich sorgt im AI-Infrastruktur-Bereich die Schwäche von Supermicro für Aufmerksamkeit, nachdem Berichte über einen verlorenen Milliardenauftrag von Oracle sowie hohe Lagerbestände bei älteren GPUs kursieren, was auf eine Verschiebung der Nachfrage hindeutet und die Aktie belastet; auch Tesla steht trotz solider Zahlen unter Druck, da die massiv steigenden Investitionen von über 25 Milliarden Dollar die freien Cashflows belasten und Zweifel nähren, ob das Bewertungsniveau gerechtfertigt ist – insgesamt zeigt sich ein Markt, der zwar weiterhin vom AI-Boom getragen wird, aber zunehmend selektiver wird und erste Ermüdungserscheinungen in den heiß gelaufenen Segmenten signalisiert. Ein Podcast - featured by Handelsblatt. ► Direkt an der Börse handeln mit tradegate.direct: https://bit.ly/wallstreet_april * ► Erhalte einen exklusiven 15% Rabatt auf Saily eSIM Datentarife! Lade die Saily-App herunter und benutze den Code wallstreet beim Bezahlen: https://saily.com/wallstreet * ► Entdecke den exklusiven NordVPN Deal! Jetzt risikofrei testen mit einer 30-Tage-Geld-zurück-Garantie: https://nordvpn.com/wallstreet * +++ Alle Rabattcodes und Infos zu unseren Werbepartnern findet ihr hier: https://linktr.ee/wallstreet_podcast +++ ► Mehr Einblicke: https://bit.ly/360wallstreetpc * Impressum: https://www.360wallstreet.de/impressum *Werbung

Drie verhalen die laten zien hoe staten en criminelen opereren in het digitale domein. Ronald begint met de meest onhandige GPU-smokkel ooit: drie man opgepakt door het Amerikaanse ministerie van Justitie voor het proberen te verschepen van $170 miljoen aan AI-chips naar China — inclusief een groeps-app genaamd "GPU Partnership" waarin de hoofdverdachte in hoofdletters schreeuwt dat niemand over China mag praten. Vervolgens de $2,5 miljard Supermicro-zaak die de week ervoor speelde. Jelle neemt je mee in Coruna, het iOS-exploitplatform dat voortkomt uit Operation Triangulation. Ooit een van de meest geavanceerde spionagecampagnes ooit, nu ingezet om via nep-crypto-exchanges je wallet leeg te trekken. Marco sluit af met BPFDoor: Chinese hackers die al vijf jaar ongemerkt in de backbone van telecombedrijven zitten en kunnen zien wie je belt en waar je bent. Nieuwtjes - Anthropic Cloud Mythos / Capybara — gelekte conceptdocumenten over nieuw AI-model met sterke cybersecurity-capabilities (vulnerability research, exploit development). Uitrol begint bij verdedigende partijen. Beurzen reageerden met een dip Bronnen GPU-smokkel / exportcontroles - US Department of Justice — "Chinese National and Two U.S. Citizens Charged with Conspiring to Smuggle Artificial Intelligence Technology to China" (25 maart 2026): https://www.justice.gov/opa/pr/chinese-national-and-two-us-citizens-charged-conspiring-smuggle-artificial-intelligence - US Department of Justice — Supermicro co-founder Wally Liaw charged in $2.5B Nvidia GPU smuggling scheme (week voor opname) (https://fortune.com/2026/03/19/supermicro-arrested-founder-smuggling-gpu-china/) - Bureau of Industry & Security (BIS) — exportcontroles op geavanceerde chips: https://www.bis.gov Coruna / Operation Triangulation / DarkSword - Kaspersky / Securelist — "Coruna framework: updated Operation Triangulation exploit" (26 maart 2026): https://securelist.com/coruna-framework-updated-operation-triangulation-exploit/119228/ - BleepingComputer — "Coruna iOS exploit framework linked to Triangulation attacks" (26 maart 2026): https://www.bleepingcomputer.com/news/security/coruna-ios-exploit-framework-linked-to-triangulation-attacks/ - Kaspersky — originele Operation Triangulation disclosure (2023): https://securelist.com/operation-triangulation/109842/ - Kaspersky — "Triangulation: undocumented hardware feature exploited" (december 2023): https://securelist.com/operation-triangulation-the-last-hardware-mystery/111669/ - Apple Security Update — patches voor Coruna en DarkSword: https://support.apple.com/en-us/126776 BPFDoor / Red Menshen / telecominfrastructuur - Rapid7 — Red Menshen BPFDoor research (maart 2026) - Achtergrond BPFDoor — Trend Micro / PwC eerdere analyses (2022-2025) - Salt Typhoon — voor context: Chinese hackers in Amerikaanse telecom (2024-2025) - CISA — "Countering China State Actors Compromise of Networks" joint advisory

Sara Awad from Tech Contrarians explains tech dynamics, geopolitical factors and increased investor scrutiny (0:35) Memory and storage: Micron, AMD, Nvidia, Google update (9:20) Energy through the lens of AI (20:00) Super Micro scandal, China chips (23:10)Show Notes:Tech Tug Of War: Fear Vs. GreedAI, chip stocks jump as Trump hints at ending Iran war within weeksRead our transcriptsFor full access to analyst ratings, stock and ETF quant scores, and dividend grades, subscribe to Seeking Alpha Premium at seekingalpha.com/subscriptions

SUMMARY:  Brian (@bgracely) and Brandon Whichard (@bwhichard, Software Defined Talk and Failover Media) discuss the biggest AI news stories from the month of March, 2026. SHOW: 1014SHOW TRANSCRIPT: The Reasoning Show #1014 TranscriptSHOW VIDEO: https://youtu.be/XwyAC-hxOQYSHOW SPONSORS:VENTION - Ready for expert developers who actually deliver?Visit ventionteams.comSHOW NOTES:Links to all the AI News covered in this months showFEEDBACK?Email: show @ reasoning dot showBluesky: @reasoningshow.bsky.socialTwitter/X: @ReasoningShowInstagram: @reasoningshowTikTok: @reasoningshow

Social media giants face a legal reckoning, Keppel races toward a $200 billion ambition, and AI stocks are back on fire - what does it all mean for investors? Markets are navigating a collision of regulation, reinvention and rally, hosted by Michelle Martin with Ryan Huang. A landmark ruling puts pressure on platforms like Meta, Instagram and YouTube, raising new risks for Big Tech. Meanwhile, Keppel pivots hard into an asset-light future, chasing scale in infrastructure, energy transition and digital assets. In the US, names like Super Micro, Dell and HPE surge as AI demand fuels a fresh wave of optimism.Plus, UP or DOWN on Microsoft, On Holding, Banyan Group and Japanese IPOs - while Apple teases its next AI leap.See omnystudio.com/listener for privacy information.

On this week's show, Patrick Gray, Adam Boileau and James WIlson discuss the week's cybersecurity news. They talk through: TeamPCP's supply chain attack on Github, and they threw in an anti-Iran wiper, because why not?! Anthropic hooks up its models to just… use your whole computer After Stryker's Very Bad Day, CISA says maybe add some more controls around your Intune? Another iOS exploit kit shows up in the cyber bargain-bin The FTC decides to ban… all new home routers?! U wot m8?! Supermicro founder was personally sanction-busting Nvidia GPUs into China?! This week's episode is sponsored by enterprise browser maker, Island. Chief Customer Officer Bradon Rogers joins Pat to explain how its customers are using Island to control the use of personal AI services in regulated industries. This episode is also available on Youtube. Show notes ‘CanisterWorm' Springs Wiper Attack Targeting Iran TeamPCP deploys CanisterWorm on NPM following Trivy compromise Andrej Karpathy on X: "Software horror: litellm PyPI supply chain" attack Checkmarx KICS GitHub Action Compromised: Malware Injected in All Git Tags Felix Rieseberg on X: "Today, we're releasing a feature that allows Claude to control your computer" A Top Google Search Result for Claude Plugins Was Planted by Hackers Lockheed Martin targeted in alleged breach by pro-Iran hacktivist CISA urges companies to secure Microsoft Intune systems after hackers mass-wipe Stryker devices FBI seems to seize website tied to Iranian cyberattack on Stryker Stryker confirms cyberattack is contained and restoration underway Hundreds of Millions of iPhones Can Be Hacked With a New Tool Found in the Wild Someone has publicly leaked an exploit kit that can hack millions of iPhones Russia-linked hackers use advanced iPhone exploit to target Ukrainians Apple rolls out first 'background security' update for iPhones, iPads, and Macs to fix Safari bug Post by @wartranslated.bsky.social — Bluesky Signal's Creator Is Helping Encrypt Meta AI Hacker says they compromised millions of confidential police tips held by US company Millions of 'anonymous' crime tips exposed in massive Crime Stoppers hack Feds Disrupt IoT Botnets Behind Huge DDoS Attacks FCC bans import of consumer-grade routers amid national security concerns White House pours cold water on cyber ‘letters of marque' speculation Google launches threat disruption unit, stops short of calling it ‘offensive' Supermicro's cofounder was just arrested for allegedly smuggling $2.5 billion in GPUs to China Cyberattack on vehicle breathalyzer company leaves drivers stranded across the US Man pleads guilty to $8 million AI-generated music scheme Two Israelis AI generated "intelligence" and sold it to Iran

JCD BACK IN THE HOUSE! Correction in some areas and sectors. Crude oil DROPS after “good” talks and a deal brewing with Iran. Airports are a mess. PLUS we are now on Spotify and Amazon Music/Podcasts! Click HERE for Show Notes and Links DHUnplugged is now streaming live - with listener chat. Click on link on the right sidebar. Love the Show? Then how about a Donation? Follow John C. Dvorak on Twitter Follow Andrew Horowitz on Twitter Warm-Up - JCD BACK IN THE HOUSE - Need a new CTP - Airports are a mess - Not Kosher - Futures moves Markets - From the Brink....All is good? - Correction in some areas and sectors - US Dollar Rises, Gold, Silver and Bitcoin Drop - Crude oil DROPS after "good" talks and a deal brewing with Iran - reversing all of the above JCD UPDATE - AH waiting by the microphone on a Tuesday in March - - no John... 9pm, 9:05, 9:15pm... - Health update etc...Can we get the story? - Thoughts on John S. Dvorak (Mimi on No Agenda) - Family backup! Market Update - Small-Caps taking the brunt of the selling - Russell 2000 small-caps are down 10% from their high - an official correction -- Interestingly the R2000 is still up this year by about 2% - Stocks up on Monday after President Trump says intense negotiations over weekend and postpones targeted attacks for 5 days (after giving a 48 hour ultimatum) Manipulation? Say it ain't so... - Dateline Monday morning... - Futures took a leg down pre-market - even after Friday (after close) President Trump said he was looking to wind down the Iran affair - At around 6:50 a.m. in New York, S&P 500 e-Mini futures trading on the CME recorded a sharp and isolated jump in volume. - A similar pattern was observed in oil markets. - Roughly 15 minutes later, at 7:05 a.m., Trump posted a market-moving announcement about Iran on Truth Social. - Futures on DJ up 1,000 and oil down 89% --- Were there really conversations and negotiations over the weekend? A Few Leftovers that need to be discussed Private Credit Again - All of a sudden they are admitting there is a problem..... - Blackstone Inc. approved redemptions of a record 7.9% from its flagship private credit fund, totaling about $3.8 billion. - Redemption requests have increased across multiple private credit funds in recent quarters. - Investor unease is being driven by concerns over the private credit asset class, particularly exposure to software companies vulnerable to AI disruption. - According to Hugh Chung, CIO of Endowus, Blackstone's experience suggests these concerns are asset-class wide, not limited to a small group of managers. - Apollo Global Management CEO Marc Rowan warned that a shakeout is coming for private credit firms, driven by rising defaults on loans to software companies. - Rowan emphasized that the shakeout is unlikely to be short-term, calling it foreseeable and predictable, and underscoring the importance of disciplined underwriting and strong risk management. - He argued that investors should prefer having credit risk reside within private markets firms, rather than on bank balance sheets backed by government-insured deposits, which can amplify systemic risk. - LATEST: Apollo is curbing redemptions from one of their biggest Private Credit funds. Michael Gayed: Private credit default rate just hit 9.2%. That's higher than 2008 bank loan peaks. $1.8 trillion in assets, $100B in secondary liquidity. 18:1 mismatch PRIVATE CREDIT More OpenAI Funding - Amazon invested $50 billion, Nvidia invested $30 billion and SoftBank invested $30 billion in the round, OpenAI said in a release Friday. - The investment boosts OpenAI to a $730 billion pre-money valuation, which marks a big jump from its $500 billion valuation in a secondary financing in October. - The will use some of the money to expland and buy more chips and cloud from NVDA and AMZN (? Circular?) MORE ON THE CIRCULAR SHAM - OpenAI said it is expanding its existing $38 billion agreement with Amazon Web Services by $100 billion over the next eight years. -  AWS will also serve as the exclusive third-party cloud distribution provider for OpenAI's enterprise platform Frontier, which it unveiled earlier this month. AI and Where we stand - Can we talk about Anthropic? Is the Government going to crush Claude? - What is our Go-to AI bots? - What stage are we at right now? LLMs > Infernce>Agentic - - What comes after Agentic Netflix OUT - Last week, Netflix exited the bidding for Warner Bros. Discovery after a competing bidder submitted a superior offer. - The decision followed pre-planned bidding scenarios, with co CEO Ted Sarandos saying the company knew exactly how to respond once the higher offer emerged. - Sarandos said the Paramount deal is likely to drive significant cost-cutting, including roughly $16 billion in reductions and thousands of job losses. - He emphasized that Netflix will continue investing in its business and explore new ways to collaborate with theater owners, rather than pursuing large acquisitions.| - Stock rose nicely on the news Tariff Refund Update - You are screwed.... -- Trump administration seems hell-bent on keeping our money Airlines - After a rather bullish commentary from Delta last week.... -  United Airlines is cutting more unprofitable flights over the next two quarters as it prepares for a prolonged period of high jet fuel prices due to the Iran war, even as strong travel demand has allowed U.S. carriers to raise fares. Chief Executive Scott Kirby said in a staff memo the airline is preparing for oil to rise as high as $175 a barrel and remain above $100 until the end of 2027. - At those levels, United's annual fuel bill would rise by about $11 billion, more than twice the profit it earned in its "best year ever," he said. - Ticket prices going up! Gas Prices - Have you seen diesel prices? - > $5 gallon on average across the U.S. -- Implications beyond --- Let's discuss the similarities to the 1973 oil embargo. (Barry switching license plates) - 1973–1974 ? Arab oil embargo (the classic “1970s oil embargo”) - 1979 ? Second oil shock caused by the Iranian Revolution (not an embargo, but another major supply shock) Even So - Fedex - FedEx Corp. raised its full-year profit forecast, with adjusted earnings expected to be $19.30 to $20.10 a share for the fiscal year. - The company's shares climbed after the announcement, with the stock advancing about 23% this year through Thursday's close. - FedEx does not expect the war in the Middle East to have a direct material effect on its business, but the broader consequences, including higher energy prices and volatile shipping patterns, are adversely affecting the global economy. - In fact, company raised its full year outlook..... --- Not a material effect??? Bad People - SuperMicro Co-Founder Charged! - Super Micro shares sank 28% last Friday after U.S. prosecutors charged three people linked with the company, including its co-founder, with helping smuggle billions of dollars worth of AI technology to China. (NVDA chips) - The U.S. Justice Department charged Super Micro co-founder Yih-Shyan Liaw, sales manager Ruei-Tsang Chang, and contractor Ting-Wei Sun with running a scheme to route U.S.-made servers through Taiwan to Southeast Asia. - The defendants allegedly used a Southeast Asian company as a middleman to place orders for high-end servers containing restricted Nvidia H200 and Blackwell chips. The equipment was then repackaged into unmarked boxes and diverted to China. - To evade U.S. audits and customs inspections, the individuals allegedly created thousands of "dummy" servers and used a hair dryer to remove and reattach serial number labels from genuine servers to the fake ones. --- Soooo, only 3 people did all of this? Amazon Phone - Amazon's new phone project codenamed 'Transformer' - Focus on AI integration, Alexa features, and mobile personalization - Here is what we know: -------It is a smartphone, not a wearable or accessory - It is AI-centric, with Alexa deeply integrated - It is meant to act as a personalized, always-on gateway into Amazon's ecosystem (shopping, Prime Video, Prime Music, services like Grubhub) - It is being built inside Amazon's Devices & Services group by a skunkworks team called ZeroOne, led by former Xbox architect J Allard OpenClaw - Nvidia CEO Jensen Huang says OpenClaw could be the next ChatGPT as AI shifts from answering questions to taking action. - Jensen said : Nvidia is building security around the technology with NemoClaw to enable safe and scalable adoption of AI agents. - Project OpenClaw: “It is now the largest, most popular, the most successful open-sourced project in the history of humanity,” - OpenClaw is an open-source autonomous AI agent platform that goes beyond traditional chatbots. -----Instead of answering questions, these agents can complete tasks, make decisions, and take actions with minimal input from users. - Use case: Prompt to study images of a kitchen, learn design tools, iterate ideas to learn how to design a kitchen ------- Jensen says: “Every carpenter can now be an architect. Every plumber will become an architect. We are going to elevate the capabilities of everyone” ---- What happens to the architects? Something.... - One of the hardest hit countries in all of this mess has been South Korea - ~70% of South Korea's crude oil imports come from the Middle East - Most of that oil transits the Strait of Hormuz - Margin calls kicked in as high margin debt with heavy retail participation - Won weakened sharply (17-year low) - Korea economy is dependent on global demand and stable energy prices - South Korea often leads sell-offs as it is the purest RISK ON market in Asia ---- SOOOOO, if this thing ends quickly, there is a potential of EWY to move up again....     Love the Show? Then how about a Donation? THE CLOSEST TO THE PIN for CATERPILLAR Winners will be getting great stuff like the new "OFFICIAL" DHUnplugged Shirt!     FED AND CRYPTO LIMERICKS   See this week's stock picks HERE Follow John C. Dvorak on Twitter Follow Andrew Horowitz on Twitter

The NIA boys discuss Nvidia GTC, AI Inference Explained, Jensen new Steve Jobs & Super Micro's $2.5B Smuggling SchemeTimestamps(00:00:00) - Intro(00:04:21) - Meme of the Week(00:05:37) - Jensen new Steve Jobs(00:09:29) - Nvidia GTC(00:13:46) - AI Agents and OpenClaw(00:22:11) - AI Inference Explained(00:29:31) - Super Micro's $2.5B Smuggling SchemeWhat Is Not Investment Advice?Every week, Jack Butcher, Bilal Zaidi & Trung Phan discuss what they're finding on the edges of the internet + the latest in business, technology and memes.Subscribe + listen on your fav podcast app:Apple: https://pod.link/notadvicepod.appleSpotify: https://pod.link/notadvicepod.spotifyOthers: https://pod.link/notadvicepodListen into our group chat on Telegram:https://t.me/notinvestmentadviceLet us know what you think on Twitter:http://twitter.com/bzaidihttp://twitter.com/trungtphanhttp://twitter.com/jackbutcherhttp://twitter.com/niapodcast Hosted on Acast. See acast.com/privacy for more information.

On today's show Andrew and Bill begin with last week's indictment of Wally Liaw, the co-founder of Super Micro, and its implications for US chip policy. Topics include: Incredible details from the indictment, US enforcement options, and bipartisan calls for government action on Nvidia exports to China and Southeast Asia. Then: Xi takes three Standing Committee members and three other Politburo members to inspect the progress at Xiong'an, signaling continued commitment to the “new area” 60 miles south of Beijing. At the end: Reports that the US visit to China is delayed indefinitely, the PRC's delicate diplomatic calculus as the Iran war continues, and tech news on Manus, Apple, OpenClaw, and an FCC ban on routers.

 In this episode, we unpack President Trump's new national framework for AI legislation (11:15), including reactions from experts and policymakers (39:44). We also discuss the indictment of a Super Micro co-founder for smuggling Nvidia chips into China (42:59) and Nvidia receiving permission to sell H200 chips to China (57:04).

David Faber and Jim Cramer kicked off a new week of trading with stocks surging and crude oil prices tumbling: President Trump said he has instructed the Defense Department to "postpone any and all military strikes against Iranian power plants and energy infrastructure" for five days, depending on how talks progress with Iran — which denies it is negotiating with the U.S. After posting the Iran news on Truth Social, the president spoke to CNBC and held a Q&A session with reporters. The anchor discussed sectors benefiting most from Trump's announcement. Also in focus: BlackRock CEO Larry Fink's letter to investors, "Mag 7" movers, Synopsys and activism, LaGuardia Airport tragedy.   Squawk on the Street Disclaimer Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Timestamps: 0:00 do u ever feel like a muppet 0:11 Google Search AI editing headlines 2:00 Super Micro co-founder smuggling charges 3:47 Android sideloading 24-hour wait period 6:09 QUICK BITS INTRO 6:25 Meta Horizon Worlds VR stays alive 7:14 multi-country botnet takedown 8:14 Musician indicted for AI music fraud 9:08 DLSS 5 only sees 2D frame, thanks Daniel Owen 10:09 Cyborg cockroaches NEWS SOURCES: https://lmg.gg/fwQbj Learn more about your ad choices. Visit megaphone.fm/adchoices

Welcome to this week's episode of the PEBCAK Podcast!  We've got four amazing stories this week so sit back, relax, and keep being awesome!  Be sure to stick around for our Dad Joke of the Week. (DJOW) Follow us on Instagram @pebcakpodcast   Please share this podcast with someone you know!  It helps us grow the podcast and we really appreciate it!   Simple 6 signup link https://simple6.co/r/CFUR98   Meta ends end to end encryption for Instagram https://mashable.com/article/instagram-meta-end-to-end-encryption   SuperMicro executives smuggle GPUs into China https://x.com/ns123abc/status/2034788101491425570?s=46 https://x.com/mweinbach/status/2034807110857347201?s=46  https://www.justice.gov/opa/pr/three-charged-conspiring-unlawfully-divert-cutting-edge-us-artificial-intelligence   RSA Conference 2026 https://www.csoonline.com/article/4146664/5-key-priorities-for-your-rsac-2026-agenda.html   Spring plans   Cybersecurity interview tips   Dad Joke of the Week (DJOW)   Find the hosts on LinkedIn: Chris - https://www.linkedin.com/in/chlouie/ Brian - https://www.linkedin.com/in/briandeitch-sase/ Glenn - https://www.linkedin.com/in/glennmedina/

AI is becoming a scale and control business. On Episode 297 of The Six Five Pod, Patrick Moorhead and Daniel Newman examine the companies building the infrastructure, forming the alliances, and making the moves that will define who wins and who gets squeezed out. Control is shifting across compute, models, infrastructure, and enterprise distribution as NVIDIA, Microsoft, OpenAI, Meta, and others push to control the next phase of the AI market. The handpicked topics for this week are: NVIDIA's Full-Stack Push Gets Bigger: Following the GTC conference in San Jose, Pat and Dan break down how NVIDIA continues expanding beyond GPUs with Vera CPU, Dynamo, and a broader agentic AI stack designed to unify training, inference, orchestration, and enterprise-grade security. Microsoft, OpenAI, and Amazon Enter a New Phase of Tension: With Microsoft reportedly weighing legal action over OpenAI's growing AWS relationship, the discussion turns to exclusivity, multi-cloud strategy, and what happens when one of AI's most important alliances starts to crack. China, Compute, and the Geopolitics of AI Access: The hosts examine NVIDIA's reported H200 restart for China and what it says about export controls, policy pressure, and the global fight over advanced AI compute. Meta's $27B Infrastructure Agreement Signals the Real Race: Meta's latest infrastructure deal reinforces a central point of this episode, demand for AI capacity is still outrunning supply, and hyperscalers are moving aggressively to lock in long-term compute. OpenAI's Enterprise Push Raises Bigger Business Model Questions: As OpenAI leans harder into enterprise and eyes an eventual IPO, Pat and Dan unpack what this pivot says about monetization pressure, competitive positioning, and the need to prove a durable AI business model. The GPU Smuggling Story Shows How Valuable AI Hardware Has Become: A major smuggling case involving NVIDIA hardware spotlights the black market for AI chips and the growing intersection of compute, national security, and enforcement. The Flip: Did NVIDIA Just Change the Inference Market Again? This week's debate centers on whether NVIDIA's $20bn Groq Technology deal kills the standalone inference chip market, or whether it actually validates the market by proving just how strategically important specialized inference has become. The Fed, Micron, and Accenture Reflect a More Complicated Market: In Bulls and Bears, the hosts cover the Fed's latest decision, Micron's AI-driven momentum, and why Accenture's results still ran into skepticism despite strong execution. Meta's Workforce Cuts and AI Spend Reflect the New Corporate Tradeoff: The episode closes on the growing tension between rising AI investment and labor efficiency, as companies look for ways to fund massive infrastructure and token budgets while restructuring headcount. For a deeper dive into each topic, please click on the provided links. Subscribe to our YouTube Channel so you never miss an episode.   The Decode   NVIDIA GTC 2026: Vera Rubin Platform, Groq LPU Integration & $1T Demand Vision https://www.cnbc.com/2026/03/16/nvidia-gtc-2026-ceo-jensen-huang-keynote-blackwell-vera-rubin.html https://investor.nvidia.com/news/press-release-details/2026/NVIDIA-Vera-Rubin-Opens-Agentic-AI-Frontier/default.aspx https://x.com/PatrickMoorhead/status/2033662536227393952 https://x.com/danielnewmanUV/status/2033649511592284352   The Groq 3 LPU: NVIDIA's $20B Bet on Inference Economics https://www.cnbc.com/2026/03/13/a-closer-look-at-nvidias-20-billion-bet-on-tech-for-a-new-ai-chip.html https://www.tomshardware.com/tech-industry/semiconductors/nvidias-20-billion-groq-deal-produces-its-first-chip https://www.servethehome.com/decoding-the-future-of-inference-at-nvidia-groq-lpus-join-vera-rubin-platform-for-low-latency-inference/ https://developer.nvidia.com/blog/inside-nvidia-groq-3-lpx-the-low-latency-inference-accelerator-for-the-nvidia-vera-rubin-platform/ https://www.jonpeddie.com/news/nvidias-groq-tie-in/ Microsoft Threatens to Sue OpenAI Over $50B Amazon AWS Frontier Deal https://www.reuters.com/technology/microsoft-weighs-legal-action-over-50-billion-amazon-openai-cloud-deal-ft-2026-03-18/ NVIDIA Restarting H200 Chip Production for China https://www.axios.com/2026/03/17/nvidia-huang-china-h200 https://x.com/danielnewmanUV/status/1999974968143257945 Meta & Nebius Sign $27B AI Infrastructure Agreement — Largest AI Compute Deal https://nebius.com/newsroom/nebius-signs-new-ai-infrastructure-agreement-with-meta https://x.com/danielnewmanUV/status/2033531056784347240 https://x.com/PatrickMoorhead/status/2033543939526193491 OpenAI Enterprise Pivot + Q4 2026 IPO Target https://www.reuters.com/business/openai-lays-groundwork-juggernaut-ipo-up-1-trillion-valuation-2025-10-29/ https://www.forbes.com/sites/josipamajic/2026/03/19/openais-pivot-to-enterprise-is-likely-a-race-against-anthropic-and-the-ipo-clock/ Supermicro's Legal Troubles https://fortune.com/2026/03/19/supermicro-arrested-founder-smuggling-gpu-china/ https://www.bbc.com/news/articles/cy41ly2d9wko The Flip: Did NVIDIA Just Kill the Inference Chip Startup Market with the Groq Acquisition? FOR: NVIDIA Killed It — The Inference Startup Market Is Over https://www.cnbc.com/2026/03/13/a-closer-look-at-nvidias-20-billion-bet-on-tech-for-a-new-ai-chip.html https://www.jonpeddie.com/news/nvidias-groq-tie-in/ AGAINST: Startups Survive — Hyperscalers Won't Deepen NVIDIA Dependency https://www.reuters.com/business/retail-consumer/cerebras-systems-amazon-strike-deal-offer-cerebras-ai-chips-amazons-cloud-2026-03-13/ https://www.tomshardware.com/pc-components/gpus/nvidia-removes-rubin-cpx-accelerators-from-its-roadmap-groq-3-lpus-take-center-stage-as-cpx-is-removed Bulls & Bears Market Reactions to Economic News https://uk.finance.yahoo.com/news/stock-market-today-dow-sinks-750-points-sp-500-nasdaq-slide-after-fed-decision-as-powell-touts-inflation-worries-200050703.html https://www.kiplinger.com/investing/live/march-fed-meeting-2026-live-updates-and-commentary https://www.investopedia.com/stock-market-today-dow-jones-s-and-p-500-03182026-11928689 $MU Micron Technology — Revenue Almost Triples, Tops Estimates https://www.cnbc.com/2026/03/18/micron-mu-q2-earnings-report-2026.html https://x.com/PatrickMoorhead/status/2034390648519024820 https://x.com/danielnewmanUV/status/2034378642613235921 $ACN Accenture — Q2 FY2026 Earnings Beat, Stock Drops ~5% on Guidance https://www.investing.com/news/earnings/accenture-falls-despite-q2-beat-as-earnings-guidance-disappoints-4570221 https://www.zacks.com/stock/news/2886706/accenture-earnings-beat-estimates-in-q2-revenues-increase-yy https://www.investing.com/news/transcripts/earnings-call-transcript-accenture-q2-2026-beats-forecasts-but-stock-dips-93CH-4570789 https://x.com/PatrickMoorhead/status/2033348794348142595  

2,5% Zinsen p.a. auf ein unbegrenztes Guthaben mit bis zu fünfmal der gesetzlichen Einlagensicherung*. Das gibt's bei Scalable Capital. ⁠Mehr Infos hier. McCormick will Knorr von Unilever. Cargill nutzt KI für mehr Fleisch. Palantir rollt Maven aus. SAP wächst stark in Rüstung. Gold hat schlechteste Woche seit 2011. Super Micro hat Schmuggel-Skandal. United Airlines hat Angst vor Ölpreis. Trump droht. Init (WKN: 575980) steigt in den SDAX auf. Die Karlsruher digitalisieren den ÖPNV weltweit. London, Houston, Atlanta. Nordamerika ist der Wachstumstreiber. KGV bei 14 mit 24% Umsatzwachstum. Dominos Pizza Enterprises (WKN: A0EQ2E) hat seit dem Hoch 90% verloren. Ein 83-jähriger Milliardär soll den Turnaround schaffen. Weniger Rabatte, teurere Pizzen. Klappt das oder laufen Kunden weg? Diesen Podcast vom 23.03.2026, 3:00 Uhr stellt dir die Podstars GmbH (Noah Leidinger) zur Verfügung. *Veränderlicher Zins auf unbegrenztes Guthaben. Konditionen sowie Guthabenverteilung auf ⁠scalable.capital/tagesgeld⁠.

What if the biggest threat to food companies… isn’t inflation but your shrinking appetite? GLP-1 drugs like Ozempic are reshaping consumer behavior, forcing food giants to rethink portions, pricing, and product strategy. Meanwhile, US markets wobble as the Russell 2000 slips into correction territory, raising questions about the durability of the rally. Asian tech earnings from Xiaomi, PDD, Meituan and BYD are now in focus as investors hunt for growth signals. Corporate headlines add to the volatility - from Super Micro’s sharp selloff to Sinopec’s profit drop and Elon Musk’s legal battles. And in tech, Amazon explores a bold return to smartphones, joining Apple, Google, Meta and OpenAI in the race to redefine AI hardware. Hosted by Michelle Martin with Ryan Huang. Companies in focus: Amazon, Apple, Google, Meta, OpenAI, Xiaomi, PDD Holdings (Pinduoduo), Meituan, BYD, Coca-Cola Andina, Super Micro, Sinopec, Singtel, Sembcorp Industries, Hongkong Land.See omnystudio.com/listener for privacy information.

Why are investors turning away from gold? And why weren't Micron Technology's blowout earnings good enough? Plus, why is Super Micro's co-founder in hot water with U.S. prosecutors? Host Hannah Erin Lang discusses the biggest stock moves of the week and the news that drove them. Sign up for the WSJ's free Markets A.M. newsletter Learn more about your ad choices. Visit megaphone.fm/adchoices

Why are investors turning away from gold? And why weren't Micron Technology's blowout earnings good enough? Plus, why is Super Micro's co-founder in hot water with U.S. prosecutors? Host Hannah Erin Lang discusses the biggest stock moves of the week and the news that drove them.Sign up for the WSJ's free Markets A.M. newsletter. Learn more about your ad choices. Visit megaphone.fm/adchoices

Charles Payne is joined by Scott Martin, Kingsview Partners CIO, to discuss the DOJ charging Supermicro with allegedly selling critical chips to China, the decision to dollar-cost average into the stock despite the scandal, and a strategy of using market volatility to add to fundamentally strong companies like Life Time. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Carl Quintanilla and Jim Cramer led off the show with the major indices on track for a four-week losing streak. Jim spoke about how investors should navigate markets he says are oversold. FedEx shares jump on a better-than-expected holiday quarter and upbeat guidance. Super Micro shares plummet after U.S. prosecutor charged three people associated with the company — including its co-founder -- with smuggling Nvidia AI chips to China. Also in focus: Oil prices and the U.S.' battle to open the Strait of Hormuz, what Fed Governor Waller told CNBC about inflation and the strait, Goldman Sachs CEO David Solomon's letter about private credit, Amazon said to be planning a new smartphone launch, OpenAI reportedly plans a "superapp" launch.   Squawk on the Street Disclaimer Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Energy prices falling, stocks under pressure, and rate cut expectations wobbling to end the week: Carl Quintanilla, Sara Eisen, and Michael Santoli discussed the latest for stocks before breaking down what comes next with Truist's Chief Investment Officer - along with more on the Fed's next moves here according to one former Fed president. Plus: Council on Foreign Relations President Michael Froman joined the team with 2 flashpoints he says could force an escalation in the Iran war... While the former head of CISA gave his read on the implications for cybersecurity.  Also this hour: details on the dramatic chip smuggling scandal slamming shares of Super Micro.   Squawk on the Street Disclaimer Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Leslie Picker and the Investment Committee debate the S&P's longest losing streak since March and how to navigate the volatility. Plus, shares of Super Micro plummeting after U.S. prosecutors charge 3 companye employees with smuggling NVIDIA chips to China, the desk debate which competitor will benefit. And later, big trouble for China stocks, the Commitee discuss their international strategy.  Investment Committee Disclosures Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Super Micro smuggled NVidia chips to China. Thune warns Senate's April recess could be canceled if DHS shutdown continues. Trump administration backs $200 million push for a cancer vaccine. Squad-backed Democrats lose Illinois primaries in progressive setbackSee omnystudio.com/listener for privacy information.

Super Micro smuggled NVidia chips to China. Thune warns Senate's April recess could be canceled if DHS shutdown continues. Trump administration backs $200 million push for a cancer vaccine. Squad-backed Democrats lose Illinois primaries in progressive setback Culvers to open in odd location downtown. Today’s Popcorn Moment: Trump's presser with Japanese Prime Minister, and his reference to Pearl Harbor. Today on the Marketplace: Half Gallon Cup Holder car adapter. Australian heckled by Islamists in his own country New Indiana law updates Ivy Tech governance, doubles down on workforce mission8:16: Trump to take Kharg Island? Russia coming to the aid of Cuba. What's that TV Theme Song? Film Friday: Superman. Autism racketSee omnystudio.com/listener for privacy information.

(Presented by Thinkst Canary: Most Companies find out way too late that they've been breached. Thinkst Canary changes this. Deploy Canaries and Canarytokens in minutes and then forget about them. Attackers tip their hand by touching 'em giving you the one alert, when it matters. With zero admin overhead and almost no false-positives, Canaries are deployed (and loved) on all 7 continents.) Three Buddy Problem - Episode 90: We remember GReAT teammate Sergey Mineev, the legendary malware hunter behind discoveries like Equation Group and Project Sauron (Remsec), including stories about his methods and why he was the best to ever do it. Plus, another in-the-wild iOS exploit kit discovery and a long overdue conversation about Apple's responsibility to hundreds of millions of users on older iOS versions; the ProPublica Microsoft/FedRAMP bombshell, Interlock ransomware sitting on a Cisco zero-day, the White House AI policy framework, and Supermicro co-founder $2.5 billion AI chip smuggling bust. Cast: Juan Andres Guerrero-Saade, Ryan Naraine and Costin Raiu.

Hour 2 Segment 1 Tony starts the second hour of the show talking about Super Micro’s co-founder being charged for smuggling Nvidia chips into China. Tony also talks about Australian Prime Minister Anthony Albanese getting chased out of a mosque by an angry crowd calling him a “genocide supporter”. Hour 2 Segment 2 Tony talks more about unpaid TSA agents due to the DHS shutdown. Hour 2 Segment 3 Tony is joined with E.J. Antoni of The Heritage Foundation to talk about how bad oil prices could get for the U.S. and for the enemies. Hour 2 Segment 4 Tony wraps up the second hour of the show talking about Senator Mazie Hironi speaking about why she disapproves of the Save Act. See omnystudio.com/listener for privacy information.

Hour 1 Segment 1 Tony starts the first hour of the show talking about TSA lines going on forever at airports due to the DHS shutdown. Hour 1 Segment 2 Tony talks about the Trump administration backing a $200M cancer vaccine initiative. Hour 1 Segment 3 Tony talks about the passing of Chuck Norris at the age of 86 and talks about the best Chuck Norris jokes. Hour 1 Segment 4 Tony wraps up the first hour of the show talking about Joe Kent making his rounds on the woke right media outlets. Hour 2 Segment 1 Tony starts the second hour of the show talking about Super Micro’s co-founder being charged for smuggling Nvidia chips into China. Tony also talks about Australian Prime Minister Anthony Albanese getting chased out of a mosque by an angry crowd calling him a “genocide supporter”. Hour 2 Segment 2 Tony talks more about unpaid TSA agents due to the DHS shutdown. Hour 2 Segment 3 Tony is joined with E.J. Antoni of The Heritage Foundation to talk about how bad oil prices could get for the U.S. and for the enemies. Hour 2 Segment 4 Tony wraps up the second hour of the show talking about Senator Mazie Hironi speaking about why she disapproves of the Save Act. Hour 3 Segment 1 Tony starts the final hour of the show joined with Griff Jenkins of FOX News to talk about the latest on the U.S./Iranian conflict, TSA affected by the DHS shutdown, and Markwayne Mullin. Hour 3 Segment 2 Tony talks about the cancellation of The Bachelorette due to a leaked video of Taylor Frankie Paul attacking her partner in 2023. Hour 3 Segment 3 Tony talks more about the passing of Chuck Norris at the age of 86. Hour 3 Segment 4 Tony wraps up another edition of the show talking more about the lines for TSA being outrageously long due to the DHS shutdown. See omnystudio.com/listener for privacy information.

From Wall Street to Main Street, the latest on the markets and what it means for your money. Updated regularly on weekdays, featuring CNBC expert analysis and sound from top business newsmakers. Anchored and reported by CNBC's Jessica Ettinger. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

Market update for Friday March 20, 2026Check out the Public app for incredible investing tools and to support the show (LINK)Follow us on Instagram (@TheRundownDaily) for bonus content and instant reactions.In today's episode:FedEx earnings signal economy still holding upAmazon working on AI-powered smartphone comebackSuper Micro stock plunges after smuggling chargesFirefly Aerospace surges on strong growthTesla Semi wins over truckers

En Capital Intereconomía seguimos en directo la apertura del Ibex 35 y del resto de bolsas europeas, que arrancan la jornada con subidas apoyadas en la relajación del precio del petróleo, lo que da un respiro a los mercados tras las últimas tensiones energéticas. En el análisis de mercados, Juan Enrique Cadiñanos, CEO Global de Bullfy, destaca que el foco sigue puesto en la inflación y la política monetaria, con el BCE advirtiendo de posibles subidas de tipos incluso en abril. Además, el mercado permanece atento al anuncio de un paquete de medidas anticrisis por parte del Gobierno, en un contexto de elevada incertidumbre económica. En el plano empresarial, sobresale el desplome de Super Micro tras acusaciones que afectan a su cofundador, así como la atención a la junta de accionistas de BBVA, en una jornada con importantes referencias corporativas. El programa se completa con el consultorio de bolsa junto a Daniel Santacreu, donde analizamos valores y resolvemos dudas de los oyentes.

Ignacio Vacchiano, country manager en Iberia de Leverage Shares, analiza el momento de las Bolsas y la última actualidad económica, que está marcada por las caídas en los índices en Estados Unidos y la decisión de tipos de los Bancos Centrales. “El S&P 500 ha bajado por rotación y por sectores que lo habían hecho mal”, afirma el invitado. Además añade que “ ya los índices venían bajando por esa rotación” y que “la venta de tecnología ya arrastraba mucho los índices antes del 28 de febrero, precisamente justo desde ese inicio del conflicto con Irán”. Sobre la decisión de la FED y su perspectiva de inflación ha dicho que “que no es creíble esa versión de los miembros de la Fed de que va a subir tampoco la inflación a fin de año”. En las últimas horas hay una tecnológica que se desploma: Super Micro Computer. Su cofundador, Yih-Shyan Liaw, ha sido acusado de enviar equipos de alto rendimiento de IA a China. Estados Unidos acusa a Liaw y a otros dos individuos de vender esta tecnología a través de una empresa del sudeste asiático, a sabiendas de que iban a parar a manos chinas. “Lo de Super Micro es una más de la compañía en esa falta de gobernanza en esos miembros de la empresa”, asegura el country manager en Iberia de Leverage Shares. También ha sido noticia en las últimas horas FedEX, ya que la empresa ha presentado cuentas del tercer trimestre. Sube más de un 10% después de anunciar que sus ingresos aumentan un 8% en este periodo, hasta los 24.000 millones, por encima de las estimaciones del mercado. Ignacio Vacchiano explica que “hay que estar atento a la empresa, porque en junio va a hacer el spin-off la separación de su parte de la compañía de transporte terrestre FedEx Pride”.

En Capital Intereconomía, en el Radar Empresarial, destacamos la detención del cofundador de Super Micro por la supuesta venta ilegal de chips a China, un caso que vuelve a poner el foco en la guerra tecnológica y el control de semiconductores a nivel global. En el Foro de la Inversión, Juan Ramón Caridad, de Pictet AM, analiza el fondo Pictet Clean Energy Transition y las oportunidades en la transición energética en un entorno marcado por la tensión geopolítica. Subraya el papel estratégico de las energías limpias, no solo por sostenibilidad, sino también por seguridad energética y diversificación en las carteras. En Cripto Capital, abordamos el paso clave de Kraken, que obtiene una cuenta en la Reserva Federal, acercando el ecosistema cripto al sistema financiero tradicional. Con Jesús Pérez y Víctor Sáez, analizamos cómo este movimiento puede impulsar la legitimación institucional de los criptoactivos y su integración en el sistema financiero global.

En el Radar Empresarial de hoy revisamos la información más reciente que ha golpeado con fuerza a Super Micro Computer, provocando una caída cercana al 20% en sus acciones durante las operaciones fuera de horario. El cofundador de la compañía, Yih-Shyan Liaw, ha sido detenido junto a otras dos personas por presuntamente haber comercializado chips y equipos tecnológicos con destino a China, eludiendo las restricciones de exportación impuestas por Estados Unidos. Según las autoridades, Liaw, en colaboración con Ruei-Tsang Chang y Ting-Wei Sun, habría participado en el envío ilegal de componentes tecnológicos valorados en unos 2.500 millones de dólares, incluyendo unidades fabricadas por Nvidia. Para llevar a cabo estas operaciones, supuestamente utilizaron una empresa fantasma ubicada en el sudeste asiático con el objetivo de esquivar la normativa vigente. No obstante, los fiscales no han presentado cargos formales contra la empresa en sí dentro de la denuncia. Tras conocerse los hechos el jueves, la compañía reaccionó de inmediato suspendiendo de forma temporal a Liaw y Chang, además de rescindir el contrato de Sun. A pesar de ello, Liaw mantiene una participación accionarial valorada en unos 400 millones de dólares. La investigación revela una compleja red logística en la que los servidores eran trasladados desde Estados Unidos a Taiwán y posteriormente a distintos países del sudeste asiático antes de llegar a China, muchas veces ocultos en paquetes sin identificar. Las autoridades sostienen que los implicados empleaban métodos sofisticados para ocultar su actividad, como retirar etiquetas y números de serie con herramientas domésticas y colocarlos en equipos falsos. También se han levantado dudas sobre las auditorías realizadas en ese periodo, ya que los controles no detectaron las irregularidades. Este nuevo episodio se suma a controversias previas, incluidas sanciones por irregularidades contables y acusaciones de manipulación financiera y violaciones regulatorias.

OpenAI va a fusionar ChatGPT, Codex y un navegador propio en una única app de escritorio antes de su IPO. La Casa Blanca presenta su marco federal de IA que anula las leyes estatales con el argumento de no perder terreno frente a China. Blue Origin pide permiso para lanzar 51.600 satélites al espacio para montar data centers orbitales, mientras SpaceX va por el millón. Tres directivos de Super Micro son imputados por contrabandear 2.500 millones de dólares en chips Nvidia a China usando servidores falsos y secadores de pelo. Y MiniMax lanza M2.7, un modelo de IA que gestionó entre el 30% y el 50% de su propio entrenamiento y rinde casi al nivel de Claude Opus y GPT-5.4.Puedes seguirnos en YouTube en https://youtube.com/olivernabani y puedes unirte al Discord Mashain en https://olivernabani.com/discord

Bryan Cantrill is the co-founder and CTO of Oxide Computer Company. We discuss why the biggest cloud providers don't use off the shelf hardware, how scaling data centers at samsung's scale exposed problems with hard drive firmware, how the values of NodeJS are in conflict with robust systems, choosing Rust, and the benefits of Oxide Computer's rack scale approach. This is an extended version of an interview posted on Software Engineering Radio. Related links Oxide Computer Oxide and Friends Illumos Platform as a Reflection of Values RFD 26 bhyve CockroachDB Heterogeneous Computing with Raja Koduri Transcript You can help correct transcripts on GitHub. Intro [00:00:00] Jeremy: Today I am talking to Bryan Cantrill. He's the co-founder and CTO of Oxide computer company, and he was previously the CTO of Joyent and he also co-authored the DTrace Tracing framework while he was at Sun Microsystems. [00:00:14] Jeremy: Bryan, welcome to Software Engineering radio. [00:00:17] Bryan: Uh, awesome. Thanks for having me. It's great to be here. [00:00:20] Jeremy: You're the CTO of a company that makes computers. But I think before we get into that, a lot of people who built software, now that the actual computer is abstracted away, they're using AWS or they're using some kind of cloud service. So I thought we could start by talking about, data centers. [00:00:41] Jeremy: 'cause you were. Previously working at Joyent, and I believe you got bought by Samsung and you've previously talked about how you had to figure out, how do I run things at Samsung's scale. So how, how, how was your experience with that? What, what were the challenges there? Samsung scale and migrating off the cloud [00:01:01] Bryan: Yeah, I mean, so at Joyent, and so Joyent was a cloud computing pioneer. Uh, we competed with the likes of AWS and then later GCP and Azure. Uh, and we, I mean, we were operating at a scale, right? We had a bunch of machines, a bunch of dcs, but ultimately we know we were a VC backed company and, you know, a small company by the standards of, certainly by Samsung standards. [00:01:25] Bryan: And so when, when Samsung bought the company, I mean, the reason by the way that Samsung bought Joyent is Samsung's. Cloud Bill was, uh, let's just say it was extremely large. They were spending an enormous amount of money every year on, on the public cloud. And they realized that in order to secure their fate economically, they had to be running on their own infrastructure. [00:01:51] Bryan: It did not make sense. And there's not, was not really a product that Samsung could go buy that would give them that on-prem cloud. Uh, I mean in that, in that regard, like the state of the market was really no different. And so they went looking for a company, uh, and bought, bought Joyent. And when we were on the inside of Samsung. [00:02:11] Bryan: That we learned about Samsung scale. And Samsung loves to talk about Samsung scale. And I gotta tell you, it is more than just chest thumping. Like Samsung Scale really is, I mean, just the, the sheer, the number of devices, the number of customers, just this absolute size. they really wanted to take us out to, to levels of scale, certainly that we had not seen. [00:02:31] Bryan: The reason for buying Joyent was to be able to stand up on their own infrastructure so that we were gonna go buy, we did go buy a bunch of hardware. Problems with server hardware at scale [00:02:40] Bryan: And I remember just thinking, God, I hope Dell is somehow magically better. I hope the problems that we have seen in the small, we just. You know, I just remember hoping and hope is hope. It was of course, a terrible strategy and it was a terrible strategy here too. Uh, and the we that the problems that we saw at the large were, and when you scale out the problems that you see kind of once or twice, you now see all the time and they become absolutely debilitating. [00:03:12] Bryan: And we saw a whole series of really debilitating problems. I mean, many ways, like comically debilitating, uh, in terms of, of showing just how bad the state-of-the-art. Yes. And we had, I mean, it should be said, we had great software and great software expertise, um, and we were controlling our own system software. [00:03:35] Bryan: But even controlling your own system software, your own host OS, your own control plane, which is what we had at Joyent, ultimately, you're pretty limited. You go, I mean, you got the problems that you can obviously solve, the ones that are in your own software, but the problems that are beneath you, the, the problems that are in the hardware platform, the problems that are in the componentry beneath you become the problems that are in the firmware. IO latency due to hard drive firmware [00:04:00] Bryan: Those problems become unresolvable and they are deeply, deeply frustrating. Um, and we just saw a bunch of 'em again, they were. Comical in retrospect, and I'll give you like a, a couple of concrete examples just to give, give you an idea of what kinda what you're looking at. one of the, our data centers had really pathological IO latency. [00:04:23] Bryan: we had a very, uh, database heavy workload. And this was kind of right at the period where you were still deploying on rotating media on hard drives. So this is like, so. An all flash buy did not make economic sense when we did this in, in 2016. This probably, it'd be interesting to know like when was the, the kind of the last time that that actual hard drives made sense? [00:04:50] Bryan: 'cause I feel this was close to it. So we had a, a bunch of, of a pathological IO problems, but we had one data center in which the outliers were actually quite a bit worse and there was so much going on in that system. It took us a long time to figure out like why. And because when, when you, when you're io when you're seeing worse io I mean you're naturally, you wanna understand like what's the workload doing? [00:05:14] Bryan: You're trying to take a first principles approach. What's the workload doing? So this is a very intensive database workload to support the, the object storage system that we had built called Manta. And that the, the metadata tier was stored and uh, was we were using Postgres for that. And that was just getting absolutely slaughtered. [00:05:34] Bryan: Um, and ultimately very IO bound with these kind of pathological IO latencies. Uh, and as we, you know, trying to like peel away the layers to figure out what was going on. And I finally had this thing. So it's like, okay, we are seeing at the, at the device layer, at the at, at the disc layer, we are seeing pathological outliers in this data center that we're not seeing anywhere else. [00:06:00] Bryan: And that does not make any sense. And the thought occurred to me. I'm like, well, maybe we are. Do we have like different. Different rev of firmware on our HGST drives, HGST. Now part of WD Western Digital were the drives that we had everywhere. And, um, so maybe we had a different, maybe I had a firmware bug. [00:06:20] Bryan: I, this would not be the first time in my life at all that I would have a drive firmware issue. Uh, and I went to go pull the firmware, rev, and I'm like, Toshiba makes hard drives? So we had, I mean. I had no idea that Toshiba even made hard drives, let alone that they were our, they were in our data center. [00:06:38] Bryan: I'm like, what is this? And as it turns out, and this is, you know, part of the, the challenge when you don't have an integrated system, which not to pick on them, but Dell doesn't, and what Dell would routinely put just sub make substitutes, and they make substitutes that they, you know, it's kind of like you're going to like, I don't know, Instacart or whatever, and they're out of the thing that you want. [00:07:03] Bryan: So, you know, you're, someone makes a substitute and like sometimes that's okay, but it's really not okay in a data center. And you really want to develop and validate a, an end-to-end integrated system. And in this case, like Toshiba doesn't, I mean, Toshiba does make hard drives, but they are a, or the data they did, uh, they basically were, uh, not competitive and they were not competitive in part for the reasons that we were discovering. [00:07:29] Bryan: They had really serious firmware issues. So the, these were drives that would just simply stop a, a stop acknowledging any reads from the order of 2,700 milliseconds. Long time, 2.7 seconds. Um. And that was a, it was a drive firmware issue, but it was highlighted like a much deeper issue, which was the simple lack of control that we had over our own destiny. [00:07:53] Bryan: Um, and it's an, it's, it's an example among many where Dell is making a decision. That lowers the cost of what they are providing you marginally, but it is then giving you a system that they shouldn't have any confidence in because it's not one that they've actually designed and they leave it to the customer, the end user, to make these discoveries. [00:08:18] Bryan: And these things happen up and down the stack. And for every, for whether it's, and, and not just to pick on Dell because it's, it's true for HPE, it's true for super micro, uh, it's true for your switch vendors. It's, it's true for storage vendors where the, the, the, the one that is left actually integrating these things and trying to make the the whole thing work is the end user sitting in their data center. AWS / Google are not buying off the shelf hardware but you can't use it [00:08:42] Bryan: There's not a product that they can buy that gives them elastic infrastructure, a cloud in their own DC The, the product that you buy is the public cloud. Like when you go in the public cloud, you don't worry about the stuff because that it's, it's AWS's issue or it's GCP's issue. And they are the ones that get this to ground. [00:09:02] Bryan: And they, and this was kind of, you know, the eye-opening moment. Not a surprise. Uh, they are not Dell customers. They're not HPE customers. They're not super micro customers. They have designed their own machines. And to varying degrees, depending on which one you're looking at. But they've taken the clean sheet of paper and the frustration that we had kind of at Joyent and beginning to wonder and then Samsung and kind of wondering what was next, uh, is that, that what they built was not available for purchase in the data center. [00:09:35] Bryan: You could only rent it in the public cloud. And our big belief is that public cloud computing is a really important revolution in infrastructure. Doesn't feel like a different, a deep thought, but cloud computing is a really important revolution. It shouldn't only be available to rent. You should be able to actually buy it. [00:09:53] Bryan: And there are a bunch of reasons for doing that. Uh, one in the one we we saw at Samsung is economics, which I think is still the dominant reason where it just does not make sense to rent all of your compute in perpetuity. But there are other reasons too. There's security, there's risk management, there's latency. [00:10:07] Bryan: There are a bunch of reasons why one might wanna to own one's own infrastructure. But, uh, that was very much the, the, so the, the genesis for oxide was coming out of this very painful experience and a painful experience that, because, I mean, a long answer to your question about like what was it like to be at Samsung scale? [00:10:27] Bryan: Those are the kinds of things that we, I mean, in our other data centers, we didn't have Toshiba drives. We only had the HDSC drives, but it's only when you get to this larger scale that you begin to see some of these pathologies. But these pathologies then are really debilitating in terms of those who are trying to develop a service on top of them. [00:10:45] Bryan: So it was, it was very educational in, in that regard. And you're very grateful for the experience at Samsung in terms of opening our eyes to the challenge of running at that kind of scale. [00:10:57] Jeremy: Yeah, because I, I think as software engineers, a lot of times we, we treat the hardware as a, as a given where, [00:11:08] Bryan: Yeah. [00:11:08] Bryan: Yeah. There's software in chard drives [00:11:09] Jeremy: It sounds like in, in this case, I mean, maybe the issue is not so much that. Dell or HP as a company doesn't own every single piece that they're providing you, but rather the fact that they're swapping pieces in and out without advertising them, and then when it becomes a problem, they're not necessarily willing to, to deal with the, the consequences of that. [00:11:34] Bryan: They just don't know. I mean, I think they just genuinely don't know. I mean, I think that they, it's not like they're making a deliberate decision to kind of ship garbage. It's just that they are making, I mean, I think it's exactly what you said about like, not thinking about the hardware. It's like, what's a hard drive? [00:11:47] Bryan: Like what's it, I mean, it's a hard drive. It's got the same specs as this other hard drive and Intel. You know, it's a little bit cheaper, so why not? It's like, well, like there's some reasons why not, and one of the reasons why not is like, uh, even a hard drive, whether it's rotating media or, or flash, like that's not just hardware. [00:12:05] Bryan: There's software in there. And that the software's like not the same. I mean, there are components where it's like, there's actually, whether, you know, if, if you're looking at like a resistor or a capacitor or something like this Yeah. If you've got two, two parts that are within the same tolerance. Yeah. [00:12:19] Bryan: Like sure. Maybe, although even the EEs I think would be, would be, uh, objecting that a little bit. But the, the, the more complicated you get, and certainly once you get to the, the, the, the kind of the hardware that we think of like a, a, a microprocessor, a a network interface card, a a, a hard driver, an NVME drive. [00:12:38] Bryan: Those things are super complicated and there's a whole bunch of software inside of those things, the firmware, and that's the stuff that, that you can't, I mean, you say that software engineers don't think about that. It's like you, no one can really think about that because it's proprietary that's kinda welded shut and you've got this abstraction into it. [00:12:55] Bryan: But the, the way that thing operates is very core to how the thing in aggregate will behave. And I think that you, the, the kind of, the, the fundamental difference between Oxide's approach and the approach that you get at a Dell HP Supermicro, wherever, is really thinking holistically in terms of hardware and software together in a system that, that ultimately delivers cloud computing to a user. [00:13:22] Bryan: And there's a lot of software at many, many, many, many different layers. And it's very important to think about, about that software and that hardware holistically as a single system. [00:13:34] Jeremy: And during that time at Joyent, when you experienced some of these issues, was it more of a case of you didn't have enough servers experiencing this? So if it would happen, you might say like, well, this one's not working, so maybe we'll just replace the hardware. What, what was the thought process when you were working at that smaller scale and, and how did these issues affect you? UEFI / Baseboard Management Controller [00:13:58] Bryan: Yeah, at the smaller scale, you, uh, you see fewer of them, right? You just see it's like, okay, we, you know, what you might see is like, that's weird. We kinda saw this in one machine versus seeing it in a hundred or a thousand or 10,000. Um, so you just, you just see them, uh, less frequently as a result, they are less debilitating. [00:14:16] Bryan: Um, I, I think that it's, when you go to that larger scale, those things that become, that were unusual now become routine and they become debilitating. Um, so it, it really is in many regards a function of scale. Uh, and then I think it was also, you know, it was a little bit dispiriting that kind of the substrate we were building on really had not improved. [00:14:39] Bryan: Um, and if you look at, you know, the, if you buy a computer server, buy an x86 server. There is a very low layer of firmware, the BIOS, the basic input output system, the UEFI BIOS, and this is like an abstraction layer that has, has existed since the eighties and hasn't really meaningfully improved. Um, the, the kind of the transition to UEFI happened with, I mean, I, I ironically with Itanium, um, you know, two decades ago. [00:15:08] Bryan: but beyond that, like this low layer, this lowest layer of platform enablement software is really only impeding the operability of the system. Um, you look at the baseboard management controller, which is the kind of the computer within the computer, there is a, uh, there is an element in the machine that needs to handle environmentals, that needs to handle, uh, operate the fans and so on. [00:15:31] Bryan: Uh, and that traditionally has this, the space board management controller, and that architecturally just hasn't improved in the last two decades. And, you know, that's, it's a proprietary piece of silicon. Generally from a company that no one's ever heard of called a Speed, uh, which has to be, is written all on caps, so I guess it needs to be screamed. [00:15:50] Bryan: Um, a speed has a proprietary part that has a, there is a root password infamously there, is there, the root password is encoded effectively in silicon. So, uh, which is just, and for, um, anyone who kind of goes deep into these things, like, oh my God, are you kidding me? Um, when we first started oxide, the wifi password was a fraction of the a speed root password for the bmc. [00:16:16] Bryan: It's kinda like a little, little BMC humor. Um, but those things, it was just dispiriting that, that the, the state-of-the-art was still basically personal computers running in the data center. Um, and that's part of what, what was the motivation for doing something new? [00:16:32] Jeremy: And for the people using these systems, whether it's the baseboard management controller or it's the The BIOS or UF UEFI component, what are the actual problems that people are seeing seen? Security vulnerabilities and poor practices in the BMC [00:16:51] Bryan: Oh man, I, the, you are going to have like some fraction of your listeners, maybe a big fraction where like, yeah, like what are the problems? That's a good question. And then you're gonna have the people that actually deal with these things who are, did like their heads already hit the desk being like, what are the problems? [00:17:06] Bryan: Like what are the non problems? Like what, what works? Actually, that's like a shorter answer. Um, I mean, there are so many problems and a lot of it is just like, I mean, there are problems just architecturally these things are just so, I mean, and you could, they're the problems spread to the horizon, so you can kind of start wherever you want. [00:17:24] Bryan: But I mean, as like, as a really concrete example. Okay, so the, the BMCs that, that the computer within the computer that needs to be on its own network. So you now have like not one network, you got two networks that, and that network, by the way, it, that's the network that you're gonna log into to like reset the machine when it's otherwise unresponsive. [00:17:44] Bryan: So that going into the BMC, you can are, you're able to control the entire machine. Well it's like, alright, so now I've got a second net network that I need to manage. What is running on the BMC? Well, it's running some. Ancient, ancient version of Linux it that you got. It's like, well how do I, how do I patch that? [00:18:02] Bryan: How do I like manage the vulnerabilities with that? Because if someone is able to root your BMC, they control the system. So it's like, this is not you've, and now you've gotta go deal with all of the operational hair around that. How do you upgrade that system updating the BMC? I mean, it's like you've got this like second shadow bad infrastructure that you have to go manage. [00:18:23] Bryan: Generally not open source. There's something called open BMC, um, which, um, you people use to varying degrees, but you're generally stuck with the proprietary BMC, so you're generally stuck with, with iLO from HPE or iDRAC from Dell or, or, uh, the, uh, su super micros, BMC, that H-P-B-M-C, and you are, uh, it is just excruciating pain. [00:18:49] Bryan: Um, and that this is assuming that by the way, that everything is behaving correctly. The, the problem is that these things often don't behave correctly, and then the consequence of them not behaving correctly. It's really dire because it's at that lowest layer of the system. So, I mean, I'll give you a concrete example. [00:19:07] Bryan: a customer of theirs reported to me, so I won't disclose the vendor, but let's just say that a well-known vendor had an issue with their, their temperature sensors were broken. Um, and the thing would always read basically the wrong value. So it was the BMC that had to like, invent its own ki a different kind of thermal control loop. [00:19:28] Bryan: And it would index on the, on the, the, the, the actual inrush current. It would, they would look at that at the current that's going into the CPU to adjust the fan speed. That's a great example of something like that's a, that's an interesting idea. That doesn't work. 'cause that's actually not the temperature. [00:19:45] Bryan: So like that software would crank the fans whenever you had an inrush of current and this customer had a workload that would spike the current and by it, when it would spike the current, the, the, the fans would kick up and then they would slowly degrade over time. Well, this workload was spiking the current faster than the fans would degrade, but not fast enough to actually heat up the part. [00:20:08] Bryan: And ultimately over a very long time, in a very painful investigation, it's customer determined that like my fans are cranked in my data center for no reason. We're blowing cold air. And it's like that, this is on the order of like a hundred watts, a server of, of energy that you shouldn't be spending and like that ultimately what that go comes down to this kind of broken software hardware interface at the lowest layer that has real meaningful consequence, uh, in terms of hundreds of kilowatts, um, across a data center. So this stuff has, has very, very, very real consequence and it's such a shadowy world. Part of the reason that, that your listeners that have dealt with this, that our heads will hit the desk is because it is really aggravating to deal with problems with this layer. [00:21:01] Bryan: You, you feel powerless. You don't control or really see the software that's on them. It's generally proprietary. You are relying on your vendor. Your vendor is telling you that like, boy, I don't know. You're the only customer seeing this. I mean, the number of times I have heard that for, and I, I have pledged that we're, we're not gonna say that at oxide because it's such an unaskable thing to say like, you're the only customer saying this. [00:21:25] Bryan: It's like, it feels like, are you blaming me for my problem? Feels like you're blaming me for my problem? Um, and what you begin to realize is that to a degree, these folks are speaking their own truth because the, the folks that are running at real scale at Hyperscale, those folks aren't Dell, HP super micro customers. [00:21:46] Bryan: They're actually, they've done their own thing. So it's like, yeah, Dell's not seeing that problem, um, because they're not running at the same scale. Um, but when you do run, you only have to run at modest scale before these things just become. Overwhelming in terms of the, the headwind that they present to people that wanna deploy infrastructure. The problem is felt with just a few racks [00:22:05] Jeremy: Yeah, so maybe to help people get some perspective at, at what point do you think that people start noticing or start feeling these problems? Because I imagine that if you're just have a few racks or [00:22:22] Bryan: do you have a couple racks or the, or do you wonder or just wondering because No, no, no. I would think, I think anyone who deploys any number of servers, especially now, especially if your experience is only in the cloud, you're gonna be like, what the hell is this? I mean, just again, just to get this thing working at all. [00:22:39] Bryan: It is so it, it's so hairy and so congealed, right? It's not designed. Um, and it, it, it, it's accreted it and it's so obviously accreted that you are, I mean, nobody who is setting up a rack of servers is gonna think to themselves like, yes, this is the right way to go do it. This all makes sense because it's, it's just not, it, I, it feels like the kit, I mean, kit car's almost too generous because it implies that there's like a set of plans to work to in the end. [00:23:08] Bryan: Uh, I mean, it, it, it's a bag of bolts. It's a bunch of parts that you're putting together. And so even at the smallest scales, that stuff is painful. Just architecturally, it's painful at the small scale then, but at least you can get it working. I think the stuff that then becomes debilitating at larger scale are the things that are, are worse than just like, I can't, like this thing is a mess to get working. [00:23:31] Bryan: It's like the, the, the fan issue that, um, where you are now seeing this over, you know, hundreds of machines or thousands of machines. Um, so I, it is painful at more or less all levels of scale. There's, there is no level at which the, the, the pc, which is really what this is, this is a, the, the personal computer architecture from the 1980s and there is really no level of scale where that's the right unit. Running elastic infrastructure is the hardware but also, hypervisor, distributed database, api, etc [00:23:57] Bryan: I mean, where that's the right thing to go deploy, especially if what you are trying to run. Is elastic infrastructure, a cloud. Because the other thing is like we, we've kinda been talking a lot about that hardware layer. Like hardware is, is just the start. Like you actually gotta go put software on that and actually run that as elastic infrastructure. [00:24:16] Bryan: So you need a hypervisor. Yes. But you need a lot more than that. You, you need to actually, you, you need a distributed database, you need web endpoints. You need, you need a CLI, you need all the stuff that you need to actually go run an actual service of compute or networking or storage. I mean, and for, for compute, even for compute, there's a ton of work to be done. [00:24:39] Bryan: And compute is by far, I would say the simplest of the, of the three. When you look at like networks, network services, storage services, there's a whole bunch of stuff that you need to go build in terms of distributed systems to actually offer that as a cloud. So it, I mean, it is painful at more or less every LE level if you are trying to deploy cloud computing on. What's a control plane? [00:25:00] Jeremy: And for someone who doesn't have experience building or working with this type of infrastructure, when you talk about a control plane, what, what does that do in the context of this system? [00:25:16] Bryan: So control plane is the thing that is, that is everything between your API request and that infrastructure actually being acted upon. So you go say, Hey, I, I want a provision, a vm. Okay, great. We've got a whole bunch of things we're gonna provision with that. We're gonna provision a vm, we're gonna get some storage that's gonna go along with that, that's got a network storage service that's gonna come out of, uh, we've got a virtual network that we're gonna either create or attach to. [00:25:39] Bryan: We've got a, a whole bunch of things we need to go do for that. For all of these things, there are metadata components that need, we need to keep track of this thing that, beyond the actual infrastructure that we create. And then we need to go actually, like act on the actual compute elements, the hostos, what have you, the switches, what have you, and actually go. [00:25:56] Bryan: Create these underlying things and then connect them. And there's of course, the challenge of just getting that working is a big challenge. Um, but getting that working robustly, getting that working is, you know, when you go to provision of vm, um, the, all the, the, the steps that need to happen and what happens if one of those steps fails along the way? [00:26:17] Bryan: What happens if, you know, one thing we're very mindful of is these kind of, you get these long tails of like, why, you know, generally our VM provisioning happened within this time, but we get these long tails where it takes much longer. What's going on? What, where in this process are we, are we actually spending time? [00:26:33] Bryan: Uh, and there's a whole lot of complexity that you need to go deal with that. There's a lot of complexity that you need to go deal with this effectively, this workflow that's gonna go create these things and manage them. Um, we use a, a pattern that we call, that are called sagas, actually is a, is a database pattern from the eighties. [00:26:51] Bryan: Uh, Katie McCaffrey is a, is a database reCrcher who, who, uh, I, I think, uh, reintroduce the idea of, of sagas, um, in the last kind of decade. Um, and this is something that we picked up, um, and I've done a lot of really interesting things with, um, to allow for, to this kind of, these workflows to be, to be managed and done so robustly in a way that you can restart them and so on. [00:27:16] Bryan: Uh, and then you guys, you get this whole distributed system that can do all this. That whole distributed system, that itself needs to be reliable and available. So if you, you know, you need to be able to, what happens if you, if you pull a sled or if a sled fails, how does the system deal with that? [00:27:33] Bryan: How does the system deal with getting an another sled added to the system? Like how do you actually grow this distributed system? And then how do you update it? How do you actually go from one version to the next? And all of that has to happen across an air gap where this is gonna run as part of the computer. [00:27:49] Bryan: So there are, it, it is fractally complicated. There, there is a lot of complexity here in, in software, in the software system and all of that. We kind of, we call the control plane. Um, and it, this is the what exists at AWS at GCP, at Azure. When you are hitting an endpoint that's provisioning an EC2 instance for you. [00:28:10] Bryan: There is an AWS control plane that is, is doing all of this and has, uh, some of these similar aspects and certainly some of these similar challenges. Are vSphere / Proxmox / Hyper-V in the same category? [00:28:20] Jeremy: And for people who have run their own servers with something like say VMware or Hyper V or Proxmox, are those in the same category? [00:28:32] Bryan: Yeah, I mean a little bit. I mean, it kind of like vSphere Yes. Via VMware. No. So it's like you, uh, VMware ESX is, is kind of a key building block upon which you can build something that is a more meaningful distributed system. When it's just like a machine that you're provisioning VMs on, it's like, okay, well that's actually, you as the human might be the control plane. [00:28:52] Bryan: Like, that's, that, that's, that's a much easier problem. Um, but when you've got, you know, tens, hundreds, thousands of machines, you need to do it robustly. You need something to coordinate that activity and you know, you need to pick which sled you land on. You need to be able to move these things. You need to be able to update that whole system. [00:29:06] Bryan: That's when you're getting into a control plane. So, you know, some of these things have kind of edged into a control plane, certainly VMware. Um, now Broadcom, um, has delivered something that's kind of cloudish. Um, I think that for folks that are truly born on the cloud, it, it still feels somewhat, uh, like you're going backwards in time when you, when you look at these kind of on-prem offerings. [00:29:29] Bryan: Um, but, but it, it, it's got these aspects to it for sure. Um, and I think that we're, um, some of these other things when you're just looking at KVM or just looks looking at Proxmox you kind of need to, to connect it to other broader things to turn it into something that really looks like manageable infrastructure. [00:29:47] Bryan: And then many of those projects are really, they're either proprietary projects, uh, proprietary products like vSphere, um, or you are really dealing with open source projects that are. Not necessarily aimed at the same level of scale. Um, you know, you look at a, again, Proxmox or, uh, um, you'll get an OpenStack. [00:30:05] Bryan: Um, and you know, OpenStack is just a lot of things, right? I mean, OpenStack has got so many, the OpenStack was kind of a, a free for all, for every infrastructure vendor. Um, and I, you know, there was a time people were like, don't you, aren't you worried about all these companies together that, you know, are coming together for OpenStack? [00:30:24] Bryan: I'm like, haven't you ever worked for like a company? Like, companies don't get along. By the way, it's like having multiple companies work together on a thing that's bad news, not good news. And I think, you know, one of the things that OpenStack has definitely struggled with, kind of with what, actually the, the, there's so many different kind of vendor elements in there that it's, it's very much not a product, it's a project that you're trying to run. [00:30:47] Bryan: But that's, but that very much is in, I mean, that's, that's similar certainly in spirit. [00:30:53] Jeremy: And so I think this is kind of like you're alluding to earlier, the piece that allows you to allocate, compute, storage, manage networking, gives you that experience of I can go to a web console or I can use an API and I can spin up machines, get them all connected. At the end of the day, the control plane. Is allowing you to do that in hopefully a user-friendly way. [00:31:21] Bryan: That's right. Yep. And in the, I mean, in order to do that in a modern way, it's not just like a user-friendly way. You really need to have a CLI and a web UI and an API. Those all need to be drawn from the same kind of single ground truth. Like you don't wanna have any of those be an afterthought for the other. [00:31:39] Bryan: You wanna have the same way of generating all of those different endpoints and, and entries into the system. Building a control plane now has better tools (Rust, CockroachDB) [00:31:46] Jeremy: And if you take your time at Joyent as an example. What kind of tools existed for that versus how much did you have to build in-house for as far as the hypervisor and managing the compute and all that? [00:32:02] Bryan: Yeah, so we built more or less everything in house. I mean, what you have is, um, and I think, you know, over time we've gotten slightly better tools. Um, I think, and, and maybe it's a little bit easier to talk about the, kind of the tools we started at Oxide because we kind of started with a, with a clean sheet of paper at oxide. [00:32:16] Bryan: We wanted to, knew we wanted to go build a control plane, but we were able to kind of go revisit some of the components. So actually, and maybe I'll, I'll talk about some of those changes. So when we, at, For example, at Joyent, when we were building a cloud at Joyent, there wasn't really a good distributed database. [00:32:34] Bryan: Um, so we were using Postgres as our database for metadata and there were a lot of challenges. And Postgres is not a distributed database. It's running. With a primary secondary architecture, and there's a bunch of issues there, many of which we discovered the hard way. Um, when we were coming to oxide, you have much better options to pick from in terms of distributed databases. [00:32:57] Bryan: You know, we, there was a period that now seems maybe potentially brief in hindsight, but of a really high quality open source distributed databases. So there were really some good ones to, to pick from. Um, we, we built on CockroachDB on CRDB. Um, so that was a really important component. That we had at oxide that we didn't have at Joyent. [00:33:19] Bryan: Um, so we were, I wouldn't say we were rolling our own distributed database, we were just using Postgres and uh, and, and dealing with an enormous amount of pain there in terms of the surround. Um, on top of that, and, and, you know, a, a control plane is much more than a database, obviously. Uh, and you've gotta deal with, uh, there's a whole bunch of software that you need to go, right. [00:33:40] Bryan: Um, to be able to, to transform these kind of API requests into something that is reliable infrastructure, right? And there, there's a lot to that. Uh, especially when networking gets in the mix, when storage gets in the mix, uh, there are a whole bunch of like complicated steps that need to be done, um, at Joyent. [00:33:59] Bryan: Um, we, in part because of the history of the company and like, look. This, this just is not gonna sound good, but it just is what it is and I'm just gonna own it. We did it all in Node, um, at Joyent, which I, I, I know it sounds really right now, just sounds like, well, you, you built it with Tinker Toys. You Okay. [00:34:18] Bryan: Uh, did, did you think it was, you built the skyscraper with Tinker Toys? Uh, it's like, well, okay. We actually, we had greater aspirations for the Tinker Toys once upon a time, and it was better than, you know, than Twisted Python and Event Machine from Ruby, and we weren't gonna do it in Java. All right. [00:34:32] Bryan: So, but let's just say that that experiment, uh, that experiment did ultimately end in a predictable fashion. Um, and, uh, we, we decided that maybe Node was not gonna be the best decision long term. Um, Joyent was the company behind node js. Uh, back in the day, Ryan Dahl worked for Joyent. Uh, and then, uh, then we, we, we. [00:34:53] Bryan: Uh, landed that in a foundation in about, uh, what, 2015, something like that. Um, and began to consider our world beyond, uh, beyond Node. Rust at Oxide [00:35:04] Bryan: A big tool that we had in the arsenal when we started Oxide is Rust. Um, and so indeed the name of the company is, is a tip of the hat to the language that we were pretty sure we were gonna be building a lot of stuff in. [00:35:16] Bryan: Namely Rust. And, uh, rust is, uh, has been huge for us, a very important revolution in programming languages. you know, there, there, there have been different people kind of coming in at different times and I kinda came to Rust in what I, I think is like this big kind of second expansion of rust in 2018 when a lot of technologists were think, uh, sick of Node and also sick of Go. [00:35:43] Bryan: And, uh, also sick of C++. And wondering is there gonna be something that gives me the, the, the performance, of that I get outta C. The, the robustness that I can get out of a C program but is is often difficult to achieve. but can I get that with kind of some, some of the velocity of development, although I hate that term, some of the speed of development that you get out of a more interpreted language. [00:36:08] Bryan: Um, and then by the way, can I actually have types, I think types would be a good idea? Uh, and rust obviously hits the sweet spot of all of that. Um, it has been absolutely huge for us. I mean, we knew when we started the company again, oxide, uh, we were gonna be using rust in, in quite a, quite a. Few places, but we weren't doing it by fiat. [00:36:27] Bryan: Um, we wanted to actually make sure we're making the right decision, um, at, at every different, at every layer. Uh, I think what has been surprising is the sheer number of layers at which we use rust in terms of, we've done our own embedded firmware in rust. We've done, um, in, in the host operating system, which is still largely in C, but very big components are in rust. [00:36:47] Bryan: The hypervisor Propolis is all in rust. Uh, and then of course the control plane, that distributed system on that is all in rust. So that was a very important thing that we very much did not need to build ourselves. We were able to really leverage, uh, a terrific community. Um. We were able to use, uh, and we've done this at Joyent as well, but at Oxide, we've used Illumos as a hostos component, which, uh, our variant is called Helios. [00:37:11] Bryan: Um, we've used, uh, bhyve um, as a, as as that kind of internal hypervisor component. we've made use of a bunch of different open source components to build this thing, um, which has been really, really important for us. Uh, and open source components that didn't exist even like five years prior. [00:37:28] Bryan: That's part of why we felt that 2019 was the right time to start the company. And so we started Oxide. The problems building a control plane in Node [00:37:34] Jeremy: You had mentioned that at Joyent, you had tried to build this in, in Node. What were the, what were the, the issues or the, the challenges that you had doing that? [00:37:46] Bryan: Oh boy. Yeah. again, we, I kind of had higher hopes in 2010, I would say. When we, we set on this, um, the, the, the problem that we had just writ large, um. JavaScript is really designed to allow as many people on earth to write a program as possible, which is good. I mean, I, I, that's a, that's a laudable goal. [00:38:09] Bryan: That is the goal ultimately of such as it is of JavaScript. It's actually hard to know what the goal of JavaScript is, unfortunately, because Brendan Ike never actually wrote a book. so that there is not a canonical, you've got kind of Doug Crockford and other people who've written things on JavaScript, but it's hard to know kind of what the original intent of JavaScript is. [00:38:27] Bryan: The name doesn't even express original intent, right? It was called Live Script, and it was kind of renamed to JavaScript during the Java Frenzy of the late nineties. A name that makes no sense. There is no Java in JavaScript. that is kind of, I think, revealing to kind of the, uh, the unprincipled mess that is JavaScript. [00:38:47] Bryan: It, it, it's very pragmatic at some level, um, and allows anyone to, it makes it very easy to write software. The problem is it's much more difficult to write really rigorous software. So, uh, and this is what I should differentiate JavaScript from TypeScript. This is really what TypeScript is trying to solve. [00:39:07] Bryan: TypeScript is like. How can, I think TypeScript is a, is a great step forward because TypeScript is like, how can we bring some rigor to this? Like, yes, it's great that it's easy to write JavaScript, but that's not, we, we don't wanna do that for Absolutely. I mean that, that's not the only problem we solve. [00:39:23] Bryan: We actually wanna be able to write rigorous software and it's actually okay if it's a little harder to write rigorous software that's actually okay if it gets leads to, to more rigorous artifacts. Um, but in JavaScript, I mean, just a concrete example. You know, there's nothing to prevent you from referencing a property that doesn't actually exist in JavaScript. [00:39:43] Bryan: So if you fat finger a property name, you are relying on something to tell you. By the way, I think you've misspelled this because there is no type definition for this thing. And I don't know that you've got one that's spelled correctly, one that's spelled incorrectly, that's often undefined. And then the, when you actually go, you say you've got this typo that is lurking in your what you want to be rigorous software. [00:40:07] Bryan: And if you don't execute that code, like you won't know that's there. And then you do execute that code. And now you've got a, you've got an undefined object. And now that's either gonna be an exception or it can, again, depends on how that's handled. It can be really difficult to determine the origin of that, of, of that error, of that programming. [00:40:26] Bryan: And that is a programmer error. And one of the big challenges that we had with Node is that programmer errors and operational errors, like, you know, I'm out of disk space as an operational error. Those get conflated and it becomes really hard. And in fact, I think the, the language wanted to make it easier to just kind of, uh, drive on in the event of all errors. [00:40:53] Bryan: And it's like, actually not what you wanna do if you're trying to build a reliable, robust system. So we had. No end of issues. [00:41:01] Bryan: We've got a lot of experience developing rigorous systems, um, again coming out of operating systems development and so on. And we want, we brought some of that rigor, if strangely, to JavaScript. So one of the things that we did is we brought a lot of postmortem, diagnos ability and observability to node. [00:41:18] Bryan: And so if, if one of our node processes. Died in production, we would actually get a core dump from that process, a core dump that we could actually meaningfully process. So we did a bunch of kind of wild stuff. I mean, actually wild stuff where we could actually make sense of the JavaScript objects in a binary core dump. JavaScript values ease of getting started over robustness [00:41:41] Bryan: Um, and things that we thought were really important, and this is the, the rest of the world just looks at this being like, what the hell is this? I mean, it's so out of step with it. The problem is that we were trying to bridge two disconnected cultures of one developing really. Rigorous software and really designing it for production, diagnosability and the other, really designing it to software to run in the browser and for anyone to be able to like, you know, kind of liven up a webpage, right? [00:42:10] Bryan: Is kinda the origin of, of live script and then JavaScript. And we were kind of the only ones sitting at the intersection of that. And you begin when you are the only ones sitting at that kind of intersection. You just are, you're, you're kind of fighting a community all the time. And we just realized that we are, there were so many things that the community wanted to do that we felt are like, no, no, this is gonna make software less diagnosable. It's gonna make it less robust. The NodeJS split and why people left [00:42:36] Bryan: And then you realize like, I'm, we're the only voice in the room because we have got, we have got desires for this language that it doesn't have for itself. And this is when you realize you're in a bad relationship with software. It's time to actually move on. And in fact, actually several years after, we'd already kind of broken up with node. [00:42:55] Bryan: Um, and it was like, it was a bit of an acrimonious breakup. there was a, uh, famous slash infamous fork of node called IoJS Um, and this was viewed because people, the community, thought that Joyent was being what was not being an appropriate steward of node js and was, uh, not allowing more things to come into to, to node. [00:43:19] Bryan: And of course, the reason that we of course, felt that we were being a careful steward and we were actively resisting those things that would cut against its fitness for a production system. But it's some way the community saw it and they, and forked, um, and, and I think the, we knew before the fork that's like, this is not working and we need to get this thing out of our hands. Platform is a reflection of values node summit talk [00:43:43] Bryan: And we're are the wrong hands for this? This needs to be in a foundation. Uh, and so we kind of gone through that breakup, uh, and maybe it was two years after that. That, uh, friend of mine who was um, was running the, uh, the node summit was actually, it's unfortunately now passed away. Charles er, um, but Charles' venture capitalist great guy, and Charles was running Node Summit and came to me in 2017. [00:44:07] Bryan: He is like, I really want you to keynote Node Summit. And I'm like, Charles, I'm not gonna do that. I've got nothing nice to say. Like, this is the, the, you don't want, I'm the last person you wanna keynote. He's like, oh, if you have nothing nice to say, you should definitely keynote. You're like, oh God, okay, here we go. [00:44:22] Bryan: He's like, no, I really want you to talk about, like, you should talk about the Joyent breakup with NodeJS. I'm like, oh man. [00:44:29] Bryan: And that led to a talk that I'm really happy that I gave, 'cause it was a very important talk for me personally. Uh, called Platform is a reflection of values and really looking at the values that we had for Node and the values that Node had for itself. And they didn't line up. [00:44:49] Bryan: And the problem is that the values that Node had for itself and the values that we had for Node are all kind of positives, right? Like there's nobody in the node community who's like, I don't want rigor, I hate rigor. It's just that if they had the choose between rigor and making the language approachable. [00:45:09] Bryan: They would choose approachability every single time. They would never choose rigor. And, you know, that was a, that was a big eye-opener. I do, I would say, if you watch this talk. [00:45:20] Bryan: because I knew that there's, like, the audience was gonna be filled with, with people who, had been a part of the fork in 2014, I think was the, the, the, the fork, the IOJS fork. And I knew that there, there were, there were some, you know, some people that were, um, had been there for the fork and. [00:45:41] Bryan: I said a little bit of a trap for the audience. But the, and the trap, I said, you know what, I, I kind of talked about the values that we had and the aspirations we had for Node, the aspirations that Node had for itself and how they were different. [00:45:53] Bryan: And, you know, and I'm like, look in, in, in hindsight, like a fracture was inevitable. And in 2014 there was finally a fracture. And do people know what happened in 2014? And if you, if you, you could listen to that talk, everyone almost says in unison, like IOJS. I'm like, oh right. IOJS. Right. That's actually not what I was thinking of. [00:46:19] Bryan: And I go to the next slide and is a tweet from a guy named TJ Holloway, Chuck, who was the most prolific contributor to Node. And it was his tweet also in 2014 before the fork, before the IOJS fork explaining that he was leaving Node and that he was going to go. And you, if you turn the volume all the way up, you can hear the audience gasp. [00:46:41] Bryan: And it's just delicious because the community had never really come, had never really confronted why TJ left. Um, there. And I went through a couple folks, Felix, bunch of other folks, early Node folks. That were there in 2010, were leaving in 2014, and they were going to go primarily, and they were going to go because they were sick of the same things that we were sick of. [00:47:09] Bryan: They, they, they had hit the same things that we had hit and they were frustrated. I I really do believe this, that platforms do reflect their own values. And when you are making a software decision, you are selecting value. [00:47:26] Bryan: You should select values that align with the values that you have for that software. That is, those are, that's way more important than other things that people look at. I think people look at, for example, quote unquote community size way too frequently, community size is like. Eh, maybe it can be fine. [00:47:44] Bryan: I've been in very large communities, node. I've been in super small open source communities like AUMs and RAs, a bunch of others. there are strengths and weaknesses to both approaches just as like there's a strength to being in a big city versus a small town. Me personally, I'll take the small community more or less every time because the small community is almost always self-selecting based on values and just for the same reason that I like working at small companies or small teams. [00:48:11] Bryan: There's a lot of value to be had in a small community. It's not to say that large communities are valueless, but again, long answer to your question of kind of where did things go south with Joyent and node. They went south because the, the values that we had and the values the community had didn't line up and that was a very educational experience, as you might imagine. [00:48:33] Jeremy: Yeah. And, and given that you mentioned how, because of those values, some people moved from Node to go, and in the end for much of what oxide is building. You ended up using rust. What, what would you say are the, the values of go and and rust, and how did you end up choosing Rust given that. Go's decisions regarding generics, versioning, compilation speed priority [00:48:56] Bryan: Yeah, I mean, well, so the value for, yeah. And so go, I mean, I understand why people move from Node to Go, go to me was kind of a lateral move. Um, there were a bunch of things that I, uh, go was still garbage collected, um, which I didn't like. Um, go also is very strange in terms of there are these kind of like. [00:49:17] Bryan: These autocratic kind of decisions that are very bizarre. Um, there, I mean, generics is kind of a famous one, right? Where go kind of as a point of principle didn't have generics, even though go itself actually the innards of go did have generics. It's just that you a go user weren't allowed to have them. [00:49:35] Bryan: And you know, it's kind of, there was, there was an old cartoon years and years ago about like when a, when a technologist is telling you that something is technically impossible, that actually means I don't feel like it. Uh, and there was a certain degree of like, generics are technically impossible and go, it's like, Hey, actually there are. [00:49:51] Bryan: And so there was, and I just think that the arguments against generics were kind of disingenuous. Um, and indeed, like they ended up adopting generics and then there's like some super weird stuff around like, they're very anti-assertion, which is like, what, how are you? Why are you, how is someone against assertions, it doesn't even make any sense, but it's like, oh, nope. [00:50:10] Bryan: Okay. There's a whole scree on it. Nope, we're against assertions and the, you know, against versioning. There was another thing like, you know, the Rob Pike has kind of famously been like, you should always just run on the way to commit. And you're like, does that, is that, does that make sense? I mean this, we actually built it. [00:50:26] Bryan: And so there are a bunch of things like that. You're just like, okay, this is just exhausting and. I mean, there's some things about Go that are great and, uh, plenty of other things that I just, I'm not a fan of. Um, I think that the, in the end, like Go cares a lot about like compile time. It's super important for Go Right? [00:50:44] Bryan: Is very quick, compile time. I'm like, okay. But that's like compile time is not like, it's not unimportant, it's doesn't have zero importance. But I've got other things that are like lots more important than that. Um, what I really care about is I want a high performing artifact. I wanted garbage collection outta my life. Don't think garbage collection has good trade offs [00:51:00] Bryan: I, I gotta tell you, I, I like garbage collection to me is an embodiment of this like, larger problem of where do you put cognitive load in the software development process. And what garbage collection is saying to me it is right for plenty of other people and the software that they wanna develop. [00:51:21] Bryan: But for me and the software that I wanna develop, infrastructure software, I don't want garbage collection because I can solve the memory allocation problem. I know when I'm like, done with something or not. I mean, it's like I, whether that's in, in C with, I mean it's actually like, it's really not that hard to not leak memory in, in a C base system. [00:51:44] Bryan: And you can. give yourself a lot of tooling that allows you to diagnose where memory leaks are coming from. So it's like that is a solvable problem. There are other challenges with that, but like, when you are developing a really sophisticated system that has garbage collection is using garbage collection. [00:51:59] Bryan: You spend as much time trying to dork with the garbage collector to convince it to collect the thing that you know is garbage. You are like, I've got this thing. I know it's garbage. Now I need to use these like tips and tricks to get the garbage collector. I mean, it's like, it feels like every Java performance issue goes to like minus xx call and use the other garbage collector, whatever one you're using, use a different one and using a different, a different approach. [00:52:23] Bryan: It's like, so you're, you're in this, to me, it's like you're in the worst of all worlds where. the reason that garbage collection is helpful is because the programmer doesn't have to think at all about this problem. But now you're actually dealing with these long pauses in production. [00:52:38] Bryan: You're dealing with all these other issues where actually you need to think a lot about it. And it's kind of, it, it it's witchcraft. It, it, it's this black box that you can't see into. So it's like, what problem have we solved exactly? And I mean, so the fact that go had garbage collection, it's like, eh, no, I, I do not want, like, and then you get all the other like weird fatwahs and you know, everything else. [00:52:57] Bryan: I'm like, no, thank you. Go is a no thank you for me, I, I get it why people like it or use it, but it's, it's just, that was not gonna be it. Choosing Rust [00:53:04] Bryan: I'm like, I want C. but I, there are things I didn't like about C too. I was looking for something that was gonna give me the deterministic kind of artifact that I got outta C. But I wanted library support and C is tough because there's, it's all convention. you know, there's just a bunch of other things that are just thorny. And I remember thinking vividly in 2018, I'm like, well, it's rust or bust. Ownership model, algebraic types, error handling [00:53:28] Bryan: I'm gonna go into rust. And, uh, I hope I like it because if it's not this, it's gonna like, I'm gonna go back to C I'm like literally trying to figure out what the language is for the back half of my career. Um, and when I, you know, did what a lot of people were doing at that time and people have been doing since of, you know, really getting into rust and really learning it, appreciating the difference in the, the model for sure, the ownership model people talk about. [00:53:54] Bryan: That's also obviously very important. It was the error handling that blew me away. And the idea of like algebraic types, I never really had algebraic types. Um, and the ability to, to have. And for error handling is one of these really, uh, you, you really appreciate these things where it's like, how do you deal with a, with a function that can either succeed and return something or it can fail, and the way c deals with that is bad with these kind of sentinels for errors. [00:54:27] Bryan: And, you know, does negative one mean success? Does negative one mean failure? Does zero mean failure? Some C functions, zero means failure. Traditionally in Unix, zero means success. And like, what if you wanna return a file descriptor, you know, it's like, oh. And then it's like, okay, then it'll be like zero through positive N will be a valid result. [00:54:44] Bryan: Negative numbers will be, and like, was it negative one and I said airo, or is it a negative number that did not, I mean, it's like, and that's all convention, right? People do all, all those different things and it's all convention and it's easy to get wrong, easy to have bugs, can't be statically checked and so on. Um, and then what Go says is like, well, you're gonna have like two return values and then you're gonna have to like, just like constantly check all of these all the time. Um, which is also kind of gross. Um, JavaScript is like, Hey, let's toss an exception. If, if we don't like something, if we see an error, we'll, we'll throw an exception. [00:55:15] Bryan: There are a bunch of reasons I don't like that. Um, and you look, you'll get what Rust does, where it's like, no, no, no. We're gonna have these algebra types, which is to say this thing can be a this thing or that thing, but it, but it has to be one of these. And by the way, you don't get to process this thing until you conditionally match on one of these things. [00:55:35] Bryan: You're gonna have to have a, a pattern match on this thing to determine if it's a this or a that, and if it in, in the result type that you, the result is a generic where it's like, it's gonna be either the thing that you wanna return. It's gonna be an okay that contains the thing you wanna return, or it's gonna be an error that contains your error and it forces your code to deal with that. [00:55:57] Bryan: And what that does is it shifts the cognitive load from the person that is operating this thing in production to the, the actual developer that is in development. And I think that that, that to me is like, I, I love that shift. Um, and that shift to me is really important. Um, and that's what I was missing, that that's what Rust gives you. [00:56:23] Bryan: Rust forces you to think about your code as you write it, but as a result, you have an artifact that is much more supportable, much more sustainable, and much faster. Prefer to frontload cognitive load during development instead of at runtime [00:56:34] Jeremy: Yeah, it sounds like you would rather take the time during the development to think about these issues because whether it's garbage collection or it's error handling at runtime when you're trying to solve a problem, then it's much more difficult than having dealt with it to start with. [00:56:57] Bryan: Yeah, absolutely. I, and I just think that like, why also, like if it's software, if it's, again, if it's infrastructure software, I mean the kinda the question that you, you should have when you're writing software is how long is this software gonna live? How many people are gonna use this software? Uh, and if you are writing an operating system, the answer for this thing that you're gonna write, it's gonna live for a long time. [00:57:18] Bryan: Like, if we just look at plenty of aspects of the system that have been around for a, for decades, it's gonna live for a long time and many, many, many people are gonna use it. Why would we not expect people writing that software to have more cognitive load when they're writing it to give us something that's gonna be a better artifact? [00:57:38] Bryan: Now conversely, you're like, Hey, I kind of don't care about this. And like, I don't know, I'm just like, I wanna see if this whole thing works. I've got, I like, I'm just stringing this together. I don't like, no, the software like will be lucky if it survives until tonight, but then like, who cares? Yeah. Yeah. [00:57:52] Bryan: Gar garbage clock. You know, if you're prototyping something, whatever. And this is why you really do get like, you know, different choices, different technology choices, depending on the way that you wanna solve the problem at hand. And for the software that I wanna write, I do like that cognitive load that is upfront. With LLMs maybe you can get the benefit of the robust artifact with less cognitive load [00:58:10] Bryan: Um, and although I think, I think the thing that is really wild that is the twist that I don't think anyone really saw coming is that in a, in an LLM age. That like the cognitive load upfront almost needs an asterisk on it because so much of that can be assisted by an LLM. And now, I mean, I would like to believe, and maybe this is me being optimistic, that the the, in the LLM age, we will see, I mean, rust is a great fit for the LLMH because the LLM itself can get a lot of feedback about whether the software that's written is correct or not. [00:58:44] Bryan: Much more so than you can for other environments. [00:58:48] Jeremy: Yeah, that is a interesting point in that I think when people first started trying out the LLMs to code, it was really good at these maybe looser languages like Python or JavaScript, and initially wasn't so good at something like Rust. But it sounds like as that improves, if. It can write it then because of the rigor or the memory management or the error handling that the language is forcing you to do, it might actually end up being a better choice for people using LLMs. [00:59:27] Bryan: absolutely. I, it, it gives you more certainty in the artifact that you've delivered. I mean, you know a lot about a Rust program that compiles correctly. I mean, th there are certain classes of errors that you don't have, um, that you actually don't know on a C program or a GO program or a, a JavaScript program. [00:59:46] Bryan: I think that's gonna be really important. I think we are on the cusp. Maybe we've already seen it, this kind of great bifurcation in the software that we writ

Why are Gartner investors so spooked by AI? And how is the AI infrastructure buildout supercharging Super Micro shares? Plus, what's behind the selloff of Coinbase shares? Host Jack Pitcher discusses the biggest stock moves of the week and the news that drove them. Sign up for the WSJ's free Markets A.M. newsletter. Learn more about your ad choices. Visit megaphone.fm/adchoices

Why are Gartner investors so spooked by AI? And how is the AI infrastructure buildout supercharging Super Micro shares? Plus, what's behind the selloff of Coinbase shares? Host Jack Pitcher discusses the biggest stock moves of the week and the news that drove them. Sign up for the WSJ's free Markets A.M. newsletter. Learn more about your ad choices. Visit megaphone.fm/adchoices

Supermicro's (SMCI) self-described "near-term margin pressure" didn't stop investors from buying shares of the company. Marley Kayden turns to the earnings drawing Wall Street back to the beaten-down tech stock. However, as Marley explains, analysts remain mixed on Supermicro's outlook. Prosper Trading Academy's Scott Bauer offers an example options trade for the stock. ======== Schwab Network ========Empowering every investor and trader, every market day.Options involve risks and are not suitable for all investors. Before trading, read the Options Disclosure Document. http://bit.ly/2v9tH6DSubscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/About Schwab Network - https://schwabnetwork.com/about

Markets digest a flood of major earnings while tech volatility takes center stage. Jim Cramer interviewed NVIDIA CEO Jensen Huang and talks the AI trade scrutiny. Huang weighs in on OpenAI's massive fundraising round. Ke reports from AMD, Amgen, Chipotle, Mondelez and Super Micro. Christopher Rolland, Senior Analyst at Susquehanna, analyzes what the AMD results mean for the broader semiconductor trade.Jackson Ader, Senior Research Analyst at KeyBanc, joins to discuss the ongoing software selloff, while Venu Krishna, Head of U.S. Equity Strategy at Barclays, offers insight on market positioning and earnings momentum. A look ahead to Alphabet's earnings with Gil Luria, Managing Director and Senior Software Analyst at D.A. Davidson. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

European bourses opened stronger, but sentiment has dipped off best levels; US equity futures are modestly firmer, with mild outperformance is seen in the NQ.DXY is flat, Antipodeans benefit from a rebound in metals prices with outperformance in the Aussie after the RBA hiked rates by 25bps (as expected), whilst the SoMP noted that underlying inflation is higher than expected.Fixed income on the backfoot with supply in focus in a shutdown-thinned US docket.Crude prices initially lower but now flat; India to stop importing Russian oil as part of the trade deal with the US. Metals rebound with spot gold returning above USD 4900/oz.Looking ahead, highlights include US RCM/TIPP (Feb), New Zealand Unemployment (Q4), Australian S&P PMIs Final (Jan), Speakers including Fed's Bowman, Barkin & ECB's Lagarde.December JOLTS has been postponed, on account of the US government shutdown. Earnings from AMD, Supermicro, Amgen, Amcor, PayPal, PepsiCo, Pfizer, Merck.Read the full report covering Equities, Forex, Fixed Income, Commodites and more on Newsquawk

We look back to look forward and predict whether three of 2025's biggest disappointments can turn it around in 2026. Can Super Micro Computer (NASDAQ: SMCI), Lululemon (NASDAQ: LULU), and Nike (NYSE: NKE) get back to beating the market? Tom King, Travis Hoium, and Tim Beyers discuss: - How losing faith with auditors cost Supermicro. - Whether fashion trends favor Lululemon. - The 2026 challenges facing Nike CEO Elliott Hill. Companies discussed: SMCI, LULU, NKE Host: Tim Beyers Guests: Tom King, Travis Hoium Producer: Anand Chokkavelu Engineer: Dan Boyd Disclosure: Advertisements are sponsored content and provided for informational purposes only. The Motley Fool and its affiliates (collectively, “TMF”) do not endorse, recommend, or verify the accuracy or completeness of the statements made within advertisements. TMF is not involved in the offer, sale, or solicitation of any securities advertised herein and makes no representations regarding the suitability, or risks associated with any investment opportunity presented. Investors should conduct their own due diligence and consult with legal, tax, and financial advisors before making any investment decisions. TMF assumes no responsibility for any losses or damages arising from this advertisement. We're committed to transparency: All personal opinions in advertisements from Fools are their own. The product advertised in this episode was loaned to TMF and was returned after a test period or the product advertised in this episode was purchased by TMF. Advertiser has paid for the sponsorship of this episode. Learn more about your ad choices. Visit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠megaphone.fm/adchoices Learn more about your ad choices. Visit megaphone.fm/adchoices

This week on Market Mondays we're getting tactical and long-term: your futures trading tip of the week, the biggest mistakes younger investors make chasing fast wins, and the most important investing lessons this year reinforced. We also get personal about the mindset shifts that matter—what we used to disagree with early on, then changed our mind about later, and the questions people should be asking if they actually want to build wealth over decades (not just catch a lucky trade).Then we dive into what's moving markets right now: Oracle as a business and investment, whether the AI narrative tied to SoftBank/OpenAI has pushed expectations too far, and what really caused Friday's sell-off—plus whether it quietly changed market structure more than most people realize. We break down the Coinbase vs. MicroStrategy vs. IBIT debate, talk about whether we're headed toward a real correction or just another emotional shakeout, and if the market is broadening beyond tech or setting up a head fake before leadership narrows again.We also hit the high-volatility conversations: Super Micro's relevance in AI infrastructure, how elite traders handle ES and NQ moving in sync, and whether leveraged ETFs like NVDL/AMDL are advanced tools—or long-term portfolio destroyers in disguise. Plus: quantum computing (obvious leaders vs. sleeper names), and a real discussion on how to balance fitness, family, investing, travel, and content creation without burning out. And we're joined by Derrick Hayes to talk about his business journey and what it really takes to scale.#MarketMondays #Investing #Stocks #FuturesTrading #DayTrading #LongTermInvesting #FinancialLiteracy #WealthBuilding #AI #Oracle #Crypto #Bitcoin #Coinbase #MicroStrategy #IBIT #ETFs #LeveragedETFs #NVDL #AMDL #TechStocks #MarketNews #TradingPsychology #RiskManagement #QuantumComputing #Entrepreneurship #DerrickHayes #EarnYourLeisureSupport this podcast at — https://redcircle.com/marketmondays/donationsAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Michel Amar, CEO of DigiPower X (DGXX), breaks down the stock's incredible six-month rise… how the company's Supermicro (SMCI) partnership will drive massive growth… and why DGXX's market cap could soar from $250M to over $2B. In this episode: Welcome back Michel Amar, CEO of DigiPower X [2:45] DGXX's incredible six-month rise: What's driving the upside? [3:12] How the Supermicro partnership will spur massive growth [7:13] Why DGXX's market cap could soar from $250M to over $2B [9:53] Investors shouldn't worry about stock dilution [23:22] DGXX is going all in on AI [29:09] 2026 and beyond: Growth forecasts [34:24] Our next Curzio One private placement is coming up [42:29] Did you like this episode? Get more Wall Street Unplugged FREE each week in your inbox. Sign up here: https://curzio.me/syn_wsu Find Wall Street Unplugged podcast… --Curzio Research App: https://curzio.me/syn_app --iTunes: https://curzio.me/syn_wsu_i --Stitcher: https://curzio.me/syn_wsu_s --Website: https://curzio.me/syn_wsu_cat Follow Frank… X: https://curzio.me/syn_twt Facebook: https://curzio.me/syn_fb LinkedIn: https://curzio.me/syn_li