Podcasts about Workflow

Send us Fan MailIf Pinterest feels like a hamster wheel you can never get off, you're probably pinning the wrong way. Most people spread their Pinterest work across seven days and wonder why they're exhausted and not seeing results. Spoiler: the problem isn't Pinterest. It's the strategy.In this episode, I'm walking you through my exact 3-part Pinterest workflow — the one I use for myself and my clients to stay consistent without the daily grind.Why batching on Mondays beats spreading Pinterest work across the weekHow I create an entire month of pins in one focused sessionThe Friday performance review that most people skip (and why it changes everything)How to use the Pinterest trends tool + search bar for keyword researchWhy obsessing over daily stats is working against youWhat data to actually track and how it shapes your next month's contentHow The Club teaches you to build this system around your scheduleResources mentioned:Visibility Vault (free Pinterest + marketing tools)The Club (DIY Pinterest with guidance)Tailwind free planThese may be affiliate links and if you purchase I'll get a stipend and at the best possible priceSupport the showHere are some free things I've got coming up:Want your account audited? Pinterest Audits LIVE on YouTube. Free Pinterest Masterclass

Struggling to create brand messaging that actually converts? In this episode, brand strategist Kate DiLeo shares her 3-part workflow for building irresistible brand messaging that captures attention, builds trust, and drives measurable growth.Learn how to craft a stronger value proposition, identify meaningful differentiators, improve your brand positioning, and create messaging that helps buyers quickly understand why they should choose you.We also explore how to use AI without losing your brand voice, why most AI-generated messaging falls flat, and how the Brand Trifecta framework helps marketers create messaging that resonates and converts.And don't forget! You can crush your marketing strategy with just a few minutes a week by signing up for the StrategyCast Newsletter. You'll receive weekly bursts of marketing tips, clips, resources, and a whole lot more. Visit https://strategycast.com/ for more details.==Let's Break It Down==05:04 Identifying the brand trifecta07:16 Clarifying your brand's differentiators10:47 Creating product differentiation16:47 Identifying target customer personas18:41 Tips for creating brand taglines22:04 Using AI for audience insights25:30 Revising a company's messaging==Where You Can Find Us==Website: https://strategycast.com/Instagram: https://www.instagram.com/strategy_cast/Facebook: https://www.facebook.com/strategycast==Leave a Review==Hey there, StrategyCast fans!If you've found our tips and tricks on marketing strategies helpful in growing your business, we'd be thrilled if you could take a moment to leave us a review on Apple Podcasts. Your feedback not only supports us but also helps others discover how they can elevate their business game!

Dolby Atmos ist heute Standard – von Kinos über Autos bis hin zum Kopfhörer-Mix via Binauralisierung. Doch egal wie man abhört: Die Erstellung von Multikanal-Inhalten stößt oft auf ein technisches Nischendasein bei Plug-Ins. Während man für Reverbs mittlerweile eine gute Auswahl an Mehrkanal-Lösungen hat, sind EQs, Kompressoren und vor allem Delays in Formaten wie 7.1.4 oft Mangelware. Die Folge sind umständliche Workarounds, die nicht immer zuverlässig funktionieren. Hier kommt Armada von Fiedler Audio ins Spiel. Als spezialisierter Entwickler für Immersive-Tools präsentiert Fiedler mit Armada einen Wrapper, der verspricht, jedes Plug-In in jedem beliebigen Format nutzbar zu machen. Aber klappt das in der Praxis wirklich? In diesem Video führe ich dich durch alle Funktionen von Armada. Ich zeige dir den praktischen Workflow, erkläre die Vorteile im Studioalltag und demonstriere die Arbeitsweise direkt mit Soundbeispielen. Am Ende teile ich meine ehrliche Meinung dazu, ob das Tool die Herausforderung der Mehrkanal-Bearbeitung für dich endlich lösen kann. In diesem Video erfährst du: - Wie Armada die Lücke bei Mehrkanal-Delays, EQs und Kompressoren schließt. - Eine detaillierte Erklärung jeder Funktion in der Praxis. - Soundbeispiele zur Veranschaulichung der klanglichen Auswirkungen. Mein Fazit nach dem ausführlichen Test. Den ganzen Testbericht findest Du auf recording.de Wenn ich Dir helfen konnte, freue ich mich über einen virtuellen Kaffee ;-) https://ko-fi.com/timheinrich Zum kostenlosen Cubase-Stammtisch anmelden: subscribepage.io/1D69jt Podcast: https://sounthcast.podbean.com/ https://sounth.de https://www.facebook.com/tim.heinrich.524/ https://www.instagram.com/tim_heinrich/ Facebook Gruppe 'Filmmusik komponieren & Sounddesign': https://www.facebook.com/groups/309751689699537 Perfekte Orchester-Mockup-Balance: Orchestra Guide https://www.sounth.de/orchestra-guide/ Dieses Video ist auch auf YouTube zu sehen: https://youtu.be/b0-FrbImqCM

Why the Most Profitable Prompt Engineers Never Call Themselves That Episode Summary Online entrepreneurship myths are costing AI entrepreneurs thousands. In this episode, we expose why the anti-AI approach to building freelance income ideas is the secret weapon parents are using to escape the side gig treadmill—and how rejecting commodity AI tools unlocks real, sustainable income. Based on years of contrarian insights. https://DarkHorseEntrepreneur.com Sponsor: https://Hostinger.com/DARKHORSE20 and use code DARKHOUSE20 for 20% off. Discover how to build a six-figure "invisible" AI consulting business by positioning yourself as a workflow optimization specialist rather than an AI consultant. Learn the exact language, positioning strategies, and retainer models that land enterprise contracts paying $2,500-$5,000 monthly - all while keeping the AI technology completely invisible to clients who just want their problems solved. Key Moments 00:00 - Opening: 34-year-old built an invisible B2B prompt agency 01:10 - The Core Problem: Most people selling the wrong thing to the wrong people using the wrong language 02:05 - The Enterprise Truth: Fortune 500 companies don't buy AI - they buy outcomes. 04:10 - The Language That Sells: Instead of "AI prompt engineer," you say 06:15 - The Retainer Model: the MRR that separates this from every other AI side hustle. 07:05 - The Credibility Requirements 09:40 - The Budget Reality 10:25 - The Uncomfortable Truth 13:25 - The Whiskered Wisdom Resources Mentioned AI Escape Plan Newsletter: For parents ready to break free from the 9-to-5 grind Workflow optimization vs. AI consulting positioning Enterprise compliance requirements (SOC 2, data handling practices) Industry association strategies for credibility building Sponsor: https://Hostinger.com/DARKHORSE20 and use code DARKHOUSE20 for 20% off. Action Item Identify one business process that takes more than 5 hours per week and involves repetitive decision-making. Document it step-by-step, time each step, and note where delays and errors occur - this becomes your first "process audit" that enterprises will pay thousands to create.  

Free: Build an AI Data Analysis Agent in Codex https://clickhubspot.com/eqfk Ep. 429 Is AI-powered data analysis light years away from replacing humans?  Kipp and guest Sundas Khalid (data science and AI leader) dive into how agentic analytics is transforming data science, what human judgment still brings to the table, and how to master cutting-edge AI tools for your work.  Learn more on how to leverage Codex and other AI tools for real-world data analysis, the crucial mindset shifts and skills every data-driven professional needs, and why asking the right questions—and validating AI output—will set you apart in the age of agentic analytics. Mentions Sundas Khalid https://www.youtube.com/sundaskhalid Codex https://openai.com/codex/ Gemini https://gemini.google.com/ Claude https://claude.ai/ Get our guide to build your own Custom GPT: https://clickhubspot.com/customgpt Resource [Free] Steal our favorite AI Prompts featured on the show! Grab them here: https://clickhubspot.com/aip We're on Social Media! Follow us for everyday marketing wisdom straight to your feed YouTube: ​​https://www.youtube.com/channel/UCGtXqPiNV8YC0GMUzY-EUFg  Twitter: https://twitter.com/matgpod  TikTok: https://www.tiktok.com/@matgpod  Thank you for tuning into Marketing Against The Grain! Don't forget to hit subscribe and follow us on Apple Podcasts (so you never miss an episode)! https://podcasts.apple.com/us/podcast/marketing-against-the-grain/id1616700934   If you love this show, please leave us a 5-Star Review https://link.chtbl.com/h9_sjBKH and share your favorite episodes with friends. We really appreciate your support. Host Links: Kipp Bodnar, https://twitter.com/kippbodnar   Kieran Flanagan, https://twitter.com/searchbrat  ‘Marketing Against The Grain' is a HubSpot Original Podcast // Brought to you by Hubspot Media // Produced by Darren Clarke.

If you started your podcast and were surprised at the amount of time and effort that goes into it, you're not alone. Luckily, there are practical ways you can simplify your podcast workflow and save time in the process. This week, episode 38 of Successful Podcasting Unlocked answers the question: How can I simplify my podcast workflow?In this episode, I share:Identify the bottlenecks in your workflow and consider outsourcing the time consuming tasks, such as editing and social media promotion. Streamline production by batching tasks and using templates for repetitive elements. Leverage tools like Calendly and ClickUp to easily manage scheduling and workflow. Optimize your recording and editing by using tools like Riverside and Descript. Repurpose your podcast content for promotion across different platforms, using a social media scheduler to save time. Be sure to download the FREE Podcast Workflow Checklist to keep your workflow on track!Be sure to tune in to all the episodes to receive tons of practical tips, tricks, and advice as I answer all your podcasting questions. Thank you for listening! If you enjoyed this episode, take a screenshot of the episode to post in your stories and tag me! And don't forget to follow, rate and review the podcast and tell me your key takeaways!CONNECT WITH ALESIA GALATI:InstagramLinkedInWork with Galati Media! LINKS MENTIONED:Ep 3: Where to Find Quality Guests for Your PodcastPodmatch*ClickUp*Riverside*Meet Edgar**Affiliate LinkProud member of the Feminist Podcasters Collective.

Hello voices from the bench community, John Wilson here and I wanted to share some news about the evolution of the Programill lineup. Most importantly, Ivoclar's new PrograMill 7. What stands out right away is the reduced air consumption this mill requires, but what you'll notice first is that impressive new touchscreen. For us, the biggest advantage has been increased spindle power. My laboratory's known for these larger cases with complex geometries, and I can tell you that extra power really makes a difference. Next time you see your Ivoclar representative, be sure to ask about the PrograMill 7 and tell them John Wilson sent you. Thank you. At exocad Insights in beautiful Mallorca, we finally caught up with Felix from Imagine USA—and the timing couldn't have been better. As an exocad dealer on the front lines of digital dentistry, Felix shared his excitement about the strong turnout, the familiar faces, and most importantly, the innovation coming from exocad. What stood out most? The new exocad Hub and its cloud-based capabilities, along with powerful AI-driven tools inside DentalDB designed for efficient batch processing. For Felix and the Imagine team, it's not just about seeing what's new—it's about putting it to the test. By running new features through their own production facility first, they ensure real-world performance before bringing solutions to their customers. Beyond the technology, Felix emphasized the value of being there in person—connecting face-to-face with partners, having meaningful conversations, and stepping back to see where the industry is headed. And of course, doing it all in Mallorca doesn't hurt either. Mallorca, Spain. exocad Insights 2026 Three completely different conversations somehow all landed on the same theme: digital dentistry keeps getting smaller, smarter, and way more connected. First up, the crew catches back up with digital designer and educator Marjorie de Andrade, who went from Brazil to New Zealand chasing opportunity, only to end up building a global career through remote design, social media, and education. Marjorie talks about creating the Mastering exocad course, freelancing for dentists around the world, and why finding purpose through teaching became more important than simply designing crowns. She also shares thoughts on the newly announced exocad Hub, remote collaboration, and how digital dentistry is making communication between dentists and technicians easier than ever. Then the microphones turn to Dr. Dwight Pate for one of the most workflow-heavy conversations the podcast has ever had. From hand waxing cases the old-school Dawson and Pankey way to designing provisionals and controlling full-mouth rehabs completely through exocad, Dr. Pate breaks down how he combines analog principles with digital workflows. The discussion dives deep into occlusion, provisionals, articulators, guided workflows, AI design, and why he believes digital dentistry still has to prove itself back in the analog world before it ever reaches the patient's mouth. Finally, the crew reconnects with Dr. Eimear O'Connell to talk about why clinicians need to attend events like Insights just as much as technicians. Eimear shares how digital workflows are improving communication between doctors, labs, and patients while making implant planning, dentures, and aesthetic dentistry more predictable than ever. From digital dentures that fit with almost zero adjustment to helping patients emotionally reconnect with their smiles, the conversation reminds everyone that behind every scanner, workflow, and software update is still a real person whose life changes because of dentistry.Special Guests: Dr. Dwight Pate, Dr. Eimear O'Connell, and Marjorie de Andrade .

Every Week How many times this week did you build a treatment plan from a completely blank page? I'm going to call it what it is: a tax. The hidden tax of starting from scratch, not just with new clients, but the third, fourth, fifth consult too. And honestly, it is quietly exhausting, isn't it. This week we are getting into:Why that scramble happens, why we resist the very thing that would fix it, and what to do about it. The real reason your consults feel heavier than they should Why "every client is different" is actually keeping you stuck Where to start so you can walk into your next consult feeling prepared, not scrambling _________________Strategy Lab members, your continuation of this episode is waiting for you inside Podia along with the June mentoring workbook. By the time you work through it you will have your four clinical templates built, your consults will stop starting from zero, and that pile up at the end of the week gets a whole lot smaller. Go and have a look. Not in the Lab yet? Jump in at https://www.geraldineheadley.com/strategy_lab and come and do this work with us.

Postproduction mit Nuendo: In diesem zweitägigen Praxis-Workshop für Audio-Postproduktion, Filmton und Sounddesign arbeiten wir gemeinsam an einem echten Trailer und durchlaufen professionelle Workflows von Dialog Editing über Sounddesign bis zur finalen TV-Mischung. Statt isolierter Tutorials oder theoretischer Präsentationen steht die praktische Arbeit im Mittelpunkt. Wir beginnen bei der Projektanlage und dem Session-Setup, importieren die Daten, organisieren das Projekt, bearbeiten Dialoge, entwickeln Sounddesign-Elemente und erstellen eine sendefähige Mischung für TV sowie Versionen für Social Media. Themen unter anderem: • Projektimport & Session-Setup • Dialog Editing & Cleanup • Sounddesign für Film • Foley • Automation • ADR / Nachsynchronisation • Mischung für TV (-23 LUFS) • Mischung in 5.1 • Templates & effiziente Workflows • Plug-ins & Tools im täglichen Einsatz • Export, Stems & Deliverables Der Workshop findet in meinem Tonstudio in Köln statt und ist bewusst auf maximal 7 Teilnehmer begrenzt. Dadurch bleibt genügend Zeit für Fragen, individuelle Themen und praktische Übungen. Eigene Rechner und eigene Projekte sind ausdrücklich willkommen. Wer möchte, kann direkt an seinem eigenen Workflow arbeiten und konkrete Fragen aus dem Arbeitsalltag mitbringen.

Have you ever stopped to think about the technology powering almost every text box you interact with online? Whether you're applying for a job, drafting a legal contract, publishing content, or updating a website, there's a good chance a rich text editor is quietly working behind the scenes. In this episode of Tech Talks Daily, I caught up with Fredrik Danielsson, Product Manager at TinyMCE, to discuss how one of the internet's most widely used editing platforms is evolving for the AI era. Frédéric shares the remarkable story behind TinyMCE, a tool that traces its roots back to the early days of the web and has played a role in creating much of the internet's human-generated content. From the days of hand-coded websites and Flash applications to today's AI-powered content workflows, we explore how the company has continually adapted to changing developer and user needs. Our conversation focuses on the launch of TinyMCE AI and why the company believes artificial intelligence belongs inside the content creation experience rather than in a separate chatbot window. We discuss the hidden productivity costs of constantly switching between applications, copying and pasting content between AI assistants and business tools, and why bringing AI directly into the editor creates a more natural and efficient workflow. We also examine the growing challenges around AI governance, content ownership, compliance, and accountability. As organizations race to adopt AI tools, how can they maintain visibility into which content was AI-assisted, who made changes, and how information flows through the business? Frédéric explains why features such as revision history, track changes, and audit trails may become increasingly important as regulations and expectations mature. Along the way, we discuss context-aware AI, model flexibility, developer experience, and the future of content creation. Frédéric also shares his thoughts on why AI adoption is becoming more natural for everyday users and what the next phase of AI-powered productivity could look like as these tools become deeply embedded in the software people already use. If AI is changing how we create, edit, review, and collaborate on content, what happens when the editor itself becomes the smartest participant in the room? And how will that reshape the way we work over the next few years?

Episode 91 |

Summer canning doesn't have to mean marathon weekends, Pinterest-perfect pantries, or preserving every tomato you grow. In this episode, we're talking about what summer canning actually looks like in a busy suburban home—from deciding what's worth canning and using a two-day workflow to freezing harvests, preserving in small batches, and fitting it all into real life with kids. If you've ever felt overwhelmed by food preservation, this episode will help you create a canning rhythm that works for you.   https://thehomesteadchallenge.com/canning-tips/  

Claude is not just another AI tool lawyers can chat with. It may be a preview of where legal work is heading. In episode 619 of the Lawyerist Podcast, Zack Glaser talks with Sam Harden about Claude, Claude for legal, and the growing role of AI in law firm workflows.  Sam breaks down how Claude can work with documents, folders, PDFs, Word files, and connected legal tools in ways that go far beyond simple prompting. They discuss the difference between Claude Chat, Claude Cowork, connectors, and skills, and why those distinctions matter for lawyers trying to understand what AI can actually do.  They also explore why law firms should not rush into automation without first building better systems. From deposition summaries to document creation to legal research support, this episode explains how AI can become more useful when it is guided by strong processes, clear instructions, and thoughtful implementation.  Listen to our previous episodes on Artificial Intelligence and the Future of Legal Practice.  #612: AI for Lawyers: What You Need to Know Before Your Clients Do, with Cat Casey  Apple | Spotify | LTN  #601: Beyond Chatbots: Using Agentic AI in Law Firm Intake, with Matt Spiegel Apple | Spotify | LTN  #590: Innovating Without Overwhelm: Practical AI Tips for Lawyers, with Graydon Trusler Apple | Spotify | LTN   #587: Future-Proofing Your Firm in the Age of AI, with Jack Newton Apple | Spotify | LTN   #577: Rethinking Law Firm Growth in the Age of AI, with Sam Harden Apple | Spotify | LTN     Have thoughts about today's episode? Join the conversation on LinkedIn, Facebook, Instagram, and X!   If today's podcast resonates with you and you haven't read The Small Firm Roadmap Revisited yet, get the first chapter right now for free! Looking for help beyond the book? See if our coaching community is right for you.   Access more resources from Lawyerist at lawyerist.com.   Chapters / Timestamps:  00:00 – Introduction  00:34 – Why Claude for Legal Matters  01:28 – Live Crabs and Work from Home Chaos  07:04 – Setting Up the Conversation  07:29 – Meet Sam Harden  08:04 – What Lawyers Should Watch with Claude  10:14 – What Claude Actually Is  11:16 – How AI Moved Beyond Chat  12:07 – From Claude Code to Claude Cowork  13:22 – How Claude Works with Documents  15:20 – Why Claude Cowork Is a Big Shift  15:45 – Creating Documents and Presentations  16:52 – Claude Chat vs. Cowork vs. Code  18:12 – Legal Plugins and Connectors  19:30 – Reducing Context Switching with AI  20:49 – Connecting Claude to Legal Tools  22:24 – What Legal Connectors Can Do  24:47 – MCP, Tools, and Connector Limits  26:37 – What Claude Skills Are  28:44 – Why SOPs Come Before AI Skills  29:43 – Using Skills for Legal Documents  30:35 – AI Skills for Deposition Summaries  31:14 – Combining Connectors and Skills  32:15 – Teaching Claude Like a Team Member  33:11 – Choosing the Right Skill  34:00 – How Bad Instructions Create AI Risk  35:49 – Building Better Skills and Plugins  37:13 – What Comes Next for Claude for Legal 

Growth does not get blocked by lack of hustle; it gets blocked by lack of structure. I sit down with Antwon Person, founder of Skillful Brands and a retired U.S. Army senior officer, to talk about what actually helps entrepreneurs move from scattered effort to a real company that can scale. If you have ever felt buried in tasks, unsure what to build next, or stuck at a “growth ceiling,” this conversation gives you a clear path forward.We get practical about the three S's Antoine teaches: structure, systems, and strategy. We talk about why many businesses stall instead of failing, how mentorship and mastermind communities help you break past your current level of knowledge, and why the first six months matter so much for business structure, asset protection, and future financing. If you want business credit or loans later, the foundation you lay early makes a difference.We also dig into modern remote leadership. Antoine shares how he runs a virtual headquarters that feels like a real office, with coworking spaces and meeting and training rooms, so remote teams can collaborate without endless email chains. Then we get into delegation and virtual assistants: when to hire, why a manager can free you up for strategic growth, and how SOPs and a solid onboarding process turn VAs into assets instead of added stress.If you find value here, subscribe, share the episode with a founder friend, and leave a quick review so more entrepreneurs can build with clarity.Learn more at SkillfulBrands.comSend us a messageBuzzsprout - Let's get your podcast launched!Start for FREEAltogether Domains, Hosting and MoreBringing your business online - domain names, web design, branded email, security, hosting and more.Digital Marketing PlatformContent Creator Machine - The integrated all-in-one online marketing platform.Small Business Legal ServicesYour Small Business Legal Plan can help with any business legal matter.Mens and Womens HatsSince 1972, American Hat Makers has been dedicated to the art of fine hat making.Disclaimer: This post contains affiliate links. If you make a purchase, I may receive a commission at no extra cost to you.Support the showWant to be a guest on Tech Diva Biz Talks? Send Audrey Wiggins a message on PodMatch, here: podmatch.com/hostdetailpreview/audreywigginsTo work with Audrey schedule a breakthrough/discovery session.

Audio from recent webinar, sponsored by Angiodynamics.  This webinar focuses on optimizing the overall efficiency of the thrombectomy procedure for pulmonary embolism (PE), with an emphasis on the AlphaVac Mechanical Thrombectomy System. Experts will explore strategies for managing blood loss during the procedure, improving patient outcomes, and streamlining workflow for faster, more effective treatment. The session will highlight how the AlphaVac system can enhance these aspects, leading to better recovery and more efficient clinical practices in PE management. Featuring the following speakers: Dr. Sabah Butty  Dr. Peter Monteleone Dr. Brian Stegman

In this episode, Matt & Lauren reveal the workflows the Lulu team has been refining for years, built to grow, scale, and streamline content marketing. Whether you're writing your next book, producing a podcast episode, or scheduling a simple social media post, reframing your approach makes your work easier and gives you back time to do more of what you love. Listen as we break it down into these steps: 1️⃣ Creation2️⃣ Production3️⃣ Distribution 4️⃣ Marketing5️⃣ Sales6️⃣ Fulfillment7️⃣ InsightOr watch the episode on YouTube!Dive Deeper

In this episode, COPYCATT dives into bass music sound design and Ableton workflows—breaking down a track, talking clipping vs limiting, fun stories, and sharing tools for getting movement and character. We'll talk about waveshaping, feedback experiments, and a few Live 12.4 favorites.COPYCATT (Andre) is an Australian-based producer with a dedicated following in the neuro/ hip-hop/ bass scene, known for his unique sound design. His collaborations include working with artists like Frequent and Mr. Bill, and his tracks have been performed by acts such as Pretty Lights, Haywyre, Mr Carmack, Tipper, Excision, and more. Since his first release in 2015, COPYCATT has built a cult following around 90's hip hop-inspired grooves, hard-hitting snares, and bone-rattling sub basses—and he also releases sample packs and video tutorials to share his production process.Follow COPYCATT below:⁠https://soundcloud.com/itscopycatt⁠⁠https://instagram.com/itscopycatt⁠https://discord.com/invite/9cW8HnszvfGrab limited-edition Producer Merch & save 10% with the code "podcast":⁠https://www.abletonpodcast.com/merchJoin the newsletter to get free downloads, early episode access, and upcoming events.⁠https://www.abletonpodcast.com/newsletter

The newspaper comic strip didn't go extinct — it evolved. But if your work doesn't keep up, your career may be fossilized! From Reddit-ready square comics to vertical-scroll storytelling, they explore how creators are adapting to phones, social media, and changing reading habits while keeping the heart of the comic strip alive. Topics covered The evolution of newspaper comic strips Why horizontal strips existed in the first place How phones changed comics formatting Square-format comics on Reddit and social media Vertical-scroll storytelling Why readers won't rotate their phones Charles Schulz and the flexible-format origins of Peanuts Newspaper syndication vs. modern web distribution YA graphic novels as the next evolution for newspaper strips Lincoln Peirce and the success of Big Nate books Why comic strips are still thriving online Modular comic formatting for webcomics The launch of The Comic Scout  Dave Kellett's Hugo Award nomination anticipation Tips for maintaining visual consistency in comics Workflow advice for newer cartoonists   You get great rewards when you join the ComicLab Community on Patreon$2 — Early access to episodes$5 — Submit a question for possible use on the show AND get the exclusive ProTips podcast. Plus $2-tier rewards.If you'd like a one-on-one consultation about your comic, book it now!Brad Guigar is the creator of Evil Inc and the author of The Webcomics Handbook. He is available for personal consultations. Dave Kellett is the creator of Sheldon and Drive. He is the co-director of the comics documentary, Stripped.

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

A lot of indie creators feel stuck between keeping things simple and wondering if they're already falling behind by not doing video. The morning show cast and crew wrestle with that pressure head-on, from whether platforms are pushing video because audiences actually want it, to how much extra work creators are expected to absorb just to stay visible. Listeners say they want audio, yet every platform insists video is the future. Do people actually watch these videos or just let them play in the background while doing something else? Every platform suddenly acts like the future is obvious and you're the only one not fully convinced. By the end, the real question isn't whether video podcasting is worth it. It's whether chasing every shift in the industry pulls you further away from the show you actually wanted to make.Episode Highlights:[01:55] Community Spotlight Invite[04:20] Podcast Activity Numbers[05:53] Spotify Business Top Five[10:48] Spotify vs. YouTube Data Bias[15:11] Blubrry and Podpage Partnership[21:56] Websites, SEO, and Ownership Debate[33:24] Podcasting Events Roundup[37:24] Paramount's Podcast Strategy[39:03] Spotify Adopts HLS[43:04] Is Video Worth It?[49:55] Workflow and Discovery Tips[52:54] Audio vs. Video Psychology[58:04] Wrap-Up and Tomorrow's ShowLinks & Resources:Podpage:https://www.podpage.com/?via=ironickmediaFeature Your Podcast on the Podcasting Morning Show:https://PodcastingMorningShow.com/spotlightThe Podcasting Morning Show:⁠⁠www.podcastingmorningshow.com⁠⁠Ways to Watch or Listen:⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠https://www.podcastingmorningshow.com/joinus/Meet the PMS Cast and Crew:⁠⁠https://podcastingmorningshow.com/people⁠⁠Join The Empowered Podcasting Facebook Group:⁠⁠www.facebook.com/groups/empoweredpodcasting⁠⁠⁠Book A Free Call With Marc:https://calendly.com/ironickmedia/freestrategycallApplication To Submit Your Show For Evaluation:⁠⁠⁠⁠⁠https://podcastingmorningshow.com/eval⁠⁠Join us every other Monday at 8 AM ET for the Obsession Worthy Podcasts:⁠⁠⁠http://podcastingmorningshow.com/owp/⁠⁠Join us LIVE every weekday morning at 8 am ET (US) on ⁠Clubhouse⁠: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://podcastingmorningshow.com/clubhouse⁠⁠EPC3 Speaker Application:⁠⁠ ⁠https://empoweredpodcasting.com/speakersPowered by⁠⁠⁠ ⁠iRonickMedia.com⁠⁠⁠⁠ and⁠ ⁠ContentCreatorsAccountant.com⁠⁠Send in your mailbag questions:⁠⁠⁠⁠ https://www.podcastingmorningshow.com/contact/⁠⁠⁠⁠ or ⁠marc@ironickmedia.com⁠Want to be a guest on The Podcasting Morning Show? Send me a message on PodMatch, here:https://podmatch.com/hostdetailpreview/1729879899384520035bad21b

Today we're talking about a significant shift taking place in artificial intelligence during the first half of 2026.For the last three years, most of the attention has been focused on foundation models. Which company has the most powerful language model? Which model scores highest on the benchmark? Which one can write code, pass exams, summarize documents, or generate images?That phase is not over. The models are still improving. But the easy gains appear to be behind us. The bigger story is no longer simply about training a larger model. The bigger story is integration.In other words, AI is moving from the lab into the workflow.That sounds simple, but it has enormous implications.There are really two movements happening at the same time.--------------**Real Estate Espresso Podcast:** Spotify: [The Real Estate Espresso Podcast](https://open.spotify.com/show/3GvtwRmTq4r3es8cbw8jW0?si=c75ea506a6694ef1)   iTunes: [The Real Estate Espresso Podcast](https://podcasts.apple.com/ca/podcast/the-real-estate-espresso-podcast/id1340482613)   Website: [www.victorjm.com](http://www.victorjm.com)   LinkedIn: [Victor Menasce](http://www.linkedin.com/in/vmenasce)   YouTube: [The Real Estate Espresso Podcast](http://www.youtube.com/@victorjmenasce6734)   Facebook: [www.facebook.com/realestateespresso](http://www.facebook.com/realestateespresso)   Email: [podcast@victorjm.com](mailto:podcast@victorjm.com)  **Y Street Capital:** Website: [www.ystreetcapital.com](http://www.ystreetcapital.com)   Facebook: [www.facebook.com/YStreetCapital](https://www.facebook.com/YStreetCapital)   Instagram: [@ystreetcapital](http://www.instagram.com/ystreetcapital)  

The rise of Private AI Systems has created a rush of developers trying to bolt AI onto everything they touch. But the developers who are actually creating long-term value are approaching AI differently. They are not starting with hype. They are starting with friction. In this interview, Matt Levenhagen shares a practical perspective on AI adoption that cuts through most of the noise surrounding modern tooling. Instead of trying to launch the next AI startup immediately, he focused on solving operational problems inside his own business first. That shift in mindset changes everything. About Matt Levenhagen Matt is the founder and CEO of Unified Web Design, a web development agency focused on custom solutions, WordPress development, e-commerce, memberships, and business systems. His background as both a builder and agency owner gave him a unique perspective on where AI creates real leverage instead of superficial automation. Follow Matt on LinkedIn. Private AI Systems Start with Operational Friction Most developers approach AI backward. They start with the technology and search for a use case later. Matt described taking the opposite path. He recognized that AI was becoming foundational technology and knew he needed hands-on experience with it. But instead of building a flashy product immediately, he asked a more important question: What problems already exist inside the business? That led him toward creating internal systems capable of understanding business context, workflows, client history, and operational memory. This matters because AI becomes exponentially more valuable when connected to existing processes. A chatbot with no context is a novelty. A system that understands your operations becomes infrastructure. The strongest AI products often begin as internal tools before becoming commercial products. Why Developers Need Persistent Business Memory One of the most important ideas Matt discussed was memory. Traditional SaaS AI tools often operate inside isolated conversations. They respond to prompts but lack continuity and deep operational understanding. Matt wanted something different: a system capable of remembering his business. That distinction is critical. Most businesses lose enormous amounts of value through fragmented information: Past client solutions Process documentation Internal discussions Technical decisions Workflow patterns Sales conversations Without persistent memory, every project starts partially from scratch. Matt envisioned a system that could recognize patterns and surface relevant historical information automatically. Instead of manually searching documentation or task systems, the AI could identify relationships between past work and current problems. This transforms AI from a content generator into an operational assistant. Private AI Systems Reduce Dependency on Generic SaaS AI A major challenge businesses face today is the rapid AI feature expansion inside existing software platforms. Every tool suddenly has "AI." Slack ClickUp HubSpot Email platforms CRM systems But Matt pointed out an important limitation: most embedded AI features solve narrow tasks. They summarize. They search. They auto-generate drafts. Useful? Yes. Transformational? Usually not. The reason is simple. These systems only understand fragments of your business. A privately controlled AI layer can aggregate context across multiple systems instead of remaining trapped inside individual platforms. That allows developers to build workflows tailored to how the business actually operates. This is where builders gain an advantage over passive software consumers. Adding AI to a workflow does not automatically improve the workflow. Poor systems become faster poor systems. The Real Advantage of Building Internal AI First One of the smartest strategic decisions Matt described was delaying external commercialization. That sounds counterintuitive in startup culture, where speed dominates every conversation. But internal development creates several advantages: 1. Lower Risk Mistakes affect internal operations instead of customers. 2. Faster Iteration Developers can experiment without worrying about public perception. 3. Better Understanding Builders learn where AI genuinely helps versus where it creates friction. 4. Operational Integration The system evolves naturally around existing workflows. This mirrors how many successful SaaS products originated historically. Internal tooling frequently becomes productized later because the creator already understands the operational problem deeply. Developers often skip this stage entirely and immediately chase scale. That usually leads to shallow products solving imaginary problems. Private AI Systems Force Better Architectural Thinking One of the deeper technical themes in the conversation involved memory architecture and contextual retrieval. Matt discussed implementing approaches like RAG (Retrieval-Augmented Generation) to avoid loading massive amounts of irrelevant context into every interaction. This highlights a major evolution happening in software development right now. AI development is becoming less about prompting and more about architecture. The real engineering challenge is: What information matters? When should it be retrieved? How should context be structured? What belongs in memory? What should remain isolated? Developers who understand contextual architecture will build significantly more valuable systems than developers focused purely on model experimentation. The future competitive advantage in AI may come less from the model itself and more from how businesses structure and retrieve institutional knowledge. Why the "Builder Mindset" Matters More Than the AI Stack One of the strongest themes throughout the episodes was mindset. Matt consistently approached AI as a builder, not as a trend follower. That mindset changes how decisions get made: Start with business friction Solve operational problems Build incrementally Learn through implementation Protect flexibility Focus on systems over hype This approach is far more sustainable than chasing every new AI release. The tools will continue changing rapidly. The builder mindset remains valuable regardless of which model dominates next year. Identify one repetitive workflow in your business this week and document how information moves through it before introducing AI. Conclusion Private AI Systems represent a shift away from generic automation and toward operational intelligence. Matt Levenhagen's approach demonstrates an important principle for developers and founders alike: the most valuable AI solutions are often built by deeply understanding your own workflows first. Instead of asking: "How do I add AI?" The better question becomes: "Where does my business repeatedly lose time, context, or knowledge?" That question leads to systems that create leverage instead of noise. Stay Connected: Join the Developreneur Community

In today's episode, Tyler Cagwin of Nostalgia Chocolates gives advice for craft chocolate makers on selling cacao nibs and other ingredients to craft breweries. Tyler has sold cacao to many breweries in upstate New York and now in North Carolina, and it's become a substantial part of his business at Nostalgia. Here he walks us through things to consider in advance, how to approach prospective brewery partners, what he presents when he meets with them, how he builds these relationships, and how he schedules cacao roasting for his brewery customers in his regular chocolate production schedule.This interview is filled with great advice for craft chocolate makers who would like to begin working with breweries. At the end, we also talk about the newest edition of Nostalgia's Hop Aged bar.You can listen to my past episode with Tyler here. You can also read a blog post about his Hop Aged bar here, and his work with New York breweries here.Episode timeline (approximate):1:00 - Introduction3:10 - How Tyler got started selling to breweries6:30 - The knowledge level of brewers in regards to cacao13:55 - Consistent questions he expects15:10 - Info he provides proactively17:20 - Pricing and sticker shock21:50 - Workflow for providing nibs23:55 - Marketing and co-branding28:45- Production schedule considerations29:55 - Roasting profiles31:45 - Impact on his own cacao bean orders35:40 - Providing husks and other ingredients39:25 - Final thoughts on selling to breweries42:20 - Hop Aged bar Check out David's book Pairing Beer & Chocolate: A Guide to Bringing the Flavors of Craft Beer and Craft Chocolate Together.Follow Bean to Barstool on social media!InstagramFacebookPinterestSign up for host David Nilsen's beer newsletter for regular beer musings, and the Bean to Barstool newsletter for pairings, collaborations, and maker profiles.

Leveraging AI for Business Efficiency and Workflow AutomationExplore how AI is revolutionising operational workflows, replatforming and client collaboration in ecommerce.This episode delves into practical applications, strategic insights and real-world examples from industry experts on integrating AI into business processes to enhance productivity, quality and value.We discuss how even imperfect AI models can vastly increase operational efficiency through automation and scaling, but explain why human experts are needed to provide sensible guardrails and oversight.Here's what you'll get from this episode:The evolution of AI in agency workflows and internal operations at leading agency Tom & Co.Practical uses of agentic versus transactional AI, including long-term memory solutions.Automating data cleansing, prototyping and content generation with AI tools like Claude and ChatGPT.Building smarter workflows with AI-driven decision-making and human-in-the-loop governance.How AI can reduce grunt work in ecommerce, freeing teams for higher-value tasks.Examples of AI supporting client needs, from statement of work creation to inquiries and service desk automation.Strategic shift from code writing to system architecture and oversight skills.This episode showcases how pragmatic AI integration can transform operational efficiency, empower teams and deliver measurable business outcomes. Whether you're an agency, vendor or ecommerce business, these insights could help you harness AI for your next growth phase.Key topics & timings:[00:45] - Guest introductions and background.[02:45] - AI's impact on ecommerce development.[05:30] - Trends in AI adoption within agencies and project workflows.[07:10] - How AI is changing / replacing developer roles.[11:00] - Replatforming made easier with AI: speed, risk reduction and quality.[13:40] - Claude Design's capabilities and benefits.[17:13] - Examples of AI facilitating project management, code analysis and client reporting.[19:20] - Simplifying prompt engineering and accessibility for non-technical teams.[20:50] - AI in documentation, cross-referencing and long-term memory strategies.[26:45]- AI-generated designs, presentations and brand-compliant assets.[30:50] - Internal use of AI at Tom & Co: workflow automation for efficiency.[35:05] - Workflow automation for client briefs, code insights and statement of work creation.[39:05 ]- Human-in-the-loop governance and risk mitigation strategies.[45:10] - Managing AI context limitations: long-term memory and retrieval strategies.[51:50] - The broader opportunity of AI for operational and marketing efficiencies.

How do freelance paralegals ACTUALLY work with law firms remotely? How are files shared? Where do projects live? How do attorneys delegate work? And how do independent paralegals avoid complete operational chaos while managing multiple firms?

The culture is obsessed with speed, scale, lean teams, massive output, and automation, but faster output does not automatically mean better direction. In part two of this connected conversation, the focus shifts to the missing human layer underneath AI-powered growth and the belief that more content, more automation, and more velocity always lead to better outcomes. Using S³ Growth Streams™ as the operating lens, you will learn how to strategize before accelerating, synergize before scaling, and systemize before sprinting forever. More importantly, you will see how to separate signal from noise, align tools with real human capacity, and build repeatable rhythms that support growth without requiring constant sacrifice. This episode is not anti-AI, anti-hustle, or anti-ambition. It is anti-default sacrifice, anti-permanent sprint, and anti-output without awareness. It also challenges the obsession with flow state by introducing five operating states that support sustainable growth: capture, clarity, commitment, flow, and reflection. Because flow is not the whole game. Sometimes the most productive thing you can do is capture the signal, get clarity, commit to the right action, recover, reflect, and return to baseline before sprinting again. The goal is not to become more machine-like. The goal is to become more intentionally human while using machines wisely. Beyond The Episode Gems: Buy My Book, Strategize Up: The Blueprint To Scale Your Business: StrategizeUpBook.com Discover All Podcasts On The HubSpot Podcast Network Get Free HubSpot Marketing Tools To Help You Grow Your Business Grow Your Business Faster Using HubSpot's CRM Platform Support The Podcast & Connect With Troy:  Rate & Review iDigress: iDigress.fm/Reviews Follow Troy's Socials @FindTroy: LinkedIn, Instagram, Threads, TikTok Subscribe to Troy's YouTube Channel For Strategy Videos & See Masterclass Episodes Need Growth Strategy, A Keynote Speaker, Or Want To Sponsor The Podcast? Go To FindTroy.com

SMJC FULL Class 35 LIVE Demo 2: Create a Quote Graphic in Adobe Express (Export + Organize Workflow) … This is a BONUS FULL CLASS from our Private Classes for Social Media Jungle Club!Learn More and Join Us at https://socialmediajungle.club/ … This is our regular SMJC check-in with a BONUS DEMO (Demo 2) you can copy anytime you need to create content quickly. Watch me create another Quote Graphic in Adobe Express, then export it and organize both the image and the caption text so it's ready to schedule later. Listen https://www.askawebgeek.com/wp-content/uploads/35-SMJC-Class-35-YT-DEMO-2-Quote-Graphic.mp3 Download Episode In this class, you'll see: How I build a clean quote graphic in Adobe Express How I export and name the file for easy organization How I save and organize the caption text for reuse How I prep everything so posting later is fast and painless Want to watch me schedule the post in Buffer too? Check out LIVE Demo: Create a Quote Graphic and Schedule It in Minutes (Adobe Express + Buffer) Ask a Web Geek: Join our FB group: See Ask a Web Geek (@FB) Jump into our ongoing conversations! What are YOUR questions? How can we HELP YOU? More Resources: More Resources & links at Jungle-Studios.com/resources BONUS Trainings and Resources! Refer to / Browse https://jungle-studios.com/meet-cj Related Episodes SMJC35 – LIVE Demo 2: Create a Quote Graphic in Adobe Express (Export + Organize Workflow) by CJ Gilbert | May 18, 2026 | EpisodesSMJC FULL Class 35 LIVE Demo 2: Create a Quote Graphic in Adobe Express (Export + Organize Workflow)... This is a BONUS FULL CLASS from our Private Classes for Social Media Jungle Club!Learn More and Join Us at https://socialmediajungle.club/ ... This is our regular... SMJC33 – LIVE Demo: Create a Quote Graphic and Schedule It in Minutes (Adobe Express + Buffer) by CJ Gilbert | May 4, 2026 | EpisodesSMJC FULL Class 33 LIVE Demo: Create a Quote Graphic and Schedule It in Minutes (Adobe Express + Buffer)... This is a BONUS FULL CLASS from our Private Classes for Social Media Jungle Club!Learn More and Join Us at https://socialmediajungle.club/ ... Want a repeatable... New Topics Discussed Weekly Join our Facebook Group Today! Want to Join Us? Join our FB Group to Ask a Question and Participate LIVE Play / Watch / Listen 1.) Join Us on Facebook 2.) Watch on YouTube 3.) Follow Us on Twitter 4.) Listen by Podcast Apple Podcasts | Google Podcasts | RSS

Send us Fan MailYou're being consistent on Pinterest. You're showing up, pinning regularly, doing everything everyone told you to do. But your Pinterest still feels like it's going nowhere.Here's what nobody tells you: consistency on Pinterest isn't just about how much you pin. It's about HOW you pin. There's a specific workflow problem that makes even the most consistent pinners invisible, and I'm showing you exactly what it is.What you'll learn:The real consistency problem most Pinterest advice gets wrongWhy "batching 20 pins on Sunday" actually hurts your growthThe under-one-hour weekly workflow that builds real momentumHow to use pin spacing to work WITH the algorithm instead of against itWhy bursts followed by gaps reset your momentum every single timeNew videos every Thursday!

Send us Fan MailAI feels like it should be a shortcut to productivity, yet most teams still struggle to turn pilots into real business value. We sit down with Karina Arteaga, CEO and founder of Visible Global and former operations leader at Meta Reality Labs, to unpack the uncomfortable reason: AI projects fail less because the tech is weak and more because the organisation is unclear, messy, or misaligned. If your objectives, decision-making, and workflows are broken, automation just scales the chaos.We explore what it takes to build a human AI operating model that actually works in the real world, where people have fears, incentives, and habits.Karina shares lessons from building an operating model from scratch in a high-growth, AR/VR and AI environment, and she explains why leaders should start with basics: map the workflow, clarify ownership, and decide what outcomes matter before choosing tools. The conversation moves into agentic AI and autonomous workflows, and why that shift makes human judgement more important, not less. Finally, we get practical about change management: listen to employees, solve the most painful parts of the job first, and use internal champions to drive adoption without creating a Big Brother culture. If you want AI transformation, organisational design, and leadership culture to pull in the same direction, subscribe, share this with a colleague, and leave us a review.We would love you to follow us on LinkedIn! https://www.linkedin.com/company/amplified-group/

A Podcast Co-Host Relationship sounds fun until different personalities, expectations, and creative habits start crashing into each other behind the scenes. In this episode, our cast and crew talk about what actually keeps a co-host partnership working, from handling conflict and sharing responsibilities to knowing when somebody's carrying too much of the weight. There's also that moment where a co-host stops feeling like just another voice on the mic and starts feeling like the reason the show works at all. By the end, you'll probably think a little differently about the conversations happening before and after the record button gets pressed. Episode Highlights:[00:00] Welcome and Topic Setup[02:41] Why Co-Hosts Matter[05:27] Rage Quit to a New Co-Host[09:01] What Makes Chemistry Work[11:04] Goals and Audience First[17:14] Communication Like a Marriage[18:52] Co-Host Prenups and Producer Roles[23:09] Workflow and Division of Labor[30:18] Finding a Co-Host[33:58] Podcasting with Spouses[52:45] Final Takeaways and Wrap-UpLinks & Resources:John Jamingo and The Duchess:https://www.boomerbunker.com/Feature Your Podcast on the Podcasting Morning Show:https://PodcastingMorningShow.com/spotlightThe Podcasting Morning Show:⁠⁠www.podcastingmorningshow.com⁠⁠Ways to Watch or Listen:⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠https://www.podcastingmorningshow.com/joinus/Meet the PMS Cast and Crew:⁠⁠https://podcastingmorningshow.com/people⁠⁠Join The Empowered Podcasting Facebook Group:⁠⁠www.facebook.com/groups/empoweredpodcasting⁠⁠⁠Book A Free Call With Marc:https://calendly.com/ironickmedia/freestrategycallApplication To Submit Your Show For Evaluation:⁠⁠⁠⁠⁠https://podcastingmorningshow.com/eval⁠⁠Join us every other Monday at 8 AM ET for the Obsession Worthy Podcasts:⁠⁠⁠http://podcastingmorningshow.com/owp/⁠⁠Join us LIVE every weekday morning at 8 am ET (US) on ⁠Clubhouse⁠: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://podcastingmorningshow.com/clubhouse⁠⁠EPC3 Speaker Application:⁠⁠ ⁠https://empoweredpodcasting.com/speakersPowered by⁠⁠⁠ ⁠iRonickMedia.com⁠⁠⁠⁠ and⁠ ⁠ContentCreatorsAccountant.com⁠⁠Send in your mailbag questions:⁠⁠⁠⁠ https://www.podcastingmorningshow.com/contact/⁠⁠⁠⁠ or ⁠marc@ironickmedia.com⁠Want to be a guest on The Podcasting Morning Show? Send me a message on PodMatch, here:https://podmatch.com/hostdetailpreview/1729879899384520035bad21b

On this episode of The Bandwich Tapes, I sit down with composer, performer, and educator Casey Cangelosi for a conversation that moves comfortably between teaching, podcasting, composing, and the realities of building a life in the percussion world. Casey teaches at James Madison University, where he directs a busy percussion studio and constantly balances artistic ambition with the practical challenges of giving students meaningful performance opportunities.We talk about how he approaches programming percussion ensemble, often leaning toward smaller-group repertoire that allows more students to develop chamber instincts and real musical ownership. That naturally leads into a larger discussion about education, specifically the gap that can exist between strong performance skills and deep knowledge of repertoire. Casey makes a compelling case for listening, score study, and curiosity as essential parts of becoming a complete musician.A big part of Casey's recent creative life has been the Percussion Podcast, where he hosted more than 300 episodes of conversations with percussionists and composers. He reflects honestly on what that project gave him, as a communicator, teacher, and community builder, as well as the real workload of producing that many episodes and the challenge of keeping conversations fresh over time.We also spend time inside Casey's composing process. He talks about the difference between writing for hands versus writing for humans, and how limitations, instrumentation, skill level, or context can actually unlock more interesting musical ideas. Increasingly, he's thinking about accessibility in repertoire: writing music that still feels compelling but can reach more performers instead of only fitting one ideal player.Toward the end, Casey shares some of the unexpected places his music has recently appeared, including projects connected to theater, dance, and visual art, from a performance context in Mannheim, to an installation tied to Ligeti's 100 Metronomes, to a circus production in Italy using his piece Bad Touch. It's a reminder that percussion music continues to travel in surprising directions.Key TakeawaysTeaching requires balancing artistry and logistics — ensemble programming often means finding ways for more students to perform meaningfully.Listening and score study deepen musicianship — strong playing should be paired with a deep knowledge of repertoire.Podcasting builds community but demands consistency — producing hundreds of episodes requires serious time and energy.Constraints can unlock creativity — limitations often lead to stronger compositional ideas.Writing for performers matters — accessible repertoire can reach more musicians without sacrificing musical depth.Percussion music is expanding beyond traditional venues — Casey's work now appears in theater, visual art, and interdisciplinary projects.Curiosity fuels long careers — staying open to new contexts keeps creative work evolving.Music from the EpisodeScry - Casey CangelosiBlink - Casey CangelosiThe Big Audition - Casey CangelosiLigeti: Symphonic Poem for 100 Metronomes - Casey CangelosiAbout the PodcastThe Bandwich Tapes is a podcast hosted by Brad Williams, featuring conversations with musicians, composers, producers, and creative thinkers about their musical journeys. Each episode explores the influences, decisions, and experiences that shape a life in music—one conversation at a time.Connect with the ShowEmail: contact@thebandwichtapes.com

This webinar covers practical video marketing for marketers, including a two-hour production workflow, AI-assisted scripting with Claude, talking head video setup, audio quality tips, editing tools like CapCut and Wistia, and how to repurpose footage across portrait and landscape. Chris Lavigne, Head of Production at Wistia, shares how to make videos that earn their keep without chasing views.Timestamps:00:00 - Introduction03:55 - The two-hour workflow06:20 - Start with one question09:15 - Scripting with AI12:45 - Shoot setup and audio19:00 - Editing tools21:00 - Publishing to LinkedIn23:00 - Real video ROI25:10 - Gear walkthrough28:20 - Q&A33:30 - Camera-shy teams41:30 - Portrait vs landscape52:55 - Outdoor shooting58:10 - Motion graphics on a budgetWatch / listen:Listen on Apple Podcasts: https://podcasts.apple.com/us/podcast/marketing-meetup-podcast/id1365546447Listen on Spotify: https://open.spotify.com/show/5QvmFdxg5pMwsfPkKjhXl9The Marketing Meetup thrives for many reasons, but one of the crucial reasons we're able to do what we do is because we have the support of some incredible individuals from some equally inspiring companies. Below is the list of our partners in crime: our amigos. All we have to say is a big, massive, thank you.Cambridge Marketing College: The place to go for marketing qualifications (CIM, CIPR) and marketing apprenticeships. Cambridge Marketing College have supported us since day one, and are an unbelievably kind bunch of people.Frontify: The Frontify DAM simplifies brand workflows so marketing teams can deliver engaging experiences on a global scale, fast.Planable: Planable's the content collaboration platform that helps marketing teams create, plan, review, and approve all their awesome marketing content.Mailchimp: Join a marketing platform that scales with your business. Save 20% for 12 months on Mailchimp Premium or Standard and see why millions of users trust Mailchimp to boost their ROI. Switch plans or cancel anytime.Wistia: Wistia is a complete video marketing platform that helps teams create, host, market, and measure their videos and webinars, all in one place.Prismic: Prismic is the CMS and landing page builder that powers scalable content infrastructure for modern marketing terms.Canva: An online design and publishing tool with a mission to empower everyone in the world to design anything and publish anywhere.Want to find out more about our sponsors, and their exclusive TMM discounts and resources? Head here: https://themarketingmeetup.com/location/virtual/, sign up to a webinar and opt-in to receive your unique offer :)

In this episode, NUEQ shares how he writes high-energy dance music in Ableton Live, breaking down his Operator-heavy sound design, groove-first drum mindset, and how he builds “call and response” ideas that stay cohesive through a track. He also digs into resampling, distortion chains, sidechaining, and favorite stock tools like Vocoder for adding character.NUEQ is a bass music producer known for detailed, rhythm-forward productions and building sounds from scratch. He's played festivals like Tipper & Friends, Infrasound, Submersion, Fire Lights, Desert Bass (IL), and Balter Festival (UK), and has supported artists including Tipper, Culprate, K.L.O, Tsuruda, kLL sMTH, Duffrey, and Thought Process. He's collaborated with Mr Bill, Culprate, Yehezkel Raz, Azaleh, and Omnist (with ongoing work w/ Vorso + Culprate), released on Inspected, VALE, Billegal Beats, Colony Productions, and Wormhole Music, and has sync placements with Tesla, Nothing Phone, and Ninja.Follow NUEQ:https://linktr.ee/NUEQGrab limited-edition Producer Merch & save 10% with the code "podcast":https://www.abletonpodcast.com/merchJoin the newsletter to get free downloads, early episode access, and upcoming events.https://www.abletonpodcast.com/newsletter

Jack Cochran and Matthew James welcome Kintan Brahmbhatt, CEO and co-founder of Olto, to discuss how AI agents are fundamentally reshaping the presales workflow and buyer experience. Drawing from over 12 years at Amazon building personalized experiences for Alexa, Amazon Music, and Prime Video, Kintan explores why B2B buyers receive generic "Acme Corp" demos while B2C consumers get highly personalized recommendations, and how product-trained agents can finally close this gap economically. The conversation goes beyond productivity gains to examine how buyers, products, and SE roles have evolved rapidly while metrics, compensation plans, and tooling have remained static.  Follow Us Connect with Jack Cochran: https://www.linkedin.com/in/jackcochran/  Connect with Matthew James: https://www.linkedin.com/in/matthewyoungjames/  Connect with Kintan Brahmbhatt: https://www.linkedin.com/in/kintan/  Links and Resources Mentioned Join Presales Collective Slack: https://www.presalescollective.com/slack  Sol/Con 2026 (Chicago, August 2026): https://www.presalescollective.com/solcon-2026  Olto: https://olto.com/psc  (3 months free promotional offer mentioned) Key Topics Covered Why AI Timing Is Better Now: Moving Beyond Productivity to Workflow Transformation The Personalization Gap Between B2C and B2B Buyer Experiences What Olto Is: Product-Trained AI Agents Across the Revenue Journey Kintan's Amazon Background: Building Personalized Experiences at Scale SE Capacity Economics and the Unspoken Rule About Qualified Deals How Product-Trained Agents Differ from Generic AI The New SE Workflow: Agents Handle Discovery, SEs Focus on Sense-Making Evolution of SE Metrics, Compensation, and Tooling for the AI Era Implementation Challenges and Change Management The Future of the Presales Profession Timestamps 00:00 Welcome 04:04 Now vs a year ago 05:40 What is Olto 07:52 B2C vs B2B personalization disconnect 11:15 Agent capabilities and limitations 21:35 Future of the solutions roles 28:26 Key takeaways from solutions leaders

In this episode of the Healthy Wealthy & Smart Podcast, Dr. Karen Litzy, PT, DPT welcomes Ashok Gupta. They explore the evolution of telehealth and hybrid care in physical therapy, discussing innovative technologies, AI applications, and regulatory shifts that are expanding access and improving patient outcomes. This conversation provides a comprehensive look at how clinicians and practices are embracing digital transformation to deliver more effective, patient-centered care.   In this episode: ·      The concept of omni-channel or hybrid care modeled after consumer experiences like Walmart and Amazon ·      How telehealth is transforming access for acute and chronic patients, with real-world success stories including ICU recovery ·      The development and integration of physical AI to guide motion recognition and real-time patient assessment ·      The critical role of clinician input and feedback in building effective telehealth tech ·      Cost-effective remote therapeutic monitoring (RTM) and regulation updates supporting scalable virtual care ·      Impact of AI on clinician efficiency, documentation, and patient engagement ·      Best practices for virtual manners, camera presence, and creating a professional digital environment ·      Strategies for integrated workflows connecting telehealth platforms, EMRs, and practice management tools ·      The importance of embracing technology to stay competitive and improve patient outcomes ·      Future outlook: seamless virtual-clinic transitions and personalized care pathways   Timestamps: ·      (00:00) - Welcome and episode overview: Redefining patient-centered hybrid healthcare ·      (02:27) - What is omni-channel hybrid care? Patient choice in physical therapy ·      (03:21) - How remote and in-clinic options combine for optimal access ·      (04:37) - From prevention to rehab: leveraging sensors and self-management tools ·      (05:33) - Real-world success stories: ICU recovery and remote therapy impact ·      (06:56) - Broadening telehealth: software, hardware, and virtual care models ·      (07:50) - Myths about telehealth: more than just video calls ·      (08:48) - Evolving tech: from initial skepticism to AI-powered diagnostics ·      (09:44) - Developing physical AI for motion analysis and patient assessment ·      (11:06) - How remote care experiences match or surpass in-clinic outcomes ·      (12:27) - Continuous monitoring and data-driven treatment tailoring ·      (14:27) - Clinician involvement in product development and validation ·      (16:52) - Addressing small practice hurdles and advances in regulation support ·      (17:19) - The 2026 CMS updates: enabling remote patient and therapeutic monitoring ·      (19:16) - Integrating virtual care into daily practice workflows ·      (20:31) - Changing data collection and insurance reimbursement for RTM ·      (22:47) - Workflow integration: enrolling patients effortlessly within existing systems ·      (24:01) - Insurance coverage landscape for remote monitoring services ·      (25:19) - AI as an efficiency tool, not a replacement, for clinicians ·      (26:42) - Enhancing patient engagement and clinical decision-making with AI summaries ·      (29:46) - The importance of bedside manners in virtual care standards ·      (30:42) - Building trust and continuity through AI-driven session analysis ·      (32:07) - Improving clinician performance: gamification and feedback tools ·      (34:00) - Building care platforms based on actual patient and clinician needs ·      (36:33) - Overcoming fears of technology and embracing digital health ·      (39:11) - Mastering virtual manners: creating a professional, private environment ·      (41:48) - The future of healthcare: seamless hybrid models and patient choice ·      (44:45) - Final thoughts: tackling large-scale problems for greater impact   Resources & Links: TheraNow:Telehealth platform for physical therapy and remote care Diary of a CEO book   Connect with Dr. Gupta: LinkedIn TheraNow on FB TheraNow on Instagram TheraNow on X TheraNow on YouTube   More About Dr. Gupta: Dr. Ashok Gupta, is the founder of TheraNow, an 8-figure virtual physical therapy platform that's supported over 70,000 patients across the US since 2021. Ashok didn't start as your usual tech guy; he started as a physical therapist treating veterans at VA hospitals, traveling through small-town America, working everywhere from ICUs to homehealth. And everywhere he went, he saw the same issue: people either had to come to you or you had to go to them, and in rural areas, services were just too far away.  Skip to 2017, Ashok and his wife (also a physical therapist) are watching TV when a commercial for virtual mental health therapy comes on. They look at each other and ask: "Why doesn't this exist for physical therapy?" Everyone said it couldn't work (the word itself is physical therapy, right?), but Ashok realized most of PT could be replicated virtually. No hospitals would pilot it, no payment model existed, then the pandemic hit, and what seemed impossible, became essential.  These days, Ashok's working with major health systems like Providence Health, and building AI-powered clinical documentation tools that are actually adopted by clinicians. Jane Sponsorship Information: Book a one-on-one demo here Mention the code LITZY1MO for a free month   Follow Dr. Karen Litzy on Social Media: Karen's Instagram Karen's LinkedIn   Subscribe to Healthy, Wealthy & Smart: YouTube Website Apple Podcast Spotify SoundCloud Stitcher iHeart Radio

Dave "CAC" Kellogg and Ray "Growth" Rike dig into the Redpoint Ventures 2026 Software and AI Market Update - a 69-page report built on proprietary CIO survey data from 141 respondents, plus public market data from Qatalyst, Pitchbook, Goldman Sachs, RBC, and McKinsey. Big report with even bigger implications. Ray and Dave unpack the data that matter most for B2B SaaS and AI-native software operators.WHAT WE COVER IN THIS EPISODEThe AI Build-Out Is Real and It's Not the Dot-Com BubbleHyperscaler CapEx is projected to hit $765B in 2026, up nearly 50% year over year. More than 90% of new data center capacity is already pre-committed. Compare that to the dot-com era when fiber utilization was under 3%. The other critical difference: today's infrastructure spend is funded primarily by free cash flow, not debt. The more important signal is demand. AI has reached 1 billion monthly active users in four years. The internet took far longer to reach 70 million. The demand is real. The risk of speculative overbuild is also real.The Agent Maturity Curve and Why Most of the Value Is Still AheadPage 7 of the report maps the four phases of agent maturity by runtime: co-pilots (seconds), task agents (minutes), workflow agents (hours), autonomous agents (days). Co-pilots represent roughly $500B in software spend. Task agents, where coding tools live today, push that to $1.2T. Workflow agents expand the TAM to $2.8T. Autonomous agents take it to $6.1T. Coding has been the beachhead use case for good reasons: structured training data, instant verification, self-improving feedback loops. The real enterprise revenue opportunity is still in phases three and four.What the CIO Survey Actually Says This is the buried lead of the report. 54% of CIOs are actively consolidating vendors. 45% of AI budgets are coming from existing software budgets, not net-new spend. 58% say AI feature additions are the top driver of incremental software spend. 54% prefer to stay with incumbent vendors if they deliver on AI. Only 13% have a strong preference for AI-native software. The 33% who are neutral are the swing vote. Incumbents are winning the preference battle but losing the execution battle — the CIO feedback on Agentforce, Copilot, and ServiceNow AI in the survey is not flattering.Terminal Value Is the Real SaaS Valuation StoryThe public SaaS median NTM revenue multiple sits at 4.1x (Meritech says 3.1x), the lowest since the global financial crisis. In a SaaS DCF, 85 to 95% of enterprise value comes from terminal value, not the five-year forecast. The implied long-term growth rate embedded in current SaaS valuations has collapsed from 4.7% to 1.1%. Short-term beats like ServiceNow's recent quarter do almost nothing to move the stock because the market's concern is not next year. It's year ten and beyond. That is a terminal value story, not a growth story.ARR Per Employee - The Benchmark EvolvesCursor and Anthropic hit $100M ARR in roughly two years. Slack took three. Salesforce and Adobe took four to five. ServiceNow took seven to eight. AI-native companies have made $1M revenue per FTE the new floor. The P&L transformation model in slide 39 projects R&D costs down 15 to 20%, sales costs down 15 to 20%, COGS increasing due to inference spend but offset by reductions in customer support and customer success. Net result: potential EBITDA expansion of 100 to 250% on the same revenue base over three to five years.Private Markets Are in an AI Love FestAI-native deals represent nearly 100% of new VC activity in Q1 2026. Deal concentration is accelerating: the top 20 deals captured 44% of total funding in 2025, up from 31% in 2024 and 7% in 2022. At the model layer, dollars and valuations are concentrated while deal volume belongs to the application layer (61% of deals). The model competition is effectively over. The only question is rank order. The application layer is where the volume plays out, and AI-native vendors are winning that battle.Redpoint 2026 Software and AI Market Update: https://www.redpoint.com/reports/2026-market-updateABOUT THE METRICS BROTHERS Ray Rike is the Founder and CEO of Benchmarkit, the leading B2B SaaS and AI-native software benchmarking company. Dave Kellogg is an EIR at Balderton Capital, independent consultant, and author of Kellblog. Together they bring a CFO-meets-GTM lens to the metrics and benchmarks that drive efficient revenue growth and enterprise value.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

What the AI?! ist live! Der neue Baby got Business Podcast für alle, die KI wirklich verstehen und sinnvoll nutzen wollen. Jetzt hier anhören! Mit „What the AI?!“ startet Baby got Business ein neues Podcast-Format rund um künstliche Intelligenz. Host ist Viktoria Rode, die als KI-Expertin mit Marken, Agenturen und Teams arbeitet und genau weiß, wo die größten Hürden im Alltag liegen. In dieser ersten Folge geht es nicht um Tools oder Hacks, sondern um den entscheidenden Denkfehler beim Einstieg in KI. Zwischen Überforderung, falschen Erwartungen und echtem Effizienzpotenzial wird klar, warum Klarheit wichtiger ist als jedes Tool und wie man KI sinnvoll in den eigenen Workflow integriert. Darüber wird gesprochen: * Warum „einfach anfangen“ beim Thema KI oft der falsche Ansatz ist * Wie man KI konkret in wiederkehrende Aufgaben integriert * Der Unterschied zwischen KI nutzen und mit KI arbeiten * Vikis Weg von ersten Experimenten mit Midjourney zur KI-Expertin * Aktuelle Entwicklungen bei ChatGPT, Claude, Gemini und Co. Hier die erste Folge anhören! Hier findest du mehr über uns:⁠⁠⁠⁠⁠⁠ ⁠⁠Website⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠TikTok⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠LinkedIn⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Impressum⁠⁠⁠⁠⁠⁠⁠⁠ Learn more about your ad choices. Visit megaphone.fm/adchoices

In the Insta360 boot at NAB 2026, Global PR Manager Poppy Zhang gives us a preview of a new creator-oriented wireless mic system that features not only high-quality recording but also a customizable screen that can display logos, emoji, or brand identities. The unit also features a compact charging case, with pricing to be announced soon.  Show Notes: Chapters: 0:03 Introduction from NAB 20260:12 Why the Insta360 booth is a must-stop0:37 New creator and media offerings introduced1:30 Product overview and professional use cases2:45 Workflow improvements and app integration3:40 Custom branding and logo uploads4:10 Ease of use and setup demonstrations5:00 Creator-focused production capabilities6:15 Closing thoughts from the Insta360 booth Support:      Become a MacVoices Patron on Patreon     http://patreon.com/macvoices      Enjoy this episode? Make a one-time donation with PayPal Connect:      Web:     http://macvoices.com      Twitter:     http://www.twitter.com/chuckjoiner     http://www.twitter.com/macvoices      Mastodon:     https://mastodon.cloud/@chuckjoiner      Facebook:     http://www.facebook.com/chuck.joiner      MacVoices Page on Facebook:     http://www.facebook.com/macvoices/      MacVoices Group on Facebook:     http://www.facebook.com/groups/macvoice      LinkedIn:     https://www.linkedin.com/in/chuckjoiner/      Instagram:     https://www.instagram.com/chuckjoiner/ Subscribe:      Audio in iTunes     Video in iTunes      Subscribe manually via iTunes or any podcatcher:      Audio: http://www.macvoices.com/rss/macvoicesrss      Video: http://www.macvoices.com/rss/macvoicesvideorss

In the Insta360 booth at NAB 2026, Global PR Manager Poppy Zhang gives us a preview of a new creator-oriented wireless mic system that features not only high-quality recording but also a customizable screen that can display logos, emoji, or brand identities. The unit also features a compact charging case, with pricing to be announced soon.  Show Notes: Chapters: 0:03 Introduction from NAB 2026 0:12 Why the Insta360 booth is a must-stop 0:37 New creator and media offerings introduced 1:30 Product overview and professional use cases 2:45 Workflow improvements and app integration 3:40 Custom branding and logo uploads 4:10 Ease of use and setup demonstrations 5:00 Creator-focused production capabilities 6:15 Closing thoughts from the Insta360 booth Support:      Become a MacVoices Patron on Patreon      http://patreon.com/macvoices      Enjoy this episode? Make a one-time donation with PayPal Connect:      Web:      http://macvoices.com      Twitter:      http://www.twitter.com/chuckjoiner      http://www.twitter.com/macvoices      Mastodon:      https://mastodon.cloud/@chuckjoiner      Facebook:      http://www.facebook.com/chuck.joiner      MacVoices Page on Facebook:      http://www.facebook.com/macvoices/      MacVoices Group on Facebook:      http://www.facebook.com/groups/macvoice      LinkedIn:      https://www.linkedin.com/in/chuckjoiner/      Instagram:      https://www.instagram.com/chuckjoiner/ Subscribe:      Audio in iTunes      Video in iTunes      Subscribe manually via iTunes or any podcatcher:      Audio: http://www.macvoices.com/rss/macvoicesrss      Video: http://www.macvoices.com/rss/macvoicesvideorss

I sit down with Meng To for his second appearance on the pod to dig into design md, Google's newly open-sourced format for capturing the soul of a design and porting it across every medium and tool. Meng walks me through a live demo of how he uses design md alongside skills, HTML references, and tools like Aura, New Form, Codex, and OpenClaw to ship landing pages, motion design, slides, and mobile mocks that actually feel custom. We get into the design drift problem with one-shot prompts, why taste is the real moat for builders right now, and how he runs four products as effectively a team of one while iterating a thousand-plus prompts deep. If you build with agents and you want your work to stand out from the sea of purple-gradient lookalikes, this one is for you. Timestamps 00:00 – Intro 04:00 – What design md actually is 07:17 – Examples: one design DNA across slides, promo videos, motion 09:31 – How to create design system 14:05 – The importance of taste and design 18:28 – Variant, remixing, and skills as ingredients 21:36 – Live demo: creating a landing page with design md and HTML 24:36 – Thoughts on Google Stitch 25:41 – Being fast and at edges is an unfair advantage 29:29 – Midjourney parallels and the queuing flow state 31:44 – Walking through skills (skeuomorphic, 3D, lasers) 34:07 – Now everyone is a designer 36:47 – The full design workflow 38:50 – Iteration versus remix 39:24 – Judgment per minute as the new craft 41:06 – Solo building vs building a team 44:34 – Taste is the moat 48:25 – Building a second brain for design inspiration 50:41 – Closing thoughts Key Points Design md is a portable blueprint for typography, color, spacing, and effects that you attach to any prompt to keep design consistent across web, mobile, slides, and motion. One-shot prompts collapse on page two; a design system carries the soul across every medium and tool you switch into. Skills work like ingredients (lasers, skeuomorphic, 3D, copywriting), and stacking them on top of design md  is what separates custom work from generic vibe-coded output. Taste is the real moat right now, and you build it by surrounding yourself with great design and using every product in your niche. Iteration (90% of the time) keeps a product evolving; remix (10%) takes the same DNA into a new medium or category. The shift in craft is from moving pixels to making judgment calls per minute, with agents handling the mechanical work. 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 MENG ON SOCIAL Aura: https://aura.build X/Twitter: https://x.com/MengTo

Want to Start or Grow a Successful Business? Schedule a FREE 13-Point Assessment with Clay Clark Today At: www.ThrivetimeShow.com   Join Clay Clark's Thrivetime Show Business Workshop!!! Learn Branding, Marketing, SEO, Sales, Workflow Design, Accounting & More. **Request Tickets & See Testimonials At: www.ThrivetimeShow.com  **Request Tickets Via Text At (918) 851-0102   See the Thousands of Success Stories and Millionaires That Clay Clark Has Helped to Produce HERE: https://www.thrivetimeshow.com/testimonials/ Download A Millionaire's Guide to Become Sustainably Rich: A Step-by-Step Guide to Become a Successful Money-Generating and Time-Freedom Creating Business HERE: www.ThrivetimeShow.com/Millionaire   See Thousands of Case Studies Today HERE: www.thrivetimeshow.com/does-it-work/  

When a liver tumor is hard to see, the limits of conventional image guidance can become the limits of treatment. In this episode of the BackTable Podcast, Netherlands interventional oncologist Dr. Maarten (M.L.J.) Smits shares a step-by-step walkthrough of the new hepatic arteriography and C-arm CT–guided ablation (HepACAGA) technique, punctuated with a real-world case series at the end. Find out how intra-arterial contrast, cone-beam CT, and 3D needle guidance can improve tumor conspicuity, targeting accuracy, and ablation margin assessment within a single angiography suite. --- Get the BackTable apphttps://www.backtable.com/app --- Timestamps 00:00 - Introduction02:55 - Netherlands Tech Access04:31 - Origin of HepACAGA07:14 - Why Use a Catheter?11:24 - Tools and Setup13:13 - Catheters and Devices17:06 - Contrast Protocol Basics22:51 - Targeting and Needle Guidance31:09 - Patient Selection35:56 - Extra Benefits and Multimodal39:58 - Workflow and Outcomes46:14 - Evidence and Early Studies51:41 - Rethinking Size Cutoffs57:54 - HCC Case Walkthrough01:02:27 - Hard-to-See Metastasis01:06:22 - Margin Driven Reablation01:11:04 - Bleeding and Embolization01:16:05 - Renal ACAGA Expansion01:23:31 - Adoption and Next Steps --- More about this episode Dr. Smits explains the origins of HepACAGA and why catheter-based contrast delivery can meaningfully change ablation planning, particularly for small lesions, poorly visualized tumors, and cases where ultrasound or conventional CT guidance may be insufficient. He walks through the practical setup, including catheter positioning, contrast dilution, timing protocols, needle navigation, apnea/end-expiration technique, and built-in fusion for immediate ablation verification. He also describes how the angio suite environment supports multimodal treatment, including intraprocedural embolization when bleeding occurs or when additional transarterial therapy is needed. The episode also examines early outcomes from Dr. Smits' group, including a reported reduction in local recurrence from approximately 25% to 5%, with a modest increase in procedure time. Case examples include HCC, small colorectal liver metastases, margin-driven re-ablation, hemorrhage management, and extension of the ACAGA concept to renal tumors (RenACAGA). --- Resources Hepatic Arteriography and C-Arm CT-Guided Ablation (HepACAGA) to Improve Tumor Visualization, Navigation and Margin Confirmation in Percutaneous Liver Tumor Ablationhttps://pubmed.ncbi.nlm.nih.gov/37704863/ Renal Arteriography and C-arm CT-Guided Ablation (RenACAGA) for Thermal Ablation of Challenging Renal Tumorshttps://pubmed.ncbi.nlm.nih.gov/40295401/ --- BackTable Vascular & Interventional (VI) is the go-to podcast for interventional radiologists, vascular surgeons, and interventional cardiologists. Download the free BackTable app to get early access to new episodes, cases, and courses curated by physicians in your specialty. ► https://www.backtable.com/app

Discover how to reclaim 10+ hours every week by turning AI into your personal execution system. In this episode, we break down a simple, real-world workflow that uses AI to handle planning, decision-making, and repetitive tasks—without adding more tools or complexity. Learn how to automate context-gathering, research, and follow-ups so you can stop digging through […]

On today's episode, Dr. Mark Costes sits down with Dr. Taher Dhoon and Dr. Dan Briskie of the Colorado Surgical Institute to break down what it really takes to manage surgical implant cases the right way from evaluation through long-term maintenance. They dive into practical pre-op and post-op protocols, medication strategies, patient communication systems, suturing tips, and ways to reduce unnecessary follow-up visits while improving outcomes.  The conversation also covers healing abutments versus cover screws, incision management, immediate loading philosophy, and how better workflows can create a smoother experience for both the patient and the practice. Be sure to check out the full episode from the Dentalpreneur Podcast! EPISODE RESOURCES https://www.coloradosurgicalinstitute.com https://www.truedentalsuccess.com Dental Success Network Subscribe to The Dentalpreneur Podcast

Walking through my complete AI workflow for creating YouTube videos! Thanks to Brevo for sponsoring today's episode. Use code LATASHA50 to save 50% on Starter and Standard Plans for the first 3 months: https://get.brevo.com/latashajames #Brevo #BrevoPartner  @brevo_official  Mentioned:TubeBuddyhttp://tubebuddy.com/latashaGammahttps://try.gamma.app/tlgecmox4986Riversidehttps://riverside.com/?utm_campaign=campaign_2&utm_medium=affiliate&utm_source=rewardful&via=latashaCastmagichttps://get.castmagic.io/g087lw4xoruo