Podcasts about DevOps

Copper twisted pair cabling serves as a fundamental component of Ethernet infrastructure and Ethan and Holly are here to break down how it works. They discuss the technical differences between cabling categories, how wire twisting cancels out electromagnetic interference, and share practical guidance on installation standards and testing methodologies. Episode Links: Watch this episode on... Read more »

Kyler and Ned are joined by former AWS Community Program Manager Jason Dunn to discuss what it takes to build and maintain a thriving tech community. Jason shares his “benevolent dictatorship” philosophy on community management, emphasizing the importance of authentic human connections. They also explore how AI can empower non-technical individuals to build custom solutions... Read more »

Kyler and Ned are joined by former AWS Community Program Manager Jason Dunn to discuss what it takes to build and maintain a thriving tech community. Jason shares his “benevolent dictatorship” philosophy on community management, emphasizing the importance of authentic human connections. They also explore how AI can empower non-technical individuals to build custom solutions... Read more »

SUMMARY: What does a Forward-Deployed Engineer actually do? And what about deploying AI Harness? Let's dig into the real-world with these evolving AI concepts and technologies. SHOW: 1039SHOW TRANSCRIPT: The Enterprise AI Show #1039 TranscriptSHOW VIDEO: https://youtu.be/QY0fqu2O84MSHOW SPONSORS:OutShift by Cisco - “Scaling Out Superintelligence”  The Internet of Cognition architectureShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!Nasuni - Activate your data for AI and request a demoSHOW NOTES:Mozilla Thunderbolt launched Mozilla Thunderbolt (homepage)Topic 1 - Welcome to the show, tell us a bit about your background and what you focus on these days.Topic 2 - Let's talk about the role of Forward Deployed Engineer, it's being talked about a lot, but you're living in that world now. What problems are FDEs usually tasked with trying to solve, or new things to implement?Topic 3 - We've seen other roles (DevOps, PlatformEng, etc.) that evolved from other roles or skills. What type of background lends itself to success in FDE? What skills are needed going forward?Topic 4 - You're also working on some AI harness implementations. What can you tell us about those challenges and the technologies behind the harness?Topic 5 - At what point does an AI harness make sense for a company? What types of AI challenges typically require those next steps? Topic 6 - Working in the middle of this evolving AI space, what are some perspectives you've gained over the last 6-12 months? What do you wish you knew ahead of time? FEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

Speaker, author, and software developer recognized with a Microsoft MVP Award for Developer Technologies. Stacy has been developing solutions since the mid-1990s across various industries. She authored Beginning Azure Static Web Apps and is passionate about Azure, DevOps, and empowering developers.You can find Stacy on the following sites:XBlogLinkedInMastodonBlueSkyHere are some links provided by Stacy:MVP ProfileSessionize PLEASE SUBSCRIBE TO THE PODCASTSpotifyApple PodcastsYouTube MusicAmazon MusicRSS FeedYou can check out more episodes of Coffee and Open Source on https://www.coffeeandopensource.comCoffee and Open Source is hosted by Isaac Levin

AWS Morning Brief for the week of June 22nd, with Corey Quinn. Links:AWS Marketplace announces AI-assisted product listingAmazon CloudWatch introduces Log Analytics for unified log analysisAmazon EKS now supports customer-routed control plane egressFree Network Bandwidth Amazon GameLift Servers is Here!AWS announces AWS Blocks, an open-source framework for composing application backends on AWS (Preview)AWS Compute Optimizer enhances EBS volume recommendations with additional performance metricsIntroducing AWS Continuum for security at machine speedAWS Management Console Private Access now works without internet connectivityAWS Security Agent announces support for Threat ModelingGrok 4.3 from xAI now available in Amazon BedrockAmazon Aurora and RDS for MySQL expand Extended Support for MySQL 5.7 through June 2029AWS Marketplace reduces listing fee for professional services to 0.5%S3 Vectors: More Results, Cheaper Queries, Fresh FeesAmazon S3 annotations: attach rich, queryable context directly to your objectsAnnouncing Amazon EC2 G7 instances accelerated by NVIDIA RTX PRO 4500 Blackwell Server Edition GPUsAWS DevOps Agent adds release management capabilities to assess code changes before production (preview)AWS WAF adds AI traffic monetization capability to help content owners charge AI bots for content accessSimulating Amazon EC2 EBS burst credits before downsizing an instanceAWS Security Bulletin Quartet: AI Tools Forget Unix 101

Ruel Nopal is the Founder of IT Philippines. IT Philippines is an active community of IT enthusiasts, professionals, learners, and innovators - a Facebook group with 600,000+ members, 15,000,000+ views, and 4,000+ posts everyday. IT Philippines is your ultimate hub for all things Information Technology in the Philippines. Their mission is to build a community where collaboration, knowledge-sharing, and mutual support are at the forefront. Whether you're a coder, network administrator, IT manager, a student, or just someone fascinated by the world of technology, this is the place for you. IT PH firmly believes in the power of diversity and inclusivity. This episode is recorded live at Yspaces in BGC, Taguig. Yspaces is our official Co-working and Event Space Partner.In this episode:00:00 Introduction01:52 Ano ang IT Philippines?11:04 Ano ang IT? 13:07 Ano ang DevOps? 34:29 How is it to build the IT Philippines community? 01:03:24 How can listeners find more information?IT PHILIPPINESFacebook: https://facebook.com/groups/itphil

Shahram Anver is the Co-Founder and CEO of Cleric, the autonomous AI SRE that investigates and root-causes production issues like an experienced teammate — often in under two minutes. Before Cleric, Shahram led MLOps, DevOps, and FinOps platform engineering at Gojek, Southeast Asia's super-app. In this conversation, he breaks down why production operations never kept pace with AI-accelerated development, and why the real unlock for an AI SRE isn't faster triage — it's an agent that *learns* and compounds operational memory across your whole org.In this episode:

Matt Lyman is the Vice President of Marketing at Flosum, an enterprise Salesforce-native platform for DevOps, data protection, backup, security, and governance. With nearly 20 years of experience across demand generation, ABM, marketing operations, and B2B growth, he leads marketing strategy for technical audiences and helps translate complex products into clear, human-centered messaging. Matt previously held marketing leadership roles at Chef Software and LeanData and brings a people-first perspective shaped by his background in theater and community building. In this episode… Marketing to technical audiences exposes weak assumptions quickly. These buyers rarely respond to vague promises or generic campaigns. So how can marketers create marketing systems that earn trust, generate demand, and keep improving? Matt Lyman, a B2B marketing leader with expertise in demand generation, technical audiences, paid media, and community-led growth, explains that the answer starts with understanding the human behind every technical buying decision. Instead of treating messaging as a static brand exercise, teams should treat it like a hypothesis: test it, listen to feedback, and adjust based on what the market reveals. Matt emphasizes the importance of tailoring messages to executives and practitioners, choosing events based on audience fit, watching leading indicators before pipeline slips, and using AI to accelerate work without replacing human strategy. The result is a more focused marketing engine built around precision, context, and continuous learning. In this episode of the Revenue Engine Podcast, Alex Gluz talks with Matt Lyman, Vice President of Marketing at Flosum, about building effective marketing engines for technical audiences. Matt shares how technical buyers shape messaging, why event and paid media strategy require focus, and what leading indicators reveal about pipeline health. He also touches on AI, community building, and mentorship.

In this sponsored episode by Cisco we explore how agentic AI is transforming network operations and what it means for your career. Robert Barton, an AI Distinguished Engineer at Cisco Systems, joins Ethan and Holly to help us snap the artificial intelligence puzzle piece into your networking picture. Together they break down the AI trifecta:... Read more »

The conversation around artificial intelligence often creates the impression that software development has already been transformed beyond recognition. Social media feeds are filled with stories about AI agents replacing teams, generating applications automatically, and eliminating the need for traditional development processes. The Enterprise AI Reality is much more nuanced. While AI has become a valuable tool inside software organizations, large enterprises are approaching adoption far differently than many public conversations suggest. The gap between experimentation and production remains significant, especially when millions of dollars, regulatory requirements, and customer trust are involved. About Samuel Otero Samuel Otero is a Software Solutions Specialist with Deloitte US and a technology consultant with nearly 14 years of experience spanning enterprise software development, government projects, commercial consulting, and large-scale digital transformation initiatives. His career began with an early Microsoft internship that shaped his approach to continuous learning and technical humility. Since then, he has worked across media, public-sector, and enterprise environments, helping organizations deliver complex software solutions while mentoring the next generation of developers. Based in Puerto Rico, Samuel is also an advocate for developer growth, career development, and practical AI adoption in modern software engineering. Links LinkedIn Enterprise AI Reality Is Different from Social Media One of the strongest observations Samuel shared was the contrast between what people see online and what happens inside large organizations. Social media often highlights extreme success stories. Teams appear to build entire products using AI agents. Individual developers showcase impressive workflows that dramatically accelerate delivery. Those examples are real. However, enterprise software operates under different constraints. Systems support financial transactions, critical business processes, compliance requirements, and large customer bases. Mistakes carry significant consequences. As a result, organizations are adopting AI incrementally rather than replacing existing development practices overnight. Enterprise AI Reality Requires Trust Before Automation Every technology faces a trust curve. Before organizations automate critical workflows, they need evidence that systems perform reliably under real-world conditions. Samuel described how enterprises often use AI first in lower-risk scenarios before allowing it to influence more critical components of a platform. Features with limited business risk become testing grounds for new approaches. This pattern mirrors previous technological shifts. Cloud adoption happened gradually. DevOps adoption happened gradually. AI adoption is following a similar trajectory. The technology may be powerful, but trust must be earned through consistent results. Enterprises don't adopt technology because it's impressive. They adopt it because it's reliable. Enterprise AI Reality Still Depends on Human Expertise One misconception surrounding AI is that generated code eliminates the need for technical understanding. In practice, the opposite may be true. The more organizations rely on AI-generated outputs, the more important validation becomes. Developers must understand architecture, business requirements, security concerns, and implementation details well enough to verify what AI produces. Samuel emphasized a simple but powerful habit: asking AI to explain exactly what it did and why it made certain decisions.   That approach transforms AI from an answer machine into a learning tool. Developers who understand generated solutions become more effective. Developers who blindly accept generated solutions create risk. Never merge AI-generated code until you can explain its behavior to another developer. Enterprise AI Reality Is Creating New Skill Gaps The rise of AI is changing how developers gain experience. Historically, growth came from solving difficult problems manually. Developers researched documentation, struggled through debugging sessions, and built mental models through repetition. AI reduces much of that friction. While this increases productivity, it also creates new challenges. Developers may complete tasks successfully without fully understanding how those tasks were accomplished. Over time, this can create a dangerous gap between perceived capability and actual expertise. Organizations must address this by emphasizing understanding rather than output alone. The future belongs to developers who combine AI acceleration with deep technical comprehension. Enterprise AI Reality May Increase Software Complexity An interesting prediction from the discussion involved software quality. As AI accelerates development, more software will be produced. More features will be released. More experiments will reach production environments. That acceleration creates opportunity. It also creates risk. Samuel suggested that many organizations are still learning where AI performs exceptionally well and where it struggles under enterprise-scale conditions. During that learning period, users may experience more bugs, patches, and corrective updates as teams discover limitations. This isn't evidence that AI has failed. It's evidence that every transformative technology goes through a maturation phase before reaching stability. Faster development cycles can produce bugs faster if organizations don't maintain engineering discipline. Enterprise AI Reality Still Comes Back to Problem Solving Perhaps the most important lesson from the entire conversation is that technology itself is rarely the source of professional value. Languages change. Frameworks change. Platforms change. AI models will change. The underlying business need remains consistent: solving problems. Samuel's closing advice focused on developing problem-solving skills rather than attaching identity to a specific technology stack. That mindset provides resilience regardless of how quickly tools evolve. Developers who can understand problems, communicate solutions, and create business value will remain relevant long after today's AI tools are replaced by tomorrow's innovations. The most durable technical skill isn't coding. It's problem-solving. Conclusion The Enterprise AI Reality is neither the dystopian future predicted by skeptics nor the fully automated paradise promised by enthusiasts. Instead, it's a period of careful experimentation, measured adoption, and ongoing learning. Organizations are discovering where AI delivers value, where human expertise remains essential, and how both can work together to build better software. The developers who succeed during this transition won't be the ones who resist AI or blindly trust it. They'll be the ones who learn how to use it responsibly while continuing to strengthen the problem-solving skills that define great engineers. Stay Connected: Join the Developreneur Community

Before he founded Render, Anurag Goel was the fifth engineer at Stripe, where he watched roughly a fifth of the engineering team disappear into managing AWS, writing brittle, repetitive, error-prone infrastructure scripts that had nothing to do with the actual product. That experience became the seed for Render: a platform that automates away the undifferentiated DevOps work and lets application teams ship without standing up their own cloud team. Today, millions of developers build on it, and Render has raised over $260M from Bessemer and General Catalyst. In this episode, Tobi and Anurag get into what's actually changing as AI moves from hype to production. Anurag makes the case that agents are simply a new kind of application, long-running, stateful, tool-heavy, and a new kind of end user you have to design for. He explains why Render deliberately refuses the "AI cloud" label, what he's building with Workflows and sandboxes, and why the hardest part of shipping agents isn't building them but seeing inside them. The conversation also goes wide: how to hire executives when interviews lie, why short-lived keys and blast-radius thinking matter more than container escapes, how distribution is shifting from SEO to getting ChatGPT and Claude to recommend you, and why, despite all the "SaaS is dead" noise, specialization isn't going anywhere. Topics covered: Why ~20% of Stripe's engineers were stuck managing AWS and how that became Render "We're not the AI cloud, we're the application cloud," and why the distinction matters Agents, as a new type of application (and a new end user), you have to build for Render Workflows and sandboxes: the consolidated AI runtime Hiring executives when interviews are an imperfect signal Security as blast-radius management: short-lived keys over "admin forever" The shift from SEO to GEO, getting chatbots to recommend your product Why SaaS isn't dying, and specialization still wins

Life sciences are at a critical inflection point, where scientific innovation, regulatory demands, and patient expectations converge with advances in data and artificial intelligence, positioning IT as a central driver of faster and more effective drug discovery and clinical development.This week, Dave and Rob continue with part 2 off the Life Sciences mini-series with Dr. Alex Zhavoronkov founder and CEO of Insilico Medicine to exploring how drug discovery and clinical development can become faster and more effective, and the role of AI in that process.  TLDR00:40 – Introduction01:00 – Hang out: Kill Bill Vol. 1 & 2 03:07 – Dig in: Life Sciences mini-series, Part 2 06:43 – Conversation with Dr Alex Zhavoronkov 42:12 – The future of AI in drug discovery and a new paradigm for pharma GuestDr. Alex Zhavoronkov: https://www.linkedin.com/in/zhavoronkov/ HostsDave Chapman:  https://www.linkedin.com/in/chapmandr/Esmee van de Giessen:  https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan:  https://www.linkedin.com/in/rob-kernahan/ ProductionMarcel van der Burg:  https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman:  https://www.linkedin.com/in/chapmandr/ SoundBen Corbett:  https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:   https://www.linkedin.com/in/louis-corbett-087250264/ 'Realities Remixed' is an original podcast from Capgemini

Tommy Cotter is Director of Data Products at Benzinga, a financial media company building the data infrastructure that sits behind trading platforms and investment apps used by millions of people daily. He's been navigating the shift to AI-assisted workflows in a space where speed and accuracy aren't just nice to have - getting it wrong has real consequences.In this episode, Peter and Dave talk with Tommy about what it actually looks like to build data products responsibly in a fast-moving AI environment. They get into where humans still need to be in the loop, how compliance has become a competitive signal, and why being nimble matters more than picking the perfect architecture from day one.Three things to take away from this conversation:Self-agency is real now. If you have a strong conviction about a product or problem, the barrier to building something has never been lower. That's a genuine shift from even five years ago.Security and compliance are no longer just internal concerns. In a world where AI startups spin up overnight, having invested in SOC2 or GDPR signals to customers that you're a legitimate, trustworthy operation. It's a market differentiator.Humans still belong in the system. Not everywhere, but in the right places. For low-risk, deterministic processes, let AI run. For anything client-facing or accuracy-critical, keep a human in the loop. Knowing the difference is the skill.If this conversation sparked something for you, send us your thoughts at feedback@definitelymaybeagile.com. And if you haven't already, hit subscribe so you don't miss the next one.

The Pope issued a recent encyclical on AI, urging developers to safeguard human agency in the age of artificial intelligence. Eyvonne and William explore this encyclical, moving beyond the headlines to the core message regarding human dignity. They examine how the document provides a values-based framework for evaluating technology and the need for a balanced... Read more »

פרק מספר 516 של רברס עם פלטפורמה - קרבורטור מספר 41. הפעם רן ואורי מארחים את נתי לשיחה על נקודת המפגש המרתקת שבין קוד פתוח לקידוד מבוסס סוכנים (Agentic Coding). דיברנו על העתיד הדיסטופי והאופטימי של מפתחי קוד פתוח, איך משווקים מוצרים ל-Agents, ולמה שורת הפקודה (CLI) חוזרת אלינו בענק. [01:04] העתיד המדומיין של AI (סיפורו של OpenClaw) נתי משתף סיפור משעשע על ניסיון לחקור את "OpenClaw". הזיות (Hallucinations) של מודלים: Claude מאשר את העובדות, בעוד ש-Gemini מנתח שמדובר בהמצאה עתידית (פברואר 2026). הבנה שמודלי שפה (LLMs) הם מנועים הסתברותיים ולא מנועי חיפוש עובדתיים. [05:58] החזון הדיסטופי: האם AI יהרוג את הקוד הפתוח? בעיית ההעתקה: בעבר קוד הוגן על ידי רישיונות (כמו AGPL), היום קל לבקש מהמודל לשכתב קוד משפה אחת לאחרת (למשל מ-NodeJS ל-Rust) בעלויות אפסיות. קריסת מודלים עסקיים: עלויות התמיכה והאופרציה (Operation) יורדות כי ה-Agent מתקן תקלות לבד, מה שחותך את ההכנסות של חברות כמו Red Hat. עומס על ה-Maintainers: קוד מג'ונרט על ידי Agents נראה מעולה ומתועד היטב, אבל לא תמיד נכון ארכיטקטונית או לוגית. גישות התמודדות: חלק דורשים לקבל את ה-Prompt (הכוונה) ולא את הקוד עצמו, בעוד שאחרים (כמו יוצר שפת Zig) אוסרים לחלוטין גישה של AI לפרויקט. [15:15] החזון האופטימי: שיווק לסוכנים (GEO) מעבר מ-SEO ל-GEO (Generative Engine Optimization): סוכני AI הם הלקוחות החדשים. איך Agent בוחר כלים? לפי איכות הקוד, הפופולריות שלו ב-GitHub, ובעיקר לפי התיעוד. קוד פתוח הופך לכלי שיווקי קריטי (Open Core) כדי שהסוכנים יוכלו למצוא, להבין ולהמליץ על המוצר. מודלים היברידיים ו-Freemium: מוצרים (כמו Postits) מציעים גישה ללא חומת תשלום (Paywall) בשלבים הראשונים, מה שמאפשר ל-Agents לעבוד איתם בקלות דרך API (Headless SaaS), ואפילו לבצע רכישות בעצמם בהמשך דרך Stripe. [30:29] שובו של ה-CLI ומגבלות ה-MCP הדיבייט סביב MCP (Model Context Protocol): הפרוטוקול כבד, "זולל" טוקנים (Token hungry) עבור הקונטקסט, ודורש תחזוקה של שרתים נוספים. למה Agents כל כך אוהבים CLI (שורת פקודה)? גישה ישירה לאקוסיסטם המקומי והרשאות (כמו Kubernetes או סביבות ענן) בלי לחשוף מפתחות לשירות חיצוני. יכולת לבצע מניפולציות מורכבות בצד הלקוח (Chaining, Grep, Sed) מבלי לשנות קוד ב-Backend, מה שהופך את המודלים לאנשי DevOps מעולים. [36:17] רישיונות קוד פתוח וה"נשמה" של המוצר האתגר באכיפת רישיונות (כמו GPL) בעולם שבו קשה להוכיח על איזה קוד המודל התאמן ואם בוצעה העתקה. הבדל חשוב בטרמינולוגיה: מודלים של "Open Weights" לעומת מודלים שה-Training Data שלהם באמת פתוח. תוכנה כיצירת אומנות מול קומודיטי (Commodity): האם קוד מג'ונרט יכול להחליף את החזון וה"נשמה" (Soul) של מפתחים בולטים? ההשוואה לעולם המוזיקה מדגישה שמשתמשים הולכים אחרי האומן והחזון, לא רק אחרי הקוד היבש. [50:25] רגולציה ומודלי Open Weights אורי מעלה נקודה מעניינת על החסימה של מודל Fable 5 / Mytos 5 (של Anthropic) למשתמשים מחוץ לארה"ב על ידי הממשל האמריקאי. ההשפעה של רגולציה: ה"תקרת זכוכית" הזו עלולה לפגוע בחברות המסחריות האמריקאיות בטווח הקצר, ודווקא לדחוף קדימה מודלים פתוחים (Open Weights) סיניים או אירופאים שאינם כפופים לאותן מגבלות. האזנה נעימה!

AWS Morning Brief for the week of June 15th, with Corey Quinn. Links:AWS announces AWS Workload Credentials ProviderAnnouncing the public preview of AWS FinOps AgentIntroducing AI-Powered Cost Investigations For Cost AnomaliesAmazon CloudWatch Logs Insights adds 23 new query commands and functionsIntroducing Target Coverage in Savings Plans Purchase AnalyzerIntroducing the AWS Credits Detail PageAnthropic Claude Fable 5 on AWS: Mythos-class capabilities with built-in safeguards now availableNow available: Amazon EC2 M9g and M9gd instances powered by new AWS Graviton5 processorsTry the new console experience in Amazon Bedrock, optimized for Anthropic- and OpenAI-compatible APIsAWS Nitro Isolation Engine: Formally verifying the hypervisor in the AWS Nitro SystemIt's safe to close your laptop now: Hosting coding agents on Amazon Bedrock AgentCore27 AWS Security Bulletins: A Patch Tuesday That Lasted a Year

In this episode, host Sandy Vance chats with Brad Schoffstall, Vice President of Health and Compliance Programs at CGI, and Dr. James Peake, Senior Vice President and former Secretary of Veterans Affairs and Army Surgeon General. They have a wide-ranging and practical conversation about what it actually takes to modernize data infrastructure at federal health agencies. With Brad's 35 years at CGI and Dr. Peake's 16 years, this is a conversation grounded in hard-won experience rather than theory. Today's conversation is a refreshingly honest and deeply practical perspective for anyone working at the intersection of government, healthcare, and AI.  In this episode, they talk about: Federal health agencies are running some of the largest healthcare operations in the world, with the VA equivalent in size to a Fortune 5 company Data silos created by contract-by-contract procurement are the primary barrier to AI-ready infrastructure at federal agencies Federated data platforms allow data to stay in its own repositories while being discoverable, mappable, and usable across the organization Policy is often the biggest obstacle to data sharing, and changing it requires executive-level support and shared governance Technology is the third most important factor in transformation; policy and business understanding come first and second CGI improved NHS Spine performance tenfold while reducing infrastructure to a tenth of its original size, saving a million euros in annual expenses Improper payments across federal health programs run into billions of dollars annually and represent one of the highest-impact areas for AI-driven improvement AI for AI's sake is not the answer; start with the business problem and work backward to the data strategy Start small with two or three systems, demonstrate value, and build from there rather than attempting a massive all-at-once implementation A Little About Brad and James: Brad Schoffstall has wide-ranging experience, deep knowledge, and skills in information technology. He has led multiple digital transformation efforts. He has 37 years of experience with a diverse set of architectures, operating systems, languages, and technologies. His experience includes enterprise architecture, cloud migration, and hands-on development. He also has significant experience in business development and project management. He has implemented large, complex systems on platforms ranging from mainframes to Microservices. He has successfully performed many solution architecture and SDLC engagements that include characteristics like high-volume processing, DevOps, and automation. He demonstrates expertise in multiple service-based secure architectures utilizing multiple application and enterprise solution sets, e.g., Data Driven, Microservices, Cloud, etc. Dr. James Peake is an American politician and former lieutenant general who served as the sixth Secretary of Veterans Affairs from 2007 to 2009. In 2004, he retired from a 38-year United States Army career, having served as the 40th Surgeon General of the United States Army. After retiring from the Army, Peake served as Executive Vice President and Chief Operating Officer of Project Hope,[4][5] a non-profit international health foundation operating in more than 30 countries. While at Project HOPE, he helped to orchestrate the use of civilian volunteers aboard the Navy Hospital Ship Mercy as it responded to the tsunami disaster in Indonesia and also as part of the Hurricane Katrina response aboard the Hospital Ship Comfort. Just before he was nominated Secretary of Veterans Affairs, Peake served as Chief Medical Officer and Chief Executive Officer for QTC, one of the largest private providers of government-outsourced occupational health and disability examination services in the nation. 

OpenChoreo is an opinionated, “batteries included”, AI-native Kubernetes platform stack for Platform Engineers that combines GitOps, Observability, AI Agents, and Workflows into a custom K8s distribution “super pack” that is managed via Backstage, CLI, API, or MCP. Now a CNCF project.Check out the video podcast version here: 

As a network engineer, you'll end up with a lot of weird problems to solve. Many times, the problems will not be with the network at all, and it’ll be up to you to figure it all out. But how? Ethan and Holly discuss techniques for effective troubleshooting. Those techniques include how to gather accurate... Read more »

What happens when two cloud economists leave AWS  behind and spend six days hiking 60 miles on the Appalachian Trail? Corey Quinn sits down with Caleb Hurd to share stories from the trail, including exploding sleeping pads, heroic shuttle drivers, lost phones, and the unique community that makes long-distance hiking special. Along the way, they draw surprising parallels between backpacking and cloud economics, discussing everything from serverless architecture and cloud cost optimization to the hidden challenges of on-prem infrastructure. It's a conversation about technology, adventure, perspective, and why sometimes the best way to solve complex problems is to step away from them entirely.Show highlights:(00:00) Why Hiking Hooks You(00:15) Meet Caleb on the Trail(01:31) Trail Miles and Ultralight Parallels(05:24) The Sleeping Pad Blowout(07:46) Shepherd Saves the Day(09:43) Trail Community and Cloud Community(11:07) Post Trail Perspective and Inside Jokes(15:35) Back to Work On Prem vs Cloud Pain(25:47) Server-less Spend and Lambda Sprawl(32:29) Wrap Up Where to Find CalebAbout Caleb: Caleb Hurd is a Cloud Economist at Duckbill, where he helps enterprises make sense of their cloud spend. Before moving to the cost side of the house, Caleb spent years in the trenches building and operating large-scale cloud environments and leading the engineering teams behind them across companies ranging from healthcare tech to enterprise Saas. He also founded CostOps.cloud, an AWS cost consulting practice, and is a vocal advocate for engineering-led FinOps — arguing that the people closest to the architecture should be the ones driving cost strategy, not spreadsheet jockeys in finance. Caleb holds a degree from Georgia Tech and made an unconventional journey into tech from a background in carpentry, which may explain his preference for building things over just talking about them. He's based in Atlanta.Links:LinkedIn: https://www.linkedin.com/in/calebrhurd/Sponsored by: duckbillhq.com

Innovation isn't about funding, it's about how organisations are built and led. Progress comes from cutting bureaucracy, empowering mission-led teams, and asking the right questions to unlock bold breakthroughs. This week, Dave, Esmee and Rob are joined again by André Loesekrug-Pietri, Chair and Scientific Director of the Joint European Disruptive Initiative (JEDI, Europe's ARPA) to explore how Europe can turn moonshot ambitions into reality by building the right people, culture and operating models for future-shaping organisations. TLDR00:41 – Introduction01:14 – Hang out: Esmee returns and the missing API has been found!05:14 – Dig in: Staying in step with global innovation12:57 – Conversation with André Loesekrug-Pietri1:02:26 – Roland Garros tennis, and unlocking creative energy GuestAndre Loeskrug-Petri: https://www.linkedin.com/in/andrepietri/X: @eurojediwww.jedi.foundation HostsDave Chapman:  https://www.linkedin.com/in/chapmandr/Esmee van de Giessen:  https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan:  https://www.linkedin.com/in/rob-kernahan/ ProductionMarcel van der Burg:  https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman:  https://www.linkedin.com/in/chapmandr/ SoundBen Corbett:  https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:   https://www.linkedin.com/in/louis-corbett-087250264/ 'Realities Remixed' is an original podcast from Capgemini

As AI matures, it becomes increasingly important to know how it's performing and what it actually costs. Ned and Kyler are joined by Anuj Tyagi, Senior Site Reliability Engineer for RingCentral, to discuss the critical shift toward AI observability. AI observability is not just about costs; Anuj breaks down why observability has to include agent... Read more »

As AI matures, it becomes increasingly important to know how it's performing and what it actually costs. Ned and Kyler are joined by Anuj Tyagi, Senior Site Reliability Engineer for RingCentral, to discuss the critical shift toward AI observability. AI observability is not just about costs; Anuj breaks down why observability has to include agent... Read more »

As AI matures, it becomes increasingly important to know how it's performing and what it actually costs. Ned and Kyler are joined by Anuj Tyagi, Senior Site Reliability Engineer for RingCentral, to discuss the critical shift toward AI observability. AI observability is not just about costs; Anuj breaks down why observability has to include agent... Read more »

IPv8 уже в драфте, Terraform хоронят в блогах, а одна компания жжёт $7M в год на Claude Code. Собрали новости DevOps, которые вы накидали через бота. О ЧЁМ ВЫПУСК Новостной выпуск: накопилось 63 новости, разобрали самое горячее. И снова с нами Ярослав. В этом выпуске: • IPv8: драфт в IETF - ASN в первых 32 битах, старый IPv4 во вторых. Без NAT и dual-stack, плюс токен-идентичность на каждый девайс • Terraform 1.15: переменные в source и version модулей, отдельная аутентификация для S3 backend • "Terraform is dead": разбираем хайповую статью - спека как desired state, Pulumi, CDK и причём тут AI • Terragrunt 1.0: units, stacks и фильтр по affected-ресурсам через git worktree • NGINX 1.30: sticky sessions, keep-alive и HTTP/2 к апстримам, Early Hints (103), Encrypted Client Hello • Экономика AI: Semi-Analysis масштабировала Claude Code до $7M/год, дефицит RAM • Google Agent Sandbox: новый Kubernetes CRD между StatefulSet и Deployment Сквозная мысль выпуска: AI ускоряет всё, но без понимания, как работают системы, спека и вайб-кодинг рано или поздно стреляют в ногу. ГОСТЬ Ярослав Бледковский - Un-principal SRE, Wargaming ССЫЛКИ Все новости выпуска (тезисы, голосование, ссылки): https://dkt-ai.github.io/episodes-news/episodes/episode-97-ru Присылайте новости через бота: @dkt_news_bot Упомянутые ресурсы: • IPv8 draft (IETF): https://www.ietf.org/archive/id/draft-thain-ipv8-00.html • Terraform 1.15: https://github.com/hashicorp/terraform/releases/tag/v1.15.0 • "Terraform is dead" (статья): https://grahamgilbert.com/blog/2026/04/20/terraform-is-dead/ • Terragrunt 1.0: https://github.com/gruntwork-io/terragrunt/releases/tag/v1.0.0 • NGINX 1.30: https://github.com/nginx/nginx/releases/tag/release-1.30.0 • AI tokens (Dylan Patel / Semi-Analysis): https://www.youtube.com/watch?v=LF3aUIM57uw • Kubernetes Agent Sandbox: https://github.com/kubernetes-sigs/agent-sandbox ПОДКАСТ YouTube - www.youtube.com/@DevOpsKitchenTalks Apple Podcasts - https://apple.co/41O6mqA Spotify - https://t.ly/Jg5_2 Yandex Music - https://music.yandex.ru/album/10151746 PodBean - https://devopskitchentalks.podbean.com НАВИГАЦИЯ 00:00 - Интро: вы уже на IPv6 или ещё IPv4? И снова в гостях Ярослав 02:53 - Anthropic и 200K карточек от Маска: лимиты Claude отпустило 04:26 - Адженда из 63 новостей через наш Telegram-бот

AWS Morning Brief for the week of June 8th, with Corey Quinn. Links:AWS Interconnect - multicloud now offers a free 500 Mbps tierOracle Database@AWS is now available in twenty AWS RegionsAmazon Cognito now supports multi-Region replicationAmazon EKS and Amazon EKS Distro now supports Kubernetes version 1.36Amazon SES now supports tenant-level suppression listsAWS Compute Optimizer now supports 32-day lookback for EBS volume and ECS service rightsizing recommendationsAWS Cost and Usage Report 2.0 now supports Athena and Redshift integrationAmazon ElastiCache for Valkey now supports durabilityUnderstanding how backups work in Amazon AuroraOpenAI models and Codex on Amazon Bedrock are now generally availableHow Bedrock Streaming optimizes its AWS costsFrom Monolith to Multi-Account: Pinterest's AWS Organization Transformation JourneyGain visibility into DDoS attacks with flow logs in AWS Shield AdvancedIdentify unused AWS KMS keys and prevent accidental key deletionsCVE-2026-10591 - Kiro IDE Insufficient File Write Restrictions to Execution-Sensitive PathsCVE-2026-10584 - HTTPS Fallback to HTTP in Graph Explorer

Jennifer St Pierre is Senior Vice President of Developer Experience and Transformation at Dell Technologies, where she leads the strategy for how Dell's Infrastructure Solutions Group builds, operates, and evolves software.In this session from DX Annual, Jen argues that the biggest challenge in adopting agentic AI is not the technology itself, but the people transition behind it. Drawing on lessons from earlier shifts like Agile, DevOps, and cloud adoption, she explains why organizations that treat AI as a simple tooling rollout may get compliance, but not commitment.Jen outlines five leadership imperatives for navigating the transition: building a shared understanding of why change is happening, defining a clear future state, clarifying how roles will evolve, creating psychological safety for experimentation, and aligning metrics and organizational structures with new ways of working. Throughout the talk, she emphasizes that while AI may generate code, humans remain responsible for direction, judgment, and meaning.Where to find Jennifer St Pierre: • LinkedIn: https://www.linkedin.com/in/jennifer-st-pierre-4935a81In this episode, we cover:(00:00) Intro(00:13) Why every major technology shift is ultimately a people transition(05:00) AI-generated code and the evolving role of software engineers(07:43) The importance of developing a shared understanding(12:00) Defining a clear future state and how engineering roles will evolve(19:12) How psychological safety enables experimentation and honest feedback(22:41) Why metrics and organizational structure must evolve for the age of AI(25:40) Why leaders must drive AI transformation intentionallyReferenced:• Measuring developer productivity with the DX Core 4• Understand team effectiveness 

PHP Podcast – June 4, 2026 Hosts: Eric Van Johnson & John Congdon Another fun episode of the PHP Podcast! Here’s what we covered: PHP Tek 2027 — New Dates, Bold New Format Mark your calendars: PHP Tek 2027 is happening April 27–29 in Chicago, and Eric and John are shaking things up. Rather than a straight three-day PHP conference, next year gets three tracks — two of which are familiar PHP-focused content, and a third specialty track that rotates each day: one day of JavaScript, one day of DevOps, and one day of Laravel. The Laravel track is specifically focused on how developers actually use the framework day-to-day, not a product pitch. Single-day passes will be available, so if you’re only coming for the DevOps or JS day, you’re covered. One important heads-up: there’s a big convention happening at a venue nearby in Rosemont, so the hotel block could sell out faster than usual. When they open reservations, don’t wait. Holly the Elephant Is Going Fast The PHP Architect conference elephant, named Holly, is now available at store.phparch.com, and demand has been remarkable. Eric woke up one morning to a flood of orders and genuinely couldn’t figure out what happened. The warning from last year applies here: people said they’d grab Tony later, and now Tony is gone forever. Holly ships June 17th for most orders, but if you’ve already ordered, it’s likely on its way. Get yours while you can. PHP Tek TV Is Doing Something Different This Year In past years, conference talk videos would get edited and uploaded weeks (or months) after the event. This year, John is doing things differently: the raw, unedited recordings are going up now, with timestamps in the description so you can jump straight to specific talks — some rooms recorded a seven-hour continuous feed and just left it running. The clean edited versions are still coming (a video editor friend in the UK is on it), but if you want to see a talk right now, the raw version is there. Audio quality varies by room, but it’s watchable. Immich — A Self-Hosted Google Photos That Actually Works John has been running Immich, a self-hosted photo management platform, in a Docker container for about a month and loves it. It does facial recognition, GPS tagging, and auto-uploads from his phone — essentially everything he cares about in Google Photos, without handing his photos to Google or Apple. He’s now planning to use it as the PHP Architect conference photo library, centralizing all the Tech photos in one browsable, shareable place. It’s fully open source, with no licensing cost, and an optional donation tier. If you’re sick of paying ever-increasing storage bills to big tech companies, this is worth a look. Ben Ramsey’s PHP Tek Homecoming Article Is Free to Read The May issue of PHP Architect magazine is now available to digital subscribers, and this month’s free article is Ben Ramsey’s piece on the PHP Tek homecoming experience. Eric reached out to Ben last minute and he delivered. If you’ve never subscribed, this is a low-barrier way to see what the magazine is like. Head to phparch.com, grab the free article, and if you like what you see, subscriptions are not expensive. John Is Resurrecting a Legacy Laravel App — With Claude’s Help John has been grinding away on a Laravel 6 app that was a passion project years ago and has now been revived as an actual client project. Using Claude to methodically baby-step through each version upgrade — starting with writing tests to establish a baseline — he’s worked up through the major Laravel versions. The turning point came when he hit the version where the old event sourcing package (Prooph) was clearly on its way out, and the decision was made to migrate to Verbs, Nuno Maduro’s Laravel-native event sourcing package. John’s now looking forward to it. He’s also accidentally been burning tokens on the company Anthropic account (not his personal account), which Eric caught live on air. They are going to talk about it after the show. Eric’s Mystery Side Project Is Almost Ready — If DNS Would Cooperate Eric teased a new side project last week and intended to reveal it this week, but he’s stuck waiting on DNS propagation. The domain was registered with DigitalOcean DNS already in use by a previous owner, so Eric moved it to Cloudflare — only to discover there may be a conflict because the previous owner was also on Cloudflare. The result: the name servers are stuck on old values. John’s live suggestion was to move it to Route 53, and Eric was immediately sold. The project is almost ready to show the world, DNS gods willing. Meta’s AI Support Bot Got Socially Engineered Eric shared a video demonstrating how someone prompt-injected Meta’s AI customer support bot into sending a verification code to an attacker-controlled email address — and then using that code to add the email to an account, enabling a full password reset and account takeover. The irony: Meta is the company behind Llama and has some of the deepest AI expertise on the planet, and they still shipped a support bot with permissions it shouldn’t have. Eric’s point was pointed: you can fire a human employee who gets social engineered, which creates accountability throughout the team. An AI has no such incentive structure. Crowbarring AI into account-modification workflows without appropriate guardrails is just asking for this. The PHP Foundation Now Publishes Board Meeting Minutes Eric discovered that the PHP Foundation has started publishing their board meeting minutes in a public GitHub repository. Nothing earth-shattering yet, but seeing who attended, what was discussed, and what decisions are being made gives the community a real window into how the foundation operates at scale. It also helps explain something Eric and John have always found interesting: why PHP stalled so hard between versions 5 and 7. There was no foundation, no financial backing, just volunteer hours. Now there’s a paid staff and governance structure — and the minutes show exactly how complex running something at PHP’s scale actually is. The PHP Foundation Has a Dedicated Security Team Now Speaking of the Foundation, it now has a dedicated security team — a sign of how seriously the supply chain attack problem has gotten. AI tools are being deployed by black hat actors to find vulnerabilities in open source projects at a scale that wasn’t possible before. PHP is not just another open source project; it underpins a massive slice of the web, and companies depend on it staying secure. Having a team specifically focused on this is the right call, even if it’s a sobering reminder of where the threat landscape is heading. Moat — Nuno’s GitHub Security Auditing Tool Nuno Maduro (of Laravel fame) quietly shipped a tool called Moat that audits your GitHub presence for security gaps. Install it globally via Brew or Composer, point it at your GitHub org, a specific repo, or even a specific branch, and it gives you a report on where your security posture could be improved. It’s read-only — it won’t change anything — and it’s explicit that it is not a security certification. Eric wants to use it to audit the PHP Architect organization’s repos, many of which haven’t been touched in years. Think of it as a fast, opinionated triage tool, not a replacement for a real security audit. Links from the show: PHP Tek 2027 — Chicago, April 27–29 PHP Architect Store — Holly the Elephant Immich — Self-Hosted Photo Management PHP Architect Magazine Verbs — Laravel Event Sourcing by Thunk Moat — GitHub Security Auditing by Nuno Maduro PHP Foundation on GitHub PHP Architect Discord Host: Eric Van Johnson X: @shocm Mastodon: @eric@phparch.social Bluesky: @ericvanjohnson.bsky.social PHPArch.me: @eric John Congdon X: @johncongdon Mastodon: @john@phparch.social Bluesky: @johncongdon.bsky.social PHPArch.me: @john Streams: Youtube Channel Twitch Connect & Hire PHP Architect Website Twitter/X Mastodon Hire PHP Developers Looking to hire PHP developers? Email support@phparch.com – Joe and the team are available for consulting, infrastructure work, Ansible playbooks, and code review. Partner This podcast is made a little better thanks to our partners Displace Infrastructure Management, Simplified Automate Kubernetes deployments across any cloud provider or bare metal with a single command. Deploy, manage, and scale your infrastructure with ease. https://displace.tech/ PHPScore Put Your Technical Debt on Autopay with PHPScore CodeRabbit Cut code review time & bugs in half instantly with CodeRabbit. Music Provided by Epidemic Sound https://www.epidemicsound.com/ Join Us Live Next Week Youtube Channel Got feedback? Join us on Discord at discord.phparch.com The post The PHP Podcast 2026.06.04 appeared first on PHP Architect.

In this episode of Elixir Wizards, hosts Charles Suggs and Emma Whamond sit down with Marek Šuppa, creator of the Missing GitHub Status page, a project that reconstructs GitHub's historical uptime data and reveals discrepancies between official status reporting and the platform's actual reliability. Marek tells us about his dev journey from open source contributor at DuckDuckGo to machine learning engineer at Cisco-acquired Slido. Then, we discuss GitHub's evolution from a hosted Git service into a critical developer tool. We cover reliability, transparency, AI-driven platform growth, developer workflows, and the challenges of balancing convenience with resilience. Along the way, we cover alternative platforms, self-hosted solutions, and whether recent outages are changing how developers think about ownership, dependency, and the future of software collaboration. Topics Discussed in this Episode: Why did Mr. Shu create the Missing GitHub Status Page? GitHub's reported uptime versus developer experiences How open source contributions shaped Marek's career The evolution of GitHub from tool to critical infrastructure Centralization risks in modern software development Git's distributed roots and today's platform-centric workflows Developer reactions to GitHub outages Transparency and accountability in status reporting AI's impact on developer platforms and infrastructure demands Microsoft's stewardship of GitHub Forgejo, Codeberg, and alternative Git hosting platforms Self-hosted Git solutions and tradeoffs Network effects and platform lock-in The social side of software collaboration Building resilience into developer workflows What GitHub outages teach us about infrastructure dependency Links Mentioned: The Missing GitHub Status Page https://mrshu.github.io/github-statuses/ Slido https://www.slido.com/ https://duckduckgo.com/ The official GitHub Status Page https://www.githubstatus.com/ Statuspage.iohttps://www.atlassian.com/software/statuspage Zig Leaves GitHub https://ziglang.org/news/migrating-from-github-to-codeberg/ Ghostty Leaves GitHub https://mitchellh.com/writing/ghostty-leaving-github GitLab https://about.gitlab.com/ Codeberg https://codeberg.org/ https://git.kernel.org/ Forgejo Lightweight Self-Hosting https://forgejo.org/ Former GitHub CEO Thomas Dohmke launches Entire https://entire.io/news/former-github-ceo-thomas-dohmke-raises-60-million-seed-round Update on Spain and LALIGA blocks of the internet https://vercel.com/blog/update-on-spain-and-laliga-blocks-of-the-internet

Realities Remixed, formerly known as Cloud Realities, launches a new season exploring the intersection of people, culture, industry and tech.Life sciences are at a turning point, where scientific innovation, regulatory pressure, and patient expectations collide with unprecedented advances in data, AI, and digital platforms. IT is no longer a supporting function but a critical driver of how therapies are discovered, developed, scaled, and delivered safely and at speed.This week, Dave and Rob kick off the Life Sciences mini‑series with Thorsten Rall, Global Industry Lead for Life Sciences at Capgemini, to exploring the current state of the sector, the key themes shaping the episodes ahead, and what it takes to drive better patient outcomes. TLDR00:30 – Introduction to Life Sciences and co‑host Thorsten Rall04:37 – Hang‑out: Navigating Waterloo Station07:50 – Deep dive with Thorsten Rall into the Life Sciences landscape28:03 - What are the main challenges in the sector and main themes45:31 – BBQ season is starting HostsDave Chapman:  https://www.linkedin.com/in/chapmandr/Esmee van de Giessen:  https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan:  https://www.linkedin.com/in/rob-kernahan/with co-host Thorsten Rall: https://www.linkedin.com/in/thorsten-alexander-rall-b232185/ ProductionMarcel van der Burg:  https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman:  https://www.linkedin.com/in/chapmandr/ SoundBen Corbett:  https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:   https://www.linkedin.com/in/louis-corbett-087250264/ 'Realities Remixed' is an original podcast from Capgemini

I ran across a statement that seems exciting to me as someone that has written a lot of code in their career. It said: "Many of the "modern" software practices of the last decade were early adaptations to this shift, even if we didn't articulate them that way. Immutable infrastructure. Stateless services. Containers. Blue-green deployments. Infrastructure as code. These ideas all share a common premise: never fix a running thing. Replace it." These are a few sentences in this piece on the death and rebirth of programming. That's how a lot of software developers have viewed the world during the last decade and we've seen a lot of software advances in that time. The very successful developers and teams, who often speak at conferences and publish papers have adopted many of these practices. Serverless, containers, lots of tests allowing continuous deployment of new objects into complex environments that scale to levels many of us never thought possible. These are the very high performances talked about in the State of DevOps report every year. Read the rest of The Data Model Matters

William and Eyvonne discuss recent tech news, including the growing political and community opposition to AI data centers driven by fears over power and water usage. They also analyze the “AI Chip War” as hyperscalers such as AWS and Google invest in specialized silicon for training and inference.  Episode Links: Amid backlash, O'Leary Digital CEO... Read more »

We've informally heard that Satya is a listener to LS for a couple years now, but it was still absolutely surreal to meet him and do a live pod at Build, together with our friends at No Priors, the leading VC AI Podcast that we also greatly admire!We covered the MAI model technical takeaways on yesterday's AINews, so I will focus our recap of Satya's main messages around three elements:* Satya's adaptation of the Bill Gates Line for positioning Microsoft as the Frontier Intelligence Platform — customers must gain much more value from the Microsoft ecosystem than Microsoft itself, by building on multi-model harnesses like OpenClaw and Scout, drawing on the full enterprise context exposed by context layers like Work IQ (heavily dogfooded by his C-suite), and building up private evals and traces as a new form of Token IP* AI ROI: On one hand, enterprises are having difficult conversations around Tokenmaxxing and Layoffs, and on the other hand, there are serious re-evaluations of the End of SaaS since the Build vs Buy equation has changed so much. Our previous SemiAnalysis guest had… interesting comments on Microsoft's position on this as the ur-SaaS titan, and Satya had great answers* Making the Impossible Possible: Kevin Scott's inspiring framing around what the most ambitious version of applying AI and technology at large to business and social problems, like education and social impact.Enjoy!Full VideoTranscriptVoiceover: Welcome swyx, Sarah Guo, Elad Gil,, and Chairman and Chief Executive Officer of Microsoft, Satya NadellaSarah Guo: Welcome to a crossover episode of No Priors and Lane Space with Satya Nadella. Um, congratulations on an amazing build. No, thank you so much, and it's great to be with both of you. I listen to both of you or b- both the podcasts all the time. It's great to be on it.Thank you so much. [00:01:00] So you're just talking about, um, these amazing, uh, announcements from across the Microsoft estate all morning for, I think, three hours. What is the, uh, what's the most important reflection or takeaway you have?AI as an Ecosystem PlatformSarah Guo: I, I'd say there are, uh, perhaps the, the biggest one for me is let's sort of conceptualize this more as an ecosystem play as opposed to a single model or even a single platform, right?Satya Nadella: I mean, you know, whatever I... At least for me, having grown up at Microsoft, having seen, whatever, four major platform shifts, uh, I sort of fall into that, um, uh, camp where a platform is defined by fundamentally its ability to create more value about the platform versus what's captured in the platform. And so if you, you view what's happening right now, I think this morning's keynote was how can any company, whether it's an AI native company or a traditional enterprise company, participate as a first-class participant where they can point to AI they created, [00:02:00] right?It's not that they don't use other people's AI. Of course they will. But to me, what's the path? What's the recipe? How do I do it? What does a stack look like? What does the tooling look like? What is valuable? How do you do that? That's it. That's sort of our job to do. Yeah. Ecosystem strategy is, uh, very complicated, right?Sarah Guo: Because you end up building certain components, partnering for certain components, supporting them. You just announced this big suite of models. Like, tell us a little bit about the, uh, training strategy for Microsoft now. Yeah.MAI Models & Training StrategySarah Guo: So, so the thing that we wanted to do with the MAI models was to build, and as Mustafa talked about, first of all, a great lineage, right?Satya Nadella: Starting with pre-training, uh, with very good data quality, uh, doing all the ablations, making sure because in, in some sense it's becoming even harder to build a clean lineage model just because there's so much stuff out there, uh, that you truly need to ablate out to be able to have a fantastic [00:03:00] pre-trained model.In fact, that's one of the challenges of a lot of the open weight models is they look great on one benchmark or two, but they're not great on practice. So that's why, in fact, even in the RFDEs are, they, they are pretty gone really excited about these MAI models because how the heck can a small five B model hill climb?Uh, and it goes back a little bit to what I think is ultimately the key thing to do, which is try to pursue finding that cognitive core. Uh, so to me, starting with a clean lineage- Then creating that ability for companies to be able to use this, right? Not just as a generalist, but to create their own specialist by building this hill climbing scaffold around it, right?So it's not just the model, but you have a hill climb scaffold around it, then you will start building your RLE. You will start collecting the traces. Most importantly, you'll have private evals because we know all the evals out there are good, interesting, [00:04:00] but they're not really that critical- They're work, yeahSwyx: at this point because they all can be maxed. And so the point is each company will have its own private eval. And so that end-to-end platform story around our models is sort of, uh, what I think is interesting. And then the one other thing, Sarah, since you brought that up, is I do feel there's a new frontier.Satya Nadella: Like people talk about the frontier and are you operating at the frontier. Um, interestingly enough, if you add a little temporality to it, you can use, let's say, in, in, in fact, the, the Lando Lakes demo we showed was pretty cool. We used, whatever, GPT-55, right? Then you collected a bunch of traces, and then you took a 5B reasoning model and achieved higher.Sarah Guo: Uh, so that is another aspect of what it means to appear... uh, you know, operate at the frontier Yeah. I, I think, uh, I first of all have to congratulate you on basically building a frontier neo lab inside of Microsoft in two years. Um, I'm wondering, you know, you have all this AI strategy that you're rolling out.Lessons from Two Years of AI DevelopmentSwyx: I'm wondering, what do you know now that you wish you would tell yourself two years ago where- or two or [00:05:00] three years ago? Three years for the Jensen partnership, two years for, uh, MEI. Yeah, I mean, I think the, the thing when, that I reflect quite a bit, right, which is sort of obviously I got into all this when I got excited by the, the scaling laws paper and, you know, when, you know, even the OpenAI partnership came about when those folks said, “Hey, we're gonna really throw a lot of computer transformers.”Satya Nadella: Uh, and they've helped. I- the thing that I always look back and say, “Wow, these things, uh, do have capability that they're climbing up.” W- I mean, this, you know, this crude way of saying it is intelligence is log of compute kind of works. Now what I think we underestimated perhaps is the real-world complexity of deploying these so that they actually deliver the value in the real world, right?So the outcomes as measured by any benchmark is interestingly important, but the true eval is when people out there are able to do unique things that they only can value, and it's very [00:06:00] measurable, right? That I wish we had sort of even, like, had more in our consciousness, right? Which is as an industry.Sarah Guo: Because right now I think when people say, “Wow, I don't want a token max,” it's an artifact of us not having thought ourselves as an industry that we are using tokens to create value every step of the way. So I think that's kind of what I wish we had gotten there, but I'm glad we are here.Real-World Value & Use CasesSarah Guo: What are some of the use cases that you've seen that have created the most value for your customers?Because I know that people talk a lot about code, and I think it's pretty clear that that's something that's having very large scale impact. Are there other areas that you find in common that your customers are really benefiting from? Yeah. I think, yeah, to your point, obviously coding is now got... But it's interesting, by the way, Elijah, to even talk about the coding, right?Satya Nadella: Which is coding has worked so well that we now have to rebuild the IDE, right? I mean, it's kind of nuts to see what we sh- launched is like, oh my God, I have these hundred agent sessions. I... The cognitive load it transfers back to me as a human is so [00:07:00] excessive that now I need a new UI. Uh, oh, by the way, I, like the, the chat as the only artifact was also impossible, so that's why we need a canvas.So it's kind of interesting for all the things about where is software needed or where is UI needed, uh, you kind of need that even for code, right? In a fully agentic world. But that said, one of the things that we are starting to see, we started seeing with co-work, but even some of the work we, we showed with auto com- uh, um, autopilot Right on what you see with claws is a good one because if you sort of think about a lot of human capital is doing the glue work, right?If you now can augment that with tokens/agents that are long-running, durable, right, then your ability to scale even what is still judgment and glue work gets amplified like coding does. Uh, so you can... Like, I'm positive that six months from now we'll all be saying, “Oh, wow,” like, all through ni- the night there was a bunch of stuff that [00:08:00] all these autopilots that I have working on my behalf with my delegated authority, so to speak, right?I can... Sort of given even my identity, did a bunch of work, then of course I'll need my new ADE to say, “Well, what did you do?” Like, I might... “Did I do this work?” And so on. So I think that that's where compressing of workflows, uh, completing of tasks, uh, that's where I think a lot of the value gets created. I think you raised a really interesting point, which is there's the actual agent that's doing the code, and then there's a harness around it, and that's the environment, that's the context, that's everything you're setting up as a developer around actually a coding agent.The Harness Concept for Enterprise AISarah Guo: What is the harness for the enterprise? Is there an equivalent concept for broader productivity work, or how do you think about that concept sort of generalized? That's right. So, so in some sense you kind of want the harness to define the models, the, the data, uh, and the tools, and so that you have a loop across those three.Satya Nadella: And so what we are trying to, first of all, make sure is each of our products that we build, right, whether it's GitHub Copilot or the security copi- the, the [00:09:00] stuff we showed with MDASH or even the discovery for science, it doesn't matter, all of them are multi-model harnesses, um, with tools access so that you can do this progressive, uh, disclosure of tools even so that they're token efficient.Uh, and then you're feeding it with very rich context because that's sort of the other hard lesson we have learned in the last two years is, oh my God, the amount of work you need to do to prep the context layer, uh, such that your plan can execute in the most efficient way is where the magic is. So we have, in our case, we have the GitHub harness, which essentially we're using across all our products.It's available in Foundry, and we are open, like you can use your Llama harness, whatever. Or you can use the, um, uh, you know, any open harness or any harness of yours and train with your tools and multiple models and your context. And so that's the pitch. Because right now a lot of dialogue is, um, “Hey, if I train the harness plus tools and the model together, you get [00:10:00] evals.”Elad Gil: And what we are proving out is... And the best example of that is what we did with MDASH, right? Because when it launched, uh, it found bugs or vulnerabilities that were not found by Mythos Uh, and so there is existence proof, I would claim, that you can have a multimodal harness, uh, that can in fact be more, uh, performant in the real world So a premise behind the, uh, training at the independent frontier labs is really, you know, we're gonna have these models, and we'll have an API business, and we'll support enterprises and startups.Sarah Guo: ButPlatform Strategy & Developer EcosystemSarah Guo: a first-party product, be it productivity or code or search, drives the majority of revenue. That's a different value equation than you're describing, I think, with the Microsoft ecosystem. Uh, if, if that's the case, tell me if it's the case, uh, ‘cause obviously you have first-party products and you have enablement products.Satya Nadella: Um, what is the role of the develop- Like what is gonna be hard and the set of skills and the value capture the developer has in that world? Yeah. So I think that there's always [00:11:00] gonna be the case that someone who is super successful in- as a platform builder can also have first-party products. It was true with Windows.It is true, uh, with, uh, the, the SaaS side and the cloud side as well with us and others and so on. But the thing that is, is it should not be a limiter to other people achieving that same success, right? That I think is the core difference, which is the, the network effects this time around, around intelligence are such because they learn from data, and not really lots of data.It's just a few samples that you have to see to understand what's novel about something. So that's why the game becomes how to protect. So that's why I would say every company, having private evals may be the biggest IP, right? Think about it, like what's that private eval that you can then use even a frontier model to hill climb on and not leak the traces may be one of the biggest [00:12:00] drivers, uh, of IP.Like, so in other words, another te- acid test is you have an eval that's private. You're using, uh, a g- a Model A. Can you switch it to Model B and e- you know, climb up? If you can, then you're in control. If you can't, you're not in control, and that's where even the harness decision becomes super important, right?swyx So therefore, having an open harness, letting all models come in, having your evals, your context, your tools help you hill climb, I think is the skills that an AI native startup needs, a SaaS company needs, or every enterprise needs. Yeah, I think in, in a very real way you are ... Microsoft historically is an operating systems company and th- then become a cloud company.Maybe like the third act is that you're a harness or evals company. Whatever w- ... whatever the, the sort of conglomerate of concepts that you wanna put together. Um, and, and I think like enabling every company to have like frontier intelligence or what- what- Yeah ... I forget the, the [00:13:00] exact term that you used, um, is the, is the mission, right?Satya Nadella: That's it. Like that is, that is the platform promise, that you build with us, you will get your intelligence, uh, for your data. That's it. That ... To, to me, that is the ... Like if there was one tagline, uh, for this entire developer conference is- Can everybody operate at the frontier with their frontier intelligence, right?To me, that is so important because otherwise it, I, I don't know how you achieve stable equilibrium, right? Which is how do I then go and say, “Well, my company is gonna have a terminal value because I now know how to continuously compound-” Yeah ... on top of what's a platform that gets better,” right? So when, like Windows obviously came out, Adobe built, Autodesk built, uh, or even like take what Jensen said.We built DX and he built, you know, CUDA on top of it. Um, right? I mean, I always say to Jensen, “God, I got the short end of that,” right? “I wish, uh, we had recognized it.” But nevertheless, but that, that idea that you can build a platform layer [00:14:00] that someone else can then extend out, um, and build their own intelligence layer in this case, I think is everything, right?Without it, why have a developer conference? I can just come and have you all sort of just worship at the altar of one model. Yeah. But that's not a developer conference. Uh,IP, Evals & Company Valueswyx: backstage we, we had a discussion about what is IP or what is the, the value in a company. It used to be the length of, uh, human experience at a company, and now it's this other thing which is the evals, the, uh, experience in sort of applying agents to the company. Can you... I just want you to like flesh that out a bit more ‘cause- Yeah ... it was very insightful.Satya Nadella: It's a great way to frame it, right? Because yeah, at the end of the day, every company is gonna have both the human capital that is still gonna be super valuable, uh, because humans, uh, and their ability to find the gaps that exist at all times is going to be the way we all will create value, right?I mean, so I'm definitely in the camp that this is going to be about expressing new forms of human agency and ambition even as token capital goes up, right? So let's say a cor- any corporation [00:15:00] has lots of tokens and lot of human capital. The question is how do you compound the two? So if you have a... Like if you take in Teams I have a bunch of agents doing work and a bunch of humans doing work, and the traces between those, that is really important context of how that enterprise is creating value.Then that goes back to train not a generalist model, but to train the company veteran agent, uh, right? That is super valuable again, right? Which is when a company goes says, “It should in fact go onto the balance sheet,” is how I think about it, right? That's so... In fact, there may be... Like human capital was never possible to go put on a balance sheet, uh, because you didn't know how to capture the tacit knowledge.swyx: Whereas now I think you can with the agents that have learned through the h- through, through time, through all the traces. Uh, so that's what at least we think will happen. I, I think the SEC is gonna have to have accounting standards- ... for token, uh, expertise Uh, y- y- you're talking about the equilibrium [00:16:00] state, um, and a stable equilibrium where companies have this compounding value and can see terminal value for themselves.Future of SaaS & Business ModelsSarah Guo: Another challenge to, you know, the considered equilibrium of, okay, there are applications and workflows that are sort of common to a vertical or a horizontal. Um, and this was, like, the generation of SaaS companies and, you know, Microsoft has lots of SaaS properties as well. And then there are things that are very specific to every enterprise that they're differentiated against.Elad Gil: Um, I'm sure you have heard much and participate in much of the debate about the end of software because all these workflows are, are cheap to generate now. Um, do you think the equilibrium looks different between what agents get built- Yeah ... in enterprises versus in their vendors in the future? Yeah. So I think what's happening there is, see, we, we had a particular way we captured, um, I would say workflow in apps, right?Satya Nadella: Because we built a, a data model, right? We schematized some part of some business process. Mm-hmm. We then built a bunch of business logic. Yep. And then we put a bunch of UI [00:17:00] on top of it, right? So that's kind of what every SaaS company- And a little configuration. For, like, 20, 20 years that was the plan.Right, that- Yeah ... and that was it. So interestingly enough, now you kind of get to re-litigate that vertical stacking, right? So I still think, for example, that data model that you built underneath every SaaS application is super good, right? Like, why reinvent it? Like, I, I, my general ledger better be a general ledger.I don't need new schema creation. No. Uh, in fact, that entity relationship, uh, is actually pretty good, robust thing that I want to feed. And you want it to be stable. That's right. Yeah. Then same thing with business logic, right? If, if you look at, uh... We have this product called Power BI, right? It is like dashboards galore people created.The beauty underneath that dashboard is a very rich semantic model, right? Someone took the pain to create a dashboard and do all the measures, and you want that. That's business logic, right? I want that to be available to me. So I think the [00:18:00] challenge of the SaaS business model is we packaged one way. We now have to learn how to unbundle these things and rebundle in new ways and discover new business models, right?I mean, if you look at it, d- what's happening today with Microsoft 365 is a great example, right? We have this thing called Work IQ. In fact, like, what we are realizing is, oh my God, like, you know, if you look at... In fact, there's a pa- historical parallel too, right? We sold first Exchange and SharePoint and, uh, you know, before Teams, we had a thing called Lync Server and what have you, and we thought, “Oh, that's all gonna move to the cloud.”But little did we realize that, um, the number of people who will use servers in the cloud is 10X, 100X, right? Because people were not buying servers, they were just buying a subscription. Mm-hmm. The same thing is now happening with M365 because with Work IQ, we have exposed what is perhaps the most important database in a company that never got used as a database because it was only captive to our apps.Mm-hmm. Right? It, it was all email operated on it, Teams operated [00:19:00] on it, Word, Excel, PowerPoint, SharePoint. But now, like this is one of the coo- coolest things I get to do with Work IQ. I go to a GitHub repo and I say, “Hey, I attended a bunch of design meetings last week related to this repo. Can you capture all that and tell me what changes I should make?”I mean, think about that, right? It literally can go look at all those transcripts, come back with a plan to change a code base, right? Previously, you could never have thought of using M365 for something like that. So the value creation opportunity now in the agent world is in fact 10X more, but it does require us to have...Sarah Guo: For example, there's going to be usage around M365, right? Which is going to be perhaps more than even the e- end users and we have to even re-architect. Like, in fact, like what I use to serve an inbox or a mailbox cannot be used to serve an agent. Uh, and so that's sort of what we are doing.Pricing Models: Per-User, Consumption & OutcomesSarah Guo: I don't believe in, like, permanent business models for any of these domains, but in the [00:20:00] near term, do you have a prediction between, uh, you know, outcomes-based pricing, token-based pricing?Elad Gil: Enterprise bundles Yeah. The way I- I think about this is always we've had... Like, let's even take the per-user pricing. Mm-hmm. The per-user pricing is really an artifact of someone creating a budget needing certainty, right? Because it's the most important thing. Like, somebody wants a budget- Mm-hmm ... they need a per user.Satya Nadella: And, and per user is just a set of entitlements to usage, right? That's kind of what it is. And so the way is, if the first bundling will be take some usage, bundle it into per user stacks and, you know, then sell subscriptions. So subscriptions I think are gonna be there, per user is gonna be there. Then the next big thing will be consumption.So people will say, “I want consumption.” And it's also possible that people will say, “I don't even want to pay for any of the subscriptions or the consumption's outcome.” Mm. But remember, most people love outcomes until they have an outcome, because once you have an outcome, it's like giving away royalty, [00:21:00] right?Mm. I mean, like I, I've talked to customers who love, you know, outcome-based pricing, and I say, “I'm all in,” until they, “Oh my God,” like, “what are you talking about? You're sharing in my outcome? No, no, no. I want you to go back to per-user pricing, and I want you to consumption price,” right? So I think that debate will go on.Uh, but and all, all, all of these business models have a particular time and a place versus one to rule them all. And if anything, if you're a SaaS vendor or you're a platform vendor, having that flexibility... And quite frankly, we face this with GitHub, right? We just recently announced a per-user pricing on GitHub because little, you know, we- GitHub Copilot was constructed at a per-user level before we understood even, uh, the intensity of usage of agents, right?It was an interactive way for a developer to use code complete, maybe tasks. It was not like, oh, I launched 10,000, you know, agents that are going on all day, right? So that is what the adjustment is about. So now that we really want, there will [00:22:00] always be a per user, but there will have to be a consumption meter.Durability of SaaS & Build vs BuySarah Guo: How do you think about the durability of SaaS more generally? One thing I've observed is in a lot of enterprises internally, there will be teams that almost have agent euphoria. They're so excited about the explosion of things they can build that they're trying to rebuild a lot of applications or going to their SaaS vendors and saying, “We're not gonna work with you anymore,” or, “We're considering an internal project.”And it seems like in six to nine months, maybe some of those people will come back and say, “Actually, we, we can't rebuild everything.” How do you think about what's durable in this world and what isn't? Yeah, it's a... It... I think we have to go through one full budget cycle on this to really see the, um- Uh, the sort of the emergence of the equilibrium, because at the end of the day, there's marginal cost to even generating the app, right?Elad Gil: In, in fact, there can be even a, a simple way to say it, like if you should always acquire something if the marginal cost of building and maintaining, uh, something on your own is higher. Uh, right? That should be like it's a quantifiable- Yeah. Right? A quantifiable thing. And [00:23:00] the maintenance part is important, right?Even, like you got to remember like, hey, you know, all the security stuff that now AI will find, you better fix them too fast. Uh, of course, there's a coding agent to help you with, but then that burns tokens, right? So whose responsibility is it? It's kind of like a, a cycle that you've got to think through.And I think we have gone through the excitement that I can generate a lot of software. I think the next thing would be what software do I really want to generate? Mm-hmm. What software do I want to use from others? How do I compose these two into some agentic workflow that I have agency over, right?Sarah Guo: Because I think there'll be very little tolerance for anybody who's inflexible, uh, at the vendor level. Uh, but at the same time, I think that anyone who has got that flexibility shows up, delivers the value, will be back at again, right? We're selling software, uh, but with just different business models, in fact Uh, speaking about building software, um, one of my favorite moments from, I think, a previous build maybe one or two years ago was they had a b- they, they...Swyx: There was a section of you building your [00:24:00] own software. I'm curious if you're building anything now. Yeah. So I, I think the... You know, first of all, let's face it, right? Building software has made it possible for even the incompetence of a CEO of a company- ... like ours, uh, you can build, so thank God. But that said, I, I, I, I do feel that, you know, something like, um, GitHub Copilot to me, and especially the new Sessions app or the new app, has just made it so much more possible for you to have agency over artifacts that you felt you couldn't touch before, right?Satya Nadella: So to, for me as a CEO, even to go to a code base, uh, to be able to learn about it, like I remember joining Microsoft long back, you know, first and then you say, man, everybody had to go in and look at, you know, whatever, Cutler's, Malik, or what have you to learn how to do good C, uh, C++ code. Um, so now that ability to be more full stack up and down is so good, but that doesn't mean every one of us should be doing the same thing.The question is: [00:25:00] how do you then have the ability to inspect things, learn things, see things, um, I think is just so much more. And so to me, what I'm building a lot of is these long-running Foundry agents. Uh, right? So there's autopilots. So the easiest thing is, to me, I think I just built one, uh, even last week, where the idea was, hey, can I have an agent that is continuously monitoring essentially my own chief of staff autopilot, right?We're gonna have that obviously in, uh, Scout. That's what, uh, uh, we showed. But it is so easy and trivial to build. I took Work IQ. I said, “Take Work IQ, go, uh, and build a Foundry long-running agent.” Uh, store all the memory in, um, uh, using Ray Fin, right? Basically at my backend as a service. And lo and behold, it built it, and not only built it, I could say publish to Teams, and it published the damn thing to Teams.Sarah Guo: So the ability, uh, to have a, you know, some end-to-end project like this complete is just pretty [00:26:00] miraculous. How do you think, uh,Future Engineering RolesSarah Guo: that impacts the different types of engineering roles that exist in the future? Because right now I think there's, you know, a dozen different types of engineers that you can be, from QA, front end, et cetera.You know, there's a big swath. I've heard some people argue that in four or five years we'll basically end up with four engineering roles. It'll be people who are managing agents, it'll be four deployed engineers or FDEs, it'll be security engineers, and then people working on large scale infrastructure for a small number of services, and then everything else just collapses into the agentic world.Satya Nadella: Yeah, I- Do you think that's a correct view of the world? Yeah, I mean, I think, I think we'll have to experiment our way through it. But what you said is what... There are some very at scale things. At LinkedIn, they did structurally change- Mm-hmm ... uh, and it, you know, basically built up a new discipline called full stack builder, right?So they went and said, “Hey, let's bring, uh, people from design and product management, front end engineering, all put them together.” Uh, but also have an edge, right? It's not like the design person still doesn't have the design edge, or the front end [00:27:00] person doesn't have the front end edge, but you can give yourself bigger scope in roles so that you're not confined to one role.Um, and then r- equally, infrastructure has become very critical, right? So in other words, like, I mean, RLEs, I mean, one thing we've realized is even for the Excel team, for example. Mm-hmm. Building the RLE in which a reward can be learned is actually one of the hardest sort of infrastructure problems.Mm-hmm. Uh, and so you kind of need even new talent, right? Distributed systems people even in what was considered an end user app team, uh, because it's a different skill set. So yes, infrastructure, science is the other one, obviously. Um, so I think we'll see how these evolve, right? Where's the s- real... I mean, always the world will have a bunch of specialists.Okay. Um, you know, I think the generalist role is going to be the most exciting, right? Because the leverage of a generalist- Mm-hmm ... um, is where we are going to see the maximum returns, right? When, when you said, “Hey, are you coding?” I'm now a gen- Like, what... I've basically translated [00:28:00] knowledge work Right?Which I did, where I created a Word document or a spreadsheet, or even, uh... And now I can build an app, right? It's in the same sentence. Uh, right? That idea that, “Oh, wow, my generalist skills have gotten higher leverage,” I think is what we're gonna see across the board. Music to the ears of CEOs and VCs that are, like, a little dangerous and a lot of- Golden age for idea peopleSarah Guo: idea people. Yeah. Uh- With a lot of agency. I- if you take that idea of personal agency and you just zoom it out to the organizational context, um, uh, my partner Mike Renall, who, uh, actually started his career at Microsoft, just wrote an essay where one of the big takeaways is i- it's an age where you can be much more ambitious, and you need to be, given the pace of the environment and how quickly, actually, users and companies are open to adopting new technologies.Satya Nadella: Um, how do you think about... I, I feel silly asking this of somebody running a, you know, trillion-dollar-plus company already, butAmbition & Making the Impossible PossibleSatya Nadella: how do you think about how Microsoft can be more ambitious now? It's a great question. Um, I [00:29:00] think, um- I think the, the thing in these type of transitions is to have a conceptual model of how work can change to go after outcomes that you could hardly imagine previously, right?In fact, Kevin Scott has this nice line, right, which is, um, when you can make the impossible... Like, when you're making hard things easier, that's sort of one point of leverage. But true ambition is about making the impossible possible. So now the thing that is missing a little bit in all of our organizations is what is that new conceptual model of what can we build?What was impossible and what can we build? And I'll give you one example of this, right, which is I take great inspiration from sort of the people who were managing the Azure net- network. And they came to the... This was from even last year. You know, we were scaling. You saw that I, I [00:30:00] talked about sort of how we built in the last 15 months more Azure capacity than we built in the first 15 years.I mean, it's crazy. Wild. Yeah. Right? It's pretty wild. And it's the same team. So they saw that and they said, “Bob, this just ain't gonna work if we don't reconceptualize our work.” So they built... Essentially they said, “Our job is not to do Azure networking. Our job is to build the agentic system does, that, that does Azure networking,” right?These are the folks managing the 500-plus fiber operators managing the VAN, right, all over. And fiber operations ultimately is a physical operation. Things get cut, things get, uh, you know, have to be repaired. You know, we have fancy words called DevOps and so on. Basically, emails are coming in and you gotta go respond to them, take care of it.So they built this agentic system. They even have a character for it. It's called Miles, and it sort of does all this stuff, right? They started sort of screaming for more tokens and so on. And so they were saying, “Look, uh, we don't need a headcount. We need tokens in order to be able to [00:31:00] manage, uh, our operation.”That reconceptualization- Mm-hmm ... of what their work is, right? They, they basically took their work and made it meta, right? That meta work is now their new work. Mm-hmm. Right? In the ‘80s, if somebody had come to us and said, “4 billion people are gonna get up in the morning and start typing,” my model would've been, we need 4 billion typists?But we're not doing typing, we're doing knowledge work. So that, to me, I think is it, right, which is whether it's Microsoft or whether it's any organization, is to give ourselves permission to do new types of metacognition, meta work, using these new tools to change the outputs that matter, uh, and then really make the impossible possible.Sarah Guo: So completing that dot or the, the connective tissue across those, I think, is where a lot of the enterprise value will get created.Data Center Build-Out & Community ImpactSarah Guo: Should we talk about data centers? Yeah, please ask. Oh, okay. Well, uh, uh, w- we-- this leads nicely into the data center build-up. I always think, I- I just-- I'm just impressed at the sheer scale of the [00:32:00] build-out from Microsoft, but also everyone else, that this is redefining what it means to be a hyperscaler.And I just feel like that, that, that is at unprecedented scale on finances, uh, on the way you run the company, but also the communities that are, that are impacted. Um, yeah, just talk a bit more about what you're seeing on the ground, like when you visit your- Yeah, I think there are two aspects of it.Satya Nadella: Obviously, the, the build-out is, uh, extraordinary. Um, you know, nothing like this has happened, and it's great to be, uh, one of the participants in it. Uh, but you brought up the other part, right? I think at this point it's clear that unless we as an industry, uh, are very principled about ensuring that the benefits of all the stuff we're talking about are felt in real ways, uh, at the community level, right?Because this is not just a, a campaign, um, right? It has to be real, where people are saying, “Look, this is not ch- changing the prices on energy for me.” In fact, if anything, it's bringing down prices because long term there's going to be a better [00:33:00] grid, there is going to be more energy. Water consumption is, in fact, not sort of, uh...In fact, water is being replenished, right? You gotta really, you know, educate folks on truly what's happening, the cl- uh, the closed loop systems we are building. We have to invest in the training, the jobs, the tax base. In fact, the least talked about stuff is the amount of jobs that get created during construction, after construction.What's the tax base that's there in the community? And, and all this has to be real. Um, and, and if that is the case, then we will have permission. If it is not, we won't have permission. It's as simple as that, right? Which is, uh, we, we... I think we have to take it as an industry pretty seriously. Uh, I think it's good for communities to be skeptical, ask the hard questions, for us to do the hard work, earn that.Um, but at the end of the day, if there's-- if we can really be the produ-- Wait. I've always felt like in human history, if you use a lot of energy but also create a lot of value for society- The story has been fantastic. If you don't [00:34:00] do that, it's not been that great. And this time around, I'm a firm believer that ultimately if you do have a token economy that drives productivity, that drives economic growth, that drives broad spread, um, you know, participation, better health outcomes, um, then I think we'll be in a great place.Sarah Guo: Uh, and that's at least what we all have to be focused on. Yeah. It, it makes me think actually that with all these initiatives that you're doing, might be e- easier to see ROI in the communities first before in enterprise. Yeah. I, I mean, I think both sides. Yeah. In fact, it comes back together. It has to be the people in the communities are going to be employed, are going to be participants, uh, in the real economy, right?Satya Nadella: That's I think the question is. Like, if we- if the broad economy is doing well and the communities are doing well, the dots get connected. It's sort of the market forces are such that we will connect the dots. And that I think is it. Like, you ought to be able to see the evidence. You can't be about o- any one company, uh, but it has to be broad economic growth and broad [00:35:00] ec- you know, community permission.Elad Gil: Yeah. I guess I wanna talk aboutSocietal Impact & Optimism About AIElad Gil: what you're most optimistic about currently or what have you most updated your personal models on regarding societal impact of AI? So you're saying what's the, the, the- What have you updated most on in terms of societal impact of AI? Yeah. I think the, um, the p- the most, um- Critical thing is the first question we even started with, which is we need to tell the story and make it real that everybody has a real shot to participate as a first-class participant in this new economy.Satya Nadella: Right? That's kind of, I think we- in the next 12 months, 18 months, we need a way for people to say, “Oh, wow, I get it.” Right? There's going to be tremendous capability, tremendous amount of infrastructure, but I can see what is going to happen, whether it's the benefits like health outcomes or my ability to create a startup or my ability to run my [00:36:00] local sort of, uh, store more efficiently.It's just happening, and I see that, uh, benefit myself, right? That to me, you know, earning that permission in a path-dependent way, we can't wait. See, the one thing, Eli, that I've now learned is I think the world is gonna be very skeptical of tech and tech companies that say, “Trust us, we've got it. The g- future is gonna be glorious.”Sarah Guo: Uh, you kind of have to deliver tangible benefits. Um, and quite frankly, politicians winning elections, uh, because they have advocated for that. That will be at least my adjustment because without it, um, thinking that somehow... Because it's too important this time around. It's too much of the economy for it not to be the case So one very simple framework I have for, you know, what are, what is gonna be the broad benefit of AI, um, beyond the communities just working in technology, are, are sort of wealth creation- Yepit's [00:37:00] gonna happen in a ton of different companies, startups and large companies. Then you have healthcare. Uh, you, you had amazing demos today. There are companies like Open Evidence. I think that is happening. Um,Education & Future of LearningSarah Guo: education seems like another one that's an- Yep ... obvious good where we haven't seen as much impact as I'd expect.Swyx: Do you have a hypothesis on why that might be, or if it'll come? Yeah, I mean, I think this is where, again, how we think about education, how... You know, recently I met with, uh, the founders of Alpha School and learnt a lot about what they were going and going about, and it's fascinating to listen, uh, to how to even rethink- MmSatya Nadella: uh, what does education really look like. Because I think it's actually very important. Mm. Uh, and I'm not saying anything traditionally being done is less important, right? I was even looking at the, uh... It's fascinating to see. I, I, I forget the which Stanford class it was, uh, the, the Asian guidelines for CS something.Mm. Uh, because you still need people to learn. Uh, like it was an interesting AI class that they were making sure people were learning how to apply softmax appropriately versus saying, “Hey, fix my training run.” Mm-hmm. Uh, so I think learning concepts is important. It's going to [00:38:00] be, uh, critical. But the way we create the incentives, what are the credentials, how we value those credentials, what is the employment opportunity for those credentials?So I think that there's a complete change that has to happen, uh, given the way to get to information, way to educate yourself, way to continuously keep yourself updated has changed so much. So I think interestingly enough, maybe the next big startup and success story could be someone who builds a new university, um, or a new, um, pedagogy even of how to get someone to go through a curriculum and find economic opportunity, uh, that's highly valuable.Well, that has felt, uh, perhaps impossible for a long time, but it's a great note to end on and something that might be possible. It's still possible. Yeah. Thank you, Satya. Thank you so much. Thank you. Yeah. I appreciate it. Thank you all. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.latent.space/subscribe

Sherwood Callaway is the founder of Sazabi (YC P26), the AI-native observability platform built for engineering teams who ship fast. He previously founded and exited a YC company — now he's back, betting that logs are all you need to replace Datadog.Logs Are All You Need: Rethinking Observability with AI Agents // MLOps Podcast #381 with Sherwood Callaway, the Founder of Sazabi

AWS Morning Brief for the week of June 1st, with Corey Quinn. Links:Monitor AWS Budgets directly in Billing and Cost Management Dashboards with new Budgets widgetIntroducing the next generation of Amazon OpenSearch Serverless for building your agentic AI applicationsOptimize costs in Amazon AuroraHow AWS DevOps Agent uses multi-agent reasoning to find root causesClaude Opus 4.8 is now available on AWSBest Practices for TCP Connection Management on EC2Introducing US-based, US citizen, 24/7 technical support for AWS GovCloud (US) customers: Your mission never sleeps, neither do weWell-architected best practices for software supply chain securityAutomate Amazon EBS gp2 to gp3 migration at scale with AWS Step Functions and AWS LambdaAWS Organizations emits CloudTrail events for account membership changesCVE-2026-9255 - Tool Execution Without Authorization via Piped Stdin in Kiro CLICVE-2026-9291 - Insecure Deserialization in Amazon Braket SDK Job Results Processing

Состояние DevOps в 2026: Platform Engineering, AI-агенты и что стало с junior-инженерами. Собрались на кухне с тимлидом системного юнита из большой компании - поговорить что и как сейча. О ЧЁМ ВЫПУСК • DevOps vs SRE в 2026: где проходит граница и почему «you build it, you run it» иногда создаёт больше проблем, чем решает. • War story: упавший Kubernetes во время корпоратива с пивом - классика первых K8s-внедрений. • Момент, когда DevOps ломается: 600 сервисов, 3600 пайплайнов и почему каждый новый инженер пишет 3601-й. • Platform Engineering: зачем нужна платформа, что такое метаплатформы и как устроены слои внутри крупной компании. • Junior + AI = middle: что изменилось с приходом AI-ассистентов и сколько теперь занимает обучение DevOps. • AI в работе DevOps прямо сейчас: мультиагентные помощники для расследования инцидентов, внутренние vs внешние модели. • Реальные AI-катастрофы 2025-2026: Replit дропнул базу и бэкапы, сервис аренды машин ушатал прод. • Multi-agent flow: refiner + архитектор + автономный бот, PR за час вместо недели. • Тимлидам: не носи инженерам PR, которые ты навайпкодил за вечер. • Что реально учить в 2026: Linux, сеть, Kubernetes, один язык программирования и AI-грамотность. • Знать базу vs спрашивать AI: почему без фундамента ты не поймёшь, куда тебя модель направляет. ГОСТЬ В гостях - Андрей Волхонский, руководитель юнита System в Центре разработки инфраструктуры Авито. 13+ лет опыта: от Windows-DevOps в TravelLine и Kaspersky до платформенной инженерии в большой продуктовой компании. ССЫЛКИ

The power of choice is in full effect! How you can leverage GitLab to publish your next Quarto document online, how to bring key R functional paradigms to a Python session, and adding a larger safety net with your unit tests with {mutagen} 0.2.0. Episode Links This week's curator: Jon Carroll - @jonocarroll@fosstodon.org (Mastodon) & @jonocarroll.fosstodon.org.ap.brid.gy (Bluesky) & @carroll_jono (X/Twitter)Deploying Quarto documents with GitLabFunctions over Idioms - Writing R in Python with rfunsmuttest 0.2.0: More Mutators, Better Reporting, and Parallel ExecutionEntire issue available at rweekly.org/2026-W22Supplement ResourcesData Science at the Command Line https://datascienceatthecommandline.com/DevOps for Data Science https://do4ds.com/{pak} System Requirements https://pak.r-lib.org/reference/sysreqs.htmlSupporting the showUse the contact page at https://serve.podhome.fm/custompage/r-weekly-highlights/contact to send us your feedbackR-Weekly Highlights on the Podcastindex.org - You can send a boost into the show directly in the Podcast Index. First, top-up with Alby, and then head over to the R-Weekly Highlights podcast entry on the index.A new way to think about value: https://value4value.infoGet in touch with us on social mediaEric Nantz: @rpodcast@podcastindex.social (Mastodon), @rpodcast.bsky.social (BlueSky) and @theRcast (X/Twitter)Mike Thomas: @mike_thomas@fosstodon.org (Mastodon), @mike-thomas.bsky.social (BlueSky), and @mike_ketchbrook (X/Twitter) Music credits powered by OCRemix Wrestling with Double Bass - Street Fighter II - Malcos - https://ocremix.org/remix/OCR01270A Simple Flip can Change Fate - Final Fantasy VI - Level 99 - https://ocremix.org/remix/OCR02692

In the previous episode of N is for Networking, Jennifer “JJ” Jabbusch gave us a thorough overview of Network Access Control (NAC) for wired networks. This week we’re going wireless! JJ walks us through the major differences between wired and wireless NAC, how 802.1X is more seamless in Wi-Fi deployments, the unpredictability of web portals,... Read more »

In this episode, Corey Quinn sits down with Dexter Horthy, CEO and Co-founder of Human Layer, to unpack what engineers are getting wrong about AI, especially when it comes to coding agents.From the obsession with “just throwing more tokens at the problem” to the reality of building scalable AI workflows, Dexter shares hard-earned insights on how to actually push models to their limits. They dive into the evolution of developer workflows, the rise of AI-powered software factories, and why understanding context and verification matters more than raw model power.If you're building with AI or trying to, this episode will challenge how you think about what these systems can (and can't) do.Show highlights: (00:00)Throwing Tokens Too Far(01:04) Meet Dexter Horthy(01:52) Personal AI Benchmarks(04:12) Human Layer Race Condition(05:59) Rewrites and Tech Debt(07:19) Software Factories Mindset(10:20) Verifiable Problems and Token Limits(13:45) Agents in the Trenches(18:05) GitHub at Agent Scale(26:23) Safety Ethics and Closing ThoughtsAbout Dexter: Dexter Horthy is the CEO and Co-Founder of HumanLayer, where he helps engineering teams tackle complex problems in large codebases using coding agents. Previously, he worked in DevOps, SRE, and Solutions Engineering at Replicated, and contributed to lunar navigation software at NASA JPL. Outside of work, he's a fan of tacos and burpees, though not necessarily in that order.Links: LinkedIn: https://www.linkedin.com/in/dexterihorthy/Website: https://humanlayer.devSponsored by: duckbillhq.com

In this episode of Elixir Wizards, hosts Charles Suggs and Emma Whamond sit down with Saša Jurić, Elixir mentor and author of Elixir in Action, to discuss software craftsmanship in the age of AI. As AI coding tools become increasingly capable, Saša argues that the real challenge isn't generating code, it's maintaining quality, clarity, and shared understanding within a codebase. We explore the difference between correct code and good code, and why code is more than a set of instructions for a machine to execute. Code is also documentation, communication, and a long-term investment that future developers must be able to understand and maintain. Saša shares his concerns about the growing "theater of pull requests," where teams go through the motions of code review without creating meaningful opportunities for learning, feedback, or knowledge sharing. The hosts and Saša talk about practical ways to work effectively with AI, including taking smaller steps, carefully reviewing AI-generated code, and using AI as a collaborative tool rather than an autonomous developer. Throughout the discussion, Saša challenges the industry's obsession with speed and makes the case that the principles of good software development (incremental progress, clear communication, and human judgment) remain important in the age of AI. Key Topics Discussed The difference between correct code and good code Code as communication, documentation, and shared understanding The "theater of pull requests" and ineffective review practices How AI is changing software development workflows Using AI as a collaborator rather than a replacement Why smaller, incremental changes lead to better outcomes Human oversight in AI-assisted development Balancing development speed with maintainability Pull request size and review effectiveness Commit history as a tool for storytelling and context The risks of accumulating technical debt faster with AI Testing and validating AI-generated code Refactoring AI-generated solutions for clarity Applying agile principles to AI-assisted workflows The role of experience and judgment in software design Why software craftsmanship still matters in the age of AI Links mentioned Code Complete by Steve McConnell https://khmerbamboo.wordpress.com/wp-content/uploads/2014/09/code-complete-2nd-edition-v413hav.pdf Harness AI for DevOps, Testing, and AppSec https://www.harness.io/ Claude Code https://claude.com/product/claude-code Claude Code GitHub https://github.com/anthropics/claude-code Pull Request for Oban https://github.com/oban-bg/oban/pull/331 SMPP https://en.wikipedia.org/wiki/Short_Message_Peer-to-Peer OpenAI Codex https://chatgpt.com/codex/ Opus AI https://opus.ai/ Tidewave https://tidewave.ai/ Credo Static Code Analysis https://github.com/rrrene/credo https://smartlogic.io/podcast/elixir-wizards/s11-e09-static-code-analyzer-elixir-credo-ruby-rubocop/ Link to Sasa's X post https://x.com/sasajuric/status/2029522378196238503 Saša Jurić “Tell Me A Story” at Goatmire https://www.youtube.com/watch?v=GOrKfCs-mr0 https://meks.quest/blogs/the-theatre-of-pull-requests-and-code-review Looks Good to Me: Constructive Code Reviews by Adrienne Braganza https://www.manning.com/books/looks-good-to-me Towards Maintainable Elixir: Testing https://medium.com/very-big-things/towards-maintainable-elixir-testing-b32ac0604b99 TDD, Where Did It All Go Wrong (Ian Cooper) https://youtu.be/EZ05e7EMOLMSpecial Guest: Saša Jurić.

Realities Remixed, formerly known as Cloud Realities, launches a new season exploring the intersection of people, culture, industry and tech.Today's most pressing challenges arise from the collision of rapid technological change with deepening economic inequality, weakening democratic systems, geopolitical instability and accelerating climate pressure, leaving world leaders wrestling with how to govern and solve these deeply interconnected crises.This week, Dave, Esmee and Rob are joined by Dex Hunter-Torricke, Founder & President The Center for Tomorrow to explore how tech can solve world macro issues. TLDR00:33 – Introduction00:40 – Hang out: The Boys on Amazon Prime final episode (spoilers) 06:02 – Dig in: How to solve world macro issues? 07:45 – Conversation with Dex Hunter-Torricke 44:52 – Writing a book and meeting world leaders GuestDex Hunter-Torricke: https://www.linkedin.com/in/dextb/https://www.centerfortomorrow.com/ HostsDave Chapman:  https://www.linkedin.com/in/chapmandr/Esmee van de Giessen:  https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan:  https://www.linkedin.com/in/rob-kernahan/ ProductionMarcel van der Burg:  https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman:  https://www.linkedin.com/in/chapmandr/ SoundBen Corbett:  https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:   https://www.linkedin.com/in/louis-corbett-087250264/ 'Realities Remixed' is an original podcast from Capgemini

Cybersecurity is Bigger Than Hacking | Nate Butler on Career Pathways, Mentorship & GRC Chapters0:00 Welcome to Cyber Crime Junkies0:31 From IT to Cybersecurity | Nate's Career Shift3:34 The Mentor Moment That Changed Everything5:33 Meet The Power of Mentorship8:13 CISM Certification | A Level Up from Security+10:43 Cybersecurity is Bigger Than Hacking12:00 GRC Explained | The Glue That Holds It Together15:40 Governance Risk Compliance for SMBs16:29 Speaking at High School | Youth Outreach17:41 Teaching Kids Cybersecurity Without Fear21:28 Parental Conversation | Gaming Safety & Sextortion Prevention23:42 Communication Across Generations25:37 Explaining Tech Simply to Business Leaders26:47 LinkedIn vs TikTok Strategy27:00 Two Platforms, Two Different Animals28:28 Live TikTok | Building Community Around Real Conversation31:26 Authenticity Over Polish | What Drives Engagement34:02 AI, Claude Code & Building Apps36:39 From Paying for Services to Building Your Own39:44 DevOps, Platform Engineering & Infrastructure Roles41:20 Using AI to Automate Your Own Workflow45:36 Book Trilogy | Breaking Into Cybersecurity48:05 The Second Book | Navigating the Space with Keith51:30 More Content Coming | Guests, Live Streams & Growth54:00 Anyone Can Do This Work56:00 Final Thoughts on Mentorship & OpportunityQuestions? Text our Studio direct. We read these and when helpful we give a special shout out for those to contact us.I wrote Moving Target because overconfidence is the enemy. Hardcover, paperback, Kindle, and audiobook. Amazon, Barnes and Noble, and more. I wrote the Moving Target Trilogy because overconfidence is the enemy. Hardcover, paperback, Kindle, and audiobook. Amazon, Barnes and Noble, and more. Growth without Interruption. Get peace of mind. Stay Competitive-Get NetGain. Contact NetGain today at 844-777-6278 or reach out at DMauro@NetGainIT.com or find more at www.NETGAINIT.com   Support the showNew Exclusive Offers for our Listeners! New non-fiction Book Series is out! Moving Target: The Art of Online Camouflage drops April 14.Moving Target: The Obedient Machine drops April 21.Book 3 -- Ghost and the Machine -- out soon!

Hosts Ned and Kyler compare notes on everything they've been doing with AI, including the successes they’ve enjoyed and headaches they've suffered building and implementing AI agents. They talk about how AI has sped up their workflows, how managing multiple AI agents is akin to raising toddlers, the necessity of using deterministic scripts for increased... Read more »

Dwayne McDaniel, developer advocate at GitGuardian.com, joins host Priyanka Raghavan to talk about the engineering challenges of secrets management. They explore what "secrets" really are in modern systems—far beyond passwords—including API keys, tokens, certificates, and machine identities, and how "secret sprawl" emerges across the SDLC. Drawing on reports from GitGuardian and Verizon, they discuss the growing scale of secret leaks and why credential abuse and phishing remain dominant attack vectors. They examine common leak points—from code repos and logs to CI/CD pipelines, containers, and SaaS integrations—and how cloud, DevOps, and AI tooling are amplifying risks. Priyanka quizzes Dwayne about recent supply chain attacks from pyPi and trivy ecosystems, highlighting recurring root causes like poor access control, long-lived credentials, and weak security hygiene. Finally, they consider detection, response, and modern solutions—short-lived credentials, secret scanning, and identity-based approaches like OWASP NHIR and SPIFFE/SPIRE—ending with practical advice for engineers to reduce blast radius and design for secure secret lifecycle management.

Hosts Ned and Kyler compare notes on everything they've been doing with AI, including the successes they’ve enjoyed and headaches they've suffered building and implementing AI agents. They talk about how AI has sped up their workflows, how managing multiple AI agents is akin to raising toddlers, the necessity of using deterministic scripts for increased... Read more »

Hosts Ned and Kyler compare notes on everything they've been doing with AI, including the successes they’ve enjoyed and headaches they've suffered building and implementing AI agents. They talk about how AI has sped up their workflows, how managing multiple AI agents is akin to raising toddlers, the necessity of using deterministic scripts for increased... Read more »

AWS Morning Brief for the week of May 25th, with Corey Quinn. Links:Amazon Bedrock expands support for request-level usage attributionAmazon ECS introduces pause and continue controls for service deploymentsAWS announces AWS Interconnect - multicloud connectivity with Oracle Cloud Infrastructure in previewAWS Organizations now supports higher quotas for service control policies (SCPs)Amazon Aurora MySQL 8.4 is now generally availableIntroducing ExtendDB: An open source DynamoDB-compatible adapter with pluggable storage backendsNine Entertainment's journey: Achieving 98% cost savings with Amazon ElastiCache Serverless for ValkeyAnnouncing updated retry behavior for AWS SDKs and ToolsAnnouncing AWS CDK Mixins: Composable Abstractions for AWS ResourcesCVE-2026-8838 - Remote Code Execution in amazon-redshift-python-driverCVE-2026-9133 - Arbitrary file read in rabbitmq-aws plugin

Welcome to this week's episode of the PEBCAK Podcast!  We've got four amazing stories this week so sit back, relax, and keep being awesome!  Be sure to stick around for our Dad Joke of the Week. (DJOW) Follow us on Instagram @pebcakpodcast   Please share this podcast with someone you know!  It helps us grow the podcast and we really appreciate it!   Simple 6 signup link https://simple6.co/r/CFUR98   Apple data and car Bluetooth signals help police identify suspect in crypto robbery https://www.forbes.com/sites/the-wiretap/2026/05/05/apple-subpoena-and-car-bluetooth-help-cops-unmask-crypto-robber-suspect/ Your phone and your car are witnesses — law enforcement used an Apple subpoena and Bluetooth signals from a connected vehicle to unmask a suspect in a physical cryptocurrency robbery, showing how everyday device data is increasingly being used to solve crimes.   FBI reports crypto ATM fraud complaints surged 23% in 2025, topping $388 million in losses https://www.ic3.gov/PSA/2026/PSA260515-2 Canada proposes a nationwide ban on crypto ATMs, calling them a primary tool for scammers https://www.cbc.ca/news/canada/toronto/canada-crypto-atm-ban-scammers-9.7180642 Bitcoin Depot, North America's largest crypto ATM operator, files for Chapter 11 bankruptcy https://www.bankingdive.com/news/bitcoin-depot-bankruptcy-chapter-11-atm-wind-down/820755 Crypto ATMs are effectively becoming extinct — the FBI documented nearly $389 million in losses through kiosks in 2025, Canada is moving to ban them outright as a fraud-enabling infrastructure, and Bitcoin Depot (the largest operator in North America with 9,000+ machines) just filed for Chapter 11 bankruptcy, blaming mounting state regulations, litigation, and an unsustainable business model.   DataCamp breaks down Claude Opus 4.7 vs. GPT-5.5 across coding, reasoning, vision, and pricing https://www.datacamp.com/blog/gpt-5-5-vs-claude-opus-4-7 The AI model race between Anthropic and OpenAI is too close to call — Claude Opus 4.7 leads on software engineering benchmarks and visual reasoning while GPT-5.5 dominates terminal/DevOps workflows and advanced math, with output token pricing favoring Claude at $25 vs. $30 per million tokens.   Dad Joke of the Week (DJOW)   Find the hosts on LinkedIn: Chris - https://www.linkedin.com/in/chlouie/ Brian - https://www.linkedin.com/in/briandeitch-sase/ Cody - https://www.linkedin.com/in/cody123anderson/

Today our Packet Pushers team assembles to discuss whether the grass is greener on the NetOps or DevOps side of the telemetry fence. William of The Cloud Gambit, Scott of Total Network Operations, and Ned and Kyler of Day Two DevOps discuss the difficulties and differences of getting telemetry and state from devices across different... Read more »