Podcasts about VMS

VMs konstigaste match tas ned. Vad sysslade egentligen Frankrike med? England med sin första VM-medalj på 60 och vind i seglet in i EM om 2 år. Sedan fokus på VM-finalen ikväll, hur slutar den mellan läromästaren och eleven? Ta VM i mål med oss!Medverkande:Linus Rosenberg, Josip Ladan & Freddie ArnessonViva America görs i samarbete med:ATG:Vi gör Viva America tillsammans med ATG! Inför VM har vi tagit fram unika långtidsspel som ni hör i dessa avsnitt. Ni hittar spelen här: https://www.atg.se/sport#sports-hub/atg_special-odds/football/viva_fotboll_specialoddsO'Learys:O'Learys är såklart den givna platsen för sommarens mästerskap, vi pratar gemenskapen, den goda maten men också den otroliga stämningen som kommer infinna sig på alla deras 60 enheter som ni finner från norr till söder. In och boka bord på https://olearys.com/sv-se/Après:Après är våra favoriter när det kommer till vitt snus. Spana in de superlimiterade VM-tröjorna vi designat tillsammans med Après på apres.se, tillsammans med massa annat merch.Passa även på att kolla in sommarens Spritz-nyheter, som Hugo Spritz och Pink Spritz. Använd koden VIVA för 15% rabatt på din order. Och glöm inte att signa upp dig på Après nyhetsbrev så du inte missar något!NORD VPN:Uppgradera ditt onlineskydd med en heltäckande säkerhetsapp!Få ett exklusivt erbjudande på NordVPN + 4 månader extra här: https://nordvpn.com/vivaDu riskerar ingenting tack vare NordVPN:s 30-dagars återbetalningsgaranti!Kontakta redaktionen: linus@k26media.seVill ditt företag samarbeta med Viva fotboll? freddie@k26media.seSociala Medier:Instagram - https://www.instagram.com/viva_fotboll/Twitter - https://x.com/vivafotbollTikTok - https://www.tiktok.com/@vivafotboll Hosted on Acast. See acast.com/privacy for more information.

Det är lördag och Expressen Fotboll laddar upp inför kvällens bronsmatch mellan Frankrike och England – en match där "hedern" känns viktigare än bronset för två lite stukade fotbollsnationer. Vi synar skandalen kring VMs final domare och diskuterar varför Argentina har VM-historiens sämsta tatueringar. Dessutom lägger vi fullt fokus på Allsvenskan! Vi analyserar IFK Göteborgs vändning och Sam Larssons succécomeback, Häckens totala defensiva kollaps, Malmös fina start under nye sportchefen och Mjällbys oväntade kräftgång. Medverkande: Isak Dahlin, Andreas Brännström & Daniel Larsson Ansvarig utgivare: Karin Olsson

Det är lördag och Expressen Fotboll laddar upp inför kvällens bronsmatch mellan Frankrike och England – en match där "hedern" känns viktigare än bronset för två lite stukade fotbollsnationer. Vi synar skandalen kring VMs final domare och diskuterar varför Argentina har VM-historiens sämsta tatueringar. Dessutom lägger vi fullt fokus på Allsvenskan! Vi analyserar IFK Göteborgs vändning och Sam Larssons succécomeback, Häckens totala defensiva kollaps, Malmös fina start under nye sportchefen och Mjällbys oväntade kräftgång. Medverkande: Isak Dahlin, Andreas Brännström & Daniel Larsson Ansvarig utgivare: Karin Olsson

Hey friends! Fair warning: today's episode is a bit of an emotional rollercoaster — we've got a big security win, some honest lab feedback, and a very personal share about my dad's funeral. Buckle up. CARTP certified, baby! — I'm officially a Certified Azure Red Team Professional (CARTP), courtesy of the folks at Altered Security. It's been a long time coming (I originally signed up for the live version and fell off after missing a couple Saturdays), but I came back for the self-paced 30-day version and finally finished the job. The lab experience — the good: — ~25 objectives, a solid lab guide, and a really fun variety of attack paths. Highlights include stealing tokens, enumerating Azure tenants, attacking apps and VMs and key vaults, simulated phishing against real tenant email addresses, popping reverse shells, and some clever OneDrive-based follow-on attacks via session hijacking. There's even some web app pen testing (hello, server-side template injection!) sprinkled in. The lab experience — the not-so-good: — The included videos are… not my favorite format. Think notepad-on-screen copy-paste tutorials with zero context. To fill in the gaps, I leaned heavily on Claude — pasting blobs of the lab guide and asking things like "why did stealing this token give me X but not Y?" — and it did a great job standing in where a live instructor would normally add color and context. Exam tips (spoiler-free, I promise): — A few things that helped me: I had Claude build me a CliffsNotes study guide from all our study-session chats — token context, command flags, the works. Before hitting start on the 24-hour clock, I fed Claude a list of all the tools I'd been using in the lab and had it build a one-shot PowerShell script to pull them all down from GitHub onto a fresh Windows VM. If your exam lab environment fails to spin up (as mine did in the US region), just try a different region — UK worked great for me. Enumerate. Enumerate. Enumerate. Know your tools, know which ones cover which areas of an Azure tenancy, and know how to get more verbose/tabular output when you need it. Take screenshots and notes as you go — the lab closes after 24 hours and you've got 48 hours to submit your report, so if you forgot to grab a screenshot of a flag… you are SOL, my friend. The exam itself: — I started around 5:30 p.m., wrapped up around 11 p.m., and had the final flag captured, a full Word report drafted, and was in bed at a reasonable hour. Submitted the report the next morning after the gym and a mint hot cocoa, and had my pass confirmation back well within their 7-business-day window. Private pen test training is happening: — I'm currently running a private 3-day session of our Active Directory pen testing class (version 2.0 — it got a big facelift!). It's built on the Game of Active Directory platform and we fully pwn three separate domains over the course of three days. If you can send 3–7 people, reach out at 7MinSec.com/training to line up a private session. I'm also building an interest list for a public version later this fall (reach out if interested)! Also: check out 7MinSec.club — I dropped a little show-and-tell video over on 7MinSec.club this week giving you a peek at what the training looks like in action. Dad's funeral: — I shared some words at my dad's service this past Saturday and wanted to capture them here while they're fresh, since this podcast is basically my journal at this point. The service was perfect — very "him." He'd actually written funeral instructions (yes, they literally sat in a safety deposit box for years) specifying things like: max 10-minute message from the pastor, specific Bible verses, specific songs, and — my favorite — if the service runs over 45 minutes, someone needs to pull the fire alarm. He came up with that final instruction at his brother's funeral, which ran nearly two hours. He leaned over, squeezed my knee and said, "If my service goes over 45 minutes, pull the fire alarm." The song: — I played and sang at the service. The song was "Jesus Savior Pilot Me" — not a personal favorite of my dad's exactly, but he called it "the one about Jesus flying airplanes" after seeing me perform it years ago at the Minnesota State Fair chapel. I practiced it in the car on the way to Caribou every morning until I could get through it without crying. My guitar teacher's advice: close your eyes, focus on your fingers, and pretend you're just playing a tune in a room. It worked. Mostly. Thank you: — Seriously, so many of you have sent kind messages and I just want you to know it means the world. He taught me a lot about being a good dad, a good husband, and how to live with passion, a good attitude about your work, and a heart for serving others.

Nine Mile Metals CEO Patrick Cruickshank joined Steve Darling from Proactive to discuss encouraging results from drill hole DDH WD-26-03 at the company's Wedge Mine project, where drilling continues to expand copper-rich volcanogenic massive sulphide (VMS) mineralization. Cruickshank said the hole successfully intersected pyrite and chalcopyrite mineralization between 212.95 and 338.20 metres, extending mineralization identified in the previous WD-26-02 drill hole. The hole encountered multiple favourable geological units, including chlorite-altered sediments associated with sulphide mineralization—an important indicator of VMS footwall alteration. A significant felsic volcanic sequence also hosted widespread pyrite and chalcopyrite mineralization, along with traces of arsenopyrite, a recognized pathfinder element for gold. One of the key highlights was the intersection of 2.4 metres of massive sulphides between 309.60 and 312.00 metres, containing coarse visible chalcopyrite. Visual estimates indicate the interval contains approximately 40–50% pyrite and 4–7% chalcopyrite, with sulphide mineralization continuing to 338.20 metres. Cruickshank said each drill hole is being strategically fanned across the northern flank of the deposit under the guidance of Apex Geoscience, with every metre of core contributing to the company's evolving 3D geological model and NI 43-101 resource work. With the majority of its planned 10,000-metre drilling program still to come, the company is now awaiting analytical results from ALS Global while continuing exploration to further define and expand the Wedge Mine mineralized system. Management believes the latest drilling continues to demonstrate the scale and strength of the copper-dominant VMS system and supports the project's resource growth potential. #proactiveinvestors #ninemilemetlas #cse #nine #otc #vmxsxf #mining #wedgemine #CopperExploration #WedgeMine #VMS #MiningNews #CopperMining #NewBrunswickMining #CriticalMinerals #ExplorationDrilling #ResourceDiscovery

The first half of 2026 has been a historic year for small-cap stocks, which have delivered their best performance in 35 years! On this episode of Market Sense, a Fidelity portfolio manager breaks down the key forces behind the small-cap comeback, and how trends like infrastructure spending and reshoring can benefit from this asset class, and how small-cap stocks can enhance portfolio diversification. If you want more insights from our Fidelity portfolio managers regarding potential investing opportunities and risks, bookmark this page for the latest articles and videos. Read the full transcript View the slides Watch the video replay

Please visit answersincme.com/860/103093269-replay to participate, download slides and supporting materials, complete the post test, and get a certificate. Presented by Stephanie Faubion, MD, MBA, FACP, MSCP and Shelby Harris, PsyD, CBSM, DBSM. In this activity, experts in menopause discuss diagnosis and management of sleep disturbances due to vasomotor symptoms. Upon completion of this activity, participants should be better able to: Recognize the burden of menopause-related VMS occurring during sleep; Explain the clinical significance of the latest data for novel non-hormonal pharmacotherapies in the treatment of menopause-related VMS, including those occurring during sleep; Identify patients with menopause-related VMS and sleep disturbances who may benefit from a non-hormonal pharmacotherapy approach; and Formulate patient-centered management plans to enhance outcomes for patients with menopause-related VMS and sleep disturbances.

Was passiert eigentlich mit deinem digitalen Leben, wenn du von heute auf morgen nicht mehr verfügbar bist? Mit Social Media allein ist es längst nicht getan. Vielleicht hängen an dir Google- und Apple-Accounts, ein Passwortmanager, Zwei-Faktor-Authentifizierung, ein Homelab bei Hetzner, Self-Hosting mit Paperless oder Immich, Backups, Domains und sogar die Heimautomatisierung. Spätestens wenn wichtige Dokumente, Fotos oder das Internet zuhause nur noch über deine private Infrastruktur laufen, wird aus einer theoretischen Frage ein sehr praktisches Problem.In dieser Episode sprechen wir über digitales Erbe, digitalen Nachlass und reales Offboarding. Wir schauen auf rechtliche Grundlagen in Deutschland und Österreich, auf vererbbare Accounts, laufende Online-Abos, Facebook, Google, Apple und die Tücken von Passwortmanager, Recovery-Kontakten und Legacy-Zugängen. Außerdem diskutieren wir, warum Kontext wichtiger ist als nur Zugangsdaten, wie Dokumentation für Nicht-Techniker:innen aussehen kann und weshalb gutes Architekturdenken im Homelab oft mehr bringt als die x-te clevere Bastellösung.Wenn du Open Source, Self-Hosting, Tech Community und pragmatische Engineering-Fragen magst, ist diese Folge genau dein Ding. Denn am Ende geht es nicht nur um Server, VMs und Wallets, sondern um die Frage, wie du deine digitale Welt so organisierst, dass deine Familie im Ernstfall nicht im Debugging deines Lebens landet.Bonus. Vielleicht ist das wichtigste Feature deines Homelabs am Ende doch ein ganz normaler Lichtschalter.Unsere aktuellen Werbepartner findest du auf https://engineeringkiosk.dev/partnersDas schnelle Feedback zur Episode:

Overview: Listen in as expert faculty explore the neuroendocrine drivers of vasomotor symptoms (VMS)—including the KNDy neuron system—and review the efficacy and safety of emerging nonhormonal treatments. Expand your toolkit to deliver more informed, up-to-date care to patients experiencing menopause.

Det er blevet fredag, regnen siler ned både ude foran lydstudiet og på Roskilde Festival, som vi vender kort i dag, samtidig med at tale om VMs strabadser, før vi dykker ned i film om rejser. I anledning af Christopher Nolans kommende film, Odyseen, taler vi i dag om moderne odysseer. Alt fra musikalske rejser i Amerikas sydstater, til Dragqueens i Australiens ørken, og eventyrlige fantasier, der både tager os til Himalayas højder og 80'ernes fantasiverden. Værter: Tobias Gilbert, Sarah Eline Nygaard, Niels Otto Relsted og Nandi Botha

Interview with Max Porterfield, President and CEO, Visionary Copper & GoldOur previous interview: https://www.cruxinvestor.com/posts/visionary-copper-gold-tsxvvcg-2026-resource-growth-confidence-plan-at-point-leamington-9535Recording date: 25th June 2026Visionary Copper & Gold is advancing its flagship Point Leamington project in Newfoundland, a 43-101 compliant volcanogenic massive sulphide (VMS) deposit containing approximately 20 million tonnes of mineralized material. The near-surface resource hosts an estimated 500,000 ounces of gold and 170 million pounds of copper within 400 metres, providing a substantial foundation for future growth in a mining-friendly Canadian jurisdiction.A key recent development is the discovery of the “Kraken” zone, a copper-rich footwall stringer system located adjacent to the existing deposit. Initial drilling has returned broad copper intersections, including 75 metres grading 0.45% copper, with continuity confirmed across a 275-metre strike length. In comparable VMS systems, such footwall zones can represent a significant portion of total resources, suggesting Kraken could materially expand the project's scale.To advance this potential, the company plans a 20,000-metre Phase Two drilling campaign beginning in the second half of 2026. Most of the drilling will focus on upgrading the current resource to higher confidence categories and defining the extent of the Kraken discovery, while a smaller portion will test five additional regional targets across an expanded 30,000-hectare land package.The project benefits from strong infrastructure, including road access, hydroelectric power, and proximity to a deep-water port, which may help reduce future development costs. Investor confidence is reflected in a significant stake held by Ross Jennings of the Quaternary Group, who has accumulated over 11% ownership.Amid rising global demand for copper driven by electrification and energy transition trends, Visionary Copper & Gold is positioning Point Leamington as a potentially scalable, lower-cost development opportunity with meaningful exploration upside.Learn more: https://www.cruxinvestor.com/companies/visionary-copper-gold-minesSign up for Crux Investor: https://cruxinvestor.com

Slide into our VMs to hear all about it.

Interview with Patrick Cruickshank, Director & CEO of Nine Mile MetalsOur previous interview: https://www.cruxinvestor.com/posts/nine-miles-metals-csenine-record-copper-gold-grades-drive-2026-expansion-drilling-9179Recording date: 24th June 2026Nine Mile Metals Ltd. (CSE:NINE) is in an active phase of exploration at its Wedge project in the Bathurst Mining Camp, New Brunswick, a region with a substantial mining history but, in the company's view, considerable untested potential. The Wedge deposit was partially mined decades ago before falling commodity prices and operational constraints brought work to a halt, and historic records suggest only a fraction of the deposit was ever extracted. Nine Mile's current strategy is built on testing the ground that was left behind, both laterally and at depth.The company is midway through its largest drill programme to date, a 10,000-metre campaign that follows smaller efforts in the falls of 2024 and 2025. The current phase targets the eastern extension of the deposit, the western flank beyond a fault structure that disrupted earlier drilling, and the system's depth potential, alongside two additional target areas known as West Wedge and TriBag. Two completed holes have already returned long intervals of visible copper-bearing mineralisation, at 234 metres and 130 metres respectively, including a horizon at depth that does not appear in any historic record for the property. This is a meaningful distinction for investors: the company is exploring genuinely new ground rather than reinterpreting previously known mineralisation.Beyond these results, Nine Mile has identified three separate mineralised lenses within the Wedge system, including a high-grade copper zone that returned grades between 5% and 8% copper before a fault structure interrupted the original hole. The current programme is designed to re-approach that zone from the opposite side of the fault, with deeper holes planned to test both its lateral extent and how far the broader system continues at depth. The deposit's mineralogy varies across these lenses, with the company reporting a lead-zinc-rich zone, a high-grade copper zone, and intervals of elevated silver and gold, along with reported occurrences of antimony and indium. This polymetallic character is typical of VMS systems generally, though it also adds complexity to eventual resource estimation, since grade and metal mix differ from lens to lens.On the resource question, historic operators are understood to have extracted around two million tonnes from Wedge, with approximately half a million tonnes believed to remain. Nine Mile's own geophysical and 3D modelling work suggests the true figure may be larger, particularly given that current drilling sits outside historic mining areas entirely. Apex Geoscience, the company's technical advisor, is expected to deliver an updated NI 43-101 technical report by autumn 2026, incorporating the 2024 through 2026 drill programmes and potentially including indicated and inferred resource categories for the first time.On funding, the company states that its 2025 programme, which produced several of the high-grade intercepts referenced above, was completed on a modest budget, and that it does not currently require additional capital to execute the 2026 campaign, while remaining open to strategic investment. For investors, the combination of new discovery zones, a forthcoming resource update, and a stated funded position offers several catalysts to monitor over the coming months with all current results remain preliminary pending certified assay confirmation.View Nine Mile Metals' company profile: https://www.cruxinvestor.com/companies/nine-mile-metalsSign up for Crux Investor: https://cruxinvestor.com

Slide Into our VMs with us to find out.

You asked, we answer! On this episode of Market Sense, we are compiling all the top questions submitted by viewers every week and taking them to our guests. From the many different ways to consider thinking about the AI buildout, to potential opportunities in emerging markets, to questions about how much cash to set aside in retirement. Fidelity leaders will tackle it all. Plus, the latest market headlines in 20 minutes. We'd love to hear what you think! Take a minute to fill out our short feedback survey — to help us make Market Sense even more valuable to you. Read the full transcript View the slides Watch the video replay Fidelity has hired Slido to collect the responses generated by the survey in this event. Fidelity and Slido are independent entities and are not legally affiliated. Neither Fidelity nor Slido will use your feedback for individual marketing efforts. Neither Fidelity nor Slido will individually respond to any feedback you provide in the event survey unless required to do so by applicable law. Please do not include any personally identifiable information related to an account in your responses. If you have questions or comments that you would like Fidelity to follow up with you on, please contact Fidelity directly through your normal contact channel.

Meridian Mining CEO Gilbert Clark returns to Mining Stock Daily to provide an update on the company's rapidly advancing Cabaçal  Belt projects in Brazil, highlighted by a new discovery of stacked VMS mineralization at the Santa Helena Project. Gilbert discusses why the latest drill results could materially expand Santa Helena into a second development hub, while also providing updates on the Cabaçal  Definitive Feasibility Study, permitting progress, and ongoing project financing efforts. The conversation also explores Meridian's aggressive regional exploration strategy, the potential for additional discoveries across the belt, and how the company is positioning itself to become Brazil's next mid-tier copper-gold producer.

Exploring Mining host Cali Vanzant sits down for a follow-up podcast with Kevin Reid, President & CEO of Arizona Eagle Mines (TSX-V: AZEM). Kevin provides updates on the company's successful TSX-V listing as AZEM, upsized $8.6M financing at $1.10 per share, and strategy to acquire three past-producing high-grade silver mines along the McCabe trend—nearly doubling strike length with potential VMS deposits in mining friendly Yavapai County, Arizona. He discusses strong balance sheet with , and approximately 50% insider/management ownership (27M shares), high-grade gold drill results at the past-producing McCabe Mine, and district-scale precious metals assets on patented ground with existing infrastructure.About Kevin Reid, President and CEO, DirectorMr. Reid has a BSc. Honours in Geological Sciences from Queen's University, Kingston, and an MBA in Finance from the Schulich School of Business, Toronto. Mr. Reid has over 20 years of capital markets experience, beginning in the Equity Research department at CIBC World Markets in 2002, and then at both GMP Securities and Maxit Capital as a Managing Partner in the Investment Banking departments. Mr. Reid has acted as the lead advisor on numerous equity, debt and merger and acquisition transactions.About Arizona Eagle Mining Corp.Arizona Eagle is a mineral exploration company focused on the acquisition, exploration and development of mineral properties. Arizona Eagle's principal asset is the Eagle Project, a 4,169-acre property comprised of patented and unpatented claims located near the town of Prescott Valley in Yavapai County, Arizona. The Eagle Project is centered on the past-producing McCabe Mine, a high-grade gold-silver deposit, and includes multiple parallel structures hosting past-producing mines that remain largely untested by modern drilling. While Arizona Eagle's primary focus is on the exploration and development of the Eagle Project, it will continue to own Core Nickel's land portfolio in the Thompson Nickel Belt of northern Manitoba. https://www.arizonaeaglemining.com/ About Investorideas.com - Big Investing Ideas Investorideas.com is the go-to platform for big investing ideas. From breaking stock news to top-rated investing podcasts, we cover it all.Disclaimer/Disclosure: This podcast and article featuring Arizona Eagle Mining is paid for content as part of a monthly featured mining stock service (payment disclosure). Our site does not make recommendations for purchases or sale of stocks, services or products. Nothing on our sites should be construed as an offer or solicitation to buy or sell products or securities. All investing involves risk and possible losses. This is not investment opinion. This site is currently compensated for news publication and distribution, social media and marketing, content creation and more. Disclosure is posted for each compensated news release, content published /created if required but otherwise the news was not compensated for and was published for the sole interest of our readers and followers. Contact management and IR of each company directly regarding specific questions. More disclaimer info: https://www.investorideas.com/About/Disclaimer.asp Learn more about publishing your news release and our other news services on the Investorideas.com newswire https://www.investorideas.com/News-Upload/ Global investors must adhere to regulations of each country. Please read Investorideas.com privacy policy: https://www.investorideas.com/About/Private_Policy.asp Follow us on X @investorideas @Exploringmining

Is this bull market too good to be true? On this episode of Market Sense, our Fidelity leaders dig into the data points driving the recent solid economic growth and resilient earnings. We'll also discuss the potential peace agreement with Iran, the historic SpaceX IPO, and the forecast for interest rates as new Fed Chair Kevin Warsh presides over his first FOMC meeting. Position your portfolios for resilience and growth potential in the second half of 2026. Check out Fidelity's 2026 Midyear Outlook page for more insights on the markets, investing and taxes from our Fidelity pros. Read the full transcript View the slides Watch the video replay

Change can happen in an instant and 2026 has already reminded us how quickly the financial landscape can shift and create volatility. Yet through it all, the bull market has remained remarkably resilient. So, the question remains: can the momentum continue? Join the Market Sense team for a timely midyear conversation with Fidelity leaders about what's driving the current environment, and how the economic backdrop may shape the rest of the year. Bookmark the Fidelity Viewpoints 2026 Midyear Investing Outlook page for the latest on market headlines, risks, opportunities, and ways to potentially safeguard your retirement. Read the full transcript View the slides Watch the video replay

Slide Into Our “unhinged” VMs.

Hey friends! Backups are not as cool as pentesting, but boy do they matter when things go sideways. This week I'm sharing how a Proxmox backup disk space meltdown led me to a completely overhauled — and honestly pretty bulletproof — backup setup for both home and work. Claude played a big role in helping me sort it all out. Here's what we get into: The backup history tour — I've been through CrashPlan, Dropbox, Backblaze (which saved my bacon after my house fire in 2019!), and a mystery one that may or may not have had "Panda" in the name. These days I'm settled on ARQ for personal backups — dead simple, backs up to just about everything (Dropbox, OneDrive, Google Drive, even their own ARQ Cloud for ~$80/year), and all data is encrypted at rest. Not a sponsor, but they should be. The 3-2-1 rule — I actually asked Siri mid-episode, and she initially thought it was a grounding/anxiety technique. (Valid, I guess?) The real answer: three copies, two different media, one offline. I've got a local copy plus OneDrive, Google Drive, and Dropbox — so I think I'm covered. The work side: Proxmox + PBS — My "data center" is a beefy Hetzner Proxmox box with about a dozen VMs. I had Proxmox Backup Server (PBS) set up on a secondary Hetzner box, happily cranking away… until it ran out of disk space and started yelling at me every night. Claude to the rescue — I spun up a Claude project, fed it terminal output and retention configs, and it gave me a straight-up honest assessment: either gut your retention policy (risky) or get more disk. It then walked me through Hetzner's auctions page — which I didn't even know existed — to find a storage-heavy, low-horsepower box. Ended up with two mirrored 8TB drives plus a 14TB drive for around $40/month. Not cheap, but totally worth it as a business expense. The new setup — PBS is now on its own dedicated Hetzner box. VMs from both my data center and my home NUC Proxmox box back up there nightly. Claude also suggested using that 14TB drive as an SFTP target for ARQ, giving me yet another redundant copy of all my personal data. It'll take a few weeks to fully sync, but I'm running some flavor of the 4-3-2-1 rule now (I made that up). Proxmox forever — Someone wrote in asking if I'd go back to ESXi now that Broadcom brought back the free version. Hard no. I've fallen in love with Proxmox and I'm not going back. 7MinSec wiki scripts repo — Head over to 7MinSec.wiki and click the Scripts button to find a new GitHub repo where I'm publishing pentesting scripts. First one up: a push-button Exegol installer. More to come — and I'll probably tease new scripts first over at 7MinSec.club on TuesdayTOOLSday! Have a backup horror story — or a setup you're proud of? Hit us up! And if you need assessments, pentesting, training, or other security goodness, find us at 7MinSec.com.

The podcast Gods have blessed us this week with VMs from The Pitt's key hairstylist, first name/last name (FNLN) Lynnae Duley as well as a check in from your best-friend's-best-friend, FNLN Daphne Arnold. Also, we highly recommend Tide evo AKA "laundry detergent tiles."ENOJY!!!!!Instagram and TikTok - momstomppodcastEmail - thismomstomps@gmail.comVM hotline - 213-640-7494Substack -  Mom Stomp Weekly

Matt Filgate, President and CEO of GreenLight Metals Inc. (TSXV: GRL) (OTCQB: GRLMF), joins us for a comprehensive introduction to this Wisconsin-focused exploration company advancing copper and gold projects across the Penokean Volcanic Belt-one of North America's most prospective VMS districts-and the Kalium Canyon epithermal gold project in Nevada's Walker Lane, which is subject to a binding term sheet for a proposed staged earn-in and joint venture with Barrick.   In Wisconsin, GreenLight's portfolio includes the flagship Bend copper-gold VMS Project in Taylor County, Wisconsin; along with the Lobo and Lobo East massive sulfide targets, and Reef high-grade gold project. Matt shares that their management team and board has deep roots in the state, and GreenLight is building a modern minerals company for Wisconsin, committed to responsible exploration, transparent engagement, and creating durable local opportunities as it helps supply the critical metals that power the energy transition.     The focus at the flagship Bend project is following up on last year's 2,000 meters of drilling, and utilizing data from the 18,000 meters of historic drilling by other operators, to guide a larger 17,000 meter follow up program. The ongoing Phase 2 Drill Program at Bend is for the initial 7,000 meters of that larger program, further delineating the VMS-style mineralization down-dip and along strike to the east of the main deposit area. The Company will also drill 2,000 meters into the Lobo and Lobo East target area later this drill season.   Next we shifted over to the Nevada asset, where on May 7, 2026, GreenLight Metals announced that it has signed a binding term sheet with a wholly owned subsidiary of Barrick Mining Corporation, for a proposed staged earn-in and joint venture at the Kalium Canyon gold project in Esmeralda County, Nevada.  Matt outlined the terms and different thresholds of this proposed earn-in process for Barrick, which if executed on, would give GreenLight a 20% fully-carried interest all the way through a Pre-Feasibility Study.  Additionally, this transaction brings in periodic stage-gate payments into the company treasury, while allowing Barrick's exploration team to focus on delineating the mineralization.   Matt highlights the strong company treasury at present, the background and experience of the management team, and the potential rerating of the company valuation should their exploration program at Bend have success in growing the mineralized footprint to a level where a resource estimate can be released next year, putting it on par with other important US-based VMS copper-gold systems.   If you have any questions for Matt regarding GreenLight Metals, then please email those in to us at Fleck@kereport.com or Shad@kereport.com.   Click here to follow the latest news from GreenLight Metals     For more market commentary & interview summaries, subscribe to our Substacks:   The KE Report: https://kereport.substack.com/ Shad's resource market commentary: https://excelsiorprosperity.substack.com/     Investment disclaimer: This content is for informational and educational purposes only and does not constitute investment advice, an offer, or a solicitation to buy or sell any security. Investing in equities and commodities involves risk, including the possible loss of principal. Do your own research and consult a licensed financial advisor before making any investment decisions. Guests and hosts may own shares in companies mentioned.

I'm excited to work with Microsoft once again as the presenting sponsors of the AI Engineer World's Fair! We'll streaming live from MS Build today for a special crossover pod with our friends at No Priors and the one and only Satya Nadella. However we did not hold back with this interview - we asked all the burning questions about uptime and Copilot that we know you have in your minds. Lets go!For almost two decades, GitHub has been the home of software, where both open source and closed flow, through commits, pull requests, reviews, actions, etc.This ecosystem flourished as open-source maintainers and contributors would continue shipping code for the benefit of the community. However as coding agents began to ship mass quantities of code - growing 1400% in 2026, it marked a new era that was both extremely exciting and challenging for GitHub.While these agents help more people ship more projects, they also significantly increase the floor of how much code is shipped, how often it is shipped, how many people commit code, and basically orders of magnitude multiples in every dimension of GitHub infrastructure:Now GitHub inevitably experiences more pressure on their infrastructure which was originally designed around human developers moving at human speed. This has resulted in a very publicly notable uptime story:So it begs the question of whether current systems around code can absorb what AI produces. Can CI/CD keep up when every idea becomes a build? Can open source maintainers survive floods of AI-generated slop contributions? Can GitHub preserve the human social contract of software while becoming the operating layer for agents?Which brings us to the perfect person to answer these questions: GitHub COO Kyle Daigle. In this episode, he joins swyx to unpack what happens when AI doesn't just autocomplete code, but starts changing how companies operate, how open source works, how pull requests get reviewed, and how GitHub itself has to scale. We go deep on GitHub's internal AI workflows: micro-skills, WorkIQ, MCP, Slack, Teams, email, Copilot workflows, the new Copilot desktop app, CLI, cloud agents, and how Kyle uses agents to look backwards across company context before deciding what to do next. Kyle also reflects on GitHub's history building webhooks, APIs, Actions, npm, Dependabot, and Semmle, why the AI era is breaking GitHub in new ways, how Actions became a general-purpose compute layer, and what Copilot becomes after code completion.Full Video PodWe discuss:* Kyle's expanded role across GitHub* How AI got Kyle coding again after years in leadership* Why GitHub rolls out AI through existing workflows instead of forcing new tools* WorkIQ, MCP, Slack, Teams, email, and GitHub as company context* Why massive “mega-skills” are giving way to small, atomic micro-skills* How AI changes summarization, communications, marketing, and analyst work* Why former developers in leadership may have a unique advantage in the AI era* Kyle's “15 agents on Saturday” workflow* How Kyle built an AI-generated executive presentation for CRO/CFO teams* Why AI changes the chief of staff role without removing the human work* GitHub Actions, webhooks, arbitrary code execution, and secure agent compute* The npm acquisition, supply-chain security, 2FA, and token invalidation* Slop forks, vendoring, and whether AI agents change dependency management* What pull requests become when most PRs come from agents* Prompt requests, vouching, AI review, and trust in open source* What counts as a “developer” when AI lowers the barrier to building* GitHub Spark, low-code, and why GitHub refuses to hide the code* 14x commit growth, Actions load, databases, monorepos, and availability* Copilot's evolution from completion to CLI, desktop app, cloud agents, and SDK* Context, memory, rules, and making GitHub “act like Kyle wants it to act”* Ambient AI, OpenClaw, enterprise security, and the new operating system for agents* What swyx should ask Satya Nadella about Microsoft's AI futureKyle Daigle* LinkedIn: https://www.linkedin.com/in/kyledaigle* X: https://x.com/kdaigleTimestamps00:00:00 Introduction00:03:36 Why AI Got Kyle Coding Again00:07:04 Running GitHub with AI: WorkIQ, MCP, Slack, Teams, and Skills00:15:39 The Golden Age for Former Developers in Leadership00:17:31 15 Agents on Saturday and AI-Generated Executive Work00:20:20 How AI Changes the Chief of Staff Role00:21:45 GitHub's History: Actions, npm, Webhooks, and Open Source00:28:45 Slop Forks, Vendoring, and AI Dependency Management00:33:57 Pull Requests, Prompt Requests, and Trust in Agent-Generated Code00:41:21 GitHub Stars, 200M+ Developers, and the New AI Builder Wave00:45:15 GitHub Spark, Low-Code, and Why GitHub Still Shows the Code00:47:38 GitHub's Hardest Era: 14x Growth, Reliability, and Scale00:59:21 Actions as the Compute Layer for CI/CD and Automation01:02:04 The State and Future of GitHub Copilot01:08:24 Ambient AI, Background Agents, and the Future of the SDLC01:13:09 OpenClaw, Enterprise Security, and the New OS for Agents01:18:03 Build Announcements, WorkIQ, FoundryIQ, and Microsoft Context01:21:41 What Should swyx Ask Satya?TranscriptIntroduction: Kyle Daigle's Expanded Role at GitHub and MicrosoftSwyx [00:00:00]: We're here with Kyle Daigle, COO of GitHub. Welcome.Kyle [00:00:07]: Hey, thanks for having me.Swyx [00:00:08]: You're not just CEO of GitHub. People know you as that. You have a new role.Kyle [00:00:11]: So I have an expanded role now. I've been working at GitHub for thirteen years and doing all things developer. Joined as a developer myself. And now, I'm also responsible as the CMO of Developer for Microsoft. And so all the kind of learnings and passion for developers and how we work with them and how we communicate and how we bring our products to market, we're also bringing that expertise to the broader Microsoft ecosystem and helping every developer that uses a Microsoft product or would like to have a sort of similar experience that they've had with GitHub over the years. So it's a different role in some ways, but it's also just building on the experience that I've had at GitHub of just sort of tell the truth, be authentic, show people how to use it and then let the products speak for themselves. Now just doing that with, all of Microsoft.Swyx [00:01:09]: We'll be releasing this in conjunction with Build. You got lots of stuff planned, and we can sort of touch on that whenever it's appropriate. I think one of the interesting things is I rarely meet a COO who's also a CMO. I think you're a very outward facing and you're very confident publicly. That's rare. Do you actually view yourself as COO? What's What is your thing?From GitHub Developer to COO/CMO: Building the Platform and Operating GitHubKyle [00:01:33]: I think for me, it's been funny. The titles have always been, a— have always felt a little strange to me. I joined GitHub as a developer? I wrote so much of theSwyx [00:01:46]: Let's bring that up. You wrote the back ends?Kyle [00:01:48]: I was going through, I was going through, some old photos, when folks were talking about how things were being built or how there was a build GitHub. I built, webhooks and worked with teams building the API, built the platform layer. Anything that integrated with GitHub, up until really twenty eighteen, I built or ran the engineering teams. And that's kind of where my the beginning of my passion always was helping people build things, deliver them to, their customers. And so being a developer, building for developers was always super unique. In a— I think as my role expanded, it became my ability to talk to not just developers, but also enterprise customers or business leaders and have this translation layer. And then through all those years, GitHub has always operated pretty uniquely. Post-pandemic, working remotely was not as novel as it was when GitHub started in two thousand and eight. But all that expertise of running remote teams, doing it well, became this sort of bigger role, ultimately turning into the COO role of how do we operate GitHub in the way that GitHub's always operated after the Microsoft acquisition. And kind of so on from there. So like for me, I think the— I've, I still code. I love coding but the problem has always been, people. It's a much harder problem to both support our own employees, a harder problem to communicate to developers and enterprise buyers what we're building why it matters, ‘cause those are two very different messages. And so getting to work in the mix of COO, CMO, also just being a dev, I think is what's kept me at GitHub for so long.AI Workflows for Leadership: Commits, Retrospectives, and ContextSwyx [00:03:40]: Apparently, you have— your commits have gone up. What's this? What's going on?Kyle [00:03:45]: Rui's called me out pretty aggressively. So I think— as you can imagine, right, you can see my normal era of being a dev In the twenty thirteen, twenty fourteen era, and then moving into management, and then ultimately the COO role. I think what you see there is me, really getting back to coding thanks to AI. I— similar to, attaching problems between how to market and how to operate a business and how to code, I find, building agents and workflows that are connecting very disparate problems to be what's driving this. So that's, some of it's writing software. A lot of it is, connecting a ton of a different data sources to, help me out. But that is completely me really diving in on the AI side in trying out our tools, trying out everyone's tools, But building for me, building for the non-technical leader, though I'm technical and how we're, able to use these tools more than just the simple, call and response that I think a lot of the non-technical, your employers, you have to get— you have to use AI, and so everyone uses, ChatGPT or Copilot or Claude or whatever. To really get into, how is this going to help me out, it— I find that it's not the I need to write a blog post, I need to those simple examples. Helping people find the workflows of, “Okay, I need you to go through all the PRs today. I need you to go through everything that we've posted online. I need you to go through what we did the last three months. Go through all of my Obsidian notes for any mentions of this then go through my transcripts at work.” We use, Teams, so, using WorkIQ, go call that MCP server, grab all the transcripts, go through all the Slack, and then build me out the plan of, what this week's messaging actually was. That's something that was, impossible because for me, I find AI in a what most of this launch here is actually, less building forward. It's actually, a recursive loop backwards. I'm always looking at what had happened first. Go back through the week and tell me what we did, what worked, what didn't work? And then tell me in the next three or four days-What would you tweak based on this sort of like looking backwards and then looking ahead a little bit? I find that to be so much more valuable, especially for like non-technical, because that retrospection is actually LLMs are very good at that. Like finding all the patterns, pulling them out, and then applying that retrospection to just a couple of days or just like a short period of time. Is all a bunch of apps that I've built and launched a bunch of, internal tools. I use the new, GitHub Copilot app, the desktop app with workflows. Every time I crack open my laptop, it's running workflows for me. It's just a ton of different stuff and of course, it all ends up on, it all ends up on GitHub.Swyx [00:06:47]: Of course. That's where, that's where, stuff is hosted. Man, there's so much to ask you. I was going to leave the how do you run a company with AI thing at the end. I have to ask one— double click one thing. You said, you are looking back at the week. You're, you're understanding what happens. When you say we That's three thousand people. How?Rolling Out AI Internally: Skills, CLIs, and Company ContextKyle [00:07:09]: I think when we started rolling out AI internally beyond engineering, right? One of the things that I was really, passionate about is like we have to do this in a way where no one has to change how they work. I don't want to have to teach you a tool. I don't want to have to teach you something new. And so for us, we tried out a few tools. Most of them don't work because I got to get you on board? I got to teach you how to use it. What we've actually ended up doing is we've built like a set of skills internally. We have we each have our set of skills, and we've just been distributing even to the non-technical folks, the CLI. And then effectively, we're just giving it access to like read about everything that we're writing. So that's for us, that's usually GitHub, Teams, Email, and Slack. So Teams for, video chat, generally speaking.Swyx [00:08:03]: Teams and Slack?Kyle [00:08:04]: so we use Teams for video communication, but we don't use it for chat. W-we— GitHub for a long history, right? We're alwaysSwyx [00:08:13]: Also SlackKyle [00:08:14]: Talking about ChatOps and like everything is built into Slack. Like every command, every flow.Swyx [00:08:18]: So even though you have been acquired for I don't know, eight years nowKyle [00:08:22]: we stillSwyx [00:08:23]: You still use Slack?Kyle [00:08:23]: it's a purpose-built tool for us, and I think the reality is that moving off of it would be so bluntly expensive? Simply because all the tooling is, baked in with that paradigm. And they both have their pros and cons but they don't work the same way at all. We still use a bunch of different tools Because it's the purpose-built tools that We need. And thenSwyx [00:08:47]: Well, the same doesn't go for the rest of Microsoft, presumably.Kyle [00:08:50]: like the like various teams like operateSwyx [00:08:53]: They make their own decisionsKyle [00:08:54]: Various ways. I think it just matters what you're trying to what you're trying to do. But we do we do work across kind of every tool that we use, and then by giving everyone access to all of that context and the new WorkIQ MCP server, which is quite cool if you do live in the M365 like world. I can ask it all these backwards-facing questions, and it's incredibly important for our teams that are working remotely. There's a lot of stuff you miss when you're not in an office, and we are spread out all over the world. So most of that is looking back. And then we post, we post either auto-automatically into GitHub issues or discussions, these sorts of like findings or like our industry reports. Like what's happening this morning, today, yesterday. A little automation gets run. We'll use the app. We might use GitHub Actions like with, our agentic workflows just to go do that run, and then we push it into GitHub, and w-we keep having a conversation. So usually for us, it's about that sort of like looking back, looking forward on the non-technical side. And then of course for a lot of those folks, it's also building an app, pushing it to GitHub pages or pushing it somewhere to host it et cetera. But it's just like enabling everyone with that power of it's going to take me a week to figure this out. Instead, we're going “Okay I built a skill. Let's put it into a repo. We'll all share that skill together, and then we'll use the CLI or now the app-” “just to run it.”Micro Skills vs. Mega Skills: How GitHub Uses AI at WorkSwyx [00:10:26]: All right. I think, I think we're going straight into like the team management and productivity thing. I think a lot of people are getting various levels of LLM psychosis. How do you manage the bloat of skills? Like everyone Has their thing, and they're Like trying to promote it to the rest of their peers in their org, right? And obviously, whoever becomes a skill influencer internally becomes like an AI leader, right? Of sorts. I assume you have those.Kyle [00:10:50]: like I think we haveSwyx [00:10:52]: And I assume it's a mess a Yeah.Kyle [00:10:54]: there's like I— like I think the reality is there's two pieces. Like first is I think that we're ending the era of these like massive, beautiful, perfect skills that are just like not any of those things. ‘cause for a while, right every tweet every day is like go download the skills, the perfectly managed thing to do this entire workflow. And I think that like what we've found and what— I was just with my team, this week, and we were talking about the skill side, and we're really talking about these like incredibly micro skills that are just doing one thing for us very well Versus a skill that's going to do I said, that full report. That doesn't really exist on our side anymore. It's usually how do— like a single skill that's going to identify the most important marketing information given any MCP server. Like this is the most important thing. Less about stitch a bunch of tools together and have it produce this mega output because then weeks go by, months go by, things change, and you want to tweakSwyx [00:11:58]: It's brittleKyle [00:11:58]: Your mega skill and you're screwed? You can't do that. And so now we're really just talking about the Legos we're using and just letting the instruction book be something we're all putting together. Whereas I think a lot of AI skills for a while have been that mega instruction book style.Swyx [00:12:15]: I've, thought a lot about Postel's law. I don't know if that's a term that is, means things to folks. It's the idea that you should be liberal in what you accept and strict in what you output, right? And I think that's like a good framing principle for skills. This is my skills, obviously on GitHub. I feel like everyone should have like how like some repos In GitHub are special repos? I feel like we should sort of reify the slash skills and everyone like give it some kind of special presentation. Anyway, so, yeah, this is one of those like download Download anything, transcribe anything, and then you can string together the atomic skills that do one thing well Into like some kind of orchestration skill that calls other skills. I assume, does that match?Kyle [00:12:56]: I like I think so. I think that theSwyx [00:13:00]: Summarize anything.Kyle [00:13:01]: Like I think the- For me, summarizing something for I do communications and PR and analyst relations and marketing and customer activities, and so my summarize everything is very different for each one of those like Contexts. What ‘Cause if I'm summarizing something for an analyst, that's a very different thing than, probably how I'm going to summarize something for like a customer meeting or an engagement. So that's I think like the difference when we're talking about the like the tools I might use on Saturday or the skills I might use on a Saturday when it's just for Kyle. Yeah, those are kind of like they have an atomic actual tool underneath or maybe skill, and then Kyle cares about X. But I think when we're talking about work and enabling the the marketers, communicators there, it's the atomic, this is what good summarization is, and then this is what I care about as for marketing for communications For whatever. And that I think is like the interesting matrix problem when we go from like a developer set of concerns to all kinds of different professions, is that what that word means to me is different than it means to you is different than it means to the analyst or the salesperson, and that's where I think the matrix mess is that we're starting to like still starting to find. It's about these mega skills but they're all just slight permutations, but those permutations are really important. It's the difference between someone reading this and going “Did AI make this?” what Or “This makes total sense, and I would expect this when I'm giving a briefing to Gartner,” or like whatever else.Swyx [00:14:37]: I think the beauty of it maybe is that you don't have to be that careful about what goes in there. It doesn't have to exactly fit as long as it like roughly is contained in there. I used to complain about plugin hell, basically. Like when you have a framework and then you have a hundred things that you need to integrate, everyone does like the GitHub used to be bloated full of these things. And now we don't need them anymore ‘cause now you just use skills.Former Developers in Leadership: AI as a Creation MultiplierKyle [00:15:00]: And like I think the most magical thing is the just that like I can just also crack it open. Like Like yes, I could go like change the how the plugin is coded, or like I could go do that now with AI, but I think there's just something more magical about getting a response back and being “That's not right,” and then you just crack the skill open, you just type English words and it's different. That building block is just, I think very unique. Once I get everyone to kind of understand how to best how to best make those changes to get the most power out of them.Swyx [00:15:36]: Is there a— you have a your peer group that Of people like you. Is there a common framing for Something I'm feeling is, which is true, is that is this a golden age for former developers who are now in leadership? Because you can wield the tools, you would know the right words, you're maybe not too close to the details. Doesn't matter. But like you're more effective than someone who doesn't come from that background.Kyle [00:15:59]: I think that like the secret has always been your ability to identify patterns and solve problems, and I think that for folks that like myself that don't code day to day anymore, that has made me successful as a developer, made me successful as a COO and now CMO. And so now that I have access to get and write code, I'm now applying that sort of like pattern finding and problem solving, and I know enough still about how to then go and say, “Oh, I want to make an app, but I don't want to break into jail or create something that's not going to be able to work or to be deployed scale or whatever.” that ability to apply all that additional business knowledge and still code I think is what makes that so interesting to me. Slightly different than I think some of the other like technical leaders that became business leaders and now are going back to their apps and updating them. Good for them? But I think the more, much more interesting thing is, well, now I have this whole new set of expertise over ten plus years. Why not take that and use that as a developer with these AI tools? So I definitely think that makes me more powerful, but I think that's true for like every dev as well. Most of the dev friends I still have also have some other underlying skill and passion. There's really talented, very kind of linear computer science software devs, absolutely. I just find that the folks that came from a different career, went to school for something else, went off and did this random thing, and then became a software dev, or were a dev, did a random thing, came back. Learning that extra set of information, learning those extra skills, and now having the power of an AI where I can crank up fifteen agents on Saturday while my kids are doing lacrosse, That's like really powerful. And I think it gets me back to that feeling of like creation, and it's very hard to replicate that in most other senses? That first time you build an app and you click it and you show someone that's magical. And so being able to do that not just in code, but across all kinds of different assets that's, that's huge. We were doing we're doing our every year we do our revenue planning. We talk about okay, what is it going to look like for next year? And of course as you imagine, there's, slideshows everywhere talking about what are we going to talk about, what's the narrative, et cetera. And so as you said I'm “Okay, well, I could probably just like build something to build this and then that way I don't have to go build the whole spreadsheet or I have to pass it to my team.” So we went through this process, and I got all the information and used the skills I mentioned. I built like a little app just to make it so I could look at some of the information in a SQLite database, more easily. And I ultimately built this entire presentation without touching any of it and I was “Okay, I'm just going to present this to our CRO, the CFO, their teams,” without mentioning I'd built it with AI. I like built a skill to make it look very much not AI driven. Just not pretty.AI-Generated Presentations, Human Taste, and the Changing Chief of Staff RoleSwyx [00:19:03]: Like a design. Yeah.Kyle [00:19:03]: Not pretty. But just like very clearly not AI. Kind of like don't do anything interesting.Swyx [00:19:08]: That's, yeah, that is valuable.Kyle [00:19:08]: Just go Exactly. We did the whole thing through. It used my notes from Obsidian, it used all the context I mentioned before, the plans, and Never came up once that it was AI generated.Swyx [00:19:20]: It didn't matter.Kyle [00:19:20]: Never once. D It didn't matter. And so now I takeSwyx [00:19:23]: This is a toolKyle [00:19:23]: I can take that tool and go, “Look, I don't want you to go build slideshows.” They're just helping us share information with each other. If this thing can do it With a little bit of crafting from you and then we can look at it together, awesome. There's no value in all that extra work. I think that the ability to, make it look humanly bad and and build a little app to, manipulate the data I think is part of, that upside for devs that are now in leadership roles. Because, the thing that I feel like I said before, this that's all a people, that's all a people problem. I know if you've used a coworker or not to build a slide deck, unless you spent a bunch of time to not do it.Swyx [00:20:07]: I know, but like it was so, I think there's a certain charm to just being blatantly AI. ‘Cause I think that you're well, you're just honest about There may be mistakes here that I cannot vouch for. So how much value is there? But anyway I think, actually the real question I want to ask is, there's a— You were a chief of staff To Thomas. And in the pre-AI world, the that job would've been a chief of staff job of like Can you prep me these slides and all that? And now you do it yourself.Kyle [00:20:35]: I still, I still have a chief of staff. Because, the difference is it's sort of the discussion every time we have some sort of technology evolution is it's not that the jobs the roles don't all go away, they just change? And so yeah, I don't have someone spending all their time building out slides for me and presentations ‘cause I don't need that anymore. But now I need that person that is able to go and find all the different connections between humans in those discussions to help me find out, okay, I should be meeting with this group and this team, and they have an opportunity, and I'm going to be in San Francisco today, I'm going to be in Seattle tomorrow. Those sorts of human connection aspects are still incredibly valuable and has always been a big part of that chief of staff role. But now just like chiefs of staff are not opening up, letters to process, they're doing emails. What It's the same thing. And now they're, they're not building out as many of these presentations because they have the the ability to have a AI take it on for, and share that with me and great. Let's keep moving ‘cause it's allowing us to go faster and make better decisions more quickly.Swyx [00:21:45]: Awesome. Well, so we can dive into more sort of, Productivity insights as you go. I did want to do a little bit of a brief history of colleague and hub. Because, we started here. And then you also involved the NPM acquisition. I did, I do want to touch upon that. And then more recently, I just want to bring up to present day where we're having uptime issues Which transparently we've already Addressed publicly, but we'll, we'll discuss in the pod. Did I miss anything? Like what, any other major highlights? Obviously, it's, it's a lot of years to cover.A Brief History of GitHub: Webhooks, Actions, Acquisitions, and Platform EvolutionKyle [00:22:15]: No the I think one of one highlight was right before the acquisition closed in twenty eighteen, I got to launch the first version of ActionsSwyx [00:22:27]: OhKyle [00:22:27]: At GitHub Universe. So it was OSwyx [00:22:29]: They're that young?Kyle [00:22:30]: It was October of twenty eighteen, I think. Yeah. Yeah.Swyx [00:22:33]: Gee, Jesus.Kyle [00:22:34]: I got to I was the engineering leader on that project and got to launch that. And then, yeah, we did acquisitions of NPM you said, Semmle, Dependabot Pul Panda a whole bunch of things. That was a bigSwyx [00:22:47]: Pul Panda.Kyle [00:22:48]: Abi is doing well.Swyx [00:22:51]: DX. Holy crap.Kyle [00:22:52]: Did well on DX. I and like that was a that was the big shift, after the acquisition. I had to join the sort of business side.Swyx [00:23:00]: So I need to hit you on some of these things ‘cause you were there. Right? And how often do I get to talk to someone who was there? But yeah, Actions. Is that the number one source of security issues on GitHub?Kyle [00:23:11]: Oh, sh I think that the number one source of, security issues is probably like all, the literal code in everyone's like underlying repositories. I would say back further than that is, if you remember I had to show in this graph was this is, I'm, didn't say this before, this is ultimately webhooks.Swyx [00:23:30]: You yeah.Kyle [00:23:31]: Like circa whatever it was.Swyx [00:23:32]: It says Hookshot in there.Kyle [00:23:32]: I forget. Yeah. Yeah, Hookshot's in there. And so like back then, it says GitHub Services. Do you see, it says Hookshot FE for front end, and then it says GitHub Services. GitHub Services back in the old days, right? You we had a repository that was Ruby code, and you could write any Ruby code in there, and then we would execute that On your behalf As a service, and then that way if an if you were trying to integrate with something, it didn't we would run it for you.Swyx [00:23:57]: And of course no containers ‘causeKyle [00:23:58]: No, ‘cause it wasSwyx [00:23:59]: Well, no containersKyle [00:24:00]: Twenty fourteen. And so there was some isolation obviously, but it was mostly the separations on the server level. That's like an example as long as the very old version of Pages, which ran on its own containerization infrastructure, not on Actions.Swyx [00:24:15]: Which like all-time great product.Kyle [00:24:16]: Pages powers the internet at this point to some degree. Those were places where like clearly there were no like issues like to my knowledge. But it was those things where I'm looking at and going “Okay, well we can't be running arbitrary Ruby code,” like on everyone's behalf. Then containerizing all of that up intoUh into actions now where yeah the containerization, is r-really good. The pinning most folks aren't pinning it the like to a particularSwyx [00:24:48]: ImagesKyle [00:24:48]: Sha, et cetera like their workflows, and so that's a big that's a big place Of pain for folks if they're just doing similar to any dependency management, just V1 or newest or latest, I think. But, that journey from that day to “Okay, we're just going to run all this arbitrary code, and, it'll basically be okay,” to now, no, we have, really good containerization. We have a new, underlying, ag-agent, containerization, service. It's like we're using it under the hood. It's through Azure. They recently announced it. The Azure, Dev Compute, but it's, very fast, very fast compute to be able to, spin up your own cloud agents, or whatnot. We're using it under the hood for some parts of the new,Swyx [00:25:36]: Microsoft Dev Box?Kyle [00:25:37]: No. Dev Compute, yeah.Swyx [00:25:41]: Hmm. Not finding it just yet.Kyle [00:25:44]: Oh, it's, it's in there somewhere.Swyx [00:25:46]: All right. Well, we'll cut that out.Kyle [00:25:47]: Sorry. But with, Dev Compute, you can, run, really fast, spin up really, small VMs really quickly, so you're doing a tool callSwyx [00:25:58]: Same conceptKyle [00:25:58]: Just do it containerize exact-exactly. So we're using that so definitely moving that direction to protect us from every every piece of code that we're ultimately running.Swyx [00:26:07]: look, that grows into the full SDLC? Code hosting was just the start and and then it's grown beyond that. Let's talk about NPM may-maybe ‘cause I think that's also, a very major point in the industry. I do think, it was looking for a home. It was, kind of struggling as a business, right? I don't know, I don't know how you would characterize that whole acquisition and how itNPM, Package Security, and Keeping the Internet RunningKyle [00:26:33]: like when we were talking to the team, I think the big thing for the both of us was to find a way to keep NPM, which was basically powering the internet then and way more so now to some degree running. Keep it going keep continuing to scale. It was having scaling problems, if I recall, back at that time. They were doing some rewrites. ItSwyx [00:27:00]: that's cute compared to now.Kyle [00:27:01]: Well, that's the thing is like when I'm talking to folks now, there's there's so many more underlying uses of NPM than there were back when we had them join in with GitHub. But that was ultimately the goal. It was really okay, we used to have pages. We have, the world's code. Let's make sure that we can keep NPM running well for the world. And we put a bunch of time and investment into fixing some of the underlying backend, changes, some of which we talked about some of the manifest work, et cetera. And then now, really trying to bring the the security posture of NPM up to speed. But, it is a unique challenge in that every move that we make to make it more secure will break a lot of people. And security is paramount. And also, we take it very seriously. We're, the any time that we have a problem with GitHub or we make a change that makes us more secure but hurts, there's, a snow day for developers or a really bad fire that they have to go put out. And so we've, have changed the 2FA policies. We've changed the way the tokens work. When we find tokens that have been exposed or potentially, exposed, we invalidate them, andSwyx [00:28:22]: I love that feature in GitHub. Yeah, it's greatKyle [00:28:23]: That creates issues, but, the but that's the thing is we're trying to push the community, forward without necessarily, doing something that is going to break the contract that's been for 15 years or close to it or some amount of years on NPM.Slop Forks, Vendoring, and the Future of Open Source Supply ChainsSwyx [00:28:43]: I think the— So now we're talking about, open source and publishing. And I think there's something here with what people are calling slop forks, which, I think Malta from Vercel is doing. And, part of me thinks, well, the way to get past any vulnerabilities, we just, let's just get rid of the concept of NPM. And we only publish source code. And anytime you want to import it you have your coding agent look at it and then adapt whatever subset you're going to use into your vendor it. But, the AI vendor it. Is that realistic? I don't know. Is it— Will that solve all our security issues? I don't know.Kyle [00:29:24]: I don't think it'll solve I so Mitchell was just talking Mitchell Hashimoto Was just talking about this today, and I think that I-in some ways, it's all all things, old or new again? Yeah, absolutely vendoring everything. Like I do I do remember twenty thirteen, twenty fourteen.Swyx [00:29:42]: This is Yeah. Let's, we must return toKyle [00:29:43]: That's what is We were vendoring everything. We were having actual discussions around, or at least I remember we were “Should we take this full thing?” “Why is this so big? We only need this one file.” And so I do think there's something true there where having either taking only what you need or the dependencies just getting incredibly small over time, I think will help to some degree, but it's not going to solve the fundamental problem, I don't think, because the vulnerabilities in an agent looking at them, there's time and time again, there's a million different ways in which we can convince an agent that this thing is, secure or not and pull it in. Or we can do static code analysis or runtime testing to say whether the code works or not. That is, I think, the step that needs to continue to be, invested in. The question is just on, how much scope. Should it be this enormous project that I'm pulling down, or should it be this piece? Either most companies are running some amount of security checking on the on the packages that they're bringing in or vendoring. That I think won't change. That's like what advanced security does to some degree, Socket does some degree. Like everyone is doing a piece of that. How we each do that like especially when we're talking to enterprise customers, is just like very different. No there's no one wants one single way to do it. And I think that's always been GitHub's, unique position in the world. I talk a lot to maintainers, I talk a lot to folks about this. It's we're— we rarely start like a process and a practice and like push it onto the community. We usually wait for the sort of like RFC process socially or literally, everyone agreeing, and then we'll cement something in. Because otherwise we'reMaintainers, RFCs, Vouching, and the Social Layer of TrustSwyx [00:31:35]: That fits your role in the ecosystem, yeahKyle [00:31:36]: We're GitHub. Yeah, we don't want to shape the whole thing. We want it to be figured out. But like how do you balance that like sort of Role in the industry to keep everything as secure as is possible and make sure that you're you're not going to be compromised as a human, ‘cause that's usually how it all happens. And Not not create a process or lock us into a flow that you're not going to or like Mitchell's not going to or other open source projects aren't going to like. That's always been a tricky balance for us, and I think that's something that we haven't talked about enough is we're not going to be able to fix everything for everyone in a way that everyone is going to like. So tell, help us, tell us what is working. When Mitchell was talking about, the Upvote, the upSwyx [00:32:22]: I was going to bring up his thing. Yeah.Kyle [00:32:23]: I forget what it Yeah. When he's talking to us, I was chatting with him and talking to him about this and I put it on Twitter and we talked to, also over DM, was “We're going to keep working.” but I think the important thing is I do actually want to hear what isn't working for you. And as, be as specific and clear for your project as is possible. And to every piece of credit over the many years that we've known each other through the industry, he's always done that and I appreciate that ‘cause there are places that we need to fix up, and we hear from him, and we'll fix up just like we do all other kinds of maintainers. But that that process between making those types of improvements and being more secure and like creating, I forget what he calls it's not the proof process, not the claims process. Do what I'm talking about? He has that he his projects have a way for you to kind of like,Swyx [00:33:13]: VouchKyle [00:33:13]: Vouch. Thank you. Yeah. He has like the vouch system for saying, “Hey, you should accept my PRs.” That's beenSwyx [00:33:20]: I just built this into GitHub. I don't know.Kyle [00:33:22]: Well, see, but that's the thing is that you say that and like he and his community really likes this and then I'll go talk to other maintainers and other maintainers, globally, and they're “No, this doesn't work for me.” And that is the tension, but also the kind of beauty of GitHub, depending on which way you look at it is we want to help maintainers, so we create all these tools to let you have more control over how much you take in from AI and PRs. But you can also use this. What You can go use this project, and if it takes off and becomes the kind of mostly standard, then yeah, we probably wouldn't enforce it but we would add it in because that's the flow that we tend to do?Swyx [00:34:02]: I hear a lot of people don't know the history of the pull request. And like like that's how, that's something that GitHub standardized basically.Kyle [00:34:08]: Yeah. It was a very messy process Like beforehand, and now the we have the benefit of it being the process? And now we have to go and Figure out the next best process or what adaptations change, or what does a pull request look like when eighty percent of your PRs are just coming from your agents and not From other devs?Swyx [00:34:31]: Do you like the prompt request idea from Peter?Kyle [00:34:34]: like I think that for each like each idea I think has its merits. I'm not, I'm not avoiding saying anything good or bad, but I feel like I've seen a version of we have that we have entire Thomas' store. Take all the assets of what you've built and put that in. I think that's got great ideas. There's all these various permutations of the PR flow, but I think the reason why there's not a single answer is ultimately we're trying to codify trust. We're trying to say “Okay, if Sean reviews this I'm going to trust it because you're Sean or you're the senior dev or you're the whatever.” And right now, when we are working in a flow where an agent writes code and another agent reviews code and then Kyle goes and looks at it the trust is kind of diffuse. And most of the tools that we're talking about are talking more about verification flows. We have more assets to look at, so I can probably say whether this is a good PR or not. But that still doesn't solve, I think, the human problem of I'm looking at a PR and I want to know if I can trust it. And we're still, we still tend to use human signals for that? Mitchell approving it or Kyle approving it or whatever. And so I think that's, I think that's why most of these options haven't really solved it is because, it's a social problem ultimately. It's a it's a human problem to review it and agree. Or you fully trust the tool and you're imbuing that tool with full trust Which I think in some cases that absolutely exists.AI-Generated PRs, Trust, and the Waymo AnalogySwyx [00:36:08]: And so like in the same way that there will be a tipping point in society when we don't allow humans to drive anymore Because machines are measurably better than Than humans. I'm looking for that tipping point, right? Like Mythos is ridiculously expensive. Someday we'll have Mythos on a desktop. I don't know. Will, does that change the equation?Kyle [00:36:30]: I think it's more I took a Waymo here, and I was on my phone and not looking around at all. There are other, self-driving, vehicles that I would not trust while, staring at the road. And I think that trust is something that isSwyx [00:36:48]: Is this a Zoox thing? What is itKyle [00:36:50]: I think that is both. I think that is both. LikeSwyx [00:36:53]: There's Zoox in this robo taxi. That's it. It'sKyle [00:36:56]: Well, depending on what level Of self-driving. But, my point is sort of that I think part of that is I strongly believe that's, a mixture of verifiable proof. Like how many accidents, how much data, and so on, and the human aspect of how I feel when I'm in this car, what it tells me, et cetera. And so that's why I think some of the like Some of these some of our AI tools tend to, imbue me with more of that feeling of trust, even if the data says this is 100% accurate. I feel like it takes more time for us to go, “Should I trust this or not?” And that's in the soft sense of, startups with high agency, weekend projects, and open source. And then there's enterprises and regulated industries and everything else, and that is an even harder problem to go solve because even when it is fully verified, not only do you have to have trust from the humans on the team, you probably have to have trust from multinational,Swyx [00:37:55]: Oh my GodKyle [00:37:55]: Multi governments around the world and regulating agencies. And so that's where I feel like until we tip over to your point on the sort of like human EQ side of it. I feel okay this feels okay I've been proven enough. Then the ball will start to roll a lot faster, where we'll end up getting to the “Okay, we can trust this,” and feel good about it in the Most difficult of cases.Reputation, Sponsors, Stars, and Bot Activity on GitHubSwyx [00:38:18]: If human trust is the thing that matters, I feel like GitHub as the developer social network could maybe do more there. Like vouchers are one system But, we have star counts, and then we have Contributor rights, and that's it. And I feel like there should be more in that space. I don't know if there's any other design decisions there.Kyle [00:38:37]: I think that one of the places that we don't really expose right now in this sort of way is, some degree of like hard trust and support, which would like for me is like sponsors is a good example of that.Swyx [00:38:49]: Ah.Kyle [00:38:49]: It like costs you something. To prove that I believe in your project and I trust you To some degree or I want to support you at the very least.Swyx [00:38:56]: Solve payments for open source. Why not?Kyle [00:38:58]: I think that I think that like as we keep moving forward, right, there's more and more projects where I'm, adding more and more dollars into sponsors personally because I want to like support them, but I also like know of I've probably never met them in person, but, I know of enough of their work that I want to support them. I think the thing that I don't love about stars or commit counts or anything else is ultimately, even with all of the various, abuse and de-spamming and deduplication work that we do or anti-abuse work that we do, these are all, not active social signals. They're passive ones that are ultimately gamifiable. And you may trust me, but another open source maintainer may not. And on what heuristic should you be, trusting me? That I think, is kind of where some of our thinking is right now. What signal from me is most important to you? You— If you can define that potentially, honestly in an agentic workflow that's what we see some of these open source projects do, where you have GitHub actions, and then you have like an agentic workflow that's calling AI, and you're setting these rules. Like if Kyle has submitted and gotten accepted PRs across any given project and has a social handle tied to his account in GitHub, and that social account's older than a certain amount. Really complex measures that matter to you ‘cause most open source projects have that heuristic built into their heads, if not written down in the contributing guidelines. You could take that and then go apply that and then just say, “Oh, we're not going to accept this PR.” Building something that is, I think, malleable to everyone's needs, is a little bit better, rather than going “Hmm, this account's too young.” Because what happens? The attackers just go and go and create a multitude of accounts, and they wait Until it ages up. Needs to have a certain amount of stars. That's how star inflation happens. Need to have a certain amount of reposSwyx [00:40:46]: Oh my God. YeahKyle [00:40:47]: With PRs. They all just create repos and submit PRs to each other, and then they come in and do something nefarious. And so, it's hard. It's hard to find the measure. So I think we're, we're looking more at how can we provide you tools so you can kind of choose what's best for you. And of course, we'll give you some standards. But the trust vector, gets down to I don't know, some version of like human digital ID like everyone's been talking about. Like how do I prove that it's meSwyx [00:41:13]: Give me your eyeballsKyle [00:41:14]: On the internet. Give me your eyeballs. Exactly.Swyx [00:41:18]: The I got to keep moving on Topics, but obviously I can go all day on this stuff because, I've been involved in GitHub and open source My entire professional career. Stars. Very superficial. Everyone knows it. But I think time to one hundred thousand stars is the fastest I've ever seen. Like people just reached that in I don't know, months. And then like at the same time I don't trust it right? Like how many of these are real or bot or like whatever. I don't know how to ask this but like what can we do about it? LikeKyle [00:41:49]: JustSwyx [00:41:49]: Is stars broken? Is stars fine?Kyle [00:41:51]: I think that there's kind of two, there's like two pieces. Obviously we're constantly like trying to find ways in which like your users are producing spam, which would, I would include like be like only doing star gamification. When we find them, we pluck ‘em out and we,Swyx [00:42:08]: But it's like a Whac-A-MoleKyle [00:42:10]: It's a hundred percent like a Whac-A-MoleSwyx [00:42:11]: There's no wayKyle [00:42:11]: Now, powered by AI to be helpful. But I think more so what I'm seeing is, a lot of the like fastest time to X tends to be because we're now inviting so many more people into like software development on GitHub That like the zeitgeist is just swarming? And it'sSwyx [00:42:32]: It's not just developers anymoreKyle [00:42:33]: And it's not you and I. Like like however you want to say like what a developer is it's not just folks who have been coding for a very long time. It's folks that have maybe started coding or only joined in since the AI era. And nowSwyx [00:42:44]: what's the latest Octoverse number? I know eighty million was my lastRem- member that a number of developers on GitHubKyle [00:42:50]: Oh, we're over 200 million now.Swyx [00:42:53]: Okay. Well, so you see?Kyle [00:42:55]: Like over 200 million developers now.Swyx [00:42:56]: But it's not developers, right? It's, it's people with a GitHub account.What Counts as a Developer in the AI Era?Kyle [00:43:00]: So, so this is, this is the biggest debate that I would say, everyone loves to have at GitHub at this point. From my perspective, right, I think that there's, there's clearly a difference between, professional enterprise developer and then developers. But I think that I think that the idea that we should be I don't know, splitting hairs or segmenting developers in the early era of software development is, not worth our not worth the time. SoSwyx [00:43:29]: When you get into gatekeepingKyle [00:43:31]: 100%Swyx [00:43:31]: What is a developer?Kyle [00:43:31]: 100%. ‘Cause I wasn't a developer when I started writing code? I was going toSwyx [00:43:36]: Oh, no. I made— I cloned a thing, seven years before I learned to code. And then I and then I wrote about my learning to code journey, and people Just called me a fraud ‘cause I had a GitHub account. And I'm “Well, no, I just use GitHub, but I don't know-” “I didn't know what I was doing.”Kyle [00:43:49]: I I remember that. I remember those sets of posts, and like that's, that's b******t. So I fight very clearly on the line of, if you create code, if you have an idea and you create it into some way of, I'm, I'm going to run it and use the app right now, you may still use AI in that moment, but that's okay. At some point you're going to do the next thing. You're going to create a big— You're going to have to learn about this database. You're going to fix a bug, whatever. We're all on some same journey, and those people are also hearing about the great new agent skill package or a new CLI tool or a new whatever. And those projects are going up because you want to be a part of this moment, just like I wanted to be a part of the Ruby community when Ruby was popping off when I started becoming a developer, and now I can just click the star button. And so I think that yes, there's clearly some amount of like spamming and game gamification that we're working against, but I really think we're just seeing this whole new cohort of folks that are moving from technology to technology because they're not working on a 20-year-old software application. They're working on a side app that they built on the weekend for their friends or for their new idea or whatever. And that's how you see these enormous charts going up and to the right with With stars.Swyx [00:44:59]: I think something that's remarkable is the persistence or, that GitHub extends to those folks. Usually when I see platforms go into a new audience, they usually have to, have like a second platform with a different name that wraps the main platform. But somehow GitHub has been able to sort of persist and extend, and it's friendly and whatever? So it's, it's nice.Spark, Low-Code, and Always Showing the CodeKyle [00:45:19]: I that's partially why I think as we've tried to move into I don't know, more like low-code-y things. We so we started working on Spark as like a way to, build an app and run it. I think that the reality is that we anytime we try to, kind of put even a veneer on top of it without when we put a veneer on top of something, we still always show you the code. That's kind of like a tenant. We're never going to, hide the code from you ever, because whatSwyx [00:45:52]: Why would you?Kyle [00:45:52]: That's, yeah, that's the whole point? However, I think that what we learned with things like Spark is that really the value of Spark for most devs is, easy runtime. And you may have a runtime or a host that you're going to use for that or you just build something and run it but, the package of making that even more simple isn't really needed for folks that are trying to build software and not just trying to build, an app, which is, slightly different, a slightly different goal. So I want to get you in, I want to get you comfortable. I think the best thing for me as, someone that did not traditionally come into software dev way back, I want anyone to be able to breach that chasm and not be in the I don't know, I feel like we're, we're still in an era of, STEM. I've got a 12-year-old and an eight-year-old, and it's “We got to get ‘em into STEM,”? Over and over. And I like I do, I do the things that good parents do. I was “Oh, you want to do coding?” “Yes, I want to do coding.” Do coding classes. But now they're just not afraid of doing software. And that's, I think, the thing that's honestly kept me at GitHub for so long. Anyone should be able to go and build a thing, just like I can go change a light switch in my house. I'm not going to go into the breaker box ‘cause I'll probably kill myself? But, I can go change that light switch. Everyone should be able to go and say, “This fricking app doesn't do what I want. I want it to work like this.” And that I think, is what's kind of kept us all connected with GitHub through the years and some and during the easiest of times or in the hard times because of that opportunity of, we're the home for all developers, and we want everyone to be able to have that feeling that we've had of, had an idea, I created it and holy s**t here it is.Swyx [00:47:37]: Here it is. All right, I'm going to try to do more spicy questions.GitHub's Hardest Scaling Moment: Growth, Agents, and UptimeKyle [00:47:42]: Great.Swyx [00:47:42]: Is it an easy time now or a hard time?Kyle [00:47:45]: Oh at GitHub? It's a hard time. Like, it's a hard time and also, I was just with my team and I said, “This is also, the best and most exciting time that I think I can remember at GitHub.” BecauseSwyx [00:47:57]: Best of times, worst of times. It's never oneKyle [00:47:59]: ‘cause we've we were talking about Octoverse reports and, usually we do an Octoverse report once a year, and we look at the numbers, and we say, “Oh my goodness.” I was at Universe in October saying, “This was the fastest year of growth that we've ever had,” right? And now we're doing more in a month than we did in a year last year.Swyx [00:48:20]: You're talking about PRs.Kyle [00:48:21]: Commits.Swyx [00:48:21]: Commits, yeah.Kyle [00:48:22]: PRs. Kind of like you name it by roughly every measure that we're looking at, there's some amount of sort of growth that is much bigger, and that is breaking our system in new ways, not old ways. Like webhooks were always notoriously, unreliable over the years?Swyx [00:48:38]: Whose fault is that?Kyle [00:48:39]: not anymore mine, but for a period of time, I'm sure you could pull up a tweet that was “It was me. I'm sorry.” but, now, that got rewritten at a scale level that is still working and is not having problems today. Now what we're finding isn't just the isn't the-The simple stuff that folks are on the sometimes on Twitter or on the internet are “Hey, why is this like this?” Sure. There's absolutely silly problems that we shouldn't exist. But now we're talking about, unique, novel permission problems that happen only at a scale across all different objects or whatever, that now we have to go rewrite this underlying system. And so it's, there are problems that yeah, caught us off guard, which I think I said. Like the growth is astronomical, but also we're making such material progress in that I'm excited once we're once we've kind of like reimagined the underlying foundation layer, or pieces of it at least, what's going to be possible when it's not just all of us and all the new people that are being developers and all of their agents and all the tools like working together. Because that'll still happen in that in that GitHub tool, that GitHub community. But it's a it's a hard day anytime we can't give you what you're looking for. We have the same problem internally. We operate through github. Com. Of course, we have backups when things go down and whatnot for our own operations but we feel it too. If it's not working it's not working for us, and that's kind of like the promise of dogfooding for GitHub. It's always been true. We're using the same tool you're using. We're not using a super secret version. We and so we also need it to be great for us for our customers of course for open source. And now an exponential growth of agents, Doing it too.Swyx [00:50:32]: I wanted to load for audio listeners who maybe haven't seen your tweets, whatever. So one billion commits in twenty-five. Now it's two hundred and seventy-five million per week on pace for fourteen billion this year, if growth remains linear. Is that still the pace? I don't know. It's been aKyle [00:50:48]: it's, it's speedingSwyx [00:50:50]: Roughly.Kyle [00:50:50]: It's still speeding up.Swyx [00:50:51]: It's, it's April, so yeah.Kyle [00:50:51]: Exactly. This was in April.Swyx [00:50:53]: All right. So basically you have fourteen x growth, right? Year on year on year. And I think that's a scaling issue. I think, I'm going to like try to really steel man this thing. People have experienced fourteen x growth. They haven't had your downtime. And that's like— C-can we go dig into that? Why? Like what's the— what broke? What are we doing to fix it? Like just anything for the community to reassure them.Why GitHub Reliability Is Breaking in New WaysKyle [00:51:18]: so there's a Like I was saying, there's a couple different places that we've seen the growth issues. Some of the growth issues, which is why we're t— I was talking about pushing hard on more CPUs is in actions in particular. More tools, more agents, more PRs mean more builds, more builds mean more CPUs. And so we are expanding through not just our data center, but obviously we were talking about moving to Azure and moving to, adding an additional cloud compute because we simply need more CPUs. Not as much GPUs. We definitely need GPUs too, but now CPUs are becoming a factor.Swyx [00:51:53]: It's very CPU heavy.Kyle [00:51:54]: Underneath the hood when it comes to some of the underlying services, we've been breaking up over the years our database infrastructure, so that way we have, more cognitive separation between our the various services. The place that we continue to have pain is in, permissioning. And so right now m-many of our permissioning layers sit into a database that we like internally call MySQL One, and old Hubbers will know what I'm talking about. And so we've been pulling things out of MySQL One for many years, because like and we use we use Vitess and we use other technologies to shard and we do it as one bigSwyx [00:52:31]: Famous thing, PlanetScale was born from this andKyle [00:52:32]: A hundred percent. Sam Old Hubber and friend. And so finding these opportunities to like break this out and then do that globally. The other thing that I think is interesting and both a unique opportunity and tricky is we also run everything I just talked about in a black box container with GitHub Enterprise Server for people that work on-prem. So we take everything I just said, and we also do it on-prem, and we also do all of that and we do it in a data residence setup for customers that need to have their data in a single location. Each of these has the unique characteristic around how we're sort of storing that data in MySQL or in a permissioning setup. That's where some of these outages have oc-occurred, where you're seeing it more like across the board rather than just like the one pieceSwyx [00:53:17]: Filling the databaseKyle [00:53:17]: Isn't quite working. Exactly. And so part of it is that. I think there's been some other places where agents are much more or more projects appear to be moving towards monorepo versus we were going the other direction for many years in the industry. Repos were smaller, but there were more of them, and now we're seeing the opposite. Repos are bigger, and there's, not fewer of them per se ‘cause there's new growth, but, we're just seeing many more big repos. Big repos, big monorepos have always had, a unique performance problem. Because each one, is slightly different if, particularly if the underlying blobs are incredibly big Inside the repos. And so we've done a ton of work that you pro— like most people haven't probably experienced, unless you're in this case of the monorepo. But that Git, infrastructure layer improvement does help the overall, system because, many of the improvements that make monorepos work better make all repo infrastructure work better. And so, I could kind of keep going down the line where it's another thing where we're moving out of, We're changing how we do j I'll just say job queuing for lack of a better, explanation changing the underlying technologies there.Swyx [00:54:32]: I spent two years being a job queuing guy, so.Kyle [00:54:34]: And so it's kind of a little bit of a little bit of piece by piece, and it's mostly because as we were— as it was built, we built everything in a way that assumed, I guess in some ways that the size of the pipe of work was going to remain the same. There's just going to be more people coming through each of those pipes. But instead now in places whereA git push was, generally a certain size for example, is now, no longer true.Swyx [00:55:03]: Oh, yeah.Kyle [00:55:03]: OrSwyx [00:55:05]: I push a thousandKyle [00:55:06]: On the average. 100%Swyx [00:55:06]: A thousand line commits like dailyKyle [00:55:07]: Same thing with PRs. Like PRs same thing. And like we've talked about optimizing that and making changes where, and there were technology choices that did not work there? And it got slow, and it didn't It was not fast. It did not do what the users wanted. And so we've been reeling that all out and going “Okay, that's just not right. Let's stop putting good money after bad and do it the do it the right way or the right way now.” So there's It's a it's a lot of things, not quite when I've experienced scale at GitHub historically, it's almost always two options that we've used. We go vertical scaling, particularly with databases, right? And we go horizontal scaling. Oh, we just have more people using this service. Great. We're going to add more servers, and we rack them in our data center, or we use it in a cloud. And now we're sort of in a like diagonal, where like vertical doesn't really work anymore. Horizontal isn't work either because we're all We all have some CPU or GPU constraints in the world now, and now we have to go in and like crack open services that have been running for 10 or 15 years and go, “Okay, the rules of this service have legitimately changed, and now we have to rewrite them.” None of this is an excuse. This is like we're We have to do the work. We have to make it better.Swyx [00:56:22]: actually as an infra guy, I'm “This is like one of the most fascinating scaling challenges I've ever seen.”Kyle [00:56:26]: That's that's, that's the thing that's the thing that it's hard for Like when we weren't talking about it publicly, and I was like I came out, and I was “Hey, I just want to explain what's going on.” Part of it comes from a very old GitHub ethos, which is it's our it's our uptime. It's down. W What I know you're a developer, so you're, you're inclined to want to understand more what's going on. But at the same time us going “Hey, this service didn't, perform the way we expected, and now we have to go change it,” we weren't We're not trying to hide anything from you i

Nick Hodge, Co-Owner of Digest Publishing and editor of Foundational Profits and Underground Alpha, joins us for our monthly longer-format discussion on different macroeconomic factors and market reactions to the war in the Middle East, his key takeaways from 2 different site visits to South Dakota and Wisconsin, and investing strategies in select copper, gold, and critical minerals stocks.   We start off reviewing the mix of macroeconomic movers and knock-on effects from geopolitics as it relates to the closure of Strait of Hormuz, the US/China meetings last week, projections around central bank monetary policy options, rising bond yields and interest rates, a strengthening US dollar, GDP growth, rising inflation, sovereign debt loads, and AI datacenter buildouts.      The US stock markets have shrugged off most of these economic datapoints and geopolitical news, continuing to blast up to new all-time highs over the last week. He points out that the CRB commodities index has also been strong lately, lead by base metals, soft commodities, and the energy space.     When reviewing the commodities,  it has been hard to ignore the strength in the copper pricing, which has been up at all-time highs over the last few weeks of May, and Nick shares his approach is to investing in the copper equities.   For exposure to the base metals producers he has been positioned in the iShares MSCI Global Metals and Mining Producers ETF (PICK), which has performed quite well over the last year and especially in 2026. Nick reiterated points from our prior conversation about 2 of the copper developers with good investor engagement, solid pounds in the ground resources, and good fundamental catalysts being: Gunnison Copper Corp. (TSX: GCU) (OTCQB: GCUMF) and Aldebaran Resources Inc.  (TSX-V: ALDE) (OTCQX: ADBRF).   Nick highlighted the recent acquisition of Arizona Sonoran Copper Company Inc. (TSX:ASCU | OTCQX:ASCUF) by Hudbay Minerals Inc (TSX, NYSE: HBM) and how that may be used as a good case study and lens for consideration of other advanced copper development assets and what kind of projects and jurisdictions may interest the senior producers. Gladiator Metals Corp. (TSXV: GLAD) (OTCQB: GDTRF) is a copper and gold exploration story in Nick's portfolio that just released some high-grade intercepts in the Yukon, and still has a lot of drilling on tap for this season as a catalyst. When reviewing why he prefers safer jurisdictions in the Americas for copper investing, he did point out a company like Ivanhoe Mines (TSX: IVN) (OTCQX: IVPAF) is an exception, due to the quality of the management team to navigate the risks when operating in Africa.   Next we got a boots-on-the-ground recap of Nick's 2 recent company site visits: Lion Rock Resources Inc. (TSXV: ROAR) (FSE: KGB) (OTCQB: LRRIF) – The company recently announced Phase One drill results at their Volney Project in South Dakota. The system features high-grade lithium, tin and tantalum hosted within spodumene-bearing LCT (Lithium-Cesium-Tantalum) pegmatites. GreenLight Metals Inc. (TSXV: GRL) (OTCQB: GRLMF)- GreenLight is a Wisconsin-focused exploration company advancing copper-gold and gold projects across the Penokean Volcanic Belt-one of North America's most prospective VMS districts. GreenLight's Wisconsin portfolio includes the Bend copper-gold deposit, the Reef high-grade gold project, and the Lobo and Lobo East massive sulfide targets.   We wrapped up getting the near-term technical price support levels that Nick is watching for in gold.  For now he is not concerned about gold falling into a true bear market, and he is treating the pullback we've seen in the precious metals a buying opportunity. Any short-term consolidation in pricing should be juxtaposed against the fundamental structural drivers for the longer-term precious metals bull market that are all still solidly in place. He's been using periods of sector weakness in the PMs to add to positions in both GDXJ and Royal Gold, Inc. (NASDAQ: RGLD), along with some other junior precious metals stocks.   Click here to follow Nick's analysis and publications over at Digest Publishing     For more market commentary & interview summaries, subscribe to our Substacks:   The KE Report: https://kereport.substack.com/ Shad's resource market commentary: https://excelsiorprosperity.substack.com/     Investment disclaimer: This content is for informational and educational purposes only and does not constitute investment advice, an offer, or a solicitation to buy or sell any security. Investing in equities and commodities involves risk, including the possible loss of principal. Do your own research and consult a licensed financial advisor before making any investment decisions. Guests and hosts may own shares in companies mentioned.

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

Pan Global Resources CEO Tim Moody discusses the company's growing copper and gold portfolio in Spain, led by the Escacena Project and its La Romana copper-tin-silver resource. Moody outlines the strategy to scale La Romana from a 36-million-tonne starter resource toward a larger VMS cluster, supported by newly won ground at Escacena South. A strategic investment from Alpayana boosts funding for a 20,000-meter drill program across multiple targets, while the Carmenes project in northern Spain adds early-stage gold upside.

 Interview with Gary Lohman, COO & VP Exploration, and Patrick J. Cruickshank, President & CEO of Thistle ResourcesRecording date: 20th May 2026Thistle Resources Inc., a recently listed explorer on the TSX Venture Exchange, is positioning itself at the crossroads of rising demand for gold and critical minerals through a diversified portfolio in Canada's Bathurst Mining Camp. The company controls five projects, with a strategic focus on three key assets: the Middle River Gold deposit, a large volcanogenic massive sulfide (VMS) target, and the high-grade Brunswick Antimony project. This multi-commodity approach reduces reliance on a single resource while offering multiple pathways for value creation.The flagship Middle River Gold project demonstrates strong scale potential. It hosts two distinct zones: a near-surface system extending to 130 meters depth with approximately 7 kilometers of mineralized folding—largely untested—and a deeper zone at 400 meters that exhibits one of the strongest geophysical conductive responses recorded in the region. Early drilling has confirmed consistent gold mineralization, while advanced surveys by two independent geophysical firms have significantly improved targeting confidence. The company is aiming to define a resource of up to 2 million ounces through systematic drilling.Equally compelling is the Brunswick Antimony project, որտեղ exceptionally high-grade mineralization occurs at surface, including antimony exceeding 10%, along with significant silver and gold values. Located near historic producing mines, the project benefits from existing infrastructure and growing geopolitical interest in securing non-Chinese sources of critical minerals. Antimony prices have surged in recent years, enhancing the project's economic potential even at modest scale.Operationally, Thistle benefits from a favorable jurisdiction with rapid permitting, strong infrastructure, and low drilling costs of roughly CAD 100 per meter. Fully funded for two years and equipped with active drill programs through 2026, the company is well positioned to advance its assets. With multiple catalysts ahead and exposure to both precious and critical minerals, Thistle represents a diversified exploration opportunity in a proven mining district.View Thistle Resources' company profile: https://www.cruxinvestor.com/companies/thistle-resourcesSign up for Crux Investor: https://cruxinvestor.com 

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

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IMPACT Silver is weighing a restart of its Capire Mine with some help from new technology, says CEO Fred Davidson in an interview with Mining Stock Daily. The company is currently evaluating the use of XRT sensor-based sorting to improve margins at the VMS deposit by electronically separating ore from waste during bulk mining. While Capire remains on care and maintenance, the company maintains active production at the Zacualpan Mining Complex, supported by the recent discovery and extraction of the high-grade Kena vein. At the Plomosas Mine, management has suspended mining to optimize the underground design and is pursuing toll milling contracts with third-party miners to generate near-term cash flow.

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In this episode of the Pure Report, we sit down with longtime colleague Robert Quimbey, Consulting Field Solution Architect, known to many as "Q." Q shares with us how his role has evolved from a back-end problem solver focusing on Microsoft integrations to a customer-facing strategist dedicated to understanding the entire solution set for customers, not just fixing siloed problems. Drawing on his deep history with Microsoft technologies, including his time on the Exchange team, Q discusses Everpure's strategic moves to simplify the modern data center. Our conversation dives into two major capability developments: ActiveCluster for File and Azure Local. ActiveCluster for File is designed to provide high availability for file services, inheriting the core benefits of the original Everpure ActiveCluster— with ease of setup and no extra licensing costs—while solving hard problems in the file space. Q explains how ActiveCluster for File implements file storage at a cousin layer to block storage, avoiding the performance and scalability issues common in competing solutions. The new capability includes continuous availability to ensure persistent sessions for VMs on SMB shares, even during non-disruptive upgrades, and is launching right as the NAS market is projected to nearly double, driven largely by AI-related unstructured data growth. Next, we explore Azure Local, formerly Azure Stack HCI, a project Q has championed for years. This initiative is key to customers looking to modernize their virtualization strategy. The new integration, which is near GA, allows customers to connect virtual machines and containers directly to FlashArray via Fibre Channel (FC), avoiding the complexities of HCI storage. Ultimately, the focus remains on the power of the core Purity foundation to deliver agility, predictable costs (like Evergreen//One), and superior performance for all hybrid-cloud workloads. To learn more, visit: https://blog.purestorage.com/products/microsoft-azure-local-and-flash-array/ and https://blog.purestorage.com/products/introducing-activecluster-for-file/ Check out the new Everpure digital customer community to join the conversation with peers and Pure experts: https://purecommunity.purestorage.com/ 00:00 Intro and Q's Career Journey 07:17 Key Development Projects 09:59 Stat of the Episode on NAS Storage 12:51 ActiveCluster for File Discussion 27:45 Protocols and Arrays Supported 34:19 Intro to Azure Local 53:04 Hot Takes Segment

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Daniel Mahncke and Shawn O'Malley take a deep dive into four companies operating in the shadow of one of the greatest compounders of the last two decades — Constellation Software. Some investors believe that Topicus, Lumine, Sygnity, and Asseco Poland represent the best way to own the CSI model today, while others argue that the spinoffs lack the institutional depth and deal flow of the mother ship. Join Daniel and Shawn as they assess which of these mini-Constellations has the most compelling setup, and whether any of them deserve a spot in the portfolio. IN THIS EPISODE, YOU'LL LEARN: 00:00:00 - Intro 00:01:12 - Why smaller VMS companies are interesting 00:09:23 - How the law of large numbers shifts CSU's focus 00:11:04 - About Topicus and why it's the closest copy of CSU 00:14:57 - Why VMS is so attractive for acquirers 00:31:13 - Lumine and its focus on the media and communication vertical 00:44:16 - Sygnity and its new chapter 01:03:51 - Asseco Poland and why it might be a the next Topicus 01:11:40 - Whether Shawn and Daniel add a Mini Constellation to the portfolio *Disclaimer: Slight timestamp discrepancies may occur due to podcast platform differences. BOOKS AND RESOURCES The Investors Podcast Network is excited to debut a new community known as The Intrinsic Value Community for investors to learn, share ideas, network, and join calls with experts: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Sign up for the waitlist(!)⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Sign up for ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The Intrinsic Value Newsletter.⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Learn how to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠join us⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ in Omaha for the 2026 Berkshire Hathaway shareholder meeting. Track ⁠⁠⁠⁠⁠⁠The Intrinsic Value Portfolio⁠⁠⁠⁠⁠⁠. Shawn & Daniel use ⁠⁠⁠⁠Fiscal.ai⁠⁠⁠⁠ for every company they research — use their ⁠⁠⁠⁠referral link⁠⁠⁠⁠ to get started with a 15% discount! Outsiders' Corner Asseco Writeup. Outsider's Corner Asseco Writeup No.2. Alankrit Capital Sygnity Writeup. Seeking Winners Lumine Writeup. Check out our previous Intrinsic Value breakdowns: ⁠⁠⁠⁠Transdigm⁠⁠⁠⁠, ⁠⁠⁠⁠Salesforce⁠⁠⁠⁠, ⁠⁠⁠⁠Berkshire Hathaway⁠⁠⁠⁠, ⁠⁠⁠⁠FICO⁠⁠⁠⁠, ⁠⁠⁠⁠PayPal,⁠⁠⁠⁠ ⁠⁠⁠⁠Uber⁠⁠⁠⁠, ⁠⁠⁠⁠Nike⁠⁠⁠⁠, ⁠⁠⁠⁠Amazon⁠⁠⁠⁠, ⁠⁠⁠⁠Airbnb⁠⁠⁠⁠, ⁠⁠⁠⁠Alphabet⁠⁠⁠⁠. Related ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠books⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ mentioned in the podcast. Ad-free episodes on our ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Premium Feed⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. NEW TO THE SHOW? Follow our official social media accounts: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠X (Twitter)⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠LinkedIn⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Facebook⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Browse through all our episodes (complete with transcripts) ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Try Shawn's favorite tool for picking stock winners and managing our portfolios: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠TIP Finance⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Enjoy exclusive perks from our ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠favorite Apps and Services⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Learn how to better start, manage, and grow your business with the ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠best business podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ References to any third-party products, services, or advertisers do not constitute endorsements, and The Investor's Podcast Network is not responsible for any claims made by them. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://theinvestorspodcastnetwork.supportingcast.fm