Podcasts about API

David Burkett, Cloud Security Researcher at Corelight, is back on Defender Fridays this week to discuss thinking in pipelines for AI agents.As a dedicated and highly experienced Cloud Detection Engineer and Security Architect, David has the privilege of working at a Fortune 50 Company where he leverages his extensive background in cybersecurity to protect digital assets. With a proven track record of building three different Cyber Security Operations Centers for multiple MSSP/MDR providers.David's expertise is backed by a strong set of GIAC certifications, including GCTI, GCIA, GPYC, and GCED... among others. He's proud to have been part of a large overall security team that won the prestigious James S. Cogswell Outstanding Industrial Security Achievement Award from the Defense Counterintelligence and Security Agency. Our security operations center was recognized as being among the top 1% of cybersecurity programs for all cleared facilities.In addition to his hands-on experience, David has consulted for over 40 Fortune 500 Companies and Large Federal Organizations, helping them manage their SOAR platforms and playbooks. As a strong believer in knowledge sharing and collaboration, he's also an active contributor to the open-source detection security project known as Sigma. Learn more at https://corelight.com/Register for Live SessionsJoin us every Friday at 10:30am PT for live, interactive discussions with industry experts. Whether you're a seasoned professional or just curious about the field, these sessions offer an engaging dialogue between our guests, hosts, and you – our audience.Register here: https://limacharlie.io/defender-fridaysSubscribe to our YouTube channel and hit the notification bell to never miss a live session or catch up on past episodes!Sponsored by LimaCharlieThis episode is brought to you by LimaCharlie, a cloud-native SecOps platform where AI agents operate security infrastructure directly. Founded in 2018, LimaCharlie provides complete API coverage across detection, response, automation, and telemetry, with multi-tenant architecture designed for MSSPs and MDR providers managing thousands of unique client environments.Why LimaCharlie?Transparency: Complete visibility into every action and decision. No black boxes, no vendor lock-in.Scalability: Security operations that scale like infrastructure, not like procurement cycles. Move at cloud speed.Unopinionated Design: Integrate the tools you need, not just those contracts allow. Build security on your terms.Agentic SecOps Workspace (ASW): AI agents that operate alongside your team with observable, auditable actions through the same APIs human analysts use.Security Primitives: Composable building blocks that endure as tools come and go. Build once, evolve continuously.Try the Agentic SecOps Workspace free: https://limacharlie.ioLearn more: https://docs.limacharlie.io/Follow LimaCharlieSign up for free: https://limacharlie.io/LinkedIn: / limacharlieio X: https://x.com/limacharlieioCommunity Discourse: https://community.limacharlie.com/Host: Maxime Lamothe-Brassard - CEO / Co-founder at LimaCharlie

Today we're speaking with Stel Valavanis, Founder and Chairman at onShore Networks and Co-Founder at The Gallery Building, about sustaining a security company over three decades of industry changes. We also dive into investing in start ups and how founders can think long term about governance and growth.Stel has over 40 years of experience ranging from software development to network design and cybersecurity. He's founded 8 companies, invested in 10 more, and sit on various boards. His goal is to build the best tech stack for his customers but also wants to pay forward and make investments in startups, leveraging his knowledge and resources. Stel is always open to board positions and speaking engagements on cybersecurity, media technology, startup investing, and entrepreneurship.Support our show by sharing your favorite episodes with a friend, subscribe, give us a rating or leave a comment on your podcast platform. This podcast is brought to you by LimaCharlie, maker of the SecOps Cloud Platform, infrastructure for SecOps where everything is built API first. Scale with confidence as your business grows. Start today for free at limacharlie.io

In this episode, the host interviews Amazon and e-commerce expert Bradley Sutton, who shares actionable strategies for successful Amazon product launches. Bradley discusses natural keyword integration, backend optimization, and advanced Helium 10 tools like Historical Cerebro and inventory management. He highlights the importance of monitoring Amazon listing changes with alerts to avoid costly mistakes, and offers advice on budgeting for product launches. The episode concludes with Bradley's personal recommendations and tips for staying informed, providing valuable insights for Amazon sellers aiming to optimize listings, manage finances, and scale their businesses effectively.Chapters:Introduction to Bradley Sutton and Amazon Listing Strategies (00:00:00)Bradley shares his background, passion for Amazon, and discusses incorporating top keywords into product listings naturally.Where to Add Keywords in Listings (00:01:15)Explains ideal keyword placement: bullets, description, backend search terms, subject matter, and special features fields.Special Features Field and Indexing Speed (00:02:47)Describes the special features field, its rapid indexing, and cautions against keyword stuffing since it appears on the listing.Advanced Helium 10 Tools for Launches (00:04:15)Introduces Helium 10 Elite tools like Historical Cerebro for seasonal keyword research and their advantages over traditional methods.Sponsored Ad Placements and New Page One Strategies (00:06:46)Discusses the proliferation of sponsored ad placements on Amazon's first page and the need for updated launch strategies.Three Actionable Takeaways for Product Launches (00:08:37)Host summarizes three key takeaways: title keyword density, running CPR via Amazon ads, and budgeting for initial losses.Financial Acumen and Scaling Successfully (00:10:57)Emphasizes the importance of understanding financials, budgeting, and cash flow to scale an Amazon business.Bradley's Most Influential Business Book (00:12:07)Bradley recommends "The Four Disciplines of Execution" and explains its impact on goal setting and business growth.Underutilized Helium 10 Tools for Sellers (00:13:59)Highlights inventory management and alerts as underused tools, sharing a cautionary tale about ignoring alerts.Where to Follow Bradley Sutton (00:16:45)Bradley shares where listeners can follow him: Serious Sellers Podcast, Helium 10 Facebook group, and Instagram.Links and Mentions:Tools and Websites"Helium 10 Listing Analyzer": "00:01:51""Helium 10 Cerebro": "00:05:09""Helium 10 Black Box": "00:05:53""Helium 10 Alerts": "00:14:13""Helium 10": "00:15:07"Additional Resources"Brand Analytics": "00:05:09"Books"The Four Disciplines of Execution": "00:12:07"Podcasts"Serious Sellers Podcast": "00:16:45"Social Media Links"Helium 10 Members Facebook Group": "00:16:45""Bradley Sutton on Instagram": "00:16:45"Key Takeaways"Alerts for SKUs": "00:15:07"Transcript:Josh 00:00:00  Today I'm super excited to introduce you to Bradley Sutton. Bradley is passionate about everything Amazon and e-commerce. He can talk about anything really. Launch strategy. Keyword research, the Amazon algorithm and everything in between. He has launched hundreds of products on Amazon for himself and clients, and he is privileged to host the most listened to podcast in the world for Amazon sellers. The Serious Sellers Podcast. Meeting helium ten customers around the world is his favorite thing to do with that. Welcome to the show, Bradley.Bradley 00:00:33  Thank you for having me here. It's great to be here.Josh 00:00:35  My question to you, Bradley, is you talked about add some of the top keywords into your listing. Where do you add them into your listing? because I could foresee an issue of, for example, maybe you're selling a calendar, right? And a pen. There's one particular type of pen, or it's a set of markers or something, right. That keeps showing up in the the frequently bought together. But those are very kind of two very different products.Josh 00:01:02  Right? So how would you go about incorporating the marker top keywords into calendar type, you know, a calendar type product and where do you put them right. Does it matter? Is it bullets? Description. Back end.Bradley 00:01:15  There's a couple of different ways. So like the most ideal way is just to get it as organic and natural as possible. You know in there. So like the you know perfect situation would be like for example, let's use that gothic, candle holder. You know, I could like, say in one of the bullet points or description, like, you know, hey, you can put a gothic candle holder on top of the coffin shelf and then you have a real spooky, you know, effect or whatever like that. You know, like something that actually makes sense. That's not that's not keyword stuffing. Yeah. You know, sometimes that doesn't you know, you're not able to do that most of the time though, if you really think about it. I mean, if two products are complementary, there's a way to tie it together.Bradley 00:01:51  I mean, otherwise it wouldn't be complementary with each other. Like like there's got to be a way. But in the extreme circumstances where there's not, of course you've got your search terms, your back end search terms. most Categories still have hidden the subject matter like you can't do it in your edit listing, but like once you create your listing, if you use like helium ten Listing Analyzer or you or your advanced user of flat files like in helium ten Listing Analyzer, we still have the subject matter and even though you don't see it there, it still works like we can tie it in the API in the back end. And then so there's usually 4 or 5 more lines of 50 characters. So you can put some of these keywords and then another one where it's very limited. But like if you just can't put it anywhere, is is this this back end feature that, that categories like home and Kitchen have that's called special features. And that doesn't help for ranking. But special features is like the most it's the craziest field I have seen in Amazon in years where I could put something there.Bradley 00:02:47  And I'll get index for it, like in less than 60s, you know, really, you know, if you change your title or your description, sometimes it takes like up to a day for you to get index or for you even to show up. You change something in the search terms. Like it was amazing that hey, like within 15 minutes you could be indexed, you know, like in the old days, this one is like less than 60s. And I could I prove that two ways. You know, using that special URL, that Ajax URL that that shows what's in the back end, or by actually just running index checker to show that, hey, this wasn't indexing then 60s later it is. So, it's it you have to be careful that you can't keyword stuff like you can in search terms and subject matter because the special features it's actually this is kind of a positive and a negative. the positive of course, is that, you know, you can index almost anything at all, even if like sometimes st...

B2B marketers struggle with dark funnel attribution challenges. Chris Golec, CEO and founder of Channel99 and former Demandbase founder, explains how to solve marketing attribution problems that misallocate millions in revenue. The discussion covers Channel99's multi-source approach using smart pixels, API integrations, and CRM connections to reveal three times more website visitor sources than industry standards. Golec demonstrates how AI-powered decision engines can generate strategic media plans in seconds by analyzing account-level engagement costs across channels like LinkedIn organic social and display advertising.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode of The Cybersecurity Defenders Podcast, we discuss some intel being shared in the LimaCharlie community.The White House released President Trump's Cyber Strategy for America, outlining a national framework to strengthen both defensive and offensive cybersecurity capabilities.Iran has expanded the scope of potential targets in the ongoing conflict with Israel and the United States by identifying infrastructure tied to major American technology companies in the Middle East as “legitimate targets.”Chinese-linked threat actors have launched cyberattacks against organizations in Qatar shortly after the initial US-Israel strikes on Iran, indicating a shift in regional targeting strategy.An Iranian-linked hacking group has claimed responsibility for a cyberattack on U.S.-based medical equipment manufacturer Stryker, which disrupted the company's technology operations across its global offices.Support our show by sharing your favorite episodes with a friend, subscribe, give us a rating or leave a comment on your podcast platform.This podcast is brought to you by LimaCharlie, maker of the SecOps Cloud Platform, infrastructure for SecOps where everything is built API first. Scale with confidence as your business grows. Start today for free at limacharlie.io.

Scott and Wes break down the world of remote coding agents — what they are, why you'd want one, and all the different ways you can run them, from Cursor Cloud and Claude Code to an old laptop sitting on your floor. They cover real-world use cases, environment setup, API key management, and the wild variety of interfaces that let agents work while you sleep. Show Notes 00:00 Welcome to Syntax! 03:14 Introduction to Remote Coding Agents 05:32 Practical Examples of Remote Agents 05:34 Website data grunt work. 07:48 Research assistant 08:57 Travel agent… agent 09:57 Where and When Remote Agents Run 10:43 Brought to you by Sentry.io 13:31 Where Remote Agents Run 19:14 CLI and User Interfaces for Remote Agents 24:53 Remote Development Environments 31:21 DIY Agents and Custom Solutions 36:09 The environment 38:08 Managing API Keys and Access 41:02 Web search Hit us up on Socials! Syntax: X Instagram Tiktok LinkedIn Threads Wes: X Instagram Tiktok LinkedIn Threads Scott: X Instagram Tiktok LinkedIn Threads Randy: X Instagram YouTube Threads

Show DescriptionAre we all going to vibe code our own bespoke apps now, can a canvas app be vibe coded, more geolocation API thoughts, CodePen v2's public beta is now out, and private pens explained. Listen on WebsiteWatch on YouTubeLinks March Mad CSS Scroll My Mac Setapp | Powerful apps for Mac & iOS Move tests to closed source repo · Issue #8082 · tldraw/tldraw Enterprising developer somehow writes an x86 CPU emulator in plain CSS — no Javascript, no WASM, just stylesheet computing Traditional Irish music on The Session CodePen Radio – CodePen

The crew on Circle Back reacts to the latest wave of national media coverage around sports betting, including a recent piece from The Atlantic that sparked debate across gambling Twitter. The panel discusses whether these stories are genuinely trying to explore the problems within the industry or if they're being produced with the intention of villainizing sports betting altogether. From misleading narratives to misunderstandings about how the market actually works, the group breaks down where they think the media continues to get it wrong. Later, the crew responds after Kelly In Vegas clapped back on Twitter following criticism of her betting content on last week's show. The discussion turns into a broader conversation about modern betting media, content quality, and accountability within sports betting Twitter. To close things out, the panel reacts to a viral Jeff Nadu tweet and satirically debates whether it's time to start teaching kids how to gamble in a world where betting is now everywhere. Hosted by Jacob Gramegna, this episode of Circle Back features professional sports bettor and CEO of The Hammer Rob Pizzola, sophisticated square Geoff Fienberg, and special guest Jason Cooper of The Hammer Daily filling in for basketball originator Kirk Evans.

Most B2B marketers can't act on their attribution data because 80% of website traffic gets misclassified as "direct." Chris Golec, CEO and founder of Channel99, explains how to solve the dark funnel problem that's costing companies millions in misallocated marketing spend. The discussion covers smart pixel implementation for view-through attribution, API integrations with LinkedIn and CRM systems to track account-level engagement, and using AI-powered decision engines to optimize marketing investment across channels based on cost-per-engagement metrics.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

The episode details a structural shift in the technology landscape: AI models are increasingly being treated as commodity components, with operational control and procurement decisions moving to the orchestration layer. This change is illustrated by government procurement actions, specifically the Pentagon's designation of Anthropic's Claude model as a supply chain risk and the subsequent shift in model eligibility requirements. Policymaking authorities are now directly dictating which models can be used within national security supply chains, reconfiguring where power, liability, and decision-making sit. The primary development is the Department of Defense's recent disqualification of Anthropic's Claude from eligible contracts, leading to both contract cancellations and legal disputes. Anthropic has responded with lawsuits contesting its supply chain risk designation, while Microsoft has sought court intervention to block the Pentagon's ban, asserting this would prevent disruption to military AI workflows. The State Department has also moved its internal chatbot infrastructure from Claude Sonic 4.5 to OpenAI's GPT-4.1, aligning with the President's compliance directive. Supporting developments include Google's deployment of Gemini-powered AI agents within the Department of Defense, and the emergence of tools such as Perplexity's APIs, which aim to simplify workflow construction across multiple models. The episode emphasizes that model swaps by agencies are not merely technical updates, but policy-driven control decisions. These actions underscore a climate in which model eligibility and operational portability are shaped by compliance and procurement authorities rather than technical teams or vendors. Operational implications for MSPs and IT providers are profound. Single-model dependencies now present measurable contract risk, especially for clients in defense, healthcare, or finance sectors. Swapping models requires revalidation of prompts, outputs, and integrations, rather than simple API repointing. Providers are advised to audit workflows for reliance on any one model, prioritize abstraction layers that enable smooth transitions, and position model-agnostic architectures as proactive risk management. In a landscape defined by commodity models and policy-driven eligibility, model diversification now represents continuity planning rather than an engineering preference. Three things to know today: 00:00 Pentagon vs. Anthropic 02:19 Beyond the Model 05:07 Why Do We Care?  Supported by:  ScalePad, Small Biz Thoughts Community

In this episode, I'll tell you about the only infinite money glitch that actually works, as I've been doing it for decades, and that's investing in quality dividend stocks. Join the world's largest free Dividend Discord ➜ https://discord.gg/kkSr5FY Join my channel membership as a GenEx Partner to access new perks: https://www.youtube.com/channel/UCuOS-UH_s4KGhArN6HdRB0Q/join Seeking Alpha Affiliate Referral Link ➜ https://link.seekingalpha.com/2352ZCK/4G6SHH/ Click my FAST Graphs Link (Use coupon code AFFILIATE25 to get 25% off your 1st payment) ➜ https://fastgraphs.com/?ref=GenExDividendInvestor Please use my Amazon Affiliates Link ➜ https://amzn.to/2YLxsiW Thanks! As an Amazon Associate I earn from qualifying purchases. Support me & get Patreon perks ➜ https://www.patreon.com/join/genexdividendinvestor Use my Financial Modeling Prep affiliate link for awesome stock API data (up to a 25% discount) ➡️ https://site.financialmodelingprep.com/pricing-plans?couponCode=genex25

In this week's show we start with FOLLOW UP: The world keeps trying to protect kids online — Indonesia just joined Australia, Spain, and Malaysia in banning social media for under-16s, while COPPA 2.0 sailed through the US Senate unanimously. Meanwhile, Roblox is using AI to clean up its chat, because apparently "Hurry TF up" is the hill they've chosen to die on — even as they're still dealing with the whole "pedophile problem" thing from January. On the AI copyright front, Gracenote is the latest company to sue OpenAI for helping itself to proprietary data, joining a growing queue of plaintiffs who apparently didn't get the memo that everything is training data now.IN THE NEWS: Anthropic is suing the Pentagon after being labeled a "supply chain risk" — apparently because the CEO said AI shouldn't be used for mass surveillance or autonomous weapons, which the Trump administration heard as fighting words. The delicious irony: the Pentagon is still running Claude in active operations while trying to phase it out. Speaking of active operations, investigators now think a missile strike on an Iranian girls' school may have been triggered by bad AI-generated intelligence from that same Claude-based system. So yes, the autocomplete that hallucinates your grocery list is also maybe accidentally bombing schools. Meta's Oversight Board is begging the company to get serious about AI-generated content after a fake war video from a Filipino fake news account racked up 700K views — while separately, Zuckerberg dropped cash on Moltbook, a "social network for AI agents" that turned out to be mostly humans larping as bots and had a security flaw that exposed everyone's API keys. The guy who built it basically vibe-coded the whole thing. Meta's own CTO said he didn't "find it particularly interesting." And yet. Oracle is hemorrhaging jobs and drowning in debt chasing AI dreams, its stock down 50% from peak — a timely reminder that "AI will replace workers" is currently manifesting as "companies set money on fire and lay people off to pay the electric bill." Researchers confirmed AI is homogenizing human thought and creativity — a thing some of us have been screaming since day one. A DOGE engineer allegedly walked out of the Social Security Administration with databases containing personal info on 500 million Americans on a thumb drive. The Ig Nobel Prize is relocating to Switzerland because it's no longer safe to invite international guests to America. Nintendo is suing the US government to get its tariff money back. SETI thinks it may have been accidentally filtering out alien signals due to space weather. And Pokémon Go players unknowingly spent a decade building a centimeter-accurate surveillance map of Earth's cities that's now guiding pizza delivery robots — which, honestly, tracks.In APPS & DOODADS: The GOG clan in Clash Royale just hit eight years old — respect. OpenAudible is the cross-platform audiobook manager your Audible library deserves, especially if you've got over a thousand books sitting there judging you.And finally in MEDIA CANDY: Monarch: Legacy of Monsters Season 2 is here, and pretty beige. Live Nation settled its DOJ antitrust case for $200 million, kept Ticketmaster, and avoided a breakup — meanwhile court documents revealed employees joking about "robbing fans blind" and gouging "stupid" customers, which explains basically every concert ticket you've bought in the last decade. YouTube is now officially the world's largest media company at $62 billion in revenue. Bluesky's CEO is stepping down, which is either a bad sign or just the natural order of "person who built the cool thing hands it to the person who scales the cool thing." Dead Set — Charlie Brooker's 2008 zombie-in-the-Big-Brother-house miniseries — is worth a watch if you haven't. And trailers dropped for Daredevil: Born Again Season 2 (March 24th), The Boys final season (April 8th), and The Super Mario Galaxy Movie (April 1st — yes, really).Sponsors:DeleteMe - Get 20% off your DeleteMe plan when you go to JoinDeleteMe.com/GOG and use promo code GOG at checkout.CleanMyMac - Get Tidy Today! Try 7 days free and use code OLDGEEKS for 20% off at clnmy.com/OLDGEEKSPrivate Internet Access - Go to GOG.Show/vpn and sign up today. For a limited time only, you can get OUR favorite VPN for as little as $2.03 a month.SetApp - With a single monthly subscription you get 240+ apps for your Mac. Go to SetApp and get started today!!!1Password - Get a great deal on the only password manager recommended by Grumpy Old Geeks! gog.show/1passwordShow notes at https://gog.show/737Watch on YouTube: https://youtu.be/DgSYnFF6twEFOLLOW UPIndonesia announces a social media ban for anyone under 16Anthropic Sues PentagonMetadata company Gracenote is the latest to sue OpenAI for copyright infringementRoblox introduces real-time AI-powered chat rephraser for inappropriate languageIN THE NEWSCOPPA 2.0 passes the Senate again, unanimously this timeAI Error Likely Led to Iran Girl's School BombingThe Oversight Board says Meta needs new rules for AI-generated contentMark Zuckerberg Decides Meta Needs More Slop, Buys the Social Network for AI AgentsOracle Axing Huge Number of Jobs as AI Crisis IntensifiesYou can (sort of) block Grok from editing your uploaded photosResearchers Say AI Is Homogenizing Human Expression and ThoughtSocial Security watchdog investigating claims that DOGE engineer copied its databasesNintendo is suing the US government over Trump's tariffsSETI Thinks It Might Have Missed a Few Alien Calls. Here's WhyIg Nobel Ceremony Relocates to Europe Amid Safety Concerns in Trump's AmericaAPPS & DOODADSClash RoyaleOpenAudibleBluesky's CEO is stepping down after nearly 5 yearsHow Pokémon Go is giving delivery robots an inch-perfect view of the worldRobot Escorted Away By Cops After Terrorizing Old WomanMEDIA CANDYMonarch: Legacy of Monsters Season 2Live Nation settlement avoids breakup with TicketmasterCourt documents reveal Live Nation employees joking about robbing, gouging "stupid" fansYouTube Is the World's Largest Media Company, MoffettNathanson SaysParadise Season 2DAREDEVIL: Born Again Season 2 Official Teaser Trailer 2 (2026)The Boys Final Season TrailerThe Super Mario Galaxy Movie | Final TrailerDead SetSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

This week, we discuss Claude Code for non-coders, automating newsletters and status reports, and AI tax prep. Plus, Coté finds unexpected joy in a coding assistant. Watch the YouTube Live Recording of Episode 563 Runner-up Titles Upgraded to Max The only innovation I was talking about was hiring me. The Patrick Stewart of the Cubicles. Should we become the Claudecast? Matt Ray in Your Pocket. Come into the tent You have agency in your life Rundown Coté went to Claude Camp Microsoft and Anthropic team up to bring Claude Cowork to Microsoft 365 Cursor is rolling out a new kind of agentic coding tool Hater Season: Corey Quinn — Better Offline Google completes acquisition of Wiz Relevant to your Interests I Worked for Block. Its A.I. Job Cuts Aren't What They Seem. Iranian news claims AWS drone strikes were deliberate Anthropic Just Won the Enterprise. Here's What Nobody's Talking About Amazon's Bahrain data center targeted by Iran for support of U.S. military, state media says Startups.RIP - Dead YC Startups, Alive Ideas Kratix Anywhere: Cloud, On-Prem, and Hybrid Without Compromise Meta just bought Moltbook, the social network for AI bots - 9to5Mac Amazon holds engineering meeting following AI-related outages Oracle is building yesterday's data centers with tomorrow's debt SUSE Reportedly May Be For Sale Yet Again When Using AI Leads to “Brain Fry” Oracle is under pressure from more than $100 billion in debt and massive layoffs as it pushes ahead with Larry Ellison's 3-step transformation Oracle is building yesterday's data centers with tomorrow's debt Oracle Job Cuts OpenAI bowed out of the Oracle MacBook Neo - Tech Specs Code Mode: give agents an entire API in 1,000 tokens MacBook Neo - Tech Specs Nonsense McDonald's C.E.O. Takes a Big Bite Out of a Burger. Maybe Scratch ‘Big.' Conferences KubeCon EU, March 23-26, 2026 - Coté will be there on a media pass. DevOpsdays Atlanta 2026, April 21-22, 2026 DevOpsDays Austin, May 5-6, 2026 WeAreDevelopers, July 8-10, 2026 Berlin, Coté speaking. VMware User Groups (VMUGs): Amsterdam (March 17-19, 2026) - Coté speaking. Minneapolis (April 7-9, 2026) Toronto (May 12-14, 2026) Dallas (June 9-11, 2026) Orlando (October 20-22, 2026) SDT News & Community Join our Slack community Email the show: questions@softwaredefinedtalk.com Free stickers: Email your address to stickers@softwaredefinedtalk.com Follow us on social media: Twitter, Threads, Mastodon, LinkedIn, BlueSky Watch us on: Twitch, YouTube, Instagram, TikTok Book offer: Use code SDT for $20 off "Digital WTF" by Coté Sponsor the show Sponsor more podcasts with Failover Media Recommendations Brandon: Token management with RTK Usage for Claude App - App Store Coté: Anker MagGo 3-in-1 Wireless Charging Station

Building software is getting dramatically easier — so what exactly are we building our businesses on? In this episode, I dig into why real-world data is the only reliable moat left for software founders. I share what I'm seeing at Podscan, where fifty million transcribed podcast episodes matter far more than any algorithm, why purely transformative software is dangerously vulnerable to agents, and how making your business API-first with full platform parity is the move that turns a data advantage into a defensible one. Having data is half the moat. Availing data is the other half.This episode of The Bootstraped Founder is sponsored by Podscan.fmThe blog post: https://thebootstrappedfounder.com/data-is-the-only-moat/ The podcast episode: https://tbf.fm/episodes/437-data-is-the-only-moatCheck out Podscan, the Podcast database that transcribes every podcast episode out there minutes after it gets released: https://podscan.fmSend me a voicemail on Podline: https://podline.fm/arvidYou'll find my weekly article on my blog: https://thebootstrappedfounder.comPodcast: https://thebootstrappedfounder.com/podcastNewsletter: https://thebootstrappedfounder.com/newsletterMy book Zero to Sold: https://zerotosold.com/My book The Embedded Entrepreneur: https://embeddedentrepreneur.com/My course Find Your Following: https://findyourfollowing.comHere are a few tools I use. Using my affiliate links will support my work at no additional cost to you.- Notion (which I use to organize, write, coordinate, and archive my podcast + newsletter): https://affiliate.notion.so/465mv1536drx- Riverside.fm (that's what I recorded this episode with): https://riverside.fm/?via=arvid- TweetHunter (for speedy scheduling and writing Tweets): http://tweethunter.io/?via=arvid- HypeFury (for massive Twitter analytics and scheduling): https://hypefury.com/?via=arvid60- AudioPen (for taking voice notes and getting amazing summaries): https://audiopen.ai/?aff=PXErZ- Descript (for word-based video editing, subtitles, and clips): https://www.descript.com/?lmref=3cf39Q- ConvertKit (for email lists, newsletters, even finding sponsors): https://convertkit.com?lmref=bN9CZw

Got a question or comment? Message us here!A massive breach has shaken the telecom world. In this episode of the #SOCBrief, we break down the alleged TELUS hack claimed by the ShinyHunters threat group, what data may have been stolen, and why the potential exfiltration of massive datasets could have far-reaching consequences for organizations worldwide. From OAuth tokens and API keys to customer PII and enterprise systems, we explore how attacks like this unfold and what organizations should be on the lookout.

Send a textWelcome to episode 369 of the Chasing Daylight Podcast! This week, Matt, Joe, Jeremy, and Dan cover Akshay's big win at the Arnold Palmer Invitational and dive into the heated debate: Is he anchoring his long putter? The boys also discuss Gary Woodland's incredibly emotional interview about his battle with PTSD, Rory McIlroy tweaking his back, and Jon Rahm capturing a LIV Golf win in Hong Kong.With major season energy in the air, we preview The Players Championship, balk at the wild $900 tee times at TPC Sawgrass, and share a legendary story about playing barefoot night golf at Shadow Creek. Plus, stick around for Matt's absolute disaster class in hosting AI-generated golf trivia, and find out who takes home the ultra-rare 1-of-100 Garsen Stadium grip!Episode Breakdown:Giveaways & Gear: We announce the 1-of-100 Garsen Stadium grip giveaway and talk about the realities of equipment tinkering.Tour News & Recaps: Recapping Akshay's API victory, Jon Rahm's LIV Hong Kong win, and Rory's back tweak.Gary Woodland's Battle: Reacting to Gary Woodland's deeply emotional interview about his post-surgery PTSD.The Anchoring Debate: Analyzing Akshay's putting stroke, the long putter trend, and whether he's breaking the rules.Matt's Knee Rehab: A candid (and painful) update on Matt's grueling physical therapy following his knee replacement.AI Trivia Disaster: Matt hosts a Jeopardy-style golf trivia game powered by Google Gemini, but completely botches the answer key.The Players Championship Preview: Discussing the "fifth major" at TPC Sawgrass, $900 tee times, and making our picks for the week.High Roller Golf: Swapping stories about expensive rounds, including playing barefoot night golf at Shadow Creek.Special thanks go out to our show sponsors:

Joined by Director of Operations for GAP Marty Emeno ahead of a huge 2026 season. We get into the BMW GAP Team Matches, the Major calendar and more! Akshay wins the API in a playoff, big news from the PGA Tour. The Tea with D, a Preview of The Players and See The Line with BetParx! Thanks for Wear SPF, Buy My Ballz and BetParx.

A weekly magazine-style radio show featuring the voices and stories of Asians and Pacific Islanders from all corners of our community. The show is produced by a collective of media makers, deejays, and activists. Tonight our show is called Feed Your Heart. Host Miko Lee speaks with the collaborators and creators of the Asian American Pacific Islander Restorative Justice Network: Elli Nagai-Rothe & Tatiana Chaterji.   Restorative Justice is a movement and a set of practices that stands as an alternative to our current punitive justice system. It focuses on people and repairing harm by engaging all the impacted people working together to repair the harm. RJ is built off of ancient indigenous practices from cultures around the globe, including Native American, African, First Nation Canadian, and so many others. To find out more about Restorative Justice and the work of our guests check out Info about the AAPI RJ Network on the Ripple website: www.ripplecollective.org/aapirjnetwork NACRJ conference in New Orleans: www.nacrj.org/2026-conference Show Transcript [00:00:00] Opening Music: Apex Express Asian Pacific expression. Community and cultural coverage, music and calendar, new visions and voices, coming to you with an Asian Pacific Islander point of view. It's time to get on board the Apex Express.   [00:00:44] Miko Lee: Good evening. I'm your host Miko Lee, and tonight our show is called Feed Your Heart. And we are speaking about the collaborators and creators of the Asian American Pacific Islander Restorative Justice Network with the collaborators, Elli Nagai-Rothe and Tatiana Chaterji.   [00:01:03] Restorative justice is a movement and a set of practices that stands as an alternative to our current punitive justice system. It focuses on people and repairing harm by engaging all the impacted folks working together to repair that harm. RJ is built off of ancient indigenous practices from cultures around the globe, including Native American, African, first Nation Canadian, and many others. So join us as we feed your heart.    [00:02:01] Welcome to Apex Express. My lovely colleagues, Elli Nagai-Rothe, and Tatiana Chaterji. I'm so happy to speak with you both today. I wanna start off with a question I ask all of my guests, and Ellie, I'm gonna start with you and then we'll go with to you, Tati. And the question is who are your people and what legacy do you carry with you?   [00:02:24] Elli Nagai-Rothe: Hmm. I love that question. Thank you. My people come from Japan and Korea and China and Germany. My people are community builders and entrepreneurs survivors, people who have caused harm, people who have experienced harm people who've worked towards repair dreamers, artists and people who like really good food.   [00:02:51] And I carry their legacy of resilience and of gaman, which is a Japanese word that's a little hard to translate, but basically means something like moving through moving through the unbearable with dignity and grace. , And I carry a legacy to continue healing the trauma from my ancestral line the trauma and justice. And that's informs a lot of the work that I do around conflict transformation and restorative justice.   [00:03:19] Miko Lee: Thank you so much. And Tati, what about you? Who are your people and what legacy do you carry with you?    [00:03:25] Tatiana Chaterji: Thank you for the question, Miko. The first thing that comes to mind, my people are the people we're, we're, we're coming up on the cusp of a possible teacher strike, and I'm thinking about workers and the labor, movement and comrades in my life from doing work as a classified school worker for about a decade.   [00:03:46] Then my people are also from, my homelands. The two that I feel very close to me are in Finland, from my mom's side, and then in Bengal, both India, west Bengal, and Bangladesh. And my people are also those who are facing facing the worst moments of their life, either from causing harm or experiencing harm as a survivor of violence.   [00:04:08] I think about this a lot and I think about also the smaller conflicts and tensions and issues that bubble up all the time. So my people are those that are not afraid to make it better, you know, to make it right. And I carry, oh gosh, what legacy do I. I wanna say first kind of the legacy of the Oakland RJ movement that really nurtured me and the youth that I've encountered in schools and in detention on the streets in the community.   [00:04:39] Youth who are young adults and becoming bigger, older adults and, and, and also elders. To me. So sort of that's whose legacy I carry in shaping the. Society that we all deserve.    [00:04:52] Miko Lee: Thank you both for answering with such a rich, well thought out response that's very expansive and worldly. I appreciate that. Ellie, I think it was two years ago that you reached out to me and said, I'm thinking about doing this thing with Asian American Pacific Islanders around restorative justice and you're working on a project with Asian Law Caucus. Can you like roll us back in time about how that got inspired, how you started and where we're at right now?   [00:05:22] Elli Nagai-Rothe: Yeah, absolutely. Yeah, I'd forgotten that we, I had reached out to you at the early stages of this miko. The idea for this emerged in the context of conversations I was having with Asian Law Caucus around, anti-Asian violence and restorative justice. There was an enthusiasm for restorative justice as a pathway toward healing for AAPI communities. One of the things that kept coming up in those conversations was this assumption that there are no, or very few Asian restorative justice practitioners. And I kept thinking this, that's not true. There are a lot, plenty of Asian practitioners. And I think that for me reflects the larger context that we're living in the US where Asians are both at the same time, like hyper visible, , right. In terms of some of the violence that was happening. If you roll back several years ago I mean it's still happening now, but certainly was, was at the height several years ago. So like hyper visible around that, but also in terms of like my model minority status, but also at the same time like invisibilized. So that strange paradox. And so my part of that was thinking about, well, what, what opportunities exist here, right? How can we actually bring together the restorative justice, Asian restorative justice practitioners in the Bay Area to be like regionally focused to come together to talk about how do we bring our identities into more fully into our work, , to build community with each other, and then also to build this pathway for new, for emergent practitioners to join us in this work. That's a little bit of the background of how it came to be, and I'd love Tati to speak more to some of that context too.   [00:07:00] Tatiana Chaterji: Yeah, thanks Ellie. Definitely thinking about work that I was doing in Chinatown and San Francisco. I was working with Chinese Progressive Association just before actually Asian Law Caucus reached out to us with this idea. I wanna shout out Lewa and Cheyenne Chen Le Wu, who are really envisioning an alternative process for their the members of this organization who are immigrant monolingual Cantonese speakers and, and working class immigrants. What are the options available to them to respond to harm and violence in any, any number of ways? And one of the things that we really saw.   [00:07:37] Miko Lee: Non carceral, right? Non carceral options to violence and harm, right?    [00:07:42] Tatiana Chaterji: Yes, exactly. That's exactly what we were thinking of is, and in the period of time where people are talking about anti-Asian hate, they're talking about hate crimes and violence against Asian Americans, there's a simultaneous rhetoric and a belief that Asian people love police or want police interventions or actually believe al punishment. And no doubt that can be true for, for some of our community, but it is not the overwhelmingly dominant truth is what I would say. What I would say, and that actually by believing that Asian folks loved the police was its own bizarre and very toxic racial stereotyping that. Very vulnerable communities who are non-English speakers and living un under wage exploitation and other conditions.   [00:08:34] And so what we were doing was looking at what are the ways that we think about justice and the right way to respond to things and our relational ecosystems. And we began with messages from our home and family dynamics and kind of went outwards and, and everything was presented in Cantonese. I'm not a Cantonese speaker. I was working closely with those two women I mentioned and many others to think about. What is. Not just the, the linguistic translation of these concepts, but what is the cultural meaning and what applies or what can be sort of furthered in that context. And there were some very inspiring stories at the time of violence across communities in the city, and particularly between the Chinese community and the African American community and leaders in those spaces working together and calling forth the abolitionist dreams that were kind of already there.   [00:09:28] That people just want this kind of harm or violence not to happen. They don't want it to happen to anyone again. And this is some thing I think about a lot as a survivor, that that is the dominant feeling is like we, you know, vengeance are not desires for some sort of punishment or not, that this should not happen again. And what can we do to prevent that and really care for the healing that needs to happen.    [00:09:53] Miko Lee: I appreciate you bringing up this solidarity between the African American and, and specifically Chinese American communities wanting a more abolitionist approach. We don't hear that very much in mainstream media. Usually it's pitted the Asian against black folks. Especially around the anti-Asian hate. We know that the majority of the hate crimes, violence against Asian folks were perpetrated by white folks. That's what the data shows, but the media showed it was mostly African American folks. So I really appreciate lifting that part up. So take us from that journey of doing that work with a Chinese progressive association, powerful work, translating that also from, you know, your English to Chinese cultural situations to this network that you all helped to develop the A API Restorative Justice Network, how did that come about?   [00:10:45] Tatiana Chaterji: Part of the origin story is, is work that had been happening across the Bay Area. I was speaking about what's happening in Chinatown. There's also this coalition of community safety and justice that really has been diving into these questions of non carceral response to harm and violence. Then on the other side of the bay in Oakland, the Asian Pacific Environmental Network has been working with Restore Oakland to sit with survivors of crime and build up skills around circle keeping and response. So that's just a little bit of this beautiful ecosystem that we are emerging out of. It almost felt like a natural extension to go here, you know, with a pen and restore Oakland. They were thinking a lot about interpretation and language justice. And so this is also just pulling these threads together for more robust future and practice.    [00:11:41] Miko Lee: Thank you so much for making those connections. We'll put a link in our show notes because we did a recent episode on the Coalition for Community Safety and Justice, and particularly the collective Knowledge based catalog, which captures all these different lessons. So I think what you're pointing out is that all these different groups are coming together, Asian American focus groups to, Pacific Islander focus groups to be able to find, alternatives to the Carceral system in an approach to justice.    [00:12:08] Elli Nagai-Rothe: Well, so it came about through lots of conversations, lots of collaborations I feel so, honored to be able to collaborate with Tati in this work. And other folks who were, , partnering alongside the Asian Law Caucus in this larger grant that was being offered to address anti-Asian hate and violence. Ultimately through many conversations, just wanting to create a space that was created for and by Asian restorative justice practitioners. And as far as we know, it's the only. Gathering or, or network if it's kind in the Bay Area, maybe in the nation. Somebody who's listening maybe can chime in if that's true, that's not true. But as far as we know, that's the only space that's like this. And part of what we've wanted to create is certainly first and foremost because this is so much of the work of restorative justice, at least for us, is about relationships. At the end of the day, it's how we relate to each other and thinking of, of different ways than is often modeled in mainstream world about how we relate to each other.   [00:13:11] We wanted to start with those relationships and so. We created space for current practitioners in the Bay Area to come together. And we had a series of both in-person and virtual conversations. And really it was a space to offer to really build this sense of community and these relationships to share our knowledge with each other, to offer really deep peer support. And specifically we were really interested in bringing and weaving more of our cultural and ancestral ways of being into our practice of restorative justice. And so what does that look like? Can we bring more of those parts of ourselves into our work, our lived experiences into our work, and how we address and hold conflict and harm. I'll speak for myself, such a nourishing space to be part of with other practitioners. Just really allowing more of like a holistic sense of ourselves into our work. And what all the things that could that have come from that. So we've been continuing to meet, so what has this been like two years now? [00:14:12] Almost? We had, in addition to the existing practitioners who were based in the Bay Area, we held a training for like an introduction to restorative justice training that built on the things we were thinking about and learning about with each other around our Asian identities. And that was for folks who were kind of in an adjacent field, social workers, therapists, educators, folks who are doing work with API community workers. And so then we train them up and then they join this net, this larger network. And we've continued to have conversations every month, in a community of practice space. For me, such a wonderful space to be able to connect, to continue, explore together how we can bring more of ourselves into our work in a more relational, integrated and holistic way.   [00:14:56] Miko Lee: Thanks so much for that overview. I wanna go into it a little bit more, but I wanna roll us back for a moment. And Tati, I'd love if you could share with our audience what is restorative justice and what does a restorative justice practitioner do.    [00:15:08] Tatiana Chaterji: The big one. Okay. I think of restorative justice as an alternative to criminal and punitive responses to harm and wrongdoing. I think that's where the definition really comes to life. Although people who are in the field will say that actually it's before the harm or wrongdoing happens, and that it's about cultural norms and practices of caring for each other in a communal way, having each other's back relying on relationships, which also includes effective communication and compassionate communication. So Restorative justice in how I've learned it in the, in the Oakland community was, a lot of the practices were carried by a European Canadian woman named Kay PRUs, who's one of my teachers and who had also, studied with first Nations people in Canada that ish and klingit people, and that there's been some controversy over how she carried those teachings and that there's native people on all sides who have sort of taken a stand.   [00:16:12] I wanna name, this controversy because it feels important to talk about cultural appropriation, cultural survival, that circle practice and how circle is done in many restorative justice spaces will feel very foreign to a person who is indigenous, who perhaps has these ancestral practices in their own lineage, their own history and family. And this is because of colonialism and, and erasure and displacement, and. Reckoning with all of this as immigrants who are on native land, you know, from all, most of us in the API RJ network. Just what, what is this? What, how do we grapple with this? You know, how do we do an appropriate recognition of practices and traditions and how do we build and think about interconnection or the inherent and intuitive knowledge that we have to do non-car work, which is at the core, I've sort of expanded off of your prompt, but an RJ practitioner is someone who holds space for for these conversations, kind of when things are the hardest, when there is heartbreak and betrayal and harm or conflict and also what, the work of setting conditions for that not to happen or for the way that we move through those difficulties to go as best as possible.    [00:17:43] Miko Lee: Thank you for expanding on that. I'm wondering if Ellie, you could add to that about like what is a circle practice, what does that look like?   [00:17:51] Elli Nagai-Rothe: A circle practice. It can look like a lot of different things, but ultimately it's being in a circle, and being able to connect with each other. Again, I talked about how relationships are at the core. That might be when we're, when we're in circling together, we are relating to each other. We're telling our stories. We're weaving our stories together that might be happening when there's no conflict and when there's no harm. In fact, ideally that's happening all the time, that we're being able to gather together, to share stories, to be known by each other and so that if and when conflict does occur, we know how to, how to connect and how to come back to each other because the relationships matter. We know. Okay. 'cause conflict will happen. We will, we are gonna hurt each other. We're humans. That's part of being human. We're gonna mess up and make mistakes. And so a prac having a practice to come back together to say, well, what, what can we do to repair this? How can we make this right, as Tati was saying? [00:18:46] And, and so then circling, be circling up and having a circle practice can also mean when there is conflict, when harm has happened, how can we have people be able to hear one another, to understand what's happening and to repair as much as possible. Um, while doing that again in the ecosystem of relationships. So sometimes that's happening with a, a couple folks and sometimes that's happening with a whole community or a whole group of people.   [00:19:10] Ayame Keane-Lee We're going to take a quick pause from the interview and listen to Tatiana recite an excerpt from the A API RJ Network Reflection document.   [00:19:18] Tatiana Chaterji: Mirrors of each other. To prepare for our closing ritual, I pull a small table with a candle and incense from the back room into the circle. This is our last in-person gathering, and we want to end with building a collective altar for the future of RJ that is rooted in the wisdom of our Asian cultural lineages.Please think of an offering to make this vision a reality. I explain that we use our imaginations to sculpt the air in front of us, shaping it into the essence of the offering. As I have done in prison with incarcerated artists who create textures and depth of story without material props, supplies, or the frills of theater production on the outside.   [00:20:01] I volunteered to go first and model how this is done. Standing and walking towards the altar. I bring my fingers to the center of my chest and pinch an imaginary ball of thread. I want to deepen my understanding of Bengali peacemaking and justice traditions. I say pulling the thread in a vertical motion, stretching up and down to create a cord of groundedness. Realizing there are actually many dimensions. I also pull the thread forwards and backwards in a lateral direction, saying this means looking to the past and dreaming the future. I hold this grided net, gather it around my body and ceremoniously place it on the altar. Others echo the desire for bringing forward parts of their Asian lineage that aren't accessible to them. People create shapes with their bodies, making offerings to the altar that symbolize taking up space, staying grounded in a world that is shaky, reciprocity with the earth, ancestors and descendants, bringing in more ancestors permission to create and play forgiveness to self and others. Timelessness with Earth as a mirror and patience.   [00:21:14] Sujatha closes her eyes and forms an image for us through stream of consciousness. She says, I see indra's net infinite with shimmering diamonds. At each point, I notice the goosebumps raise on the skin of my arms as she continues it is as if she has reached inside of me pulling from the sutra of ra, which was part of my childhood. It is a piece of scripture and a spiritual concept that deeply grounds my practice in RJ as an adult. I see her hands, which she has raised, and fingers trembling, glimmering ever so slightly. She speaks slowly carrying us with her in a visualization de drops, mirrors. I cannot be who I am meant to be unless you are who you are meant to be. RJ is the material of the web. This was a rare moment of belonging for me, as I seamlessly reflected in the speech and cultural symbols of a peer seamless. This integration as South Asian and as an RJ practitioner, seamless, being able to hang onto a reference from religious traditions that are hidden in the diaspora or distorted by mainstream social messaging.   [00:22:28] Ayame Keane-Lee We hope you enjoyed that look into the AAPI RJ Network Reflection. Let's get back to the interview.   [00:22:35] Miko Lee: Can you each share what brought you to this work personally?   [00:22:40] Tatiana Chaterji: Sure. As a young activist involved in Insight Women of Color against Violence and aware of the work of Critical Resistance, and I had a pretty clear politics of abolition, but I didn't. Really think that it impacted me as personally as it did when I was in my early twenties and I suffered a brain injury from a vehicular assault, a hit and run that may have been gang affiliated or, a case of mistaken identity. My recovery is, is, is complicated. My journey through various kinds of disabilities has shaped me. But I think the way that I was treated by the police and by the justice quote unquote justice system, which I now call the criminal legal system, it because there was no justice. I sort of don't believe that justice is served in the ways that survivors need. yeah, I really, I got very close to the heart of what an RJ process can do and what RJ really is. I got introduced to Sonya Shah and the work of Suha bga and I was able to do a surrogate victim offender dialogue and then later to facilitate these processes where people are kind of meeting at the, at the hardest point of their lives and connecting across immense suffering and layers of systemic and interpersonal internalized oppression. [00:23:59] Just so much stuff and what happens when you can cross over into a shared humanity and recognition. It's just, it's just so profound and and from that space of healing and, and, and compassion, I've been able to think about. Other ways that RJ can look and have sort of been an advan, what is it evangelical for it? You know, I think that because we don't see these options, I, I, because I knew people, I was able to connect in this way and I would just shout out David uim, who's the one who told me that even if I didn't know the person who harmed me, that this was possible. People so often give up, they're just like, well, I have to feel this way. I have to just deal with it. Swallow the injustice and the lack of recognition. Just sort of keep going. Grit your teeth. I think we don't have enough knowledge of what's possible and so we harden ourselves to that. Yeah, I'll stop there. Thanks for listening.    [00:24:59] Miko Lee: Oh, that's the gaman that Ellie was talking about, right? In Chinese we say swallow the bitter. Right. To be able to just like keep going, keep moving. And I think so much of us have been programmed to just something horrible happens. You just swallow it, you bite it down, you don't deal with it and you move on. Which is really what RJ is trying to teach us not to do, to recognize it, to to talk to it, to speak to it, to address it so that we could heal. Ellie, what about you? How did you get involved?    [00:25:30] Elli Nagai-Rothe: Yeah. And Tati, thanks so much for sharing. I always appreciate hearing. I like your story and what draws you to this work is so powerful. For me, I'll take it a little bit more meta further back. What draws me to this work is my family history. I'm multiracial. My family, my ancestry comes from many different places. And part of that my grandparents, my aunties, uncles, Japanese Americans who were, who were born, some of them, my grandpa, and his family here in Oakland, in this area. And, um, other my grand, my grandmother and her family in Southern California. During World War II, were unjustly incarcerated along with 125,000 Japanese Americans in ways that were so deeply harmful and traumatic and are so parallel to what is happening right now to so many communities who are being detained and deported. And that experience has deeply, deeply impacted certainly my community's experience, but my family's experience of trauma.   [00:26:30] And I'm yonsei, fourth generation Japanese American. And though I wasn't directly involved or impacted by that incarceration, I feel it very viscerally in my body, that feeling of loss, of disconnection of, of severance from community, from family, from place, and, . Even before I knew what restorative justice was, I was in my body striving to find justice for these things that have happened? That drew me into conflict transformation work and ultimately restorative justice work. And that's where I found really at the, at the core, so much of this, this intuitively feels right to me. I didn't wanna have a place of, I wanted to heal. That was what I wanted to feel the feeling of, can we heal and repair and can I heal and repair what's happened in this, my experience and my family's experience and community's experiences?   [00:27:23] That work ultimately led me to do restorative justice work here in the Bay Area. I started doing that work with schools and community organizations. And so I really hold the bigger possibilities of what's possible when we think differently about how we hold relationships and how we hold deep, deep pain and harm and what's possible when we can envision a different kind of, a world, a different kind of community where we can take accountability for things that have happened. And knowing that all of us at, at different places, I know that's true in my family line, have caused harm and also experienced harm, that those things can happen at the same time. And so how can we have a sense of humanity for what's possible when we actually come, come to each other with a humility of what, how can we heal? How can we heal this together? How can we make this as right as possible? So that's, that's a bit of my story.    [00:28:13] Miko Lee: Thank you both for sharing.   [00:28:15] Ayame Keane-Lee Next we're going to take a music break and listen to Miya Folick “Talking with Strangers”   MUSIC   [00:34:05] that was “Talking with Strangers” by Miya Folick   [00:34:09] Miko Lee: I'm wondering, I know this, Asian American, Pacific Islander, RJ Circle, a bunch of it has been online just because this is how we do in these times and I'm wondering if there's something unique and empowering about doing this online. I bring that up because there have been many in person gatherings. I've been a part of this circle, so I'm really happy to be a part of it. For me, the vibe of being in person where we're sharing a meal together, we're in a circle, holding onto objects, making art together is very different from being online. And I'm wondering, if there's something uniquely positive about being online?   [00:34:47] Tatiana Chaterji: I would just say that yeah, the intimacy and the warmth and the sort of the strength of the bonds that we have in this network are, are so beautiful and it's possible to have incredible, virtual experiences together. A lot of us do movement art or theater or creative. We have creative practices of our own. And when we lead each other in those exercises, we are really just a feeling of togetherness. Like that's so special. And for people who have had that online, they know what I'm talking about. That can be really, really incredible. And, you know, we've been in the Bay Area and really in Oakland, but we want to expand or we want to think about what are all the ways that we can connect with other people. Around this intersection of API identity and RJ practice. And so that's the potential, I guess is what I would say is just to really, move across time and space that way.   [00:35:47] Miko Lee: Ellie, do you have thoughts on this, the online versus in real life?    [00:35:51] Elli Nagai-Rothe: I think there's so many wonderful things about being in person because I feel like so much, at least I don't know about your worlds, but my world, so much of it is online these days on Zoom. There is something really special about coming together, like you said, to share a meal to be in each other's physical presence and to interact in that way. At the same time when we're online, there's still so much warmth and connection and intimacy that comes from these relationships that I've been building over now, like two years for some of us. The opportunities are more about being able to reach accessibility, right? Folks to be able to come online and, and potentially even broaden. I mean, who knows what that will look like right now it's regionally focused, but maybe there's a future in which that happens to be outside the Bay Area.   [00:36:31] Miko Lee: And speaking of the future and where it's going. This initially started by, funding from one of the Stop the Hate grants, which sadly has concluded in the state of California. I'm wondering what this means for this, process that it doesn't have any set funding anymore what does the future look like?    [00:36:52] Elli Nagai-Rothe: We really wanna continue this miko and being able to continue to meet and gather in community. Right now we're continuing to meet monthly in our community of practice space to support each other and to continue to explore really this intersection, right, of restorative justice in our idea, our Asian identities. There's so much more opportunity to continue to build together, to create a larger community and base of folks who are exploring and ex doing this work together. Also for the intention of what does that mean for our communities? How can we find ways to take this practice that many of us do, right?   [00:37:27] As practitioners, how can we translate that to our community so that we know, we know at its core that this work, there are things from our cultural practices that are just. So familiar, right? Certain practices around how we you know, this radical, some of the things we talked about, radical acts of hospitality and care are so intuitive to our Asian communities. How can we translate that practice in our work so that we can continue to make this these pathways available to our community? So we hope to continue, we wanna continue to gather, we wanted to continue to build, um, and make space for more people to join us in this exploration and this opportunity for yeah, more expansion of what's possible for our communities.   [00:38:11] Miko Lee: For me as somebody who's Chinese American and being a part of this network, I've learned from other Asian American cultures about some of the practices, well, I did know about things like tsuru folding a paper crane as part of the Japanese American culture, learning different things from different community members about elements that are part of their cultures and how they incorporate that, whether that's yoga or a type of, Filipino martial art or a type of Buddhist practice. And how they fit that into their RJ work has actually helped me kind of expand my mind and made me think about more ways that I could bring in my own Chinese American culture. So for me, that was one of those things that was like a blessing. I'm wondering what each of you has learned personally about yourself from being part of this network.   [00:39:02] Tatiana Chaterji: What comes to mind is the permission to integrate cultural identity and practice more explicitly and to know that there are others who are similarly doing that. It's sort of this, this acceptance of sort of what I know and how I know it that can be special. You know, in the, in the similar way that I mentioned about cultural appropriation and the violence that various communities have felt under capitalism and white supremacist structures. Everything there is, there is, I don't, something, something so magical to just step outside of that and be like, this is, it's a mess. It's a mess out there. We are constantly battling it. How do we actually not make ourselves smaller right here?    [00:39:50] Miko Lee: I totally hear that. And I'm thinking back to this gathering we had at Canticle Farms, where I think Tati, you said, when was the last time you were in a space where you were the only Asian person and how you walk through that mostly white space and what is that like for you and how do you navigate? And so many people in the room are like, what their minds were blown. For me, I'm in mostly Asian American spaces and Pacific Islander spaces, so I'm like, oh wow, that wasn't always true for me. So that's my time in my life right now. So it was really fascinating to kind of ponder that.   [00:40:24] Tatiana Chaterji: Yeah. And I think many of us, I'm so glad that you feel that because many of us, don't really know what exactly our ancestral technologies might be, or even what to name. This gave us, again, permission to look back or to reframe what we know or that we've understood from community as being from various traditions, homelands, you know, longer legacies that we're carrying and just to, to, to, to celebrate that or to even begin to, to, to bring language to that and feel a place of our own belonging. Whereas, I mean, as a South Asian diasporic member of the diaspora, I see so many the words that are coming from Sanskrit, which has its own, history of castes violence and like sort of what the expansion and the co-optation is, is, is really quite massive to the point where I feel like I'm on the outside and I don't believe that I should own it any more than anyone else. But I think if there's a way that it's practiced that is in, in, in integrity and less commodified because it is ancient, because it is medicine. You know, that I, I deserve to feel that, you know, and to tend to be welcomed into it in, in this you know, outside of the homeland to be here in Asian America or whatever it is, and to claim it is something quite special.   [00:41:50] Miko Lee: Love that. Thank you for sharing. Ellie, what about you? What have you learned from being in part of this network?    [00:41:55] Elli Nagai-Rothe: I was just gonna say like, yes, Tati to all the things you just said. So appreciate that. I, it's very similar, similar in some ways to what Tati was saying, like the, the permission giving, the space that we, oh, permission giving that we give to each other, to to claim, like, to claim and reclaim these practices. And I think that's what I heard so often from people in this network and continue to hear that this, the time, our time together and the things that we're doing. Feel like it's, it doesn't feel like a so much about like our, what is our professional practice. And I say professional with quotes. It's more of like, how do we integrate this part, this really profound journey of ancestral reclaiming, of remembering, of healing. And, and when we do that, we're working from this really. A deep place of relationship, of interdependence, of where we're like, our identity and our sense of who we are is so connected to our communities. It's connected to the natural world. And so like how can we, that's part of what I've appreciated is like really in this deep way, how can we remember and reconnect to, in some cases, like practices, pre-colonial practices and wisdom that was suppressed or taken away, certainly in my and family experience, right?   [00:43:11] It was very deliberately state sponsored violence severed those practices. And so some of this reclaiming as a part of my own healing has been really given me more voice and space to say like, yeah, I can, I can, I want to, and I, that's part of my own practice, but also share that with the, the groups that I'm part of. And that feels a little bit. We talked about that a little bit in the network of how do we share these practices in ways that feel authentic, like Tati said, with integrity, but also what does that mean to share these practices in spaces that are outside of, you know, Asian communities? I don't know, like that's a whole other conversation, right? It feels because there is so much cultural co-opting that's happening, right? And so I feel, I think that's why this network is so valuable and, and helpful to be in a space. Of course, it's a very diverse group of Asian identities and yet it's a space where we can feel like we can try on in these practices to see what that feels like in our bodies in ways that feel really like, have a lot of integrity and a lot of authenticity and to support each other in that.   [00:44:12] And so that we can feel able to then share that in spaces than, in our communities and the work that we're doing in terms of, restorative justice work.  [00:44:19] Miko Lee: So how can our audience find out more about these circles if they wanna learn more about how they could potentially get involved?   [00:44:29] Elli Nagai-Rothe: The best way to go is to look at the Ripple Collective website, ripple collective.org. We have some information about, the A API Restorative Justice Network there. I'm hoping that we can continue this. I really am excited about, members of the network continuing to stay in relationship with each other, to support each other. Tati and I are gonna be offering a session at the upcoming national Association for Community and Restorative Justice Conference that's happening in New Orleans in July. We're gonna be sharing what we learned about our experiences with this network and centering our Asian identities and restorative justice practice. We're gonna be holding a a caucus space for Asian practitioners to come and join us. Yeah, so what else? Tati.    [00:45:14] Tatiana Chaterji: We're also compiling reflections from various participants in the network around what this has meant. What, what have they learned or discovered, and what's to come. I think a question that I've had, a question that we've been stewing on with other South Asian, , practitioners is what does you know, what does caste how does caste show up and reckoning with harm doing? And our communities are not a monolith, and, and as we are treated as part of a, sort of like a brown solidarity, third world movement space in the West, there's just a lot of unrecognized and unnamed oppression that is actively happening. So, you know, really like being, being brave and humble to, to, to talk about that.    [00:46:01] Miko Lee: Thank you both so much for sharing your time with me today.    [00:46:05] Elli Nagai-Rothe: Thanks so much, Miko.    [00:46:06] Tatiana Chaterji: Thanks, Miko.   [00:46:07] Ayame Keane-LeeTo finish off our show tonight, we'll be listening to “Directions” by Hāwane.   MUSIC   [00:49:55] That was “Directions” by Hāwane.   [00:49:57] Miko Lee: Thank you so much for listening tonight. Remember to reconnect to your ancestral technologies and hold in the power of tenderness. To find out more about restorative justice and the work of our guests, check out info about the A API RJ network on the Ripple website, ripple collective.org, and about the conference that Ellie and Tati will be presenting at at the NAC RJ Conference in New Orleans, both of which we'll have linked in our show notes.   [00:50:30] Please check out our website, kpfa.org/program/apex Express to find out more about our show and our guests tonight. We thank all of you listeners out there. Keep resisting, keep organizing, keep creating, and sharing your visions with the world because your voices are important. Apex Express is produced by Ayame Keane-Lee, Anuj Vaidya, Cheryl Truong, Isabel Li, Jalena Keane-Lee, Miko Lee, Miata Tan, Preeti Mangala Shekar and Swati Rayasam. Tonight's show was produced by me Miko Lee, and edited by Ayame Keane- Lee. Have a great night.   The post APEX Express – 3.12.26- Feed Your Heart appeared first on KPFA.

The PHP Podcast streams live, typically every Thursday at 3 PM PT. Come join us and subscribe to our YouTube channel. Another fun episode of the PHP Podcast! Here’s what we covered: Internet Woes & Technical Difficulties Eric continued his saga with connectivity issues, dropping multiple times on Zoom calls and even during the podcast. After trying everything from coax cable converters to different network setups, he’s considering just running a new network cable to his office. The Wi-Fi experiment during the show… didn’t go great. First Waymo Experience John shared his first ride in a Waymo self-driving car! While the wife wasn’t thrilled about having to walk to a specific pickup spot, the experience was pretty impressive. One weird moment: the car got confused by a bus at a 45-degree angle and started creeping into the left lane. Overall verdict: comfortable, cheaper than Uber, and no awkward small talk required. Eric’s Coding Adventure In a rare “Eric writes code” moment, he debugged a POC project by littering the codebase with 15+ write-to-log statements (because who needs X debug?). The culprit? A renamed variable he forgot to update elsewhere. Classic. John was horrified to learn there’s no static analysis running. The demo went well… until someone asked to see the customer interface. MySQL 8.0 → 8.4 Upgrade Planning John’s been preparing for the MySQL 8.0 to 8.4 upgrade (8.0 is end of life). The previous team left amazing documentation, but there’s one major issue: the DBA rejected converting from utf8mb3 to utf8mb4 character set because the tables are so massive it would lock them for way too long. That’s a problem for future John. AWS S3 Cleanup – 75 Million Files! John tackled a years-old problem: phone call recordings stored as both WAV and MP3 files in S3. The cleanup script identified 75 million WAV files to delete, which took a day and a half to process. Potential savings: $100/day. Joe asked about intelligent tiering, which… yeah, probably should look into that. PHP Tek 2026 – 68 Days Away! The conference schedule is live! Four tracks (three PHP Tek + one JS Tek), hotel rooms at the discounted rate are going fast, and Eric admitted he skipped Scale this year because he was just too exhausted. Focus is on PHP Tek now! Laravel 13 Dropping March 17 Laravel 13 is dropping on Tuesday with a focus on moving from protected properties to attributes. According to the article, there are no breaking changes (we’ll see about that). Overall, it’s a light upgrade with some new features but nothing earth-shattering. March Friday the 13th Anniversary Eric and Beck’s dating anniversary! They started dating on March Friday the 13th, 1987, when Eric picked her up at 5 PM for a midnight showing of a terrible Burt Reynolds movie called “Heat” (which apparently doesn’t exist according to IMDB). The whole show tried to help figure out what movie it actually was. Spoiler, it was called HEAT PHPUnit 13 Released Sebastian Bergmann appeared on PHP Alive & Kicking to talk about PHPUnit 13. The big change: array of assertions. The show also features a hard deprecation of some older methods. Check out the release for all the details. OpenClaw/Archie AI Success Eric’s thrilled with how the team is using the OpenClaw AI agent for daily standups. Team members are not only doing their morning standups but updating it throughout the day and even asking it to check for security alerts. The engagement has been way beyond expectations. Now Eric’s fighting the temptation to buy a Mac Mini to run it properly and get it back on Ollama, saving on API costs. Links from the show: PHP Tek 2026 – The Premier PHP Conference WiFi Mapping User Guide – Turn your router into a see-through-walls device WiFi Mapping Demo on X Laravel 13 drops March 17 — here’s every new feature with code examples X: https://x.com/phparch Mastodon: https://phparch.social/@phparch Bluesky: https://bsky.app/profile/phparch.com Discord: https://discord.phparch.com Subscribe to our magazine: https://www.phparch.com/subscribe/ 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 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/ The post The PHP Podcast 2026.03.12 appeared first on PHP Architect.

Marco Benitez moved his family to the US to build Rook, an API for wearables. But when a familiar face shows up in The Pitch Room, he learns just how much vibes matter in venture. This is The Pitch for Rook. Featuring investors Elizabeth Yin, Jesse Middleton, Laura Lucas, and Mike Ma. Watch Marco's pitch uncut on Patreon (@ThePitch) Join us for the Season 16 taping and founder happy hour in Tampa Subscribe to our email newsletter: insider.pitch.show Learn more about The Pitch Fund: thepitch.fund *Disclaimer: No offer to invest in Rook is being made to or solicited from the listening audience on today's show. The information provided on this show is not intended to be investment advice and should not be relied upon as such. The investors on today's episode are providing their opinions based on their own assessment of the business presented. Those opinions should not be considered professional investment advice. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Isaac Rose-Berman, a sharp tennis bettor, uncovered a hidden edge at a recent Indian Wells tournament that most bettors completely missed. The opportunity came from a subtle change in tennis balls, and Isaac breaks down exactly how he spotted it, why it mattered, and the impact it had on his betting strategy. Fans of tennis and sports betting will get a rare, inside look at a true all-time advantage and the methods that sharp bettors use to find opportunities others overlook. In this episode of Legendary Loopholes, host Jacob Gramegna is joined by Isaac Rose-Berman to dive deep into the edge and explain his thought process. Together, they walk viewers through the discovery, making this episode essential for anyone interested in betting strategy, tennis insights, or spotting hidden advantages in sports.

Adam talks with Tailscale co-founder and Chief Strategy Officer David Carney about where Tailscale is headed next: TSIDP, TSNet, multiple tailnets, and Aperture. They get into clickless auth (via TSIDP), TSNet apps, multiple tailnets for isolation and control, and Aperture, Tailscale's private AI gateway for API key management, observability, and agent security.

Players Preview & Picks | Daniel Berger vs. Akshay Bhatia | Scheffler Panic | McIlroy WD & MoreOn the show we recap API and talk through best bets for Akshay in 2026. Is it the Max Homa caddy change that is making the difference. Scott Scheffler panic alarm continues to be hit. Could he be on a Matt Wolff mental decline. Rory McIlroy WD's after a back injury and is ready for The Players. Does Rickie 'Bucky' Fowler look like Leonard DiCaprio? If so does Howard Sterns Beetlejuice look like Denzel. We get into The Players 2026 best bets. We like Min Woo, Si Woo and more. Looking forward to a great week. We also chat some movies with best villains over the years. Is Jack better than Heath, Keaton over Bale?03:00 Travel Stories and Upcoming Guests06:01 Golf Insights and Tournament Discussions08:55 Analyzing Player Performances and Strategies11:59 Controversies in Golf: Anchoring and Equipment18:00 Press Conferences and Player Personalities24:29 Tournament Insights and Caddy Changes27:24 Upcoming Tournaments and Player Performances30:51 Tiger Woods and Tournament Eligibility32:14 Panic Alarm: Player Performance Concerns35:03 Recent Winners and Betting Strategies38:43 Heroes and Villains in Golf Betting41:23 Analyzing Player Stats and Future Bets48:10 Betting Insights and Predictions50:58 One and Done Picks53:59 Film and Character Discussions57:03 Recency Bias in Film Characters01:00:10 Batman and Villains Analysis01:02:55 Future Movie Ideas and RemakesApparel for the show provided by turtleson. Be sure to check them out online for the new season lineup at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://turtleson.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠/⁠⁠⁠⁠ Thanks to Fantasy National Golf Club for providing the stat engine for the show. They can be found at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.fantasynational.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ The Neat Glass. Be sure to check out The Neat Glass online at ⁠⁠⁠⁠theneatglass.com⁠⁠⁠⁠ or on Instagram @theneatglass for an improved experience and use discount code: bb10 to receive your Birdies & Bourbon discount. Thank you for taking the time listen to the Birdies & Bourbon Show for all things PGA Tour, golf, gear, bourbon and mixology. Dan & Cal aim to bring you entertaining and informative episodes weekly. Please help spread the word on the podcast and tell a friend about the show. You can also help by leaving an 5-Star iTunes review. We love to hear the feedback and support! Cheers. Follow on Twitter & Instagram (@birdies_bourbon)

How to Grow Your Business With SEO (Without Social Media) — Faith Hanan on Her Faith at WorkEpisode OverviewAre you tired of posting on Instagram and TikTok every day — only to watch your content die in 24 hours? In this episode of Her Faith at Work, host Jan Touchberry sits down with Faith Hanan, accidental SEO expert, copywriter, barrel racer, and mom of three, to talk about one of the most powerful (and misunderstood) tools for growing a Christian woman's business online: search engine optimization.Faith has not posted on social media for her business in over three years — and her business is still growing. In this conversation, she breaks down why SEO is the "crockpot of marketing," how to find the right keywords for your business, and what tools you can use today even if your budget is $0.About Faith HananFaith Hanan is an accidental SEO expert, copywriter, podcaster, homeschool mom, worship leader, and competitive barrel racer. She runs a copywriting and SEO agency and teaches faith-filled entrepreneurs how to scale their online businesses using SEO, keywords, and blogging — all in less than 20 hours a week.She is the host of the Simple SEO & Marketing podcast and creator of the Simple SEO Framework (SSF) group coaching program.What You'll Learn in This EpisodeWhat SEO actually is — and why it shortens your sales cycle by putting you in front of "hot leads" instead of cold audiencesWhy social media content has a half-life of less than 24 hours (and what to do instead)How Faith hasn't posted on social media for her business in 3+ years — and still growsThe #1 mistake entrepreneurs make with keywords (hint: you're speaking a different language than your customers)Why targeting 120 highly specific monthly searches beats chasing 10,000 broad onesThe free tools you can start using today: Ubersuggest and Google Search ConsoleHow to know if your SEO is actually workingFaith's simple framework: get your core pages optimized first, then add SEO-rich blog contentHow to write an SEO-optimized blog post in 90 minutes and maintain your traffic machine in 2 hours a weekKey TakeawaysWhat is SEO and why does it matter for small business owners?SEO (Search Engine Optimization) helps search engines like Google understand what your business does and surface your website to the right people at the right time. Unlike social media, which dies within 24 hours, SEO-optimized content can drive traffic for years. Faith describes it as "the crockpot of marketing" — you do the work upfront and results compound over time.How do I find the right keywords for my business?Faith recommends a two-step process:Start on paper — brainstorm words and phrases your ideal client would type into Google when searching for the problem you solve.Then validate with a tool — Ubersuggest (free version) connects directly to Google's API and gives you real search data, not estimates.Key insight: A keyword with only 120 monthly searches from your exact ideal client is far more valuable than a keyword with 10,000 monthly searches dominated by Nike and Under Armour.How long does SEO take to work?Most businesses start seeing results within 1.5 to 3 months, with more significant momentum around 6 months. The speed depends on your website's current health, how long you've had a web presence, and how competitive your keywords are.Can I do SEO without being on social media?Yes. Faith is living proof. She stopped posting on social media for her business over three years ago and relies entirely on SEO and long-form content (blogs, podcasts). Because SEO-optimized content continues to be indexed and discovered for years, it works for you 24/7 — even while you sleep.Episode Timestamps00:00 Introduction — Meet Faith Hanan02:25 Faith's background: SEO agency, homeschooling, and barrel racing03:55 Jan's personal SEO journey — 6 months in, seeing momentum04:32 SEO is the “crockpot of marketing” — why people quit too soon05:00 What SEO actually does (and why it shortcuts the sales process)06:33 The social media rat race and why SEO is a better long-term strategy07:13 Faith hasn't posted on social media for 3+ years — and it started as a church fast08:10 The half-life of social media vs. the longevity of blog content09:17 How to get started with SEO without getting overwhelmed09:45 The keyword language gap: how you talk vs. how clients search10:57 Why small, specific keywords beat high-volume broad terms13:40 Free and affordable keyword tools — Ubersuggest deep dive15:00 Start keyword research on paper first, then use tools16:36 How to know if SEO is working — Google Analytics & Search Console17:00 Optimize your core website pages before your blog19:16 Broken links, analytics, and getting coaching (barrel racing analogy)22:05 About the Simple SEO Framework (SSF) group coaching program24:42 Special discount code for Her Faith at Work listeners: JAN26:11 Where to find Faith — FaithHanan.com/framework26:25 The Workflow Exchange — SEO for blogging workflow from FaithResources & Links MentionedFaith Hanan's websiteSimple SEO Framework (SSF) Group CoachingKeyword Research Kickstart (affordable beginner course)Simple SEO & Marketing PodcastThe Workflow Exchange (free SEO for Blogging workflow)Ubersuggest (free keyword research tool)Google Search Console (free)Google Analytics (free)

Show DescriptionThe Zero Day Clock is ticking — and the numbers should make every security leader uncomfortable. In this episode, I sit down with Sergej Epp, CISO at a leading security firm, who built the Zero Day Clock after a weekend experiment using AI to discover vulnerabilities firsthand. What he found shocked him: with no professional vulnerability research background and just a few hours of work, he was successfully finding zero days across major security projects using AI models and basic scaffolding.Sergej breaks down his concept of the "Verifier's Law" — the idea that offense has the cheapest verifier in cybersecurity because feedback is binary and instant (you either popped a shell or you didn't), while defense operates in a space where validation is expensive, ambiguous, and slow. We dig into what this asymmetry means for the industry, why 20 years of warnings from Ross Anderson, Bruce Schneier, Halvar Flake, and others have gone unheeded, and whether coordinated disclosure models are broken now that AI can reverse engineer a patch into a working exploit in minutes.We also discuss the tension between regulation and deregulation playing out in the U.S. and EU, why the answer might be outcome-based accountability rather than prescriptive compliance, and what a realistic defensible posture actually looks like when the mean time to exploit for actively exploited vulnerabilities is under two days — while most organizations are still operating on 30-day patch cycles.Show NotesSergej shares how a weekend AI experiment led him to discover multiple zero days across major security projects with no professional vulnerability research experience — and why that should alarm the entire industryThe "Verifier's Law" explained: offense has cheap, deterministic validators (pop a shell, exfiltrate data, trigger an XSS) while defense faces expensive, ambiguous validation (parsing SIM alerts, measuring security posture), giving AI-accelerated offense a structural advantageThe Zero Day Clock synthesizes 3,500+ CVE-exploit pairs and shows the mean time to exploit for actively exploited vulnerabilities is now under two days — while organizations still operate on 14-to-30-day patch cycles20 years of ignored warnings: from Ross Anderson's 2001 economics paper through Bruce Schneier, Halvar Flake's "the patch is the advisory" insight, and DARPA's Cyber Grand Challenge — the industry has consistently failed to act on clear signalsAI can now reverse engineer patches to identify underlying flaws and generate working exploits in minutes, potentially breaking coordinated disclosure models and compressing the window between patch release and active exploitation to near zeroThe regulation paradox: the EU risks overregulating AI in ways that hamper defenders while attackers face no such constraints, while the U.S. is pushing deregulation that may remove the only forcing function for vendor accountability — Sergej and Chris discuss outcome-based regulation as a potential middle pathDefenders have a data advantage: by understanding their own environments, infrastructure, and processes, security teams can detect AI-driven attacks through behavioral anomalies like hallucinated API calls, non-existent user accounts, and other artifacts of AI-generated attack playbooksThe Zero Day Clock's real power is as a board-level communication tool — a single slide that translates the patching gap into a number executives and policymakers can't ignore, shifting the conversation from "are we compliant?" to "are we fast enough?"

If you're a software engineer right now, you likely feel like your world is changing overnight. We are writing half or less the amount of code that we wrote even a year ago, which represents a seismic, groundbreaking shift in our industry. However, the rapid introduction of new tools can slide quickly from exciting to purely chaotic, leaving you feeling like you are falling behind. In today's episode, I explore how this changes the nature of our day-to-day work, and why the key to surviving this transition is shifting your mindset from a traditional "Software Engineer" to an "Agent Manager". The Illusion of Velocity vs. Actual Chaos: While the big-picture promise of AI is that the software development pipeline will move exponentially faster, the reality on the ground often feels like unadulterated chaos. Trying to adopt every new tool while spinning up multiple agents to work on parallel tickets introduces a massive new cognitive burden. The Context-Switching Trap: Understand why parallelizing agent workflows fundamentally changes your context-switching overhead. You are no longer just reloading context to build something yourself; you are reloading it to manage, review, and validate a building agent, which rapidly drains your cognitive ability and leads to burnout. The "Agent Manager" Mindset: Treating AI as just a "smart autocomplete" while you try to do the same old job will not work. You need to start viewing your role more like assembly line or process management, focusing on facilitating the system rather than typing every line of syntax. Adopt Old-School Quality Control Tactics: Discover how traditional management methods are becoming essential for individual contributors. Just like a factory manager doesn't inspect every single item off the line, you must develop methods for spot checks, anomaly detection, and standardizing outputs to evaluate the quality and quantity of your agents' work. Shift Your Work Upfront: Recognize that your core effort must move to the specification and planning phases. Your job is increasingly about setting the context, defining the prompt, and establishing strict guardrails before the agent begins its work. Redefining Your Work in Progress (WIP): Proven principles like limiting WIP and focusing on finishing rather than starting are more important than ever to reduce cognitive burden. However, you must adapt these principles to fit a workflow where you are managing processes rather than manually coding. Episode Homework: Take a step back and ask yourself: "What is my true work in progress? Am I actually manually doing these tickets, or am I managing the processes that produce quality ticket work?".

For episode 688 of the BlockHash Podcast, host Brandon Zemp is joined by Viktor Ihnatiuk, Co-Founder and CEO of Utexo, a Bitcoin-native stablecoin settlement network backed by Tether. Utexo enables private, compliant USDT payments with fixed costs, powered by the Lightning Network and RGB.Viktor is a Bitcoin and Web3 engineer with over 12 years of experience building core infrastructure, protocol tooling, and privacy-preserving distributed systems. A serial entrepreneur, he has founded and scaled multiple successful ventures across the crypto industry. Previously, Viktor scaled Boosty Labs into the leading European Web3 development house, growing the team to 150+ engineers and partnering with major industry players including Coinbase, Ledger, Consensys, MoonPay, and Blockchain.com. Earlier in his career, he joined Storj Labs to help build decentralized cloud infrastructure, where he led the Growth team. He was responsible for expanding the distributed node network and shipping operator-facing tools that improved usability and long-term sustainability. Following this period of growth and infrastructure maturation, Storj achieved a successful exit after its acquisition. In parallel with these ventures, Viktor co-founded Astroid to support early BTCFi teams, helped launch the RGB Association, and contributed to Thunderstack—the primary infrastructure provider for RGB—built in collaboration with Tether and Fulgur. Across his work, Viktor focuses on expanding Bitcoin's utility and driving real-world adoption through scalable, privacy-first financial applications. 

How should software engineering evolve for the age of AI? As organizations rush to weave GenAI and agentic AI into every product and workflow, engineering teams face a new reality: you can't scale AI without redesigning how software gets built.   In this episode, Gartner experts Manjunath Bhat, Akis Sklavounakis and Shameen Pillai break down what that redesign actually looks like. They'll explore the team structures that help scale GenAI to repeatable delivery, the platform patterns that reduce cognitive load and drive value, and the API strategies that AI implementation can't function without.   You'll learn: Why GenAI efforts fail without the right team structures How platform engineering reduces complexity and accelerates delivery Why APIs are the backbone of GenAI and agentic AI The five‑dimension API maturity model and where to focus first The tools and next steps to scale AI safely and effectively   Dig deeper: Learn more with Gartner for Software Engineering Leaders See why Gartner is the world authority on AI Become a client to try AskGartner

Our congrats to Akshay Bhatia for notching his third PGA Tour win at Bay Hill. Dan and Jordan are back to discuss his playoff win and how an entertaining Sunday at the API unfolded when it did not look likely too.We discuss Jordan Spieth and his continual progression along with what we thought he did unexpectedly well.Enjoy!

Join Kyle, Nader, Vibhu, and swyx live at NVIDIA GTC next week!Now that AIE Europe tix are ~sold out, our attention turns to Miami and World's Fair!The definitive AI Accelerator chip company has more than 10xed this AI Summer:And is now a $4.4 trillion megacorp… that is somehow still moving like a startup. We are blessed to have a unique relationship with our first ever NVIDIA guests: Kyle Kranen who gave a great inference keynote at the first World's Fair and is one of the leading architects of NVIDIA Dynamo (a Datacenter scale inference framework supporting SGLang, TRT-LLM, vLLM), and Nader Khalil, a friend of swyx from our days in Celo in The Arena, who has been drawing developers at GTC since before they were even a glimmer in the eye of NVIDIA:Nader discusses how NVIDIA Brev has drastically reduced the barriers to entry for developers to get a top of the line GPU up and running, and Kyle explains NVIDIA Dynamo as a data center scale inference engine that optimizes serving by scaling out, leveraging techniques like prefill/decode disaggregation, scheduling, and Kubernetes-based orchestration, framed around cost, latency, and quality tradeoffs. We also dive into Jensen's “SOL” (Speed of Light) first-principles urgency concept, long-context limits and model/hardware co-design, internal model APIs (https://build.nvidia.com), and upcoming Dynamo and agent sessions at GTC.Full Video pod on YouTubeTimestamps00:00 Agent Security Basics00:39 Podcast Welcome and Guests07:19 Acquisition and DevEx Shift13:48 SOL Culture and Dynamo Setup27:38 Why Scale Out Wins29:02 Scale Up Limits Explained30:24 From Laptop to Multi Node33:07 Cost Quality Latency Tradeoffs38:42 Disaggregation Prefill vs Decode41:05 Kubernetes Scaling with Grove43:20 Context Length and Co Design57:34 Security Meets Agents58:01 Agent Permissions Model59:10 Build Nvidia Inference Gateway01:01:52 Hackathons And Autonomy Dreams01:10:26 Local GPUs And Scaling Inference01:15:31 Long Running Agents And SF ReflectionsTranscriptAgent Security BasicsNader: Agents can do three things. They can access your files, they can access the internet, and then now they can write custom code and execute it. You literally only let an agent do two of those three things. If you can access your files and you can write custom code, you don't want internet access because that's one to see full vulnerability, right?If you have access to internet and your file system, you should know the full scope of what that agent's capable of doing. Otherwise, now we can get injected or something that can happen. And so that's a lot of what we've been thinking about is like, you know, how do we both enable this because it's clearly the future.But then also, you know, what, what are these enforcement points that we can start to like protect?swyx: All right.Podcast Welcome and Guestsswyx: Welcome to the Lean Space podcast in the Chromo studio. Welcome to all the guests here. Uh, we are back with our guest host Viu. Welcome. Good to have you back. And our friends, uh, Netter and Kyle from Nvidia. Welcome.Kyle: Yeah, thanks for having us.swyx: Yeah, thank you. Actually, I don't even know your titles.Uh, I know you're like architect something of Dynamo.Kyle: Yeah. I, I'm one of the engineering leaders [00:01:00] and a architects of Dynamo.swyx: And you're director of something and developers, developer tech.Nader: Yeah.swyx: You're the developers, developers, developers guy at nvidia,Nader: open source agent marketing, brev,swyx: and likeNader: Devrel tools and stuff.swyx: Yeah. BeenNader: the focus.swyx: And we're, we're kind of recording this ahead of Nvidia, GTC, which is coming to town, uh, again, uh, or taking over town, uh, which, uh, which we'll all be at. Um, and we'll talk a little bit about your sessions and stuff. Yeah.Nader: We're super excited for it.GTC Booth Stunt Storiesswyx: One of my favorite memories for Nader, like you always do like marketing stunts and like while you were at Rev, you like had this surfboard that you like, went down to GTC with and like, NA Nvidia apparently, like did so much that they bought you.Like what, what was that like? What was that?Nader: Yeah. Yeah, we, we, um. Our logo was a chaka. We, we, uh, we were always just kind of like trying to keep true to who we were. I think, you know, some stuff, startups, you're like trying to pretend that you're a bigger, more mature company than you are. And it was actually Evan Conrad from SF Compute who was just like, you guys are like previousswyx: guest.Yeah.Nader: Amazing. Oh, really? Amazing. Yeah. He was just like, guys, you're two dudes in the room. Why are you [00:02:00] pretending that you're not? Uh, and so then we were like, okay, let's make the logo a shaka. We brought surfboards to our booth to GTC and the energy was great. Yeah. Some palm trees too. They,Kyle: they actually poked out over like the, the walls so you could, you could see the bread booth.Oh, that's so funny. AndNader: no one else,Kyle: just from very far away.Nader: Oh, so you remember it backKyle: then? Yeah I remember it pre-acquisition. I was like, oh, those guys look cool,Nader: dude. That makes sense. ‘cause uh, we, so we signed up really last minute, and so we had the last booth. It was all the way in the corner. And so I was, I was worried that no one was gonna come.So that's why we had like the palm trees. We really came in with the surfboards. We even had one of our investors bring her dog and then she was just like walking the dog around to try to like, bring energy towards our booth. Yeah.swyx: Steph.Kyle: Yeah. Yeah, she's the best,swyx: you know, as a conference organizer, I love that.Right? Like, it's like everyone who sponsors a conference comes, does their booth. They're like, we are changing the future of ai or something, some generic b******t and like, no, like actually try to stand out, make it fun, right? And people still remember it after three years.Nader: Yeah. Yeah. You know what's so funny?I'll, I'll send, I'll give you this clip if you wanna, if you wanna add it [00:03:00] in, but, uh, my wife was at the time fiance, she was in medical school and she came to help us. ‘cause it was like a big moment for us. And so we, we bought this cricket, it's like a vinyl, like a vinyl, uh, printer. ‘cause like, how else are we gonna label the surfboard?So, we got a surfboard, luckily was able to purchase that on the company card. We got a cricket and it was just like fine tuning for enterprises or something like that, that we put on the. On the surfboard and it's 1:00 AM the day before we go to GTC. She's helping me put these like vinyl stickers on.And she goes, you son of, she's like, if you pull this off, you son of a b***h. And so, uh, right. Pretty much after the acquisition, I stitched that with the mag music acquisition. I sent it to our family group chat. Ohswyx: Yeah. No, well, she, she made a good choice there. Was that like basically the origin story for Launchable is that we, it was, and maybe we should explain what Brev is andNader: Yeah.Yeah. Uh, I mean, brev is just, it's a developer tool that makes it really easy to get a GPU. So we connect a bunch of different GPU sources. So the basics of it is like, how quickly can we SSH you into a G, into a GPU and whenever we would talk to users, they wanted A GPU. They wanted an A 100. And if you go to like any cloud [00:04:00] provisioning page, usually it's like three pages of forms or in the forms somewhere there's a dropdown.And in the dropdown there's some weird code that you know to translate to an A 100. And I remember just thinking like. Every time someone says they want an A 100, like the piece of text that they're telling me that they want is like, stuffed away in the corner. Yeah. And so we were like, what if the biggest piece of text was what the user's asking for?And so when you go to Brev, it's just big GPU chips with the type that you want withswyx: beautiful animations that you worked on pre, like pre you can, like, now you can just prompt it. But back in the day. Yeah. Yeah. Those were handcraft, handcrafted artisanal code.Nader: Yeah. I was actually really proud of that because, uh, it was an, i I made it in Figma.Yeah. And then I found, I was like really struggling to figure out how to turn it from like Figma to react. So what it actually is, is just an SVG and I, I have all the styles and so when you change the chip, whether it's like active or not it changes the SVG code and that somehow like renders like, looks like it's animating, but it, we just had the transition slow, but it's just like the, a JavaScript function to change the like underlying SVG.Yeah. And that was how I ended up like figuring out how to move it from from Figma. But yeah, that's Art Artisan. [00:05:00]Kyle: Speaking of marketing stunts though, he actually used those SVGs. Or kind of use those SVGs to make these cards.Nader: Oh yeah. LikeKyle: a GPU gift card Yes. That he handed out everywhere. That was actually my first impression of thatNader: one.Yeah,swyx: yeah, yeah.Nader: Yeah.swyx: I think I still have one of them.Nader: They look great.Kyle: Yeah.Nader: I have a ton of them still actually in our garage, which just, they don't have labels. We should honestly like bring, bring them back. But, um, I found this old printing press here, actually just around the corner on Ven ness. And it's a third generation San Francisco shop.And so I come in an excited startup founder trying to like, and they just have this crazy old machinery and I'm in awe. ‘cause the the whole building is so physical. Like you're seeing these machines, they have like pedals to like move these saws and whatever. I don't know what this machinery is, but I saw all three generations.Like there's like the grandpa, the father and the son, and the son was like, around my age. Well,swyx: it's like a holy, holy trinity.Nader: It's funny because we, so I just took the same SVG and we just like printed it and it's foil printing, so they make a a, a mold. That's like an inverse of like the A 100 and then they put the foil on it [00:06:00] and then they press it into the paper.And I remember once we got them, he was like, Hey, don't forget about us. You know, I guess like early Apple and Cisco's first business cards were all made there. And so he was like, yeah, we, we get like the startup businesses but then as they mature, they kind of go somewhere else. And so I actually, I think we were talking with marketing about like using them for some, we should go back and make some cards.swyx: Yeah, yeah, yeah. You know, I remember, you know, as a very, very small breadth investor, I was like, why are we spending time like, doing these like stunts for GPUs? Like, you know, I think like as a, you know, typical like cloud hard hardware person, you go into an AWS you pick like T five X xl, whatever, and it's just like from a list and you look at the specs like, why animate this GP?And, and I, I do think like it just shows the level of care that goes throughout birth and Yeah. And now, and also the, and,Nader: and Nvidia. I think that's what the, the thing that struck me most when we first came in was like the amount of passion that everyone has. Like, I think, um, you know, you talk to, you talk to Kyle, you talk to, like, every VP that I've met at Nvidia goes so close to the metal.Like, I remember it was almost a year ago, and like my VP asked me, he's like, Hey, [00:07:00] what's cursor? And like, are you using it? And if so, why? Surprised at this, and he downloaded Cursor and he was asking me to help him like, use it. And I thought that was, uh, or like, just show him what he, you know, why we were using it.And so, the amount of care that I think everyone has and the passion, appreciate, passion and appreciation for the moment. Right. This is a very unique time. So it's really cool to see everyone really like, uh, appreciate that.swyx: Yeah.Acquisition and DevEx Shiftswyx: One thing I wanted to do before we move over to sort of like research topics and, uh, the, the stuff that Kyle's working on is just tell the story of the acquisition, right?Like, not many people have been, been through an acquisition with Nvidia. What's it like? Uh, what, yeah, just anything you'd like to say.Nader: It's a crazy experience. I think, uh, you know, we were the thing that was the most exciting for us was. Our goal was just to make it easier for developers.We wanted to find access to GPUs, make it easier to do that. And then all, oh, actually your question about launchable. So launchable was just make one click exper, like one click deploys for any software on top of the GPU. Mm-hmm. And so what we really liked about Nvidia was that it felt like we just got a lot more resources to do all of that.I think, uh, you [00:08:00] know, NVIDIA's goal is to make things as easy for developers as possible. So there was a really nice like synergy there. I think that, you know, when it comes to like an acquisition, I think the amount that the soul of the products align, I think is gonna be. Is going speak to the success of the acquisition.Yeah. And so it in many ways feels like we're home. This is a really great outcome for us. Like we you know, I love brev.nvidia.com. Like you should, you should use it's, it's theKyle: front page for GPUs.Nader: Yeah. Yeah. If you want GP views,Kyle: you go there, getswyx: it there, and it's like internally is growing very quickly.I, I don't remember You said some stats there.Nader: Yeah, yeah, yeah. It's, uh, I, I wish I had the exact numbers, but like internally, externally, it's been growing really quickly. We've been working with a bunch of partners with a bunch of different customers and ISVs, if you have a solution that you want someone that runs on the GPU and you want people to use it quickly, we can bundle it up, uh, in a launchable and make it a one click run.If you're doing things and you want just like a sandbox or something to run on, right. Like open claw. Huge moment. Super exciting. Our, uh, and we'll talk into it more, but. You know, internally, people wanna run this, and you, we know we have to be really careful from the security implications. Do we let this run on the corporate network?Security's guidance was, Hey, [00:09:00] run this on breath, it's in, you know, it's, it's, it's a vm, it's sitting in the cloud, it's off the corporate network. It's isolated. And so that's been our stance internally and externally about how to even run something like open call while we figure out how to run these things securely.But yeah,swyx: I think there's also like, you almost like we're the right team at the right time when Nvidia is starting to invest a lot more in developer experience or whatever you call it. Yeah. Uh, UX or I don't know what you call it, like software. Like obviously NVIDIA is always invested in software, but like, there's like, this is like a different audience.Yeah. It's aNader: widerKyle: developer base.swyx: Yeah. Right.Nader: Yeah. Yeah. You know, it's funny, it's like, it's not, uh,swyx: so like, what, what is it called internally? What, what is this that people should be aware that is going on there?Nader: Uh, what, like developer experienceswyx: or, yeah, yeah. Is it's called just developer experience or is there like a broader strategy hereNader: in Nvidia?Um, Nvidia always wants to make a good developer experience. The thing is and a lot of the technology is just really complicated. Like, it's not, it's uh, you know, I think, um. The thing that's been really growing or the AI's growing is having a huge moment, not [00:10:00] because like, let's say data scientists in 2018, were quiet then and are much louder now.The pie is com, right? There's a whole bunch of new audiences. My mom's wondering what she's doing. My sister's learned, like taught herself how to code. Like the, um, you know, I, I actually think just generally AI's a big equalizer and you're seeing a more like technologically literate society, I guess.Like everyone's, everyone's learning how to code. Uh, there isn't really an excuse for that. And so building a good UX means that you really understand who your end user is. And when your end user becomes such a wide, uh, variety of people, then you have to almost like reinvent the practice, right? Yeah. You haveKyle: to, and actually build more developer ux, right?Because the, there are tiers of developer base that were added. You know, the, the hackers that are building on top of open claw, right? For example, have never used gpu. They don't know what kuda is. They, they, they just want to run something.Nader: Yeah.Kyle: You need new UX that is not just. Hey, you know, how do you program something in Cuda and run it?And then, and then we built, you know, like when Deep Learning was getting big, we built, we built Torch and, and, but so recently the amount of like [00:11:00] layers that are added to that developer stack has just exploded because AI has become ubiquitous. Everyone's using it in different ways. Yeah. It'sNader: moving fast in every direction.Vertical, horizontal.Vibhu: Yeah. You guys, you even take it down to hardware, like the DGX Spark, you know, it's, it's basically the same system as just throwing it up on big GPU cluster.Nader: Yeah, yeah, yeah. It's amazing. Blackwell.swyx: Yeah. Uh, we saw the preview at the last year's GTC and that was one of the better performing, uh, videos so far, and video coverage so far.Awesome. This will beat it. Um,Nader: that wasswyx: actually, we have fingersNader: crossed. Yeah.DGX Spark and Remote AccessNader: Even when Grace Blackwell or when, um, uh, DGX Spark was first coming out getting to be involved in that from the beginning of the developer experience. And it just comes back to what youswyx: were involved.Nader: Yeah. St. St.swyx: Mars.Nader: Yeah. Yeah. I mean from, it was just like, I, I got an email, we just got thrown into the loop and suddenly yeah, I, it was actually really funny ‘cause I'm still pretty fresh from the acquisition and I'm, I'm getting an email from a bunch of the engineering VPs about like, the new hardware, GPU chip, like we're, or not chip, but just GPU system that we're putting out.And I'm like, okay, cool. Matters. Now involved with this for the ux, I'm like. What am I gonna do [00:12:00] here? So, I remember the first meeting, I was just like kind of quiet as I was hearing engineering VPs talk about what this box could be, what it could do, how we should use it. And I remember, uh, one of the first ideas that people were idea was like, oh, the first thing that it was like, I think a quote was like, the first thing someone's gonna wanna do with this is get two of them and run a Kubernetes cluster on top of them.And I was like, oh, I think I know why I'm here. I was like, the first thing we're doing is easy. SSH into the machine. And then, and you know, just kind of like scoping it down of like, once you can do that every, you, like the person who wants to run a Kubernetes cluster onto Sparks has a higher propensity for pain, then, then you know someone who buys it and wants to run open Claw right now, right?If you can make sure that that's as effortless as possible, then the rest becomes easy. So there's a tool called Nvidia Sync. It just makes the SSH connection really simple. So, you know, if you think about it like. If you have a Mac, uh, or a PC or whatever, if you have a laptop and you buy this GPU and you want to use it, you should be able to use it like it's A-A-G-P-U in the cloud, right?Um, but there's all this friction of like, how do you actually get into that? That's part of [00:13:00] Revs value proposition is just, you know, there's a CLI that wraps SSH and makes it simple. And so our goal is just get you into that machine really easily. And one thing we just launched at CES, it's in, it's still in like early access.We're ironing out some kinks, but it should be ready by GTC. You can register your spark on Brev. And so now if youswyx: like remote managed yeah, local hardware. Single pane of glass. Yeah. Yeah. Because Brev can already manage other clouds anyway, right?Vibhu: Yeah, yeah. And you use the spark on Brev as well, right?Nader: Yeah. But yeah, exactly. So, so you, you, so you, you set it up at home you can run the command on it, and then it gets it's essentially it'll appear in your Brev account, and then you can take your laptop to a Starbucks or to a cafe, and you'll continue to use your, you can continue use your spark just like any other cloud node on Brev.Yeah. Yeah. And it's just like a pre-provisioned centerswyx: in yourNader: home. Yeah, exactly.swyx: Yeah. Yeah.Vibhu: Tiny little data center.Nader: Tiny little, the size ofVibhu: your phone.SOL Culture and Dynamo Setupswyx: One more thing before we move on to Kyle. Just have so many Jensen stories and I just love, love mining Jensen stories. Uh, my favorite so far is SOL. Uh, what is, yeah, what is S-O-L-S-O-LNader: is actually, i, I think [00:14:00] of all the lessons I've learned, that one's definitely my favorite.Kyle: It'll always stick with you.Nader: Yeah. Yeah. I, you know, in your startup, everything's existential, right? Like we've, we've run out of money. We were like, on the risk of, of losing payroll, we've had to contract our team because we l ran outta money. And so like, um, because of that you're really always forcing yourself to I to like understand the root cause of everything.If you get a date, if you get a timeline, you know exactly why that date or timeline is there. You're, you're pushing every boundary and like, you're not just say, you're not just accepting like a, a no. Just because. And so as you start to introduce more layers, as you start to become a much larger organization, SOL is is essentially like what is the physics, right?The speed of light moves at a certain speed. So if flight's moving some slower, then you know something's in the way. So before trying to like layer reality back in of like, why can't this be delivered at some date? Let's just understand the physics. What is the theoretical limit to like, uh, how fast this can go?And then start to tell me why. ‘cause otherwise people will start telling you why something can't be done. But actually I think any great leader's goal is just to create urgency. Yeah. [00:15:00] There's an infiniteKyle: create compelling events, right?Nader: Yeah.Kyle: Yeah. So l is a term video is used to instigate a compelling event.You say this is done. How do we get there? What is the minimum? As much as necessary, as little as possible thing that it takes for us to get exactly here and. It helps you just break through a bunch of noise.swyx: Yeah.Kyle: Instantly.swyx: One thing I'm unclear about is, can only Jensen use the SOL card? Like, oh, no, no, no.Not everyone get the b******t out because obviously it's Jensen, but like, can someone else be like, no, likeKyle: frontline engineers use it.Nader: Yeah. Every, I think it's not so much about like, get the b******t out. It's like, it's like, give me the root understanding, right? Like, if you tell me something takes three weeks, it like, well, what's the first principles?Yeah, the first principles. It's like, what's the, what? Like why is it three weeks? What is the actual yeah. What's the actual limit of why this is gonna take three weeks? If you're gonna, if you, if let's say you wanted to buy a new computer and someone told you it's gonna be here in five days, what's the SOL?Well, like the SOL is like, I could walk into a Best Buy and pick it up for you. Right? So then anything that's like beyond that is, and is that practical? Is that how we're gonna, you know, let's say give everyone in the [00:16:00] company a laptop, like obviously not. So then like that's the SOL and then it's like, okay, well if we have to get more than 10, suddenly there might be some, right?And so now we can kind of piece the reality back.swyx: So, so this is the. Paul Graham do things that don't scale. Yeah. And this is also the, what people would now call behi agency. Yeah.Kyle: It's actually really interesting because there's a, there's a second hardware angle to SOL that like doesn't come up for all the org sol is used like culturally at aswyx: media for everything.I'm also mining for like, I think that can be annoying sometimes. And like someone keeps going IOO you and you're like, guys, like we have to be stable. We have to, we to f*****g plan. Yeah.Kyle: It's an interesting balance.Nader: Yeah. I encounter that with like, actually just with, with Alec, right? ‘cause we, we have a new conference so we need to launch, we have, we have goals of what we wanna launch by, uh, by the conference and like, yeah.At the end of the day, where isswyx: this GTC?Nader: Um, well this is like, so we, I mean we did it for CES, we did for GT CDC before that we're doing it for GTC San Jose. So I mean, like every, you know, we have a new moment. Um, and we want to launch something. Yeah. And we want to do so at SOL and that does mean that some, there's some level of prioritization that needs [00:17:00] to happen.And so it, it is difficult, right? I think, um, you have to be careful with what you're pushing. You know, stability is important and that should be factored into S-O-L-S-O-L isn't just like, build everything and let it break, you know, that, that's part of the conversation. So as you're laying, layering in all the details, one of them might be, Hey, we could build this, but then it's not gonna be stable for X, y, z reasons.And so that was like, one of our conversations for CES was, you know, hey, like we, we can get this into early access registering your spark with brev. But there are a lot of things that we need to do in order to feel really comfortable from a security perspective, right? There's a lot of networking involved before we deliver that to users.So it's like, okay. Let's get this to a point where we can at least let people experiment with it. We had it in a booth, we had it in Jensen's keynote, and then let's go iron out all the networking kinks. And that's not easy. And so, uh, that can come later. And so that was the way that we layered that back in.Yeah. ButKyle: It's not really about saying like, you don't have to do the, the maintenance or operational work. It's more about saying, you know, it's kind of like [00:18:00] highlights how progress is incremental, right? Like, what is the minimum thing that we can get to. And then there's SOL for like every component after that.But there's the SOL to get you, get you to the, the starting line. And that, that's usually how it's asked. Yeah. On the other side, you know, like SOL came out of like hardware at Nvidia. Right. So SOL is like literally if we ran the accelerator or the GPU with like at basically full speed with like no other constraints, like how FAST would be able to make a program go.swyx: Yeah. Yeah. Right.Kyle: Soswyx: in, in training that like, you know, then you work back to like some percentage of like MFU for example.Kyle: Yeah, that's a, that's a great example. So like, there's an, there's an S-O-L-M-F-U, and then there's like, you know, what's practically achievable.swyx: Cool. Should we move on to sort of, uh, Kyle's side?Uh, Kyle, you're coming more from the data science world. And, uh, I, I mean I always, whenever, whenever I meet someone who's done working in tabular stuff, graph neural networks, time series, these are basically when I go to new reps, I go to ICML, I walk the back halls. There's always like a small group of graph people.Yes. Absolute small group of tabular people. [00:19:00] And like, there's no one there. And like, it's very like, you know what I mean? Like, yeah, no, like it's, it's important interesting work if you care about solving the problems that they solve.Kyle: Yeah.swyx: But everyone else is just LMS all the time.Kyle: Yeah. I mean it's like, it's like the black hole, right?Has the event horizon reached this yet in nerves? Um,swyx: but like, you know, those are, those are transformers too. Yeah. And, and those are also like interesting things. Anyway, uh, I just wanted to spend a little bit of time on, on those, that background before we go into Dynamo, uh, proper.Kyle: Yeah, sure. I took a different path to Nvidia than that, or I joined six years ago, seven, if you count, when I was an intern.So I joined Nvidia, like right outta college. And the first thing I jumped into was not what I'd done in, during internship, which was like, you know, like some stuff for autonomous vehicles, like heavyweight object detection. I jumped into like, you know, something, I'm like, recommenders, this is popular. Andswyx: yeah, he did RexiKyle: as well.Yeah, Rexi. Yeah. I mean that, that was the taboo data at the time, right? You have tables of like, audience qualities and item qualities, and you're trying to figure out like which member of [00:20:00] the audience matches which item or, or more practically which item matches which member of the audience. And at the time, really it was like we were trying to enable.Uh, recommender, which had historically been like a little bit of a CP based workflow into something that like, ran really well in GPUs. And it's since been done. Like there are a bunch of libraries for Axis that run on GPUs. Uh, the common models like Deeplearning recommendation model, which came outta meta and the wide and deep model, which was used or was released by Google were very accelerated by GPUs using, you know, the fast HBM on the chips, especially to do, you know, vector lookups.But it was very interesting at the time and super, super relevant because like we were starting to get like. This explosion of feeds and things that required rec recommenders to just actively be on all the time. And sort of transitioned that a little bit towards graph neural networks when I discovered them because I was like, okay, you can actually use graphical neural networks to represent like, relationships between people, items, concepts, and that, that interested me.So I jumped into that at [00:21:00] Nvidia and, and got really involved for like two-ish years.swyx: Yeah. Uh, and something I learned from Brian Zaro Yeah. Is that you can just kind of choose your own path in Nvidia.Kyle: Oh my God. Yeah.swyx: Which is not a normal big Corp thing. Yeah. Like you, you have a lane, you stay in your lane.Nader: I think probably the reason why I enjoy being in a, a big company, the mission is the boss probably from a startup guy. Yeah. The missionswyx: is the boss.Nader: Yeah. Uh, it feels like a big game of pickup basketball. Like, you know, if you play one, if you wanna play basketball, you just go up to the court and you're like, Hey look, we're gonna play this game and we need three.Yeah. And you just like find your three. That's honestly for every new initiative that's what it feels like. Yeah.Vibhu: It also like shows, right? Like Nvidia. Just releasing state-of-the-art stuff in every domain. Yeah. Like, okay, you expect foundation models with Nemo tron voice just randomly parakeet.Call parakeet just comes out another one, uh, voice. TheKyle: video voice team has always been producing.Vibhu: Yeah. There's always just every other domain of paper that comes out, dataset that comes out. It's like, I mean, it also stems back to what Nvidia has to do, right? You have to make chips years before they're actually produced.Right? So you need to know, you need to really [00:22:00] focus. TheKyle: design process starts likeVibhu: exactlyKyle: three to five years before the chip gets to the market.Vibhu: Yeah. I, I'm curious more about what that's like, right? So like, you have specialist teams. Is it just like, you know, people find an interest, you go in, you go deep on whatever, and that kind of feeds back into, you know, okay, we, we expect predictions.Like the internals at Nvidia must be crazy. Right? You know? Yeah. Yeah. You know, you, you must. Not even without selling to people, you have your own predictions of where things are going. Yeah. And they're very based, very grounded. Right?Kyle: Yeah. It, it, it's really interesting. So there's like two things that I think that Amed does, which are quite interesting.Uh, one is like, we really index into passion. There's a big. Sort of organizational top sound push to like ensure that people are working on the things that they're passionate about. So if someone proposes something that's interesting, many times they can just email someone like way up the chain that they would find this relevant and say like, Hey, can I go work on this?Nader: It's actually like I worked at a, a big company for a couple years before, uh, starting on my startup journey and like, it felt very weird if you were to like email out of chain, if that makes [00:23:00] sense. Yeah. The emails at Nvidia are like mosh pitsswyx: shoot,Nader: and it's just like 60 people, just whatever. And like they're, there's this,swyx: they got messy like, reply all you,Nader: oh, it's in, it's insane.It's insane. They justKyle: help. You know, Maxim,Nader: the context. But, but that's actually like, I've actually, so this is a weird thing where I used to be like, why would we send emails? We have Slack. I am the entire, I'm the exact opposite. I feel so bad for anyone who's like messaging me on Slack ‘cause I'm so unresponsive.swyx: Your emailNader: Maxi, email Maxim. I'm email maxing Now email is a different, email is perfect because man, we can't work together. I'm email is great, right? Because important threads get bumped back up, right? Yeah, yeah. Um, and so Slack doesn't do that. So I just have like this casino going off on the right or on the left and like, I don't know which thread was from where or what, but like the threads get And then also just like the subject, so you can have like working threads.I think what's difficult is like when you're small, if you're just not 40,000 people I think Slack will work fine, but there's, I don't know what the inflection point is. There is gonna be a point where that becomes really messy and you'll actually prefer having email. ‘cause you can have working threads.You can cc more than nine people in a thread.Kyle: You can fork stuff.Nader: You can [00:24:00] fork stuff, which is super nice and just like y Yeah. And so, but that is part of where you can propose a plan. You can also just. Start, honestly, momentum's the only authority, right? So like, if you can just start, start to make a little bit of progress and show someone something, and then they can try it.That's, I think what's been, you know, I think the most effective way to push anything for forward. And that's both at Nvidia and I think just generally.Kyle: Yeah, there's, there's the other concept that like is explored a lot at Nvidia, which is this idea of a zero billion dollar business. Like market creation is a big thing at Nvidia.Like,swyx: oh, you want to go and start a zero billion dollar business?Kyle: Jensen says, we are completely happy investing in zero billion dollar markets. We don't care if this creates revenue. It's important for us to know about this market. We think it will be important in the future. It can be zero billion dollars for a while.I'm probably minging as words here for, but like, you know, like, I'll give an example. NVIDIA's been working on autonomous driving for a a long time,swyx: like an Nvidia car.Kyle: No, they, they'veVibhu: used the Mercedes, right? They're around the HQ and I think it finally just got licensed out. Now they're starting to be used quite a [00:25:00] bit.For 10 years you've been seeing Mercedes with Nvidia logos driving.Kyle: If you're in like the South San Santa Clara, it's, it's actually from South. Yeah. So, um. Zero billion dollar markets are, are a thing like, you know, Jensen,swyx: I mean, okay, look, cars are not a zero billion dollar market. But yeah, that's a bad example.Nader: I think, I think he's, he's messaging, uh, zero today, but, or even like internally, right? Like, like it's like, uh, an org doesn't have to ruthlessly find revenue very quickly to justify their existence. Right. Like a lot of the important research, a lot of the important technology being developed that, that's kind ofKyle: where research, research is very ide ideologically free at Nvidia.Yeah. Like they can pursue things that they wereswyx: Were you research officially?Kyle: I was never in research. Officially. I was always in engineering. Yeah. We in, I'm in an org called Deep Warning Algorithms, which is basically just how do we make things that are relevant to deep warning go fast.swyx: That sounds freaking cool.Vibhu: And I think a lot of that is underappreciated, right? Like time series. This week Google put out time. FF paper. Yeah. A new time series, paper res. Uh, Symantec, ID [00:26:00] started applying Transformers LMS to Yes. Rec system. Yes. And when you think the scale of companies deploying these right. Amazon recommendations, Google web search, it's like, it's huge scale andKyle: Yeah.Vibhu: You want fast?Kyle: Yeah. Yeah. Yeah. Actually it's, it, I, there's a fun moment that brought me like full circle. Like, uh, Amazon Ads recently gave a talk where they talked about using Dynamo for generative recommendation, which was like super, like weirdly cathartic for me. I'm like, oh my God. I've, I've supplanted what I was working on.Like, I, you're using LMS now to do what I was doing five years ago.swyx: Yeah. Amazing. And let's go right into Dynamo. Uh, maybe introduce Yeah, sure. To the top down and Yeah.Kyle: I think at this point a lot of people are familiar with the term of inference. Like funnily enough, like I went from, you know, inference being like a really niche topic to being something that's like discussed on like normal people's Twitter feeds.It's,Nader: it's on billboardsKyle: here now. Yeah. Very, very strange. Driving, driving, seeing just an inference ad on 1 0 1 inference at scale is becoming a lot more important. Uh, we have these moments like, you know, open claw where you have these [00:27:00] agents that take lots and lots of tokens, but produce, incredible results.There are many different aspects of test time scaling so that, you know, you can use more inference to generate a better result than if you were to use like a short amount of inference. There's reasoning, there's quiring, there's, adding agency to the model, allowing it to call tools and use skills.Dyno sort came about at Nvidia. Because myself and a couple others were, were sort of talking about the, these concepts that like, you know, you have inference engines like VLMS, shelan, tenor, TLM and they have like one single copy. They, they, they sort of think about like things as like one single copy, like one replica, right?Why Scale Out WinsKyle: Like one version of the model. But when you're actually serving things at scale, you can't just scale up that replica because you end up with like performance problems. There's a scaling limit to scaling up replicas. So you actually have to scale out to use a, maybe some Kubernetes type terminology.We kind of realized that there was like. A lot of potential optimization that we could do in scaling out and building systems for data [00:28:00] center scale inference. So Dynamo is this data center scale inference engine that sits on top of the frameworks like VLM Shilling and 10 T lm and just makes things go faster because you can leverage the economy of scale.The fact that you have KV cash, which we can define a little bit later, uh, in all these machines that is like unique and you wanna figure out like the ways to maximize your cash hits or you want to employ new techniques in inference like disaggregation, which Dynamo had introduced to the world in, in, in March, not introduced, it was a academic talk, but beforehand.But we are, you know, one of the first frameworks to start, supporting it. And we wanna like, sort of combine all these techniques into sort of a modular framework that allows you to. Accelerate your inference at scale.Nader: By the way, Kyle and I became friends on my first date, Nvidia, and I always loved, ‘cause like he always teaches meswyx: new things.Yeah. By the way, this is why I wanted to put two of you together. I was like, yeah, this is, this is gonna beKyle: good. It's very, it's very different, you know, like we've, we, we've, we've talked to each other a bunch [00:29:00] actually, you asked like, why, why can't we scale up?Nader: Yeah.Scale Up Limits ExplainedNader: model, you said model replicas.Kyle: Yeah. So you, so scale up means assigning moreswyx: heavier?Kyle: Yeah, heavier. Like making things heavier. Yeah, adding more GPUs. Adding more CPUs. Scale out is just like having a barrier saying, I'm gonna duplicate my representation of the model or a representation of this microservice or something, and I'm gonna like, replicate it Many times.Handle, load. And the reason that you can't scale, scale up, uh, past some points is like, you know, there, there, there are sort of hardware bounds and algorithmic bounds on, on that type of scaling. So I'll give you a good example that's like very trivial. Let's say you're on an H 100. The Maxim ENV link domain for H 100, for most Ds H one hundreds is heus, right?So if you scaled up past that, you're gonna have to figure out ways to handle the fact that now for the GPUs to communicate, you have to do it over Infin band, which is still very fast, but is not as fast as ENV link.swyx: Is it like one order of magnitude, like hundreds or,Kyle: it's about an order of magnitude?Yeah. Okay. Um, soswyx: not terrible.Kyle: [00:30:00] Yeah. I, I need to, I need to remember the, the data sheet here, like, I think it's like about 500 gigabytes. Uh, a second unidirectional for ENV link, and about 50 gigabytes a second unidirectional for Infin Band. I, it, it depends on the, the generation.swyx: I just wanna set this up for people who are not familiar with these kinds of like layers and the trash speedVibhu: and all that.Of course.From Laptop to Multi NodeVibhu: Also, maybe even just going like a few steps back before that, like most people are very familiar with. You see a, you know, you can use on your laptop, whatever these steel viol, lm you can just run inference there. All, there's all, you can, youcan run it on thatVibhu: laptop. You can run on laptop.Then you get to, okay, uh, models got pretty big, right? JLM five, they doubled the size, so mm-hmm. Uh, what do you do when you have to go from, okay, I can get 128 gigs of memory. I can run it on a spark. Then you have to go multi GPU. Yeah. Okay. Multi GPU, there's some support there. Now, if I'm a company and I don't have like.I'm not hiring the best researchers for this. Right. But I need to go [00:31:00] multi-node, right? I have a lot of servers. Okay, now there's efficiency problems, right? You can have multiple eight H 100 nodes, but, you know, is that as a, like, how do you do that efficiently?Kyle: Yeah. How do you like represent them? How do you choose how to represent the model?Yeah, exactly right. That's a, that's like a hard question. Everyone asks, how do you size oh, I wanna run GLM five, which just came out new model. There have been like four of them in the past week, by the way, like a bunch of new models.swyx: You know why? Right? Deep seek.Kyle: No comment. Oh. Yeah, but Ggl, LM five, right?We, we have this, new model. It's, it's like a large size, and you have to figure out how to both scale up and scale out, right? Because you have to find the right representation that you care about. Everyone does this differently. Let's be very clear. Everyone figures this out in their own path.Nader: I feel like a lot of AI or ML even is like, is like this. I think people think, you know, I, I was, there was some tweet a few months ago that was like, why hasn't fine tuning as a service taken off? You know, that might be me. It might have been you. Yeah. But people want it to be such an easy recipe to follow.But even like if you look at an ML model and specificKyle: to you Yeah,Nader: yeah.Kyle: And the [00:32:00] model,Nader: the situation, and there's just so much tinkering, right? Like when you see a model that has however many experts in the ME model, it's like, why that many experts? I don't, they, you know, they tried a bunch of things and that one seemed to do better.I think when it comes to how you're serving inference, you know, you have a bunch of decisions to make and there you can always argue that you can take something and make it more optimal. But I think it's this internal calibration and appetite for continued calibration.Vibhu: Yeah. And that doesn't mean like, you know, people aren't taking a shot at this, like tinker from thinking machines, you know?Yeah. RL as a service. Yeah, totally. It's, it also gets even harder when you try to do big model training, right? We're not the best at training Moes, uh, when they're pre-trained. Like we saw this with LAMA three, right? They're trained in such a sparse way that meta knows there's gonna be a bunch of inference done on these, right?They'll open source it, but it's very trained for what meta infrastructure wants, right? They wanna, they wanna inference it a lot. Now the question to basically think about is, okay, say you wanna serve a chat application, a coding copilot, right? You're doing a layer of rl, you're serving a model for X amount of people.Is it a chat model, a coding model? Dynamo, you know, back to that,Kyle: it's [00:33:00] like, yeah, sorry. So you we, we sort of like jumped off of, you know, jumped, uh, on that topic. Everyone has like, their own, own journey.Cost Quality Latency TradeoffsKyle: And I, I like to think of it as defined by like, what is the model you need? What is the accuracy you need?Actually I talked to NA about this earlier. There's three axes you care about. What is the quality that you're able to produce? So like, are you accurate enough or can you complete the task with enough, performance, high enough performance. Yeah, yeah. Uh, there's cost. Can you serve the model or serve your workflow?Because it's not just the model anymore, it's the workflow. It's the multi turn with an agent cheaply enough. And then can you serve it fast enough? And we're seeing all three of these, like, play out, like we saw, we saw new models from OpenAI that you know, are faster. You have like these new fast versions of models.You can change the amount of thinking to change the amount of quality, right? Produce more tokens, but at a higher cost in a, in a higher latency. And really like when you start this journey of like trying to figure out how you wanna host a model, you, you, you think about three things. What is the model I need to serve?How many times do I need to call it? What is the input sequence link was [00:34:00] the, what does the workflow look like on top of it? What is the SLA, what is the latency SLA that I need to achieve? Because there's usually some, this is usually like a constant, you, you know, the SLA that you need to hit and then like you try and find the lowest cost version that hits all of these constraints.Usually, you know, you, you start with those things and you say you, you kind of do like a bit of experimentation across some common configurations. You change the tensor parallel size, which is a form of parallelismVibhu: I take, it goes even deeper first. Gotta think what model.Kyle: Yes, course,ofKyle: course. It's like, it's like a multi-step design process because as you said, you can, you can choose a smaller model and then do more test time scaling and it'll equate the quality of a larger model because you're doing the test time scaling or you're adding a harness or something.So yes, it, it goes way deeper than that. But from the performance perspective, like once you get to the model you need, you need to host, you look at that and you say, Hey. I have this model, I need to serve it at the speed. What is the right configuration for that?Nader: You guys see the recent, uh, there was a paper I just saw like a few days ago that, uh, if you run [00:35:00] the same prompt twice, you're getting like double Just try itagain.Nader: Yeah, exactly.Vibhu: And you get a lot. Yeah. But the, the key thing there is you give the context of the failed try, right? Yeah. So it takes a shot. And this has been like, you know, basic guidance for quite a while. Just try again. ‘cause you know, trying, just try again. Did you try again? All adviceNader: in life.Vibhu: Just, it's a paper from Google, if I'm not mistaken, right?Yeah,Vibhu: yeah. I think it, it's like a seven bas little short paper. Yeah. Yeah. The title's very cute. And it's just like, yeah, just try again. Give it ask context,Kyle: multi-shot. You just like, say like, hey, like, you know, like take, take a little bit more, take a little bit more information, try and fail. Fail.Vibhu: And that basic concept has gone pretty deep.There's like, um, self distillation, rl where you, you do self distillation, you do rl and you have past failure and you know, that gives some signal so people take, try it again. Not strong enough.swyx: Uh, for, for listeners, uh, who listen to here, uh, vivo actually, and I, and we run a second YouTube channel for our paper club where, oh, that's awesome.Vivo just covered this. Yeah. Awesome. Self desolation and all that's, that's why he, to speed [00:36:00] on it.Nader: I'll to check it out.swyx: Yeah. It, it's just a good practice, like everyone needs, like a paper club where like you just read papers together and the social pressure just kind of forces you to just,Nader: we, we,there'sNader: like a big inference.Kyle: ReadingNader: group at a video. I feel so bad every time. I I, he put it on like, on our, he shared it.swyx: One, one ofNader: your guys,swyx: uh, is, is big in that, I forget es han Yeah, yeah,Kyle: es Han's on my team. Actually. Funny. There's a, there's a, there's a employee transfer between us. Han worked for Nater at Brev, and now he, he's on my team.He wasNader: our head of ai. And then, yeah, once we got in, andswyx: because I'm always looking for like, okay, can, can I start at another podcast that only does that thing? Yeah. And, uh, Esan was like, I was trying to like nudge Esan into like, is there something here? I mean, I don't think there's, there's new infant techniques every day.So it's like, it's likeKyle: you would, you would actually be surprised, um, the amount of blog posts you see. And ifswyx: there's a period where it was like, Medusa hydra, what Eagle, like, youKyle: know, now we have new forms of decode, uh, we have new forms of specula, of decoding or new,swyx: what,Kyle: what are youVibhu: excited? And it's exciting when you guys put out something like Tron.‘cause I remember the paper on this Tron three, [00:37:00] uh, the amount of like post train, the on tokens that the GPU rich can just train on. And it, it was a hybrid state space model, right? Yeah.Kyle: It's co-designed for the hardware.Vibhu: Yeah, go design for the hardware. And one of the things was always, you know, the state space models don't scale as well when you do a conversion or whatever the performance.And you guys are like, no, just keep draining. And Nitron shows a lot of that. Yeah.Nader: Also, something cool about Nitron it was released in layers, if you will, very similar to Dynamo. It's, it's, it's essentially it was released as you can, the pre-training, post-training data sets are released. Yeah. The recipes on how to do it are released.The model itself is released. It's full model. You just benefit from us turning on the GPUs. But there are companies like, uh, ServiceNow took the dataset and they trained their own model and we were super excited and like, you know, celebrated that work.ZoomVibhu: different. Zoom is, zoom is CGI, I think, uh, you know, also just to add like a lot of models don't put out based models and if there's that, why is fine tuning not taken off?You know, you can do your own training. Yeah,Kyle: sure.Vibhu: You guys put out based model, I think you put out everything.Nader: I believe I know [00:38:00]swyx: about base. BasicallyVibhu: without baseswyx: basic can be cancelable.Vibhu: Yeah. Base can be cancelable.swyx: Yeah.Vibhu: Safety training.swyx: Did we get a full picture of dymo? I, I don't know if we, what,Nader: what I'd love is you, you mentioned the three axes like break it down of like, you know, what's prefilled decode and like what are the optimizations that we can get with Dynamo?Kyle: Yeah. That, that's, that's, that's a great point. So to summarize on that three axis problem, right, there are three things that determine whether or not something can be done with inference, cost, quality, latency, right? Dynamo is supposed to be there to provide you like the runtime that allows you to pull levers to, you know, mix it up and move around the parade of frontier or the preto surface that determines is this actually possible with inference And AI todayNader: gives you the knobs.Kyle: Yeah, exactly. It gives you the knobs.Disaggregation Prefill vs DecodeKyle: Uh, and one thing that like we, we use a lot in contemporary inference and is, you know, starting to like pick up from, you know, in, in general knowledge is this co concept of disaggregation. So historically. Models would be hosted with a single inference engine. And that inference engine [00:39:00] would ping pong between two phases.There's prefill where you're reading the sequence generating KV cache, which is basically just a set of vectors that represent the sequence. And then using that KV cache to generate new tokens, which is called Decode. And some brilliant researchers across multiple different papers essentially made the realization that if you separate these two phases, you actually gain some benefits.Those benefits are basically a you don't have to worry about step synchronous scheduling. So the way that an inference engine works is you do one step and then you finish it, and then you schedule, you start scheduling the next step there. It's not like fully asynchronous. And the problem with that is you would have, uh, essentially pre-fill and decode are, are actually very different in terms of both their resource requirements and their sometimes their runtime.So you would have like prefill that would like block decode steps because you, you'd still be pre-filing and you couldn't schedule because you know the step has to end. So you remove that scheduling issue and then you also allow you, or you yourself, to like [00:40:00] split the work into two different ki types of pools.So pre-fill typically, and, and this changes as, as model architecture changes. Pre-fill is, right now, compute bound most of the time with the sequence is sufficiently long. It's compute bound. On the decode side because you're doing a full Passover, all the weights and the entire sequence, every time you do a decode step and you're, you don't have the quadratic computation of KV cache, it's usually memory bound because you're retrieving a linear amount of memory and you're doing a linear amount of compute as opposed to prefill where you retrieve a linear amount of memory and then use a quadratic.You know,Nader: it's funny, someone exo Labs did a really cool demo where for the DGX Spark, which has a lot more compute, you can do the pre the compute hungry prefill on a DG X spark and then do the decode on a, on a Mac. Yeah. And soVibhu: that's faster.Nader: Yeah. Yeah.Kyle: So you could, you can do that. You can do machine strat stratification.Nader: Yeah.Kyle: And like with our future generation generations of hardware, we actually announced, like with Reuben, this [00:41:00] new accelerator that is prefilled specific. It's called Reuben, CPX. SoKubernetes Scaling with GroveNader: I have a question when you do the scale out. Yeah. Is scaling out easier with Dynamo? Because when you need a new node, you can dedicate it to either the Prefill or, uh, decode.Kyle: Yeah. So Dynamo actually has like a, a Kubernetes component in it called Grove that allows you to, to do this like crazy scaling specialization. It has like this hot, it's a representation that, I don't wanna go too deep into Kubernetes here, but there was a previous way that you would like launch multi-node work.Uh, it's called Leader Worker Set. It's in the Kubernetes standard, and Leader worker set is great. It served a lot of people super well for a long period of time. But one of the things that it's struggles with is representing a set of cases where you have a multi-node replica that has a pair, right?You know, prefill and decode, or it's not paired, but it has like a second stage that has a ratio that changes over time. And prefill and decode are like two different things as your workload changes, right? The amount of prefill you'll need to do may change. [00:42:00] The amount of decode that you, you'll need to do might change, right?Like, let's say you start getting like insanely long queries, right? That probably means that your prefill scales like harder because you're hitting these, this quadratic scaling growth.swyx: Yeah.And then for listeners, like prefill will be long input. Decode would be long output, for example, right?Kyle: Yeah. So like decode, decode scale. I mean, decode is funny because the amount of tokens that you produce scales with the output length, but the amount of work that you do per step scales with the amount of tokens in the context.swyx: Yes.Kyle: So both scales with the input and the output.swyx: That's true.Kyle: But on the pre-fold view code side, like if.Suddenly, like the amount of work you're doing on the decode side stays about the same or like scales a little bit, and then the prefilled side like jumps up a lot. You actually don't want that ratio to be the same. You want it to change over time. So Dynamo has a set of components that A, tell you how to scale.It tells you how many prefilled workers and decoded workers you, it thinks you should have, and also provides a scheduling API for Kubernetes that allows you to actually represent and affect this scheduling on, on, on your actual [00:43:00] hardware, on your compute infrastructure.Nader: Not gonna lie. I feel a little embarrassed for being proud of my SVG function earlier.swyx: No, itNader: wasreallyKyle: cute. I, Iswyx: likeNader: it's all,swyx: it's all engineering. It's all engineering. Um, that's where I'mKyle: technical.swyx: One thing I'm, I'm kind of just curious about with all with you see at a systems level, everything going on here. Mm-hmm. And we, you know, we're scaling it up in, in multi, in distributed systems.Context Length and Co Designswyx: Um, I think one thing that's like kind of, of the moment right now is people are asking, is there any SOL sort of upper bounds. In terms of like, let's call, just call it context length for one for of a better word, but you can break it down however you like.Nader: Yeah.swyx: I just think like, well, yeah, I mean, like clearly you can engage in hybrid architectures and throw in some state space models in there.All, all you want, but it looks, still looks very attention heavy.Kyle: Yes. Uh, yeah. Long context is attention heavy. I mean, we have these hybrid models, um,swyx: to take and most, most models like cap out at a million contexts and that's it. Yeah. Like for the last two years has been it.Kyle: Yeah. The model hardware context co-design thing that we're seeing these days is actually super [00:44:00] interesting.It's like my, my passion, like my secret side passion. We see models like Kimmy or G-P-T-O-S-S. I'm use these because I, I know specific things about these models. So Kimmy two comes out, right? And it's an interesting model. It's like, like a deep seek style architecture is MLA. It's basically deep seek, scaled like a little bit differently, um, and obviously trained differently as well.But they, they talked about, why they made the design choices for context. Kimmy has more experts, but fewer attention heads, and I believe a slightly smaller attention, uh, like dimension. But I need to remember, I need to check that. Uh, it doesn't matter. But they discussed this actually at length in a blog post on ji, which is like our pu which is like credit puswyx: Yeah.Kyle: Um, in, in China. Chinese red.swyx: Yeah.Kyle: It's, yeah. So it, it's, it's actually an incredible blog post. Uh, like all the mls people in, in, in that, I've seen that on GPU are like very brilliant, but they, they talk about like the creators of Kimi K two [00:45:00] actually like, talked about it on, on, on there in the blog post.And they say, we, we actually did an experiment, right? Attention scales with the number of heads, obviously. Like if you have 64 heads versus 32 heads, you do half the work of attention. You still scale quadratic, but you do half the work. And they made a, a very specific like. Sort of barter in their system, in their architecture, they basically said, Hey, what if we gave it more experts, so we're gonna use more memory capacity.But we keep the amount of activated experts the same. We increase the expert sparsity, so we have fewer experts act. The ratio to of experts activated to number of experts is smaller, and we decrease the number of attention heads.Vibhu: And kind of for context, what the, what we had been seeing was you make models sparser instead.So no one was really touching heads. You're just having, uh,Kyle: well, they, they did, they implicitly made it sparser.Vibhu: Yeah, yeah. For, for Kimmy. They did,Kyle: yes.Vibhu: They also made it sparser. But basically what we were seeing was people were at the level of, okay, there's a sparsity ratio. You want more total parameters, less active, and that's sparsity.[00:46:00]But what you see from papers, like, the labs like moonshot deep seek, they go to the level of, okay, outside of just number of experts, you can also change how many attention heads and less attention layers. More attention. Layers. Layers, yeah. Yes, yes. So, and that's all basically coming back to, just tied together is like hardware model, co-design, which isKyle: hardware model, co model, context, co-design.Vibhu: Yeah.Kyle: Right. Like if you were training a, a model that was like. Really, really short context, uh, or like really is good at super short context tasks. You may like design it in a way such that like you don't care about attention scaling because it hasn't hit that, like the turning point where like the quadratic curve takes over.Nader: How do you consider attention or context as a separate part of the co-design? Like I would imagine hardware or just how I would've thought of it is like hardware model. Co-design would be hardware model context co-designKyle: because the harness and the context that is produced by the harness is a part of the model.Once it's trained in,Vibhu: like even though towards the end you'll do long context, you're not changing architecture through I see. Training. Yeah.Kyle: I mean you can try.swyx: You're saying [00:47:00] everyone's training the harness into the model.Kyle: I would say to some degree, orswyx: there's co-design for harness. I know there's a small amount, but I feel like not everyone has like gone full send on this.Kyle: I think, I think I think it's important to internalize the harness that you think the model will be running. Running into the model.swyx: Yeah. Interesting. Okay. Bash is like the universal harness,Kyle: right? Like I'll, I'll give. An example here, right? I mean, or just like a, like a, it's easy proof, right? If you can train against a harness and you're using that harness for everything, wouldn't you just train with the harness to ensure that you get the best possible quality out of,swyx: Well, the, uh, I, I can provide a counter argument.Yeah, sure. Which is what you wanna provide a generally useful model for other people to plug into their harnesses, right? So if youKyle: Yeah. Harnesses can be open, open source, right?swyx: Yeah. So I mean, that's, that's effectively what's happening with Codex.Kyle: Yeah.swyx: And, but like you may want like a different search tool and then you may have to name it differently or,Nader: I don't know how much people have pushed on this, but can you.Train a model, would it be, have you have people compared training a model for the for the harness versus [00:48:00] like post training forswyx: I think it's the same thing. It's the same thing. It's okay. Just extra post training. INader: see.swyx: And so, I mean, cognition does this course, it does this where you, you just have to like, if your tool is slightly different, um, either force your tool to be like the tool that they train for.Hmm. Or undo their training for their tool and then Oh, that's re retrain. Yeah. It's, it's really annoying and like,Kyle: I would hope that eventually we hit like a certain level of generality with respect to training newswyx: tools. This is not a GI like, it's, this is a really stupid like. Learn my tool b***h.Like, I don't know if, I don't know if I can say that, but like, you know, um, I think what my point kind of is, is that there's, like, I look at slopes of the scaling laws and like, this slope is not working, man. We, we are at a million token con

In this episode, host Kalie Moore talks with Bastian Bergmann, Co-founder & COO of Solsten, about the collision between gaming and branding, and why most companies still don't know how to show up in games without feeling like an ad. With 3B+ people playing worldwide and gaming still capturing only ~5% of global ad spend, Bastian argues the opportunity isn't awareness, it's audience strategy. Kalie and Bastian break down why gaming is the only medium that truly spans every demographic, from Gen Alpha to “silver surfers,” and why brands fail when they lead with stereotypes or build empty “brand worlds” instead of experiences grounded in what players actually want.They also explore why gaming should be treated as a real conversion channel, even if measurement hasn't fully caught up yet, and how platforms like Roblox and UEFN will be pushed toward clearer attribution as more dollars move in. Bastian shares standout examples like The New York Times' games-led subscription growth and Chipotle's Roblox activations that drove real-world sales and loyalty signups. For studios and creators, the takeaway is clear: know your audience deeply, design integrations that are brand-agnostic but partnership-ready, and pitch brands with real segmentation and fit, not vague “access to gamers.” The episode closes with what's next at Solsten: Alaris, an AI tool powered by Solsten's psychological dataset, plus an upcoming API layer aimed at unlocking deeper personalization across games, matchmaking, recommendations, and advertising.We'd like to thank Neon – a global payments and e-commerce platform designed to help game publishers earn more money and gain independence from app stores – for making the episode possible. Neon's DTC platform handles everything from webshops and checkout to global payments, tax, and compliance, with full transparency and all-in pricing. Learn more:https://www.neonpay.com/?utm_source=Naavik-Sponsorship-General&utm_medium=Paid-Sponsorship We'd also like to thank modl.ai for making this episode possible! Using a combination of computer vision, reasoning models, and feedback loops, modl:QA+ autonomously explores builds, detects bugs, and generates actionable reports that sync directly with your existing workflows. To learn more, visit modl.ai.If you like the episode, please help others find us by leaving a 5-star rating or review! And if you have any comments, requests, or feedback shoot us a note at podcast@naavik.co.Who's On:Guest - Bastian Bergmann: https://www.linkedin.com/in/bergmannbastian/Host - Kalie Moore: https://www.linkedin.com/in/kaliemoore/ Watch the episode: YouTube ChannelFor more episodes and details: Podcast WebsiteFree newsletter: Naavik DigestFollow us: Twitter | LinkedIn | WebsiteSound design by Gavin Mc Cabe.

Virtuals introduces the ERC-8183 Agentic Commerce Standard. The EF increases its bug bounty program reward to $1 million. LI.​FI introduces an API for Agentic Commerce. And BitMine holds 4.5 million ETH. Read more: https://ethdaily.io/899 Are you running a treasury? You need liquidity but don't want to sell ETH? Get the lowest fixed rates to borrow against ETH and LSTs on Liquity V2 on liquity.org  Disclaimer: Content is for informational purposes only, not endorsement or investment advice. The accuracy of information is not guaranteed.

House and Nathan are joined by Justin Ray to recap Akshay Bhatia's win at the Arnold Palmer Invitational. Then, they preview The Players and share the golfers they think can make some noise, including their sleeper picks. Finally, they discuss what Brian Rolapp may say at his press conference and share their winner picks.(0:00) Welcome to Fairway Rollin' with Justin Ray!(1:45) Akshay Bhatia's short game was phenomenal(6:40) Who else impressed at API?(29:20) Let's preview The Players(49:15) What sleepers do we like?(57:45) On Brian Rolapp's upcoming press conference(1:02:20) Players Championship winner picksThe Ringer is committed to responsible gaming. Please visit www.rg-help.com to learn more about the resources and helplines available.Hosts: Joe House and Nathan HubbardGuest: Justin RayProducers: Tucker Tashjian, and Mike Wargon Learn more about your ad choices. Visit podcastchoices.com/adchoices

The crew reacts to one of the strangest betting markets in recent UFC memory, breaking down the suspicious line movement in the Michael Johnson vs Drew Dober fight and why so many bettors immediately questioned what was happening. Was it sharp action, bad numbers from sportsbooks, or something even stranger? The panel dives into how the market moved, why it raised eyebrows across gambling Twitter, and what bettors should actually take away from situations like this. They also discuss whether sports bettors truly need projections or models to succeed, when gambling is actually the most fun for bettors, and other stories from the week in betting. Circle Back is hosted by Jacob Gramegna and features professional sports bettor and CEO of The Hammer, Rob Pizzola, basketball originator Kirk Evans, and sophisticated square Geoff Fienberg. The group reacts to the biggest conversations across the betting world each week — from market drama and industry controversies to betting strategy debates and everything in between.

I sit down with Oliver Henry, a full-time employee who is generating hundreds of dollars in monthly recurring revenue from mobile apps he barely touches, thanks to an AI marketing agent he built on OpenClaw called Larry. We walk through how Larry autonomously creates TikTok slideshow content, reads analytics, iterates on hooks and CTAs, and feeds performance data back into the content loop. Oliver also shares how he packaged the entire system as a free, downloadable skill on Larry Brain so anyone can replicate it. By the end of the episode, you will understand the full “Larry Loop”—from content creation to conversion optimization and why skills are poised to reshape how we think about SaaS altogether. I'm hosting a free workshop so you can build your business in the age of AI. Sign up here: https://startup-ideas-pod.link/build-with-ai-2026 Links Mentioned: Larry Brain: https://startup-ideas-pod.link/Larry-brain QMD Skill: https://startup-ideas-pod.link/qmd-skill Timestamps 00:00 – Intro 01:25 – Background on Marketing IOS app with OpenClaw 06:43 – Larry's first posts and iterating 03:55 – Posting Strategy and First viral hit: 137K views 12:01 – Communicating with Larry via WhatsApp 12:53 – Mission control vs. single-agent workflow 14:36 – The CTA problem: views without conversions 17:07 – The Larry Loop explained: analytics → content → metrics → iterate 18:15 – Boomers, engagement bait, and the algorithm boost 20:33 – The importance of iteration 23:36 – How Larry brainstorms and validates new hooks 27:57 – The power of OpenClaw 30:04 – The vision for Larry 31:49 – Model choices: Claude vs. OpenAI and over-optimization 34:38 – OpenClaw vs. cloud alternatives (Manus, Cowork) 37:39 – Getting started: Larry Brain onboarding and 80+ skills 40:13 – Ernesto Lopez: $70K MRR using the Larry Loop 41:27 – Doing all of this with a full-time job 42:28 – QMD Skill for cutting token usage and closing thoughts Key Points An AI agent (Larry) built on OpenClaw autonomously creates TikTok slideshows, reads analytics, and iterates on content—driving hundreds of dollars in MRR with almost zero manual effort. The “Larry Loop” is a full-funnel feedback cycle: TikTok analytics feed into content creation, and app metrics feed back into the top of the funnel so the agent continuously improves. Posting TikTok content as a draft (rather than directly via API) lets you add trending sounds and avoids the algorithm penalty for bot-posted content. Hooks drive views; CTAs drive conversions. Diagnosing which is underperforming is the key to scaling. OpenClaw skills are locally owned, fully editable, and free from hosting or subscription costs—Oliver argues they will change how we think about SaaS. Picking a model (Claude or OpenAI) matters far less than learning how to work with it; 98% of users will see little difference between incremental model upgrades. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND OLIVER ON SOCIAL X: https://x.com/oliverhenry Larry Brain: https://www.larrybrain.com

Monday – Alejandro joins us today. We review the inaugural Bourbon Bus and talk Cuba, insurance tracking, wings and drummies, the recent time change, the teacher prank tragedy, Brandon Kravitz on the dramatic finish at the API, Mike Evans leaving the Bucs, other NFL moves and Magic are hot. Attorney Ray Traendly on the death of a Georgia teacher after a prank gone wrong, and the DOJ vs. Live Nation/Ticketmaster. Plus, JCS News, JCS Trivia & You Heard it Here First. See omnystudio.com/listener for privacy information.

This week on Marketing O'Clock: Google is disabling the Ads API Customer Match feature for certain users starting in April. Also, Meta is adding click and engage-through attribution to its ad measurement framework. Visit us at - https://marketingoclock.com/

Saurabh Shintre, Founder and CEO of Realm Labs, is on Defender Fridays today to discuss securing AI from within.Saurabh previously led the AI security research at Splunk and Symantec. He has been at the forefront of AI security research for nearly a decade with multiple publications and patents and regularly features on public forums on issues regarding security and AI. Saurabh holds a PhD from Carnegie Mellon. Learn more at https://www.realmlabs.ai/Register for Live SessionsJoin us every Friday at 10:30am PT for live, interactive discussions with industry experts. Whether you're a seasoned professional or just curious about the field, these sessions offer an engaging dialogue between our guests, hosts, and you – our audience.Register here: https://limacharlie.io/defender-fridaysSubscribe to our YouTube channel and hit the notification bell to never miss a live session or catch up on past episodes!Sponsored by LimaCharlieThis episode is brought to you by LimaCharlie, a cloud-native SecOps platform where AI agents operate security infrastructure directly. Founded in 2018, LimaCharlie provides complete API coverage across detection, response, automation, and telemetry, with multi-tenant architecture designed for MSSPs and MDR providers managing thousands of unique client environments.Why LimaCharlie?Transparency: Complete visibility into every action and decision. No black boxes, no vendor lock-in.Scalability: Security operations that scale like infrastructure, not like procurement cycles. Move at cloud speed.Unopinionated Design: Integrate the tools you need, not just those contracts allow. Build security on your terms.Agentic SecOps Workspace (ASW): AI agents that operate alongside your team with observable, auditable actions through the same APIs human analysts use.Security Primitives: Composable building blocks that endure as tools come and go. Build once, evolve continuously.Try the Agentic SecOps Workspace free: https://limacharlie.ioLearn more: https://docs.limacharlie.io/Follow LimaCharlieSign up for free: https://limacharlie.io/LinkedIn: / limacharlieio X: https://x.com/limacharlieioCommunity Discourse: https://community.limacharlie.com/Host: Maxime Lamothe-Brassard - CEO / Co-founder at LimaCharlie

In this episode of The Cybersecurity Defenders Podcast, we discuss some intel being shared in the LimaCharlie community.Iranian drone strikes damaged three Amazon Web Services data center facilities in the Middle East, highlighting the physical risks associated with large-scale cloud infrastructure.Cyber activity linked to Iran and pro-Iranian actors has intensified following a joint US–Israeli military strike on Iran that killed Supreme Leader Ayatollah Ali Khamenei and several other government officials.The India-linked advanced persistent threat group known as “Sloppy Lemming” has significantly increased its cyber operations over the past year, targeting organizations in Pakistan, Bangladesh, and other parts of South and Southeast Asia.A cybersecurity researcher has reported a potentially serious vulnerability in Honeywell's IQ4 building management controller, though the vendor disputes both the severity and practical impact of the issue.Support our show by sharing your favorite episodes with a friend, subscribe, give us a rating or leave a comment on your podcast platform.This podcast is brought to you by LimaCharlie, maker of the SecOps Cloud Platform, infrastructure for SecOps where everything is built API first. Scale with confidence as your business grows. Start today for free at limacharlie.io.

“They're both naughty boys in the playground, leveraging the absence of clarity to their own advantage. Neither one of them is an authoritative leader of opinion with the interests of everyone at heart.” — Keith TeareWhat a difference a week makes. Last Saturday, Keith Teare was arguing that Anthropic was wrong to push back against the US government's use of AI in warfare. This week his editorial is entitled “No Good Guys.” He's used AI to put images of Sam Altman, Dario Amodei, and Pete Hegseth around the same table—and found all three guilty of poor leadership. According to Keith, Amodei is “ideologically” (whatever that means) driven. Altman is commercially driven and Hegseth is just following orders. None of them is asking the all-important questions about AI policy. And the man who should be—Trump's AI czar David Sacks—is absent-without-leave. All four should be court martialed.Yes, a lot has happened in seven days. Altman publicly supported Amodei's position on surveillance and autonomous weapons—then pulled a classic Sam u-turn and signed a contract with the Department of War. Amodei's internal memo was leaked to The Information, revealing that he'd interpreted the government's “no unlawful use” language as meaning there is no law. And the US military used Claude in the Iran war anyway. As Keith puts it: they're all naughty boys in the playground, leveraging the gaps to their own self-advantage.The only problem, of course, is that this isn't a playground game. And that these men are all shaping the lives (and deaths) of countless people around the world.Meanwhile, Om Malik's “Post of the Week” offers a devastating contrast between Xi's China and Trump's America. China, Om argues, has published a five-year AI plan built on open-source software and bottom-up adoption. America, in contrast, has AI theater. No strategy, no policy, no leadership—just contracts, leaks, and perpetual spin. Then there's the Startup of the Week, Jobright, which hit $5 million in annual revenue with nine people, suggesting that the companies of the future may not need humans at all. Keith's own SignalRank has four people and claims to be going public. We seem to be heading for post-human companies before we've figured out who's managing the humans.Maybe we should court martial everyone. What a difference a week makes. Five Takeaways•       No Good Guys: Keith Teare's editorial puts Sam Altman, Dario Amodei, and Pete Hegseth in the same room—and finds all three guilty of bad leadership. Amodei is ideologically driven, Altman is commercially driven, and Hegseth is just doing his job. None of them is asking the big questions about AI policy. The real culprit may be the invisible AI czar, David Sacks.•       Altman Said One Thing, Then Did Another: Last week Altman publicly supported Amodei's position on surveillance and autonomous weapons. This week he signed a contract with the Department of War. The contract uses “no unlawful use” language—which, as Amodei's leaked memo points out, effectively means there is no law.•       The US Used Claude in Iran Anyway: Despite the very public dispute between Anthropic and the government, the US military used Claude in the Iran operation. The government doesn't need your permission to use your product. It just needs an API key and a credit card.•       China Has a Plan. America Has Theater: Om Malik's “Post of the Week” contrasts China's published five-year AI strategy—built on open-source software and bottom-up adoption—with America's complete absence of AI policy. The Chinese approach is more inclusive and practical than anything coming out of Washington or Silicon Valley.•       The Future Company Has Nine Employees: Startup of the week Jobright hit $5 million in annual recurring revenue with just nine people. Keith's own company, SignalRank, has four people and is going public. The implication: the companies of the future will be run mostly by software agents, not humans. We're heading for post-human companies. About the GuestKeith Teare is the publisher of That Was The Week, founder and CEO of SignalRank, and a recurring sparring partner on Keen On America. A serial entrepreneur and investor, he is the co-founder of TechCrunch and RealNames. He joins the show every Saturday for the weekly tech roundup.ReferencesEssays, posts, and interviews referenced:•       Keith Teare, “No Good Guys” — That Was The Week editorial•       Om Malik, “The Great AI Game versus AI Theater” — Post of the Week•       Ross Douthat, “If AI Is a Weapon, Who Should Control It?” — New York Times•       Ben Thompson, Stratechery — on “no unlawful use” and the absence of international law•       Paul Krugman on the economics of technological change — technology, jobs, wages, and monopolies•       Tim O'Reilly, “How We Bet Against the Bitter Lesson” — skills and the future knowledge economy•       Yascha Mounk and Danielle Allen on participatory democracy and AI governance•       Previous Keen On episodes: Tom Wells on the Kissinger tapes; Michael Ellsberg on Daniel Ellsberg and the Pentagon Papers•       Startup of the Week: Jobright — $5M ARR with nine employeesAbout Keen On AmericaNobody asks more awkward questions than the Anglo-American writer and filmmaker Andrew Keen. In Keen On America, Andrew brings his pointed Transatlantic wit to making sense of the United States—hosting daily interviews about the history and future of this now venerable Republic. With nearly 2,800 episodes since the show launched on TechCrunch in 2010, Keen On America is the most prolific intellectual interview show in the history of podcasting.WebsiteSubstackYouTubeApple PodcastsSpotify Chapters:(00:00) - Introduction: What a difference a week makes (01:14) - “No Good Guys”: Keith's editorial and Om Malik's wake-up call (02:30) - Amodei, Altman, Hegseth: three self-interested players (04:02) - How the Iran invasion changed the AI debate (05:28) - “No unlawful use”: a meaningless phrase in a lawless context (06:50) - The US used Claude in Iran despite the Anthropic dispute (08:15) - Naughty boys in the playground: spinning vs. leadership (09:31) - Bobby Kenn...

This week on Circle Back, we break down some of the worst sports betting advice currently circulating on Gambling Twitter. The crew reacts to a viral strategy suggesting bettors should blindly fade steam moves in low-liquidity mid-major college basketball games, and explains why sportsbooks adjusting to sharp action does NOT suddenly create value on the other side. We also discuss bankroll management advice encouraging bettors to constantly withdraw profits instead of allowing their bankroll and unit size to scale properly, and debate a controversial take dismissing the importance of closing line value (CLV) as a core indicator of long-term betting success. Plus, we round up some of the latest viral moments, arguments, and drama from Gambling Twitter this week. Circle Back is hosted by Jacob Gramegna and is part of Circles Off on The Hammer Betting Network. This episode features Joey Knish alongside Porter from BA Analytics and Chinamaniac as the panel breaks down the latest conversations, debates, and controversies happening across Gambling Twitter.

Are you trying to figure out if your team should build an AI model from scratch or integrate an off-the-shelf solution? You aren't alone.In this episode of the MongoDB Podcast, Shane McAlister sits down with Akshaya Murthy, Director of AI Transformation at Zendesk, to decode the maze of building enterprise AI products. They dive into why integrating is often the winning move for speed-to-market, the hidden costs of custom models, and why bad data will break even the most perfect transformer model.What you'll learn in this episode:The Build vs. Buy Calculus: Why lower Total Cost of Ownership (TCO) and rapid deployment favor integration for most enterprises.Spotting "AI Washing": How to avoid vendor buzzword salads and focus on actual problem-solving and ROI.Architectural Must-Haves: Why your AI stack needs modular API layers, model hot-swapping, and CI/CD pipelines just like your standard code.The "Garbage In, Hype Out" Rule: Why a solid data strategy and a centralized single source of truth are non-negotiable.Ready to stop experimenting and start delivering real AI value? Tune in now.

Last episode, Ron and Marcus made predictions. This episode, they brought the receipts. A journalist built an app with vibe coding and got hacked on live television.  A social network built entirely by AI (not a single line of human code!) exposed 1.5 million authentication tokens and private messages between agents.  And 88% of organizations have already had an AI security incident, while barely 14% of deployed agents ever saw a security review.  The warnings from last episode aged fast. Marcus J. Carey is back to talk about what that actually means for the people building right now, not the people theorizing about it. Ron and Marcus are in the code themselves, and this conversation is what that experience actually looks like: OpenClaw running loose on your machine, agents racking up API bills, and why guidance, not prompts, not tools, is the real skill that separates builders who thrive from builders who ship disasters. Impactful Moments 00:00 - Introduction 02:00 - Vibe coding hack on live TV 03:30 - Mo Book leaks 1.5M auth tokens 06:00 - Marcus' origin story: War Games, 1983 08:00 - OpenClaw escapes the lab 13:30 - AT&T cuts help desk spend 90% 17:00 - Context is king, guidance is everything 19:00 - Can AI do your job rec right now? 24:00 - The first cybersecurity jobs agents will replace 27:00 - Expertise + AI = 1000x yourself 30:00 - Focus on outcomes, not new tools   Links Connect with our guest, Marcus J. Carey, on LinkedIn: https://www.linkedin.com/in/marcuscarey/   Read the articles we referenced in this episode: The vibe coding hack that aired on live TV, ICAEW breaks down exactly how it happened and what it means for anyone building with AI: https://www.icaew.com/insights/viewpoints-on-the-news/2026/feb-2026/cyber-dangers-of-agents-and-vibe-coding 88% of organizations have already had an AI security incident. See the full data from the Cisco State of AI Security 2026 report: https://www.helpnetsecurity.com/2026/02/23/ai-agent-security-risks-enterprise/   Check out our upcoming events: https://www.hackervalley.com/livestreams Love Hacker Valley Studio? Pick up some swag: https://store.hackervalley.com Become a sponsor of the show to amplify your brand: https://hackervalley.com/work-with-us/  

Everyone's chasing the next big model drop.

────────────────────────────────────────00:01:06:19 — AI Firms Accused of Enabling Mass Surveillance and Autonomous WeaponsOpenAI and other technology companies face backlash for allegedly cooperating with Pentagon projects involving mass surveillance systems and autonomous lethal weapons.────────────────────────────────────────00:02:09:26 — Claims of “Unlimited” U.S. Weapons Stockpiles ChallengedStatements that the United States possesses virtually unlimited weapons stockpiles are disputed using reported production figures showing interceptor missile shortages.────────────────────────────────────────00:03:41:29 — Missile Production Gap Exposes Strategic VulnerabilityIranian missile production is estimated at about 100 per month while U.S. interceptor production may be only six to seven per month, highlighting a severe imbalance in defensive capability.────────────────────────────────────────00:07:34:20 — Reports of Cluster Missile Technology Increasing Defense ChallengesClaims circulate that certain Iranian missiles contain dozens of sub-munitions, multiplying the difficulty for missile defense systems already facing interceptor shortages.────────────────────────────────────────00:09:14:14 — U.S. Proposal to Insure Oil Tankers Through Strait of HormuzThe U.S. government reportedly considers guaranteeing or insuring oil tankers traveling through the Strait of Hormuz to keep global energy shipments moving despite military risks.────────────────────────────────────────00:11:16:19 — Debate Over Israeli Influence on U.S. War DecisionsArguments emerge that U.S. policy may be influenced by Israeli strategic priorities, while critics insist American leaders remain responsible for their own decisions.────────────────────────────────────────00:16:24:03 — 1953 Iran Coup Framed as Origin of Modern ConflictCurrent tensions are linked to the CIA-backed overthrow of Iran's government in 1953 and the installation of the Shah, described as a foundational moment for long-term hostility.────────────────────────────────────────00:38:46:16 — U.S. Troops Killed in Missile Strike on Kuwait BaseSix U.S. service members are reported killed and multiple others injured when a missile strike hits a makeshift operations center described as a “fortified” trailer.────────────────────────────────────────00:43:05:25 — Christian Prophecy Narratives Used to Justify WarReports emerge of military leadership invoking biblical prophecy and Armageddon narratives to frame the conflict with Iran as part of a divine plan.────────────────────────────────────────00:58:33:09 — California Law Requires Age-Tracking Internet InfrastructureCalifornia unanimously passes AB-1043 requiring operating systems to collect age data at account setup and transmit it to app developers via a real-time API beginning January 2027.────────────────────────────────────────01:10:36:14 — Trump Targeting Law Firms Sparks Constitutional ConcernsExecutive orders reportedly removed security clearances and federal building access from law firms associated with political opponents.────────────────────────────────────────01:27:56:15 — AI Industry Conflict Over Military Surveillance ContractsAnthropic's Claude AI reportedly refuses Pentagon uses tied to mass surveillance or autonomous weapons while OpenAI moves forward with defense contracts.──────────────────────────────────────── Money should have intrinsic value AND transactional privacy: Go to https://davidknight.gold/ for great deals on physical gold/silver For 10% off Gerald Celente's prescient Trends Journal, go to https://trendsjournal.com/ and enter the code KNIGHT Find out more about the show and where you can watch it at TheDavidKnightShow.com If you would like to support the show and our family please consider subscribing monthly here: SubscribeStar https://www.subscribestar.com/the-david-knight-showOr you can send a donation throughMail: David Knight POB 994 Kodak, TN 37764Zelle: @DavidKnightShow@protonmail.comCash App at: $davidknightshowBTC to: bc1qkuec29hkuye4xse9unh7nptvu3y9qmv24vanh7Become a supporter of this podcast: https://www.spreaker.com/podcast/the-david-knight-show--2653468/support.

────────────────────────────────────────00:01:06:19 — AI Firms Accused of Enabling Mass Surveillance and Autonomous WeaponsOpenAI and other technology companies face backlash for allegedly cooperating with Pentagon projects involving mass surveillance systems and autonomous lethal weapons.────────────────────────────────────────00:02:09:26 — Claims of “Unlimited” U.S. Weapons Stockpiles ChallengedStatements that the United States possesses virtually unlimited weapons stockpiles are disputed using reported production figures showing interceptor missile shortages.────────────────────────────────────────00:03:41:29 — Missile Production Gap Exposes Strategic VulnerabilityIranian missile production is estimated at about 100 per month while U.S. interceptor production may be only six to seven per month, highlighting a severe imbalance in defensive capability.────────────────────────────────────────00:07:34:20 — Reports of Cluster Missile Technology Increasing Defense ChallengesClaims circulate that certain Iranian missiles contain dozens of sub-munitions, multiplying the difficulty for missile defense systems already facing interceptor shortages.────────────────────────────────────────00:09:14:14 — U.S. Proposal to Insure Oil Tankers Through Strait of HormuzThe U.S. government reportedly considers guaranteeing or insuring oil tankers traveling through the Strait of Hormuz to keep global energy shipments moving despite military risks.────────────────────────────────────────00:11:16:19 — Debate Over Israeli Influence on U.S. War DecisionsArguments emerge that U.S. policy may be influenced by Israeli strategic priorities, while critics insist American leaders remain responsible for their own decisions.────────────────────────────────────────00:16:24:03 — 1953 Iran Coup Framed as Origin of Modern ConflictCurrent tensions are linked to the CIA-backed overthrow of Iran's government in 1953 and the installation of the Shah, described as a foundational moment for long-term hostility.────────────────────────────────────────00:38:46:16 — U.S. Troops Killed in Missile Strike on Kuwait BaseSix U.S. service members are reported killed and multiple others injured when a missile strike hits a makeshift operations center described as a “fortified” trailer.────────────────────────────────────────00:43:05:25 — Christian Prophecy Narratives Used to Justify WarReports emerge of military leadership invoking biblical prophecy and Armageddon narratives to frame the conflict with Iran as part of a divine plan.────────────────────────────────────────00:58:33:09 — California Law Requires Age-Tracking Internet InfrastructureCalifornia unanimously passes AB-1043 requiring operating systems to collect age data at account setup and transmit it to app developers via a real-time API beginning January 2027.────────────────────────────────────────01:10:36:14 — Trump Targeting Law Firms Sparks Constitutional ConcernsExecutive orders reportedly removed security clearances and federal building access from law firms associated with political opponents.────────────────────────────────────────01:27:56:15 — AI Industry Conflict Over Military Surveillance ContractsAnthropic's Claude AI reportedly refuses Pentagon uses tied to mass surveillance or autonomous weapons while OpenAI moves forward with defense contracts.──────────────────────────────────────── Money should have intrinsic value AND transactional privacy: Go to https://davidknight.gold/ for great deals on physical gold/silver For 10% off Gerald Celente's prescient Trends Journal, go to https://trendsjournal.com/ and enter the code KNIGHT Find out more about the show and where you can watch it at TheDavidKnightShow.com If you would like to support the show and our family please consider subscribing monthly here: SubscribeStar https://www.subscribestar.com/the-david-knight-showOr you can send a donation throughMail: David Knight POB 994 Kodak, TN 37764Zelle: @DavidKnightShow@protonmail.comCash App at: $davidknightshowBTC to: bc1qkuec29hkuye4xse9unh7nptvu3y9qmv24vanh7Become a supporter of this podcast: https://www.spreaker.com/podcast/the-real-david-knight-show--5282736/support.

Today, we are continuing our series, entitled Developer Chats - hearing from the large scale system builders themselves.In this episode, we are talking with Oleksandr Piekhota, Principal Software Engineer at Teaching Strategies. Oleksandr helps to show us at what point of scale platform approaches are required, when to run experiments and when to stop, and perhaps more importantly - engineering ownership beyond the code.QuestionsYou've moved from hands-on engineering into principal and technical leadership roles, working on architecture and platforms.At what point did you realize your work was no longer about individual features, but about the system as a wholeAcross several projects, growth didn't break functionality — it exposed architectural limits.Can you recall a moment when it became clear that shipping more features wouldn't solve the problem, and a platform approach was required?You've designed and supported APIs end-to-end, from architecture to real customers. How do you distinguish between an API that simply works and one that can truly support business scale?Internal systems like invoicing and HR workflows began as automation, but evolved into real products.What tells you that an internal tool is worth developing seriously rather than treating as a temporary workaround?In R&D, you explored CI/CD automation, server-less, and infrastructure experiments — not all reached production. How do you decide when an experiment should continue, and when it's no longer worth the engineering cost?You've hired teams, set standards, and shaped long-term technical direction. At what point does an engineer stop being a contributor and start owning business-level outcomes?You contributed to open-source tools that later became part of your company's infrastructure. Why do you see open source contributions as part of serious engineering work rather than a side activity?Looking across your projects, how do you now recognize a truly mature engineering system? Is it code quality, process, or how teams respond when things go wrong?If we look five to seven years into the future, which architectural assumptions we treat as “standard” today are most likely to turn out to be naive or limiting?SponsorsIncogniLinkshttps://www.linkedin.com/in/oleksandr-piekhota-b675ba53/https://teachingstrategies.com/Support this podcast at — https://redcircle.com/codestory/donationsAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

The fight between Anthropic and the Pentagon goes deeper than a simple contract dispute. In some ways, it's the culmination of a tech rivalry that's been simmering since the early days of OpenAI.Anthropic wasn't some scrappy outsider that stumbled into national security. It'd already had top secret clearance, working with the CIA for years, and had seemingly made peace with the idea that its models would be used inside the American intelligence apparatus. So let's dispense with the notion that this is a company discovering government power for the first time. The rupture didn't happen because the Pentagon suddenly knocked on the door. The door had been open.The disagreement came down to terms. Anthropic wanted to draw lines beyond the law. No mass surveillance of civilians. No autonomous weapons without a human in the loop. Not “we'll follow U.S. statute.” They wanted something stricter, something moral, something aligned with Dario Amodei's effective altruist worldview. The Pentagon's response was blunt: we obey US law, but we don't sign up to a private company's expanded terms of service.That's where the temperature rose.Politics Politics Politics is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.Because this isn't just any company. Dario left OpenAI over exactly this kind of philosophical divide. He believed OpenAI was becoming too commercial, too focused on product, not focused enough on safety and existential risk. So he built Anthropic as the safety lab. The kinder, gentler, crunchier alternative. But ironically, Anthropic was already cashing government checks while telling itself it was the adult in the room.From the Pentagon's perspective, the risk was operational. If you're going to integrate a model into defense infrastructure, you can't have the supplier yank the API mid-mission because the CEO decides the vibes are off. There were even reports that during negotiations, Pentagon officials asked whether Anthropic would allow its technology to respond to incoming ballistic missiles if civilian casualties were possible. The alleged answer, “you can always call,” wasn't reassuring to people whose job is to eliminate hesitation.And hovering over all of this is Sam Altman.Because while Anthropic was sparring with the Department of Defense, OpenAI was in conversation. The rivalry here isn't new. The effective altruist faction at OpenAI once helped push Altman out of his own company before he managed to return days later. Anthropic ran a Super Bowl ad that took thinly veiled shots at OpenAI's commercialization. So when Anthropic stumbled, OpenAI stepped in and secured its own defense agreement.Then came the nuclear option talk: labeling Anthropic a “supply chain risk.” In Pentagon language, this is the category you reserve for companies like Huawei, for hostile foreign hardware, for entities you believe can't be trusted inside American systems. Most people inside and outside the tech landscape agree that goes too far. Anthropic may be principled. It may be stubborn. It may even be naive. But it isn't malicious.Meanwhile, something fascinating happened in the market. Claude, Anthropic's consumer product, exploded in downloads. It became a kind of digital resistance symbol, a signal that you weren't with the war machine. The company that once insisted it didn't care about consumer dominance suddenly found itself riding a consumer wave, experience mass traffic it hadn't planned to account for.What this entire episode reveals is that AI isn't a lab experiment anymore. It's infrastructure. It's missile defense. It's geopolitical leverage. And when you build something that powerful, you don't get to exist outside power structures. You either align with them, fight them, or try to morally outmaneuver them. Anthropic tried the third path. The Pentagon reminded them that in wartime procurement, ambiguity isn't a feature.Cooler heads may yet prevail. Right now, the Pentagon's got bigger problems than a Silicon Valley slap fight. But this was the moment when AI stopped being a culture war talking point and became a live wire in national security. And once you plug into that grid, there's no going back.Chapters00:00:00 - Intro00:02:25 - Texas Primary Final Predictions00:15:20 - The Pentagon vs. Anthropic, Explained00:40:30 - Update00:40:52 - Iran00:45:41 - Clintons00:49:08 - Kalshi00:52:19 - Interview with Kenneth Lowande01:18:03 - Wrap-up This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.politicspoliticspolitics.com/subscribe

AI is bringing massive changes to our industry, but it's not just about how fast you can write code or use agentic flows. In this episode, I explore how AI is fundamentally shifting the economic bottleneck of software development, and how you can use your systems-thinking engineering mindset to adapt and thrive in this new era.

"Even if it ends up being something that ends the universe, it at least will have been a fun ride. So let's do it." That's what Karl Meisterheim said when Kurt pitched him on building a Shopify app. Over a year later, Promo Party Pro is live, and the journey from "this should be easy" to "why is the cart API doing that" was anything but smooth. Kurt, Paul Reda, and Karl sit down to talk through the whole thing: why free gift with purchase is Kurt's favorite promo, the edge cases that nearly broke them, the popup cooldown debate that consumed days, and what it actually takes to ship a polished app on Shopify in 2025. SPONSORS Swym - Wishlists, Back in Stock alerts, & more getswym.com/kurt Cleverific - Smart order editing for Shopify cleverific.com Zipify - Build high-converting sales funnels zipify.com/KURT LINKS Promo Party Pro: https://promoparty.app/ Crowdfunder App: https://apps.shopify.com/crowdfunder Ethercycle: https://ethercycle.com WORK WITH KURT Apply for Shopify Help ethercycle.com/apply See Our Results ethercycle.com/work Free Newsletter kurtelster.com The Unofficial Shopify Podcast is hosted by Kurt Elster and explores the stories behind successful Shopify stores. Get actionable insights, practical strategies, and proven tactics from entrepreneurs who've built thriving ecommerce businesses.