Podcasts about Airtable

In this episode we cover: The exciting rebrand currently underway and why it feels like the grown-up version of my business Working with branding specialist Sheridan Burns and photographer Sophie Jane Photography Why we're moving away from Kajabi after five years The shift to ConvertKit, Squarespace, Airtable and purpose-built platforms Preparing the business for two months of travel across the United States How I'm "bulletproofing" client delivery while working across multiple time zones My current thoughts on AI, ChatGPT and Claude Why I'm using AI more for systems, automation and strategy than content creation The difference between workshops and masterclasses, and why workshops are becoming a core part of my business model What's working with trial reels and recent social media growth The growth of The Regional Experts and the impact clients are creating across regional Australia Navigating the first year without having a child at home full-time Finding balance between business growth, motherhood and personal fulfilment What's coming next on the podcast Resources mentioned ConvertKit Squarespace Airtable ThriveCart Claude ChatGPT The Regional Experts Monthly workshops Connect with Tori Come and say hello on Instagram and let me know what questions you'd love answered in future behind-the-scenes episodes. This new series is your chance to peek inside the business, ask questions and hear what's really happening as we grow, scale and navigate the realities of running a regional business. Apply to join the Regional Experts here. Connect with me on Instagram here. 

Join us for the Blueprint to Bot Workshop June 17. Save $70 with coupon: PODCAST70--------------------------------------------------------------------------------------------------------------------Here's the thing nobody's telling you: being good at AI has nothing to do with being technical.I know, I know—you've been spiraling thinking you need to learn to code or become some kind of tech wizard. But the real skills that make AI work? They're human skills. And you probably already have them.In this episode, I'm breaking down the two critical abilities that separate people who get mediocre results from AI and people who build bot squads that actually work and make money.Spoiler: it's not about prompt engineering or knowing Python. It's about communication and systems thinking.I'm sharing what I've learned as co-founder of an AI tech company (pause for dramatic reflection), how I've been using Airtable to finally organize my entire podcast guest pipeline, and why your messy Google Drive full of random screenshots from 2019 is absolutely wrecking your AI outputs.Plus, I'm walking you through a real example of how I built a marketing strategy for Wave's next beta phase—and how that one document became the single source of truth for an entire bot squad that writes emails, creates social content, and scripts podcasts.If you've ever felt like AI just "doesn't get you," this episode will show you exactly why—and what to do about it.You'll learn:Why communication (not coding) is the #1 skill for getting great AI resultsThe difference between tasks that need AI and tasks that need a humanWhy I finally started using Airtable in 2026 (and how it changed everything)How to think in systems so you can build bot squads that work for multiple clientsThe framework for any bot squad>>Introducing wAIvThis episode is brought to you by wAIv—our brand-new platform built for online experts who want to securely build and sell AI tools powered by YOUR thinking, YOUR frameworks and YOUR methodology.wAIv helps you create Bot Squads—a suite of AI tools that work together to help your clients implement your expertise faster and with better results than ever before.We're currently rolling out in beta, and you can join the waitlist now to access our AI Tool Launch Playbook, which walks you through exactly how to start thinking about your first Bot Squad—what to put in it, what it will solve for your clients, what to name it, and exactly how to build it.Head to https://waiv-ai.com to get on the list.>>Your Next Steps:

Ever felt like you needed a complex script or a third-party automation just to rank your records or find the 'next' item in a sequence? In this episode, we show you a much cleaner, more stable way to do it using nothing but Airtable's native Rollup and Lookup field sorting! We break down the exact formulas and structural setups needed to build dynamic leaderboards and sequential approval workflows. Whether you're managing a sales leaderboard or a multi-step landscaping route, these hacks will help you build more robust, efficient bases. Join us as we reveal the 'Utility Record' trick and show you how to master the math behind these powerful formulas.

Felipe Carvalho is Co-Founder and Chief Revenue Officer of Camu — an AI workflow automation platform. Previously, Felipe spent 10 years building the global go-to-market organization at Pipefy alongside founder Alessio Alionço, scaling a horizontal workflow platform that serves Volvo, Capgemini, IBM, Accenture, Visa, Santander, Itaú, and thousands of other SMBs and enterprises across Brazil, the US, and beyond. Before Pipefy, he built and scaled the fundraising function at Hospital Pequeno Príncipe — Brazil's largest children's hospital — raising over $20M and growing a team of 50.In this TJC Operators episode, Felipe shares the brutal sales lesson from Pipefy — why selling everything to everyone is a GTM trap that hides inefficiency through inbound demand, and why outbound exposed it overnight. He walks through the "who would be crazy not to buy this" framework from Seth Shaw (former CRO of Airtable) that reshaped Pipefy's outbound motion, how Camu got from 1–2% to 17% to 33% conversion by progressively narrowing focus to a single ERP (SAP Business One) and one specific workflow (invoice intake), why charging monthly with no strings attached was the cleanest way to validate true product-market fit, the Sean Ellis "very disappointed" PMF survey methodology and how Camu hit high-50s on a V1 product, why saying no to massive enterprise RFPs is a superpower in the early days, how Felipe now manages 68 active opportunities solo by using Claude and AI to automate 50–70% of sales back-office work (CRM updates, ROI calculations, proposal generation, deal-power scoring), the FCA (Fact, Cause, Action) framework Pipefy used to run monthly results meetings and why analyzing wins matters as much as analyzing losses, why "building a plane is different from flying a plane" — and why founders should nail the sales playbook themselves before hiring senior enterprise sellers, the shift from selling software-as-a-service to delivering recurring impact and how risk has moved from buyer to seller in the AI era, and the lesson he most wants Brazilian founders to learn about building credibility before the market gives it to you.Subscribe to The J Curve Insider newsletter for deeper insights and follow Olga on LinkedIn and Instagram.

Ever wondered how to let users submit multiple line items in a single Airtable form without paying for a dozen editor licenses? We've got you covered! In this episode, Kamille walks you through three practical and creative ways to handle sub-records and order forms using native Airtable tools and even AI. We also recap the latest from the Airspace event and discuss the potential of 'Canvas,' Airtable's new interface designer. Whether you're looking for a clever automation hack to bundle items into a cart or want to use AI to parse messy text into clean data, this episode is packed with insights for every Airtable builder. Tune in to learn how to optimize your workflows, manage your token usage, and decide when to use AI versus traditional, time-tested methods.

Harry Duran, founder of Fullcast and creator of Podisphere, joins Jeff Mains to explore what it really takes to build a sustainable podcast, grow a content brand, and stay ahead in a rapidly AI-shaped media world.Harry shares his journey from corporate marketing at JPMorgan Chase and E-Trade, to launching his first podcast Podcast Junkies in 2014, to building Fullcast — a podcast production and marketing consultancy that has helped over 130 business owners launch and grow shows. He also dives deep into his newest ventures: Podisphere (a G2-style SaaS directory for podcast tools) and Podclaw (an agent-first podcast hosting platform built for AI agents, not humans).The conversation covers the seismic shift happening in content creation right now — from vibe coding and Claude Code to autonomous AI agents that market products while you sleep. Harry and Jeff also discuss why long-form human conversations are becoming more valuable in an era flooded with AI-generated content, the power of niche podcasting, and why the most important skill for the next decade may simply be learning how to talk to robots.Key Takeaways0:00 — Intro: What it takes to build a podcast and a business around it in an AI-driven content landscape4:40 — Recap of previous guests: Justin Trombold on AI strategy and Rick Delisi on The Effortless Experience6:10 — Welcoming Harry Duran — how he helped launch SaaS Fuel and what Fullcast does9:50 — Harry's origin story: From JPMorgan Chase and Unilever to electronic music, DJing, and discovering podcasting at New Media Expo in 201413:30 — Meeting Pat Flynn and Amy Porterfield; pivoting from a DJ podcast to Podcast Junkies; recognizing podcasting as your own personal stage17:10 — How Harry's first paying client (a $1,000 PayPal from John Livesay) launched Fullcast in 201522:10 — Introducing Podisphere: A G2.com-style directory for podcast tools — the inspiration, the build journey, and why traffic is the only metric that matters to sponsors27:30 — Building with no-code tools (Airtable, Webflow, Bubble), the frustrations of non-technical founding, and how vibe coding changed everything in 202531:30 — Claude Code, Agent OS, and spec-driven development: how Harry built more in six months than in five years combined37:50 — SEO strategy for Podisphere: Fathom Analytics, Ahrefs, programmatic blog posts, Google Search Console, and hitting 7,000 page views/month without a press release45:20 — The power of founder relationships: How 12 years of Podcast Junkies led to meeting Andrew Mason (Descript), the SquadCast acquisition, and building a network that fuels Podisphere51:00 — Why every founder should have a podcast: relationship-building, opening doors, and earning "street cred"54:40 — Introducing Podclaw: An agent-first podcast hosting platform built for AI agents, not humans1:01:30 — Moltbook: The AI agent social network, digital wallets for agents, and autonomous marketing via cron jobs1:08:00 — The "agent economy" and why SaaS companies that block agents are "dead men walking"1:15:30 — Why the most important future skill is learning how to talk to robots; parallels to the dot-com era of 19991:21:30 — The future of podcasting: AI-generated shows, long-form authentic conversation, niche doubling down, and why human voices are becoming more valuable1:28:00 — NotebookLM and the rise of AI podcast hosts; the disclosure debate1:33:20 — Harry's personal operating system: morning meditation, written intentions, strength training, and protecting attention before screens1:37:30 — Where to find Harry: fullcast.co, thepodisphere.com, podclaw.ioTweetable Quotes"The most important skill in the future is learning how to talk to robots." — Harry Duran"You can't speak to someone for an hour and forget their face. That's the magic of podcasting — it builds relationships that nothing else can replicate." — Harry Duran"The people who made money in the gold rush were the ones who sold the picks, the shovels, and Levi's." — Harry Duran"Companies that block agents are dead men walking. If agents can't get the data from you, someone else will build what they need." — Jeff Mains"It never feels done — you just have to ship it. Get it out there." — Harry Duran"AI is like having the vision in your head and finally being able to build at the speed of thought." — Harry DuranSaaS Leadership Lessons1. Build Your Distribution Before You Need ItHarry spent over a decade building Podcast Junkies before it became the foundation of Podisphere. His relationships with founders like Andrew Mason (Descript) and the SquadCast team weren't accidental — they were built over 500+ interviews. Leaders who invest in platforms, relationships, and audiences compounding quietly are the ones who have leverage when they need it.2. Sell Picks and Shovels — Build for the EcosystemRather than fighting for space in a crowded software category, Harry positioned Podisphere as the infrastructure layer (the G2 of podcasting). Great SaaS leaders ask: What does this entire ecosystem need that nobody is building? Being a connector and aggregator often outlasts being just another point solution.3. Non-Technical Founders Must Learn to Build at the Speed of ThoughtHarry's journey from Airtable → Bubble → Fiverr developers → Claude Code is a roadmap for any non-technical founder in 2025. The bottleneck is no longer code — it's vision and prompting. The founder who can articulate their product clearly to an AI builds faster, iterates faster, and maintains greater ownership of the product direction.4. Traffic Is the Only Metric That Converts to Revenue — Build for Discovery FirstPodisphere hit 7,000 page views/month organically before a single press release by treating every page as an SEO asset. Harry obsessed over internal links, programmatic blog posts, and AEO (Answer Engine Optimization) for AI search. SaaS leaders building content or marketplace products should think like search engines think — not just build pretty interfaces.5. Agent-First Is the New Mobile-First — Design for It NowHarry didn't build Podclaw for human users. He built it for AI agents, complete with clean APIs, no unnecessary dashboards, and agent-friendly architecture. As agent economies emerge (complete with digital wallets and autonomous purchasing), SaaS products that block or ignore agents will be displaced. Build your API surface today like agents are your power users tomorrow.6. Protect Your Peak Performance Hours — Your Best Output Comes from Taking Care of Yourself FirstHarry meditates 20 minutes every morning, writes intentions in the present tense, and strength trains three days a week before opening a laptop. He's explicit: this is not a nice-to-have. The onslaught of screens, AI noise, and constant stimulation hijacks your nervous system. The leaders who perform at the highest level over the longest runway are the ones who treat personal maintenance as a non-negotiable operating system.Guest Resourceshttps://fullcast.co/hdbioEpisode SponsorThe Futureproof Series - https://www.youtube.com/playlist?list=PLfkXKUPZ5xuOqMPR7_gzGybncTtavyR1NThe Captain's KeysSmall Fish, Big Pond – https://smallfishbigpond.com/ Use the promo code ‘SaaSFuel'Champion Leadership Group – https://championleadership.com/SaaS Fuel ResourcesWebsite - https://championleadership.com/Jeff Mains on LinkedIn - https://www.linkedin.com/in/jeffkmains/Twitter - https://twitter.com/jeffkmainsFacebook - https://www.facebook.com/thesaasguy/Instagram - https://instagram.com/jeffkmains

L'automatisation peut sembler intimidante. Quand on entend parler de Zapier, Make, agents IA, no-code, workflows… on peut vite avoir l'impression que c'est réservé aux gens très techno.Mais en réalité, automatiser son travail, ce n'est pas nécessairement compliqué.Et surtout, ce n'est pas une question de devenir programmeur.C'est plutôt de savoir de repérer les tâches répétitives qui grugent ton temps, ton énergie et ton attention… puis de créer des systèmes simples pour que tes outils travaillent davantage pour toi.Dans cet épisode, je reçois Stéphanie Beaubien, aussi connue sous le nom de La Frondeuse.Stéphanie est travailleuse autonome depuis 2012. Elle s'est lancée dans la techno non pas parce qu'elle venait du monde du développement, mais parce qu'elle en avait besoin pour mieux gérer son entreprise.Aujourd'hui, elle dirige l'Agence La Fronde, une agence québécoise spécialisée en IA, automatisation et outils no-code pour les entrepreneurs.Dans cet épisode, tu vas découvrir :✅ C'est quoi concrètement l'automatisation, expliquée simplement✅ Comment des outils comme Make, Airtable ou Zapier peuvent t'aider à gagner du temps✅ Pourquoi ce n'est pas réservé aux programmeurs ou aux experts techno✅ Comment identifier les premières tâches à automatiser dans ton travail✅ Des exemples concrets d'automatisations utilesOn parle aussi de courriels, d'agents IA et de la place des nouveaux outils comme Claude, Codex et les assistants agentiques.Si tu sens que tu perds encore trop de temps dans des tâches répétitives, cet épisode va t'aider à voir beaucoup plus clair.LIENS ET RESSOURCES MENTIONNÉS

85% of AI teams will hit a serious production failure this year. The only thing separating them from the 15% who don't? Evals.After nearly two decades of building AI systems at Microsoft, Facebook, and Dropbox, Ameya Bhatawdekar is now Field CTO at Braintrust, the AI observability platform used by Airtable, Notion, Stripe, Dropbox, Vercel, Cloudflare, Lovable, and Replit.We discuss a shift that most teams underestimate. The winners in AI are not just shipping faster. They are building systems that behave predictably, improve continuously, and earn user trust over time. As traditional monitoring breaks down in a probabilistic world, observability now requires learning how an AI system reasons, not just how it performs. This leads to a new paradigm where agents are no longer just executing tasks, but also analyzing and debugging other agents.The episode also traces the evolution of machine learning itself. From feature engineering to deep learning to transformers , each leap increased capability and reduced control. Evaluation is now where control sits.Ameya is clear on one point. Moving fast with weak evaluations feels like velocity, but it compounds into technical debt, unpredictable failures, and ultimately a loss of user trust. The teams that win are the ones that invest early in rigor, especially in understanding context, which is quickly becoming the hardest and most critical layer in AI systems.If you are a founder or engineer moving beyond the demo phase and trying to build durable, high-quality AI systems, this episode will change how you think about shipping.0:00 — Trailer00:55 — What's Braintrust?05:01 — What agents are shipping today07:54 — What evals look like in practice for Notion & Zapier09:44 — Evals vs Classic monitoring11:33 — Who is the Field CTO?16:35 — What goes wrong when agents fail18:26 — Agents analyzing other agents24:17 — Evals are existential in vibecoding25:52 — Ship fast with weak evals or slow with strong evals?25:41 — What makes enterprises trust an LLM?29:25 — Do AI startups know how good their product is?30:23 — 3 ML systems: Microsoft, Dropbox, Meta36:30 — How the 2017 transformer paper changed everything38:20 — All algorithms are predicting the next word43:40 — What LLMs will do in 1 year-------------India's talent has built the world's tech—now it's time to lead it.This mission goes beyond startups. It's about shifting the center of gravity in global tech to include the brilliance rising from India.What is Neon Fund?We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that's done it before.Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we're doing it all at Neon.-------------Check us out on:Website: https://neon.fund/Instagram: https://www.instagram.com/theneonshoww/LinkedIn: https://www.linkedin.com/company/beneon/Twitter: https://x.com/TheNeonShowwConnect with Siddhartha on:LinkedIn: https://www.linkedin.com/in/siddharthaahluwalia/Twitter: https://x.com/siddharthaa7-------------This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.Send us Fan Mail

When your nonprofit outgrows spreadsheets and sticky notes, your impact can stall. In this episode, discover how smart, accessible data systems can free your team from copy‑and‑paste drudgery and unlock real capacity for relationship-building and growth.   Key Takeaways: Resilience in the face of uncertainty can become the catalyst for building an entirely new, impact-driven business. As organizations grow, decentralized spreadsheets eventually break; a centralized database becomes essential to scale programs and funding. The most effective systems are co-created with the people doing the work, so they're intuitive, low-friction, and actually get used. Thoughtful automation should target repetitive, manual, time-consuming tasks so staff can focus on high-value relationship and strategy work. The people who step up to improve operations and systems often position themselves for future leadership opportunities inside their organizations.   "You can think of Airtable like spreadsheets on steroids, or smarter spreadsheets."   “Airtable really comes in at a point where people are really struggling with all of their spreadsheets and their data is in too many places, and that's when you start implementing a database to store and centralize all of that information.”   “The key thing in automation that hasn't changed in the last while is just what sorts of things we want to automate: It's the repetitive work, the manual work, and the time-consuming work.” - Cherry Yang   Cherry Yang is the founder of Claribase, an award-winning Airtable consultancy and Airtable's Non-Profit Vertical Partner of the Year. She helps mission-driven organizations streamline operations with custom Airtable databases and automations so teams can save time, reduce chaos, and make better data-driven decisions.   Reach out to Cherry Yang at: Website: https://claribase.com/ LinkedIn: https://www.linkedin.com/in/cherry-yang-12368141/       Let's Work Together to Amplify Your Leadership + Influence1. Group Coaching for Nonprofit LeadersWant to lead with more clarity, confidence, and influence? My group coaching program is designed for nonprofit leaders who are ready to communicate more powerfully, navigate challenges with ease, and move their organizations forward. 2. Team Coaching + TrainingI work hands-on with nonprofit teams to strengthen leadership, improve communication, and align around a shared vision. Whether you're growing fast or feeling stuck, we'll create more clarity, collaboration, and momentum—together. 3. Board Retreats + TrainingsYour board has big potential. I'll help you unlock it. My engaging, no-fluff retreats and trainings are built to energize your board, refocus on what matters, and generate real results.Get your free starter kit today at www.theinfluentialnonprofit.comConnect with Maryanne about her coaching programs:https://www.courageouscommunication.com/connect Book Maryanne to speak at your conference:https://www.courageouscommunication.com/nonprofit-keynote-speaker

Okay, I'll just say it: I am an Airtable evangelist. I have been for years. It runs my episode archive, my client data, my business dashboard, my production workflows - honestly, it runs a lot of my personal life too. And I know that sounds like something I'm pitching, but I genuinely make zero money on Airtable. I just really, really believe in this tool.The problem is that what Airtable does can be hard to explain - and that makes a lot of photographers click around in it for a few minutes, get confused, and close the tab forever. That's exactly why I brought Ashley Rose back on the show this week.Ashley was here in February for a conversation about organizing your business (go back and listen to that one if you missed it). This time, we went deeper on Airtable specifically: what makes it genuinely different from a spreadsheet, how it stacks up against tools like Dubsado or HoneyBook, and the kinds of things photographers are actually building inside it that you might not have imagined yet.In this episode, we cover:  The real difference between a spreadsheet and a database - and why it matters for your client experience  How automations inside Airtable can handle client follow-up, reminders, and team communication without you lifting a finger  Why Ashley recommends Airtable even for photographers who have zero clients yet  A conversation about whether you should keep your CRM alongside Airtable (or if you can let one of them go)  Where to start if the blank canvas feels overwhelmingIf you've been curious about Airtable but didn't know where to begin, this one's for you.LINKS:Follow Systems Over Stress by Ashley Rose for practical systems, workflows, and business tips and Ashley's masterclass. Explore The Photographer's Business Dashboard — an all-in-one Airtable system and course designed to help photographers organize leads, projects, finances, and workflows with ease. Sign Up for the FREE Webinar: Economy Proof Your Business - 3 Ways to Make More Without Charging MoreResources:New to the podcast? Go to thiscantbethathard.com/welcome to get access to 3 of Annemie's best free resources.Join our community! We'd love to welcome you into our supportive, business-focused private Facebook group. Go to facebook.com/groups/thiscantbethathard to request access.Long-time listener? Leave a review!

Ever wished you could just talk to your Airtable base and have it do the heavy lifting? In this episode, we explore the incredible potential of the Model Context Protocol (MCP) and how it allows Claude to "speak" Airtable. We walk through a live setup and demonstration, showing you how to use natural language to discover your interfaces, query specific records, and even build out new tables and sample data in seconds. Whether you're a developer or a low-code enthusiast, this episode will change how you think about interacting with your data.

The Business Tools That Actually Keep Your VO Career Running One of the biggest misconceptions in voiceover is that success comes from talent plus a good booth. And yes, performance matters. Audio quality matters. But what actually creates consistency in this career is operational support. It's the systems you build that allow you to track opportunities, manage relationships, understand your income, organize your marketing, and reduce decision fatigue. Because decision fatigue is real, and it will stop you in your tracks and you will end up doing nothing. So today I want to walk you through some simple, accessible tools that you can use right now. Even if you don't have a team. Even if you don't have fancy software. Even if you feel completely disorganized. These are the tools that turn creative chaos into professional clarity. Excel or Google Sheets I know. A spreadsheet is not anyone's favorite thing. Nobody got into acting because they love spreadsheets. But spreadsheets give you something emotional actors often lack, which is objective data. If you don't have data, how will you know what's working and what isn't? How will you know how much time to keep spending on something or when to let it go or if you're underpricing yourself in a certain category? You can track auditions, bookings, client names, rates, follow-ups, usage conflicts, marketing outreach. When you track patterns you stop guessing. And we cannot have a successful career if we are constantly guessing. A spreadsheet is not restrictive. It's clarifying. Canva Canva is essentially the modern actor's design department. I know nothing about design and luckily Canva is there for social media graphics, pitch decks, rate sheets, lead magnets, ebooks, presentations. Actors often think marketing has to look DIY. It doesn't. Clean visual communication builds trust before you ever speak. I send cold leads lead magnets all the time. Sometimes it's an ebook like how to hire a voiceover actor or a checklist of what to expect when you've hired one. When you are the authority and expert in the room that's when you have true leadership within the role. Canva helps you look like a business with structure instead of a freelancer who's improvising. I use Canva Pro. You don't have to. There is plenty on the free version that makes it worth having in your arsenal. A Lightweight CRM When I say CRM a lot of actors panic. Customer relationship management systems can feel very corporate. But you can create a lightweight version with Airtable or Notion or even a spreadsheet. I have one I can send you the link to. The things you want to track are simple. Who you contacted, when, what their response was, what your email subject line was. Without those few things you can end up re-pitching the same person too soon or forgetting a warm lead entirely. Consistency beats charisma in client development. I promise you. A Calendar System Your calendar is not just for appointments. It's for marketing blocks, financial review days, audition batching, content creation, relationship maintenance. Actors live in reactive mode. A structured calendar helps you move into intentional career design. Time becomes something you allocate strategically instead of something that constantly feels like it's slipping away. When I transitioned into my block calendar system it changed my life. I know that sounds dramatic but I was constantly chasing minutes and feeling like I never had enough. Now I have control. I can actually plan things out and I'm never just too busy or not busy enough. It really did change my life. File Organization I know this sounds tiny. It is not. Clear folder systems on your desktop. Client name, project, scripts, finals. Demos organized by vertical and year. Invoices separated into paid and unpaid. Contracts sorted by active versus expired. When your files are organized you move faster. Speed is a competitive advantage in this industry, especially if you are working with agents or pay to plays. Disorganization creates friction that drains your creative energy. Spend twenty minutes on this. I promise you will feel so much better and more in control. A Password Manager This one is very adult and very real. My information was recently hacked and someone stole a significant amount of money from me and spent it all on DoorDash. I was very upset. Actors juggle casting sites, payment portals, editing software, social platforms. A password manager like LastPass or 1Password protects your business infrastructure. Security is professionalism. Nothing screams professional like having your shit together. A Capture System for Ideas Your brain is a constant working creative machine. But ideas disappear. How many times have you had a great idea and then completely lost it two minutes later? Use your notes app, voice memos, Notion boards, Trello. Capture content ideas, client leads, script concepts, branding language. Marketing consistency comes from capturing inspiration before it evaporates. I create a note, title it something like TikTok ideas, make a checkbox list, and add ideas as they come. When I've done it I check the box. I don't delete it because I might come back to it someday. I wish I had been doing this years ago. The Bottom Line Tools make you more sustainably creative. They don't make you less creative. They reduce chaos and they reduce the emotional decision-making spiral that actors can get wrapped up in. The actors who last in this business are not always the most naturally gifted. They're just the most together. Your homework this week is simple. Choose one tool and implement it imperfectly. It doesn't have to be beautiful or complete. Just begin. Because actors are not built in grand gestures. They are built in small systems that compound over time. Want to Keep the Conversation Going? Send me an email at mandy@actingbusinessbootcamp.com about the tools you're using or maybe a tool I haven't mentioned that's been a game changer for you. I love to hear from you. Find me on TikTok  or on Substack at The Actor's Index.    

Ever wondered what's hiding in the Airtable API documentation? In this episode, we're playing detective! Kamille uncovers a potentially game-changing undocumented automation scope that could change how you manage your bases forever. We also get hands-on with Airtable's AI Labs. Watch (and listen) as we test the limits of AI image and video generation, attempt to build web prototypes, and explore how structured data can make your automations more reliable. It's an experimental, high-energy exploration of where Airtable is headed next!

You chose the salad to be healthy, but is your dressing secretly working against you? Many popular dressings once contained titanium dioxide, an additive now banned in the EU over concerns it could potentially damage DNA. While many brands have removed it, your salad might still be swimming in a cocktail of inflammatory oils, hidden sugars (like high-fructose corn syrup), and artificial colors like Red 40. In this episode, we uncover the truth about what's really in your salad dressing. We'll show you how to become an ingredient-list detective, what to look for, and what to avoid. Plus, we share the absolute best and easiest way to take back control of your health: a delicious, two-minute homemade vinaigrette recipe that will save you money and upgrade your salads forever!   Stop drowning your greens in junk. It's time to make your healthy meal truly healthy.   **Chapters:** 0:00 - The Secret in Your "Healthy" Meal 1:05 - The Chemical Banned in Europe 2:58 - The Cocktail of Additives Still on Shelves 4:45 - How to Reclaim Your Salad 6:10 - The 2-Minute Homemade Dressing Recipe #healthyeating #saladdressing #titaniumdioxide #hiddensugars #nutritiontips Health Declassified is brought to you by Peter Wright & Kathleen Beauvais https://HealthDeclassified.com  peter@healthdeclassified.com    kathleen@healthdeclassified.com  Get our weekly newsletter for links to articles mentioned on the show, holistic health tips and news of future guests. Subscribe here   Content on our website, in our newsletter, in our audio and video episodes has been obtained from reliable sources, is for information only and should not be taken as medical advice. Check with your doctor before starting a new exercise or supplement programme especially if you have any joint, skeletal, mobility or digestive issues.   Here are some of the tools we use to produce this podcast. Kit for sending emails and caring for subscribers Hostgator for website hosting. Airtable for organizing our guest bookings and automations.   Clicking on some links on this site will let you buy products and services which may result in us receiving a commission, however, it will not affect the price you pay.  

In this episode, Joe Crane sits down with Anna Redmond, the Founder and CEO of Braav, to discuss her journey from Harvard and venture capital into the high-stakes world of corporate security and digital innovation. Through her work with Braav, Anna discovered the deep significance of the challenge coin tradition and realized that the 30 million Americans who own them often lack a way to preserve the oral histories they represent. To solve this, she created AllCoin, a platform that builds "digital twins" on the blockchain to ensure these legacies are immutable and accessible for future generations. Anna shares how she leveraged modern AI tools like Airtable's Hyper-Agent to build her business. Plus, listeners who mention the Veteran On the Move podcast can jump to the front of the AllCoin waiting list at allcoin.braav.co.   About Our Guest Anna Redmond is the Founder and CEO of Braav, where she deploys experienced Chief Security Officers into organizations that need to get serious about safety and riskfast. Her path into security was unconventional; she started in venture capital and studied at Harvard before shifting into the security world after recognizing how unprepared most companies are for real-world threats. She is now focused on modernizing challenge coins by building the first platform that gives these legacy symbols a digital twinpreserving not just the coin itself, but the story behind it. Her goal is to transform challenge coins from private artifacts into tools for identity, community, recognition, and eventually access and fundraising.   About Our Sponsors Navy Federal Credit Union   Navy Federal Credit Union is here to help you dominate your debt with the Platinum Card. Transfer your credit card balance to the Platinum card within your first 60 days and get a zero percent intro APR for 12 months. Visit here to start dominating debt. Join now at Navy Federal Credit Union. At Navy Federal, our members are the mission.      Join the conversation on Facebook! Check out Veteran on the Move on Facebook to connect with our guests and other listeners. A place where you can network with other like-minded veterans who are transitioning to entrepreneurship and get updates on people, programs and resources to help you in YOUR transition to entrepreneurship. Want to be our next guest? Send us an email at interview@veteranonthemove.com.  Did you love this episode? Leave us a 5-star rating and review!  Download Joe Crane's Top 7 Paths to Freedom or get it on your mobile device. Text VETERAN to 38470. Veteran On the Move podcast has published 600 episodes. Our listeners have the opportunity to hear in-depth interviews conducted by host Joe Crane. The podcast features people, programs, and resources to assist veterans in their transition to entrepreneurship.  As a result, Veteran On the Move has over 7,000,000 verified downloads through Stitcher Radio, SoundCloud, iTunes and RSS Feed Syndication making it one of the most popular Military Entrepreneur Shows on the Internet Today. Disclosure: Some of the links above are affiliate links. This means that, at zero cost to you, I will earn an affiliate commission if you purchase via the link provided.

Robby chats with Evan Tobias (Associate Professor of Music Education at Arizona State University) about imagining new possibilities for music teaching in a rapidly shifting digital landscape–from rethinking what curriculum even means, to the everyday tools that power his research, writing, and thinking. Subscribe to the Blog… RSS | Email Newsletter Subscribe to the Podcast in… Apple Podcasts | Overcast | Castro | Spotify | RSS Support Music Ed Tech Talk Become a Patron! Buy me a coffee Chapters and Notes 00:00:00 Greetings first 00:08:41 Introductions second Evan Tobias, Arizona State University YouTube TikTok Instagram Podcast AT Protocol Cory Doctorow's Book 00:26:04 What possibilities that exist when music teachers use technology in different ways Obsidian Weight of Light: A Collection of Solar Futures 00:54:38 What is curriculum? Podcast Episode 4: Music Curriculum Perspectives with Brian Laakso Hal Leonard Modern Band Series littleBits 01:11:25 Research and writing tools: writing, interviews, reading…lots! Connecting ideas across many mediums… Scite.AI - used to scan across databases, answer questions Hazel - file management DEVONthink - store, organize, work zotero - collect, organize, annotate, cite, and share research PDF Expert - PDF editing TextSniper - extract text from images 01:26:07 Surveys Qualtrics - creating surveys Calendly - scheduler that integrates with calendars TextExpander - type a keystroke that fills in email body or other text Keyboard Maestro - automate applications or websites Fantastical - give your calendar superpowers Craft - you know it, you love it 01:42:35 Interviews Descript - record, edit, transcribe Snipd - AI-powered podcast app Airtable - database to help keep track of where people are in the project Notion - database in place of Google Doc OmniFocus - Task management ClickUp - Task and project management Readwise Reader - PDF reader Raindrop.io Speechify - listen to text/PDF files Please don't forget to rate the show and share it with others!

Watch the YouTube version of this episode HEREAtlanta family law attorney Regina Edwards has been flat-fee for 15 years in one of the toughest practice areas: contested family litigation. In this episode, she breaks down how she uses automation, tight client selection, and a no‑phone policy to protect her time, deliver better results, and actually enjoy practicing law again.You'll hear how she intentionally stretches out her intake process to filter out “lava and piranha” clients, why she signs most divorces without doing a traditional consult, and how she trains her team to sell the process instead of selling access to her. Regina walks through her tech stack (Lawmatics, Pipefile, Motion.io, Airtable, portals, and more) and shows how she uses guides, portals, and automated updates to keep clients informed while dramatically cutting down on interruptions.If you've ever wondered whether flat fees can work in high‑conflict family law, or how to build a practice that supports vacations, boundaries, and deep work, this episode gives you a complete playbook you can start adapting today.Timestamps00:00 – You Don't Have To Bill Hourly ForeverRegina's story, 15 years of flat‑fee family law, and the “Lawyer on the Beach” mindset.02:00 – Stop Letting ‘Lava Clients' In The DoorBuilding a clear client avatar and stretching intake to filter out bad‑fit, high‑drama cases.05:10 – Flat Fees Only Work With RulesPaperless‑only firm, payment expectations, and why the team (not Regina) runs the intake machine.07:40 – Write The Rules Before Clients DoCommunication policy, no desk phone, redefining emergencies, and using autoresponders to hold boundaries.10:30 – One Guide, A Thousand Fewer QuestionsThe tinyURL client guide that covers timelines, portals, mediation, discovery, and vacation expectations.12:40 – Make Discovery Suck Less For EveryoneUsing Pipefile, reminders, and organized folders so clients actually finish discovery on time.15:40 – Turn Your Case File Into A Client PortalMotion.io + Airtable + Google Drive powering automated updates, status views, and task lists.18:20 – Build A Business You Still LoveHer tech stack, Profit First, value pricing, lifestyle design books, and why she still enjoys practicing law.Connect with Regina:Website Instagram Facebook Resources:Join the Guild MembershipSubscribe to the Maximum Lawyer Youtube ChannelFollow us on InstagramJoin the Facebook GroupFollow the Facebook PageFollow us on LinkedIn

Hey y'all — if you've ever felt like you need to chase down brand new leads every time you want to hit an income goal… this one is going to stop you in your tracks.In this episode, I'm joined by Erin Ollila — SEO strategist, copywriter, and host of Talk Copy to Me — for a conversation that originally aired on her podcast. We're talking about why the fastest path to more revenue is almost never a bigger audience. It's the people who are already in your world. Your past clients, your unconverted leads, your email list. And what you're actually supposed to do with them.Because here's the thing: if someone didn't book you three months ago, that doesn't mean they're never going to. And if you're ignoring them while you hustle to find someone brand new, you're making your business way harder than it needs to be.What You'll Learn in This EpisodeWhy your first stop for any income goal should be the people already in your CRM — not InstagramHow to generate referrals from clients in one-and-done businesses like wedding photography (without a paid referral program)How to re-engage past leads who didn't book the first time without being pushy or weird about itWhy tracking your lead-to-purchase timeline in Airtable will change how you think about nurturingWhat a strategic offboarding process looks like — and why it's one of your best sales toolsWhy creating more content is often just procrastination in disguiseLinks + Resources MentionedLearn more about Systems in Session: https://coliejames.com/systemsLearn more about Email Like You Mean It: https://coliejames.com/emailFind Erin Ollila at erinollila.comListen to Erin's podcast Talk Copy to Me

Limited BONUS: First 1,000 builders get $1,000. Claim yours while supplies lasts.: https://startup-ideas-pod.link/hyperagent I sit down with Howie Liu, co-founder and CEO of Airtable, to talk about the agent economy and the launch of HyperAgent. We walk through Sequoia's charts on AI agent deployment, the economics of token-based work versus human labor, and why frontier agents have crossed a threshold that changes how companies get built. Howie then does a live show-and-tell of HyperAgent, including a custom "Greg Isenberg contrarian AI" skill he spins up in real time. This one is for anyone building a solopreneur business, operating a fleet of agents, or trying to figure out where to place their bet in the agent ecosystem Timestamps 00:00 – Intro 02:22 – Sequoia's AI agent deployment chart reaction 04:41 – Copilot vs Autopilot territory and the $1T+ opportunity 08:13 – Agent economics vs human labor costs 11:12 – Fastest enterprise adoption curve in history 14:48 – The agent command center and fleet of 20 agents 18:03 – What is HyperAgent? 19:43 – Live demo: hyperlocal real estate market reports 22:38 – HyperAgent as the founder, not just the developer 23:21 – Street View, Zillow redesigns, and visual tool power 24:15 – Command center view across a fleet of agents 25:48 – Skills as the key primitive for frontier agents 26:30 – Building the Greg Isenberg contrarian AI skill live 32:31 – HyperAgent vs Perplexity Computer, Manus, OpenClaw, Codex 34:52 – Reviewing writing skill 36:55 – The arbitrage of persistence 41:31 – Confidence milestones: first dollar, $10K/month 35:27 – Reviewing contrarian tweet drafts live 45:05 – Giving the agent feedback and building rubrics 50:15 – Connectors, OAuth, and building custom API skills 53:03 – How to get started with HyperAgent 01:01:54 – Credit giveaway for listeners 01:03:31 – Closing Thoughts Key Points Frontier agents have crossed a threshold in the last 4–5 months where they function as true autonomous coworkers, not just chat assistants. Reframe agent cost by value delivered: a $150 token spend for a board memo beats hours of human time, so anchor on opportunity cost. The real arbitrage is persistence: 99% of people quit after one shot, while daily practice for 30/60/90 days produces top 1% operators. Skills are the most important primitive in frontier agents, turning generally intelligent models into domain experts through playbooks. HyperAgent's differentiation is a low floor plus a high ceiling, with rubrics, LLM-as-judge evals, and fleet-wide observability for scaling. Aim for $100B companies with under 5 employees, built on fleets of always-on agents mapped to human job roles. 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 HOWIE ON SOCIAL X/Twitter: https://x.com/howietl Hyperagent: https://www.hyperagent.com Airtable: https://www.airtable.com-

Ever thought about learning Airtable by playing a role-playing game? In this episode, we sit down with special guest Lisa to explore her brilliant hackathon project: 'Friends with Airtable.' It's a playful, immersive way to master the basics of the platform using the world of the hit TV show. Lisa takes us through her creative process—from being inspired by the intentional design of Super Mario to building a custom RPG that turns Airtable's features into fun challenges. You'll hear how she navigated the technical hurdles of using Airtable's Omni and Claude to bring her vision to life. Whether you're an Airtable pro or a total beginner, Lisa's insights on 'progressive learning' and her 'data-first' building strategy are game-changers for anyone looking to build more intuitive, user-friendly interfaces.

This episode focuses on the newly updated second edition of the Research Like a Pro with AI genealogy workbook. Nicole and Diana discuss how the book shifts its attention from early 2025 models to the most powerful models available in mid-February 2026, specifically ChatGPT 5.2, Claude Opus 4.6, and Gemini 3. Diana highlights the most significant change, which is the introduction of "agentic" browsers, including Claude in Chrome, Perplexity Comet, and ChatGPT Atlas. These autonomous agents can now perform tasks like actively clicking through family tree lines to find research gaps, navigating library catalogs to compile relevant collections, and autonomously executing research plans directly from a Google Doc. Nicole details the expanded coverage of Handwritten Text Recognition (HTR), which now includes specialized tools such as Gemini in Google AI Studio, Leo for paleography, and Ancestry.com's Image Transcript beta tool. Diana covers the native AI features built into genealogy platforms like Ancestry's "Ideas" and FamilySearch's AI Research Assistant, as well as productivity tools like Goldie May and Airtable. Nicole notes that Airtable AI is now more accessible to free users and describes how its new Omni sidebar can synthesize evidence across multiple rows, such as pulling together scattered land and tax records to build a case for a parent-child relationship. Diana provides crucial privacy updates, alerting users that Claude now trains on user data by default, and she outlines the specific limits on "Deep Research" features. She also discusses NotebookLM's ability to process YouTube video transcripts and Gemini 3's "spatial grounding" capabilities for reading complex historical documents. Listeners learn that the 2026 Second Edition moves from manual AI prompting to autonomous, integrated research workflows, equipping genealogists with cutting-edge efficiency. This summary was generated by Google Gemini. Links Agentic Browsers and Native Integrations: Inside the New Edition of Research Like a Pro with AI - https://familylocket.com/agentic-browsers-and-native-integrations-inside-the-new-edition-of-research-like-a-pro-with-ai/ Research Like a Pro with AI Workbook – Second Edition (eBook) - https://familylocket.com/product/research-like-a-pro-with-ai-workbook-second-edition-ebook/ Sponsor – Newspapers.com For listeners of this podcast, Newspapers.com is offering new subscribers 20% off a Publisher Extra subscription so you can start exploring today. Just use the code "FamilyLocket" at checkout.  Research Like a Pro Resources Airtable Universe - Nicole's Airtable Templates - https://www.airtable.com/universe/creator/usrsBSDhwHyLNnP4O/nicole-dyer Airtable Research Logs Quick Reference - by Nicole Dyer - https://familylocket.com/product-tag/airtable/ Research Like a Pro: A Genealogist's Guide book by Diana Elder with Nicole Dyer on Amazon.com - https://amzn.to/2x0ku3d 14-Day Research Like a Pro Challenge Workbook - digital - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-digital-only/ and spiral bound - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-spiral-bound/ Research Like a Pro Webinar Series - monthly case study webinars including documentary evidence and many with DNA evidence - https://familylocket.com/product-category/webinars/ Research Like a Pro eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-e-course/ RLP Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-study-group/ Research Like a Pro Institute Courses - https://familylocket.com/product-category/institute-course/ Research Like a Pro with DNA Resources Research Like a Pro with DNA: A Genealogist's Guide to Finding and Confirming Ancestors with DNA Evidence book by Diana Elder, Nicole Dyer, and Robin Wirthlin - https://amzn.to/3gn0hKx Research Like a Pro with DNA eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-with-dna-ecourse/ RLP with DNA Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-with-dna-study-group/ Thank you Thanks for listening! We hope that you will share your thoughts about our podcast and help us out by doing the following: Write a review on iTunes or Apple Podcasts. If you leave a review, we will read it on the podcast and answer any questions that you bring up in your review. Thank you! Leave a comment in the comment or question in the comment section below. Share the episode on Twitter, Facebook, or Pinterest. Subscribe on iTunes or your favorite podcast app. Sign up for our newsletter to receive notifications of new episodes - https://familylocket.com/sign-up/ Check out this list of genealogy podcasts from Feedspot: Best Genealogy Podcasts - https://blog.feedspot.com/genealogy_podcasts/

Hiring more people doesn't fix a broken leadership structure. Today, I'm joined by Kasia Lane, founder of Iron Peak Solutions, for an unfiltered forensic audit of the scaling process. Kasia pulls back the curtain on the "messy middle" of growth—from building their first loadboard in Airtable to the hard realization that being a founder and being a leader are two completely different skill sets. We dive into the "Hard Lessons in Hiring," including why emotional hiring leads to "B-Player" rot, how to stop over-coaching the wrong people, and the exact moment they realized that clear expectations remove the emotion from management. If you've ever felt like your team is drifting away from your standards, this episode is your blueprint for reclaiming your culture and scaling with structure.   Inside this Leadership Briefing: The Airtable to Revenova Journey: Scaling your tech stack as your volume explodes. The Emotional Hiring Trap: Why hiring friends and "mini-mes" stunts your growth. Accountability vs. Empathy: How to stop avoiding hard conversations and start setting non-negotiables. The 'Never Give It Back' Mentality: Instilling a bias for action and ownership in your ops team. Skills Over Gut: Using structured assessments to find "A-Players" who actually execute.   About Katherine Lane Kasia is a co-founder and CEO of Iron Peak Solutions, a freight brokerage built from the ground up in Colorado. She leads the company's growth and tech stack development, while overseeing the moving parts of the business to keep everything aligned and executing. Kasia is known for her honest take on what it actually looks like to scale a business, including the mistakes, lessons, and leadership challenges that come with it.   Connect with Kasia Website: https://ironpeaksolutions.com/   Email: katherine@ironpeaksolutions.com  

What if you could guarantee five-star reviews—without being on-site, glued to your phone, or buried in repetitive tasks? In this episode, AirDNA's Jamie Lane sits down with Sean McGregor, Founder of NoCodeSTR.com to unpack how automation, no-code tools, and AI are transforming what's possible in short-term rental operations.Sean McGregor helps short-term rental hosts and property managers “Automate the Annoying” parts of their business using NoCode tools, automation, and AI — so they can run leaner, deliver better guest experiences, and get their time back. He's the founder of NoCodeSTR.com (has hosted over 5,000 groups on Airbnb, and has maintained a 4.98★ rating since 2018. He even offers a 5★ Guarantee — meaning he doesn't take a commission if a guest leaves anything less than a 5-star review. All while running his business remotely from 40+ countries with his family).Sean shares how he went from manually managing a growing STR portfolio to building fully automated systems that deliver consistent, high-quality guest experiences—even while traveling internationally. By focusing relentlessly on guest satisfaction and eliminating friction through proactive communication, he created a system so reliable that he offered a bold guarantee: no five-star review, no commission.The conversation dives deep into the evolving tech stack—from tools like Airtable and Zapier to AI-powered messaging and custom-built workflows—and what it means for hosts and property managers today. Whether you're managing one listing or scaling to hundreds, this episode explores how to think about automation strategically, balance tech with hospitality, and unlock new levels of efficiency without sacrificing the human touch.You don't want to miss this episode!Key Takeaways for STR Hosts & ManagersAutomate proactively, not reactively: Anticipate guest needs (like check-in details or local recommendations) before they ask to prevent issues from turning into negative reviews.Use “second-day check-ins” to protect reviews: A simple automated message during the stay can surface problems early—giving you a chance to fix them before checkout.Centralize your data to unlock automation: Tools like Airtable can act as the brain of your operation, connecting bookings, messaging, maintenance, and guest insights.Start small, then layer complexity: Even a basic automation (like sending booking data to a spreadsheet) can spark momentum and lead to more advanced systems over time.Balance AI with human touch: Automate repetitive tasks, but stay personally available for high-touch moments—hospitality still matters.Sign up for AirDNA for FREE

Get our free Claude Cowork Workflow: https://clickhubspot.com/detf Ep. 419 How do you publish 250 pieces of content per week with zero employees? Kipp and Sabrina Ramonov of Blotato, dive into the exact AI-powered content workflow that built a 2 million-person audience—all as a solo creator. Learn more on building repeatable brand voice skills with AI, automating content creation from raw images, and managing an entire social media calendar through smart connectors and tools. Sabrina Ramonov is on a mission to teach 1 million people AI. She's the solo founder of Blotato.com, an AI SaaS app for creators and entrepreneurs to go viral on multiple social platforms like me (0 to 500k+ in 6 months solo). Mentions Sabrina Ramonov https://www.youtube.com/@sabrina_ramonov Blotato https://www.blotato.com/ Claude Cowork https://support.claude.com/en/articles/13345190-get-started-with-claude-cowork Airtable https://www.airtable.com/ Canva https://www.canva.com/ Get our guide to build your own Custom GPT: https://clickhubspot.com/customgpt We're creating our next round of content and want to ensure it tackles the challenges you're facing at work or in your business. To understand your biggest challenges we've put together a survey and we'd love to hear from you! https://bit.ly/matg-research 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  Join our community https://landing.connect.com/matg 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.

Ready to level up your Airtable development workflow? Today, we're diving deep into Airtable Sandboxes! If you've ever wanted to test a massive schema overhaul or a complex new automation without the fear of breaking your team's live work, this episode is for you. Kamille walks us through exactly how sandboxes work, acting much like a development branch for your data structure. But be warned: it's not as simple as 'test and click publish.' We reveal the hidden dangers of record ID mismatches and the one specific mistake that could accidentally cripple your entire base once you push your changes live. Tune in to learn how to use sandboxes like a pro and the best practices for building logic that stays stable across environments!

Want to take your Airtable game to the next level? In this episode, our team shares their top tips and tricks for maintaining and updating your bases. From creating new fields to avoiding common pitfalls, we've got you covered. Tune in for actionable advice and expert insights to help you optimize your workflow and get the most out of Airtable.

You know that moment when you look at your bank statement and realize you're still paying for software you stopped using three months ago? Yep. We've all been there.Profitability isn't just about what you charge - it's about what you keep. And for most photographers, there's money unnecessarily leaking out of the business every single month that a little attention could stop.In this episode, I'll walk you through my strategic approach to evaluating business expenses - not as a slash-and-burn exercise, but as a way to make your spending actually work for your business model. You'll come away with:  A clear process for getting every expense out of your head and onto paper (or into Airtable!)  Two simple filters to help you decide what's worth keeping and what isn't  The "don't starve your business" principle (because cutting the wrong things can cost you more in the long run)  A lightweight tracking system to keep expenses from getting away from you againWhether your bank account is looking slim after slow season or you just want to feel more in control of where your money goes, this episode gives you a practical framework to work through it.LINKS:  Photographer's Business Dashboard Business model quizResources:New to the podcast? Go to thiscantbethathard.com/welcome to get access to 3 of Annemie's best free resources.Join our community! We'd love to welcome you into our supportive, business-focused private Facebook group. Go to facebook.com/groups/thiscantbethathard to request access.Long-time listener? Leave a review!

Get ready to be inspired by the creativity and innovation of the Airtable community! In this episode, we explore the recent Airtable Build-a-Thon and the community-led hackathon, where participants showcased their skills and built amazing projects using Airtable. Our special guest, Mike Simmons, shares his experience judging the hackathon and we announce the winners of each category. Tune in to learn more about the latest updates and trends in the Airtable space and get inspired by the possibilities of what you can build with Airtable.

How do you know if the event agency you hired is actually a strategic partner? Or just a middleman? Choosing the right agency partner can shape the success of an entire event program, yet many teams still rely on RFP processes that miss what truly matters.In this episode, Matt Kleinrock sits down with event strategist and fractional Head of Events Gianna Gaudini to unpack how organizations should rethink agency selection from the start. Together, they explore how event leaders can run smarter RFPs, ask better questions, and evaluate agencies based on strategic value rather than surface-level proposals.You'll learn:✅ Why many RFP processes fail to reveal whether an agency can truly be a strategic partner✅ What questions event leaders should ask agencies to uncover real capabilities and alignment✅ Red flags that signal when an agency relationship may create more friction than valueWith experience spanning Google, AWS, and Airtable, Gianna brings a unique perspective from both brand-side and agency-side roles. Tune in to rethink how you choose agency partners and how better questions can lead to better event outcomes.---------------------------------- Connect with Gianna GaudiniLinkedIn: https://www.linkedin.com/in/giannagaudini/ Connect with Matt Kleinrock LinkedIn: https://www.linkedin.com/in/matt-kleinrock-9613b22b/Company: https://rockwayexhibits.com/

Send us Fan MailThis episode explores how nonprofits can fix fragmented data systems by centralizing information, improving reporting, and building scalable infrastructure that supports growth and better decision-making.  A strong nonprofit data management strategy is no longer optional—it's essential for scaling impact, improving reporting, and saving valuable staff time.Cherry Yang, CEO of Claribase and an award-winning Airtable consultant, shares how nonprofits can move from fragmented systems and spreadsheet overload to centralized, scalable data operations. If your team is constantly switching tools, copying and pasting data, or struggling to produce reports, this conversation offers a clear path forward.Cherry explains why most nonprofit systems fail: they operate in silos. Fundraising platforms, program data, financial tools, and spreadsheets often live separately—creating inefficiencies and increasing risk. As she notes, “People end up doing a lot of copy and pasting… and it just doesn't work. It's not efficient, and people waste so much time.” Instead, she advocates for centralized data systems that connect teams, automate workflows, and provide real-time dashboards for leadership. With the right structure, nonprofits can eliminate manual processes, reduce errors, and give decision-makers immediate access to insights.The business impact is significant. One organization Cherry worked with grew from 2 to 25 staff members in five years—largely because they could clearly report outcomes and secure funding through strong data practices. As Cherry puts it, “It's all about setting the organization up for scale… so leadership can get data at their fingertips.” This episode also addresses:How data fragmentation creates operational drag Why dashboards are critical for leadership and grant reporting How to structure training across different roles The connection between data systems and organizational growth If your nonprofit is ready to operate more efficiently and grow with confidence, this is a must-watch. 00:00:00 Introduction to nonprofit data challenges 00:02:00 What a nonprofit data strategy really means 00:05:05 Why nonprofit systems fail in silos 00:06:45 The hidden cost of copy-and-paste workflows 00:10:15 Real-world example: event and speaker data chaos 00:11:30 Centralizing systems with automation 00:14:00 Training teams for data success 00:16:30 Leadership dashboards and self-serve reporting 00:21:30 How dashboards improve grant reporting 00:22:20 Case study: scaling from 2 to 25 staff 00:24:30 Expanding data systems into finance and grants 00:27:30 Where to start: data health check and next steps #NonprofitData #NonprofitLeadership #TheNonprofitShowFind us Live daily on YouTube!Find us  Live daily on LinkedIn!Find us Live daily on X: @Nonprofit_ShowOur national co-hosts and amazing guests discuss management, money and missions of nonprofits!  12:30pm ET   11:30am CT  10:30am MT  9:30am PTSend us your ideas for Show Guests or Topics: HelpDesk@AmericanNonprofitAcademy.comVisit us on the web:The Nonprofit Show

In this episode of the Small Business PR Podcast, Gloria Chou breaks down the AI tool she says is saving her over $10,000 a month and replacing multiple team members: Claude Cowork.While most small business owners think of AI as just writing captions or emails, Gloria explains how “agentic AI” actually executes tasks across your business.What Makes This Different✔️ Not just writing—AI that completes tasks for you ✔️ Connects to your tools (Drive, Airtable, Calendar) ✔️ Analyzes data, workflows, and customer behavior ✔️ Works like a digital team, not just a chatbotThe 4 Roles It Replaces

Gokul Rajaram is one of the greatest operators turned investors of the last 2 decades. He is trusted as the go to advisor for the greatest founders in the world. Today he serves as a Board Director at three public companies: Coinbase, Pinterest and The Trade Desk. Prior to Marathon (his firm), Gokul served on the executive team at DoorDash and Block. Before Block, he served as Product Director of Ads at Facebook. Earlier in his career, Gokul served as a Product Management Director for Google AdSense. Gokul is also a prolific angel investor, having invested in 700+ companies, including Airtable, Figma, Groq, Runway, Supabase, and Vercel.  AGENDA: 03:53 — Investing Lessons from Google, Doordash and Facebook 05:32 — Why Mark Zuckerberg is the Greatest Distribution Genius Alive 07:23 — Why Every Company Today Needs to be Multi-Product 09:16 — Negative Gross Margins: Are the Best Companies Actually Built on "Shit" Economics? 10:50 — The SaaS Apocalypse: Is the Entire Sector Going to Zero? 12:15 — The 8 Moats of Enduring Software Companies: How to Analyse Companies 14:50 — Why Brand is No Longer a Strong Moat (And What Replaced It) 16:13 — Salesforce vs. Atlassian: Which Systems of Record are Dying? 18:13 — Outcome-Based Pricing: Is This the Total Death of Seat Pricing? 20:16 — The Bolt-On AI Trap: Why Rebuilding Your Entire UX is Non-Negotiable 23:44 — Are the Outcome Sizes of Vertical SaaS Large Enough for VC Today? 28:16 — The Zombie Cohort: What Happens to Private Companies with High Valuations? 32:44 — Is "King Making" Complete Bullshit? 34:21 — Durability Over Margins: What Really Matters in a 100x Growth World 35:36 — The Non-Consumption Miracle: Why Granola and Gamma are Crushing It 38:50 — The PayPal Rule: Can You Raise Prices 5 Times in 3 Years? 42:47 — My Biggest Miss: How I Misread the Shopify Billion-Dollar Mark 45:18 — The Courage to Bet: Why Instacart is the Best VC Deal Ever 46:33 — Seed vs. Growth Pricing: When Does Price Actually Destroy Returns? 50:53 — Does "Proprietary Founder Access" Even Exist? 54:33 — Double Down or Diversify? The Truth About Fund Reserves 59:44 — The Vanta Anti-Portfolio: A Mistake I'll Never Forget 01:01:21 — When to Sell: The "Sell a Third, Hold a Third, Trade a Third" Rule 01:04:12 — Why Remote Early-Stage Companies are Dying 01:07:33 — Why Mid-Level Partners are Fleeing Mega Funds 01:09:47 — The Best CEO Superpowers: Larry, Mark, Jack, and Tony 01:12:33 — The Next 10 Years: Why Dropouts are "AI Maxing" the World    

In this episode of Research Like a Pro, Diana and Nicole discuss the all-new Version 4.2 (2026) of the Research Like a Pro with DNA Airtable Research Log. The updates are designed to streamline the genetic genealogy workflow, making DNA research more flexible and reducing duplicate data entry.  Diana details the biggest change: the "Test-taker" and "DNA Match" fields in the DNA Match Details table are renamed to "Person 1 (P1)" and "Person 2 (P2)." This simple but powerful update allows users to record the shared DNA between any two people, including matches and their shared matches, which is particularly useful for analyzing data from Ancestry Pro Shared Matches, MyHeritage, and FTDNA. Nicole highlights that the family tree URLs, kit administrator fields, and match usernames are now centralized exclusively in the People table. This makes them lookup fields in other tables, meaning users enter the information only once and save significant time. Furthermore, Nicole discusses the Timeline table enhancement, where a new formula automatically converts varied date entries (e.g., "March 1857") into a standardized sortable format. Diana confirms that core tables like Locations, FANs, and Segments remain the same, preserving existing workflows. Listeners will learn how to make the most of the new base, with tips for migrating data from older versions. Diana concludes that the changes are designed for maximum efficiency, helping researchers focus more on analysis and discovery. This summary was generated by Google Gemini. Links RLP with DNA Research Log 4.2 (2026) Airtable Template Updates - https://familylocket.com/rlp-with-dna-research-log-4-2-2026-airtable-template-updates/ RLP with DNA Airtable Template 2026 – Updates and Change Log (https://docs.google.com/document/d/1UYWptPpc02N5S8Rn8muSoGXvE2SfCkcl_DehG9TVRvQ/edit?usp=sharing Airtable Research Logs Quick Reference - by Nicole Dyer - https://familylocket.com/product-tag/airtable/ Research Like a Pro Institute Courses including Merging and Separating Identities - https://familylocket.com/product-category/institute-course/ Sponsor – Newspapers.com For listeners of this podcast, Newspapers.com is offering new subscribers 20% off a Publisher Extra subscription so you can start exploring today. Just use the code "FamilyLocket" at checkout.  Research Like a Pro Resources Airtable Universe - Nicole's Airtable Templates - https://www.airtable.com/universe/creator/usrsBSDhwHyLNnP4O/nicole-dyer Airtable Research Logs Quick Reference - by Nicole Dyer - https://familylocket.com/product-tag/airtable/ Research Like a Pro: A Genealogist's Guide book by Diana Elder with Nicole Dyer on Amazon.com - https://amzn.to/2x0ku3d 14-Day Research Like a Pro Challenge Workbook - digital - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-digital-only/ and spiral bound - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-spiral-bound/ Research Like a Pro Webinar Series - monthly case study webinars including documentary evidence and many with DNA evidence - https://familylocket.com/product-category/webinars/ Research Like a Pro eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-e-course/ RLP Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-study-group/ Research Like a Pro with DNA Resources Research Like a Pro with DNA: A Genealogist's Guide to Finding and Confirming Ancestors with DNA Evidence book by Diana Elder, Nicole Dyer, and Robin Wirthlin - https://amzn.to/3gn0hKx Research Like a Pro with DNA eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-with-dna-ecourse/ RLP with DNA Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-with-dna-study-group/ Thank you Thanks for listening! We hope that you will share your thoughts about our podcast and help us out by doing the following: Write a review on iTunes or Apple Podcasts. If you leave a review, we will read it on the podcast and answer any questions that you bring up in your review. Thank you! Leave a comment in the comment or question in the comment section below. Share the episode on Twitter, Facebook, or Pinterest. Subscribe on iTunes or your favorite podcast app. Sign up for our newsletter to receive notifications of new episodes - https://familylocket.com/sign-up/ Check out this list of genealogy podcasts from Feedspot: Best Genealogy Podcasts - https://blog.feedspot.com/genealogy_podcasts/

257 | IT Security ist ein Milliarden-Business. Mit AI wird IT Security zu Human Security - diese Geschäftsideen sind jetzt vielversprechend.Partner dieser Folge:HolviFinanzen für kleine Unternehmen: Von Chaos zu Klarheit mit HOLVI - Das kostenlos Holvi Flex Konto ist perfekt für Solopreneure, Freelancer und Unternehmen, die wachsen wollen. ⁠⁠www.holvi.com⁠Mach das 1-minütige Quiz und finde eine Geschäftsidee, die zu dir passt: digitaleoptimisten.de/quiz.Kapitel(00:00) Intro(05:20) Project Genie und Wehrpflicht(19:42) Sequoia Artikel: Service-as-a-software → https://sequoiacap.com/article/services-the-new-software/(33:15) Roast my Geschäftsidee: Christians Anti-Enkeltrick (habe Post von Optimisten genutzt, weil du das so anmoderiert hast)(41:40) AI Use Case der Woche: Samuels Demand & Supply Analyst mit Claude und Make(54:18) Samuels Geschäftsidee: Lan Corner(58:52) Alex' Geschäftsidee: Nudge PayLearningsService als Software-AnsatzSequoia beschreibt Servatisation of Startups: statt Softwarelizenzen werden Ergebnisse geliefert; AI macht diese Dienstleistungen skalierbar. Aus diesem Grund wächst der Fokus auf Services statt reiner Software. Hypothese: Dieser Trend könnte künftig dominante Geschäftsmodelle formen, weil Service-Outcomes leichter skalierbar sind als herkömmliche Software.Vier-Quadranten-DenkregelEs ergibt sich ein Vier-Quadranten-Modell: zwei Achsen Intelligence versus Judgment und Outsourced versus Insourced. Beispiele: Versicherungsbroker fällt in Outsourced + Intelligenz, NDAs werden als spezialisiertes Outsourcing gesehen. Die Einordnung hilft bei der Priorisierung von Markt-Chancen, Personalplanung und go-to-market-Strategien. Hypothese: Unternehmen werden stärker auf AI-unterstützte Outsourcing-Angebote setzen, um Kosten zu senken und Skalierung zu ermöglichen.AI-Agenten für Demand-Supply-PlanungEin konkreter Use Case ist der Einsatz von AI-Agenten für Demand-Supply-Planning: Daten aus Airtable fließen in einen Monthly-Report über Make.com, Claude und Anthropic-Module, der per Slack versendet wird. So entsteht eine automatisierte Forecast- und Allocations-Ansicht für Vertrieb und Marketing. Damit lassen sich Budgets gezielt auf Gewerke und Regionen lenken und kurzfristig Anpassungen vornehmen.Gesellschaftliche Vernetzung in AI-Zeit Project Genie zeigt, wie AI Jobs entgrenzt und gemeinsame kulturelle Erlebnisse gefährden könnte; es werden Ideen wie Wehrpflicht oder gemeinschaftliche Formate diskutiert, um soziale Bindung zu stärken. Hypothese: in einer von AI geprägten Arbeitswelt braucht es kollektive Rahmen, um gesellschaftliche Kohäsion und Austausch zu erhalten.KeywordsAI-AgentenProject GenieService-as-a-Software-ModellAI-AutopilotAI-DienstleistungenAI-Autopilot für VersicherungsbrokerNDAs automatisieren mit AIKYC-Automatisierung durch AIAI-gestützte Lieferanten- und HandwerkeranalyseAutomatisierungOutsourcing vs InsourcingHuman SecurityIntelligenz vs UrteilsvermögenGesellschaftliche Auswirkungen von KI

Kenny Harper interviews Brenda Canaan about reducing tax-season chaos by scheduling tax prep and controlling workload instead of accepting documents anytime. Cannon explains how her firm previously promised 2–3 week turnarounds without knowing capacity, leading to bottlenecks like 105 clients submitting documents on March 15, and how the pandemic highlighted the lack of workload control. Inspired by a podcast, she implemented a scheduling system using Calendly, Make, and Airtable, then co-developed the Schedule E software to better track client scheduling, automate reminders, and support flexible calendars by preparer or client type. She emphasizes proactive client communication about extensions, using tax projections when needed, improving efficiency, reducing status checks and errors, and using scheduling for capacity planning, client fit, and better work-life balance. 00:00 Why Scheduling Matters 01:12 Meet Brenda Cannon 03:26 From Chaos to Control 05:11 Building Schedule E 06:34 Client Buy In 08:42 Rolling It Out 15:22 Handling Extensions 15:48 Community and Setup 22:28 Capacity and Team 24:51 Lessons and Wrap Up

Turbopuffer came out of a reading app.In 2022, Simon was helping his friends at Readwise scale their infra for a highly requested feature: article recommendations and semantic search. Readwise was paying ~$5k/month for their relational database and vector search would cost ~$20k/month making the feature too expensive to ship. In 2023 after mulling over the problem from Readwise, Simon decided he wanted to “build a search engine” which became Turbopuffer.We discuss:• Simon's path: Denmark → Shopify infra for nearly a decade → “angel engineering” across startups like Readwise, Replicate, and Causal → turbopuffer almost accidentally becoming a company • The Readwise origin story: building an early recommendation engine right after the ChatGPT moment, seeing it work, then realizing it would cost ~$30k/month for a company spending ~$5k/month total on infra and getting obsessed with fixing that cost structure • Why turbopuffer is “a search engine for unstructured data”: Simon's belief that models can learn to reason, but can't compress the world's knowledge into a few terabytes of weights, so they need to connect to systems that hold truth in full fidelity • The three ingredients for building a great database company: a new workload, a new storage architecture, and the ability to eventually support every query plan customers will want on their data • The architecture bet behind turbopuffer: going all in on object storage and NVMe, avoiding a traditional consensus layer, and building around the cloud primitives that only became possible in the last few years • Why Simon hated operating Elasticsearch at Shopify: years of painful on-call experience shaped his obsession with simplicity, performance, and eliminating state spread across multiple systems • The Cursor story: launching turbopuffer as a scrappy side project, getting an email from Cursor the next day, flying out after a 4am call, and helping cut Cursor's costs by 95% while fixing their per-user economics • The Notion story: buying dark fiber, tuning TCP windows, and eating cross-cloud costs because Simon refused to compromise on architecture just to close a deal faster • Why AI changes the build-vs-buy equation: it's less about whether a company can build search infra internally, and more about whether they have time especially if an external team can feel like an extension of their own • Why RAG isn't dead: coding companies still rely heavily on search, and Simon sees hybrid retrieval semantic, text, regex, SQL-style patterns becoming more important, not less • How agentic workloads are changing search: the old pattern was one retrieval call up front; the new pattern is one agent firing many parallel queries at once, turning search into a highly concurrent tool call • Why turbopuffer is reducing query pricing: agentic systems are dramatically increasing query volume, and Simon expects retrieval infra to adapt to huge bursts of concurrent search rather than a small number of carefully chosen calls • The philosophy of “playing with open cards”: Simon's habit of being radically honest with investors, including telling Lachy Groom he'd return the money if turbopuffer didn't hit PMF by year-end • The “P99 engineer”: Simon's framework for building a talent-dense company, rejecting by default unless someone on the team feels strongly enough to fight for the candidate —Simon Hørup Eskildsen• LinkedIn: https://www.linkedin.com/in/sirupsen• X: https://x.com/Sirupsen• https://sirupsen.com/aboutturbopuffer• https://turbopuffer.com/Full Video PodTimestamps00:00:00 The PMF promise to Lachy Groom00:00:25 Intro and Simon's background00:02:19 What turbopuffer actually is00:06:26 Shopify, Elasticsearch, and the pain behind the company00:10:07 The Readwise experiment that sparked turbopuffer00:12:00 The insight Simon couldn't stop thinking about00:17:00 S3 consistency, NVMe, and the architecture bet00:20:12 The Notion story: latency, dark fiber, and conviction00:25:03 Build vs. buy in the age of AI00:26:00 The Cursor story: early launch to breakout customer00:29:00 Why code search still matters00:32:00 Search in the age of agents00:34:22 Pricing turbopuffer in the AI era00:38:17 Why Simon chose Lachy Groom00:41:28 Becoming a founder on purpose00:44:00 The “P99 engineer” philosophy00:49:30 Bending software to your will00:51:13 The future of turbopuffer00:57:05 Simon's tea obsession00:59:03 Tea kits, X Live, and P99 LiveTranscriptSimon Hørup Eskildsen: I don't think I've said this publicly before, but I just called Lockey and was like, local Lockie. Like if this doesn't have PMF by the end of the year, like we'll just like return all the money to you. But it's just like, I don't really, we, Justine and I don't wanna work on this unless it's really working.So we want to give it the best shot this year and like we're really gonna go for it. We're gonna hire a bunch of people. We're just gonna be honest with everyone. Like when I don't know how to play a game, I just play with open cards. Lockey was the only person that didn't, that didn't freak out. He was like, I've never heard anyone say that before.Alessio: Hey everyone, welcome to the Leading Space podcast. This is Celesio Pando, Colonel Laz, and I'm joined by Swix, editor of Leading Space.swyx: Hello. Hello, uh, we're still, uh, recording in the Ker studio for the first time. Very excited. And today we are joined by Simon Eski. Of Turbo Farer welcome.Simon Hørup Eskildsen: Thank you so much for having me.swyx: Turbo Farer has like really gone on a huge tear, and I, I do have to mention that like you're one of, you're not my newest member of the Danish AHU Mafia, where like there's a lot of legendary programmers that have come out of it, like, uh, beyond Trotro, Rasmus, lado Berg and the V eight team and, and Google Maps team.Uh, you're mostly a Canadian now, but isn't that interesting? There's so many, so much like strong Danish presence.Simon Hørup Eskildsen: Yeah, I was writing a post, um, not that long ago about sort of the influences. So I grew up in Denmark, right? I left, I left when, when I was 18 to go to Canada to, to work at Shopify. Um, and so I, like, I've, I would still say that I feel more Danish than, than Canadian.This is also the weird accent. I can't say th because it, this is like, I don't, you know, my wife is also Canadian, um, and I think. I think like one of the things in, in Denmark is just like, there's just such a ruthless pragmatism and there's also a big focus on just aesthetics. Like, they're like very, people really care about like where, what things look like.Um, and like Canada has a lot of attributes, US has, has a lot of attributes, but I think there's been lots of the great things to carry. I don't know what's in the water in Ahu though. Um, and I don't know that I could be considered part of the Mafi mafia quite yet, uh, compared to the phenomenal individuals we just mentioned.Barra OV is also, uh, Danish Canadian. Okay. Yeah. I don't know where he lives now, but, and he's the PHP.swyx: Yeah. And obviously Toby German, but moved to Canada as well. Yes. Like this is like import that, uh, that, that is an interesting, um, talent move.Alessio: I think. I would love to get from you. Definition of Turbo puffer, because I think you could be a Vector db, which is maybe a bad word now in some circles, you could be a search engine.It's like, let, let's just start there and then we'll maybe run through the history of how you got to this point.Simon Hørup Eskildsen: For sure. Yeah. So Turbo Puffer is at this point in time, a search engine, right? We do full text search and we do vector search, and that's really what we're specialized in. If you're trying to do much more than that, like then this might not be the right place yet, but Turbo Buffer is all about search.The other way that I think about it is that we can take all of the world's knowledge, all of the exabytes and exabytes of data that there is, and we can use those tokens to train a model, but we can't compress all of that into a few terabytes of weights, right? Compress into a few terabytes of weights, how to reason with the world, how to make sense of the knowledge.But we have to somehow connect it to something externally that actually holds that like in full fidelity and truth. Um, and that's the thing that we intend to become. Right? That's like a very holier than now kind of phrasing, right? But being the search engine for unstructured, unstructured data is the focus of turbo puffer at this point in time.Alessio: And let's break down. So people might say, well, didn't Elasticsearch already do this? And then some other people might say, is this search on my data, is this like closer to rag than to like a xr, like a public search thing? Like how, how do you segment like the different types of search?Simon Hørup Eskildsen: The way that I generally think about this is like, there's a lot of database companies and I think if you wanna build a really big database company, sort of, you need a couple of ingredients to be in the air.We don't, which only happens roughly every 15 years. You need a new workload. You basically need the ambition that every single company on earth is gonna have data in your database. Multiple times you look at a company like Oracle, right? You will, like, I don't think you can find a company on earth with a digital presence that it not, doesn't somehow have some data in an Oracle database.Right? And I think at this point, that's also true for Snowflake and Databricks, right? 15 years later it's, or even more than that, there's not a company on earth that doesn't, in. Or directly is consuming Snowflake or, or Databricks or any of the big analytics databases. Um, and I think we're in that kind of moment now, right?I don't think you're gonna find a company over the next few years that doesn't directly or indirectly, um, have all their data available for, for search and connect it to ai. So you need that new workload, like you need something to be happening where there's a new workload that causes that to happen, and that new workload is connecting very large amounts of data to ai.The second thing you need. The second condition to build a big database company is that you need some new underlying change in the storage architecture that is not possible from the databases that have come before you. If you look at Snowflake and Databricks, right, commoditized, like massive fleet of HDDs, like that was not possible in it.It just wasn't in the air in the nineties, right? So you just didn't, we just didn't build these systems. S3 and and and so on was not around. And I think the architecture that is now possible that wasn't possible 15 years ago is to go all in on NVME SSDs. It requires a particular type of architecture for the database that.It's difficult to retrofit onto the databases that are already there, including the ones you just mentioned. The second thing is to go all in on OIC storage, more so than we could have done 15 years ago. Like we don't have a consensus layer, we don't really have anything. In fact, you could turn off all the servers that Turbo Buffer has, and we would not lose any data because we have all completely all in on OIC storage.And this means that our architecture is just so simple. So that's the second condition, right? First being a new workload. That means that every company on earth, either indirectly or directly, is using your database. Second being, there's some new storage architecture. That means that the, the companies that have come before you can do what you're doing.I think the third thing you need to do to build a big database company is that over time you have to implement more or less every Cory plan on the data. What that means is that you. You can't just get stuck in, like, this is the one thing that a database does. It has to be ever evolving because when someone has data in the database, they over time expect to be able to ask it more or less every question.So you have to do that to get the storage architecture to the limit of what, what it's capable of. Those are the three conditions.swyx: I just wanted to get a little bit of like the motivation, right? Like, so you left Shopify, you're like principal, engineer, infra guy. Um, you also head of kernel labs, uh, inside of Shopify, right?And then you consulted for read wise and that it kind of gave you that, that idea. I just wanted you to tell that story. Um, maybe I, you've told it before, but, uh, just introduce the, the. People to like the, the new workload, the sort of aha moment for turbo PufferSimon Hørup Eskildsen: For sure. So yeah, I spent almost a decade at Shopify.I was on the infrastructure team, um, from the fairly, fairly early days around 2013. Um, at the time it felt like it was growing so quickly and everything, all the metrics were, you know, doubling year on year compared to the, what companies are contending with today. It's very cute in growth. I feel like lot some companies are seeing that month over month.Um, of course. Shopify compound has been compounding for a very long time now, but I spent a decade doing that and the majority of that was just make sure the site is up today and make sure it's up a year from now. And a lot of that was really just the, um, you know, uh, the Kardashians would drive very, very large amounts of, of data to, to uh, to Shopify as they were rotating through all the merch and building out their businesses.And we just needed to make sure we could handle that. Right. And sometimes these were events, a million requests per second. And so, you know, we, we had our own data centers back in the day and we were moving to the cloud and there was so much sharding work and all of that that we were doing. So I spent a decade just scaling databases ‘cause that's fundamentally what's the most difficult thing to scale about these sites.The database that was the most difficult for me to scale during that time, and that was the most aggravating to be on call for, was elastic search. It was very, very difficult to deal with. And I saw a lot of projects that were just being held back in their ambition by using it.swyx: And I mean, self-hosted.Self-hosted. ‘causeSimon Hørup Eskildsen: it's, yeah, and it commercial, this is like 2015, right? So it's like a very particular vintage. Right. It's probably better at a lot of these things now. Um, it was difficult to contend with and I'm just like, I just think about it. It's an inverted index. It should be good at these kinds of queries and do all of this.And it was, we, we often couldn't get it to do exactly what we needed to do or basically get lucine to do, like expose lucine raw to, to, to what we needed to do. Um, so that was like. Just something that we did on the side and just panic scaled when we needed to, but not a particular focus of mine. So I left, and when I left, I, um, wasn't sure exactly what I wanted to do.I mean, it spent like a decade inside of the same company. I'd like grown up there. I started working there when I was 18.swyx: You only do Rails?Simon Hørup Eskildsen: Yeah. I mean, yeah. Rails. And he's a Rails guy. Uh, love Rails. So good. Um,Alessio: we all wish we could still work in Rails.swyx: I know know. I know, but some, I tried learning Ruby.It's just too much, like too many options to do the same thing. It's, that's my, I I know there's a, there's a way to do it.Simon Hørup Eskildsen: I love it. I don't know that I would use it now, like given cloud code and, and, and cursor and everything, but, um, um, but still it, like if I'm just sitting down and writing a teal code, that's how I think.But anyway, I left and I wasn't, I talked to a couple companies and I was like, I don't. I need to see a little bit more of the world here to know what I'm gonna like focus on next. Um, and so what I decided is like I was gonna, I called it like angel engineering, where I just hopped around in my friend's companies in three months increments and just helped them out with something.Right. And, and just vested a bit of equity and solved some interesting infrastructure problem. So I worked with a bunch of companies at the time, um, read Wise was one of them. Replicate was one of them. Um, causal, I dunno if you've tried this, it's like a, it's a spreadsheet engine Yeah. Where you can do distribution.They sold recently. Yeah. Um, we've been, we used that in fp and a at, um, at Turbo Puffer. Um, so a bunch of companies like this and it was super fun. And so we're the Chachi bt moment happened, I was with. With read Wise for a stint, we were preparing for the reader launch, right? Which is where you, you cue articles and read them later.And I was just getting their Postgres up to snuff, like, which basically boils down to tuning, auto vacuum. So I was doing that and then this happened and we were like, oh, maybe we should build a little recommendation engine and some features to try to hook in the lms. They were not that good yet, but it was clear there was something there.And so I built a small recommendation engine just, okay, let's take the articles that you've recently read, right? Like embed all the articles and then do recommendations. It was good enough that when I ran it on one of the co-founders of Rey's, like I found out that I got articles about, about having a child.I'm like, oh my God, I didn't, I, I didn't know that, that they were having a child. I wasn't sure what to do with that information, but the recommendation engine was good enough that it was suggesting articles, um, about that. And so there was, there was recommendations and uh, it actually worked really well.But this was a company that was spending maybe five grand a month in total on all their infrastructure and. When I did the napkin math on running the embeddings of all the articles, putting them into a vector index, putting it in prod, it's gonna be like 30 grand a month. That just wasn't tenable. Right?Like Read Wise is a proudly bootstrapped company and it's paying 30 grand for infrastructure for one feature versus five. It just wasn't tenable. So sort of in the bucket of this is useful, it's pretty good, but let us, let's return to it when the costs come down.swyx: Did you say it grows by feature? So for five to 30 is by the number of, like, what's the, what's the Scaling factor scale?It scales by the number of articles that you embed.Simon Hørup Eskildsen: It does, but what I meant by that is like five grand for like all of the other, like the Heroku, dinos, Postgres, like all the other, and this then storage is 30. Yeah. And then like 30 grand for one feature. Right. Which is like, what other articles are related to this one.Um, so it was just too much right to, to power everything. Their budget would've been maybe a few thousand dollars, which still would've been a lot. And so we put it in a bucket of, okay, we're gonna do that later. We'll wait, we will wait for the cost to come down. And that haunted me. I couldn't stop thinking about it.I was like, okay, there's clearly some latent demand here. If the cost had been a 10th, we would've shipped it and. This was really the only data point that I had. Right. I didn't, I, I didn't, I didn't go out and talk to anyone else. It was just so I started reading Right. I couldn't, I couldn't help myself.Like I didn't know what like a vector index is. I, I generally barely do about how to generate the vectors. There was a lot of hype about, this is a early 2023. There was a lot of hype about vector databases. There were raising a lot of money and it's like, I really didn't know anything about it. It's like, you know, trying these little models, fine tuning them.Like I was just trying to get sort of a lay of the land. So I just sat down. I have this. A GitHub repository called Napkin Math. And on napkin math, there's just, um, rows of like, oh, this is how much bandwidth. Like this is how many, you know, you can do 25 gigabytes per second on average to dram. You can do, you know, five gigabytes per second of rights to an SSD, blah blah.All of these numbers, right? And S3, how many you could do per, how much bandwidth can you drive per connection? I was just sitting down, I was like, why hasn't anyone build a database where you just put everything on O storage and then you puff it into NVME when you use the data and you puff it into dram if you're, if you're querying it alive, it's just like, this seems fairly obvious and you, the only real downside to that is that if you go all in on o storage, every right will take a couple hundred milliseconds of latency, but from there it's really all upside, right?You do the first go, it takes half a second. And it sort of occurred to me as like, well. The architecture is really good for that. It's really good for AB storage, it's really good for nvm ESSD. It's, well, you just couldn't have done that 10 years ago. Back to what we were talking about before. You really have to build a database where you have as few round trips as possible, right?This is how CPUs work today. It's how NVM E SSDs work. It's how as, um, as three works that you want to have a very large amount of outstanding requests, right? Like basically go to S3, do like that thousand requests to ask for data in one round trip. Wait for that. Get that, like, make a new decision. Do it again, and try to do that maybe a maximum of three times.But no databases were designed that way within NVME as is ds. You can drive like within, you know, within a very low multiple of DRAM bandwidth if you use it that way. And same with S3, right? You can fully max out the network card, which generally is not maxed out. You get very, like, very, very good bandwidth.And, but no one had built a database like that. So I was like, okay, well can't you just, you know, take all the vectors right? And plot them in the proverbial coordinate system. Get the clusters, put a file on S3 called clusters, do json, and then put another file for every cluster, you know, cluster one, do js O cluster two, do js ON you know that like it's two round trips, right?So you get the clusters, you find the closest clusters, and then you download the cluster files like the, the closest end. And you could do this in two round trips.swyx: You were nearest neighbors locally.Simon Hørup Eskildsen: Yes. Yes. And then, and you would build this, this file, right? It's just like ultra simplistic, but it's not a far shot from what the first version of Turbo Buffer was.Why hasn't anyone done thatAlessio: in that moment? From a workload perspective, you're thinking this is gonna be like a read heavy thing because they're doing recommend. Like is the fact that like writes are so expensive now? Oh, with ai you're actually not writing that much.Simon Hørup Eskildsen: At that point I hadn't really thought too much about, well no actually it was always clear to me that there was gonna be a lot of rights because at Shopify, the search clusters were doing, you know, I don't know, tens or hundreds of crew QPS, right?‘cause you just have to have a human sit and type in. But we did, you know, I don't know how many updates there were per second. I'm sure it was in the millions, right into the cluster. So I always knew there was like a 10 to 100 ratio on the read write. In the read wise use case. It's, um, even, even in the read wise use case, there'd probably be a lot fewer reads than writes, right?There's just a lot of churn on the amount of stuff that was going through versus the amount of queries. Um, I wasn't thinking too much about that. I was mostly just thinking about what's the fundamentally cheapest way to build a database in the cloud today using the primitives that you have available.And this is it, right? You just, now you have one machine and you know, let's say you have a terabyte of data in S3, you paid the $200 a month for that, and then maybe five to 10% of that data and needs to be an NV ME SSDs and less than that in dram. Well. You're paying very, very little to inflate the data.swyx: By the way, when you say no one else has done that, uh, would you consider Neon, uh, to be on a similar path in terms of being sort of S3 first and, uh, separating the compute and storage?Simon Hørup Eskildsen: Yeah, I think what I meant with that is, uh, just build a completely new database. I don't know if we were the first, like it was very much, it was, I mean, I, I hadn't, I just looked at the napkin math and was like, this seems really obvious.So I'm sure like a hundred people came up with it at the same time. Like the light bulb and every invention ever. Right. It was just in the air. I think Neon Neon was, was first to it. And they're trying, they're retrofitted onto Postgres, right? And then they built this whole architecture where you have, you have it in memory and then you sort of.You know, m map back to S3. And I think that was very novel at the time to do it for, for all LTP, but I hadn't seen a database that was truly all in, right. Not retrofitting it. The database felt built purely for this no consensus layer. Even using compare and swap on optic storage to do consensus. I hadn't seen anyone go that all in.And I, I mean, there, there, I'm sure there was someone that did that before us. I don't know. I was just looking at the napkin mathswyx: and, and when you say consensus layer, uh, are you strongly relying on S3 Strong consistency? You are. Okay.SoSimon Hørup Eskildsen: that is your consensus layer. It, it is the consistency layer. And I think also, like, this is something that most people don't realize, but S3 only became consistent in December of 2020.swyx: I remember this coming out during COVID and like people were like, oh, like, it was like, uh, it was just like a free upgrade.Simon Hørup Eskildsen: Yeah.swyx: They were just, they just announced it. We saw consistency guys and like, okay, cool.Simon Hørup Eskildsen: And I'm sure that they just, they probably had it in prod for a while and they're just like, it's done right.And people were like, okay, cool. But. That's a big moment, right? Like nv, ME SSDs, were also not in the cloud until around 2017, right? So you just sort of had like 2017 nv, ME SSDs, and people were like, okay, cool. There's like one skew that does this, whatever, right? Takes a few years. And then the second thing is like S3 becomes consistent in 2020.So now it means you don't have to have this like big foundation DB or like zookeeper or whatever sitting there contending with the keys, which is how. You know, that's what Snowflake and others have do so muchswyx: for goneSimon Hørup Eskildsen: Exactly. Just gone. Right? And so just push to the, you know, whatever, how many hundreds of people they have working on S3 solved and then compare and swap was not in S3 at this point in time,swyx: by the way.Uh, I don't know what that is, so maybe you wanna explain. Yes. Yeah.Simon Hørup Eskildsen: Yes. So, um, what Compare and swap is, is basically, you can imagine that if you have a database, it might be really nice to have a file called metadata json. And metadata JSON could say things like, Hey, these keys are here and this file means that, and there's lots of metadata that you have to operate in the database, right?But that's the simplest way to do it. So now you have might, you might have a lot of servers that wanna change the metadata. They might have written a file and want the metadata to contain that file. But you have a hundred nodes that are trying to contend with this metadata that JSON well, what compare and Swap allows you to do is basically just you download the file, you make the modifications, and then you write it only if it hasn't changed.While you did the modification and if not you retry. Right? Should just have this retry loops. Now you can imagine if you have a hundred nodes doing that, it's gonna be really slow, but it will converge over time. That primitive was not available in S3. It wasn't available in S3 until late 2024, but it was available in GCP.The real story of this is certainly not that I sat down and like bake brained it. I was like, okay, we're gonna start on GCS S3 is gonna get it later. Like it was really not that we started, we got really lucky, like we started on GCP and we started on GCP because tur um, Shopify ran on GCP. And so that was the platform I was most available with.Right. Um, and I knew the Canadian team there ‘cause I'd worked with them at Shopify and so it was natural for us to start there. And so when we started building the database, we're like, oh yeah, we have to build a, we really thought we had to build a consensus layer, like have a zookeeper or something to do this.But then we discovered the compare and swap. It's like, oh, we can kick the can. Like we'll just do metadata r json and just, it's fine. It's probably fine. Um, and we just kept kicking the can until we had very, very strong conviction in the idea. Um, and then we kind of just hinged the company on the fact that S3 probably was gonna get this, it started getting really painful in like mid 2024.‘cause we were closing deals with, um, um, notion actually that was running in AWS and we're like, trust us. You, you really want us to run this in GCP? And they're like, no, I don't know about that. Like, we're running everything in AWS and the latency across the cloud were so big and we had so much conviction that we bought like, you know, dark fiber between the AWS regions in, in Oregon, like in the InterExchange and GCP is like, we've never seen a startup like do like, what's going on here?And we're just like, no, we don't wanna do this. We were tuning like TCP windows, like everything to get the latency down ‘cause we had so high conviction in not doing like a, a metadata layer on S3. So those were the three conditions, right? Compare and swap. To do metadata, which wasn't in S3 until late 2024 S3 being consistent, which didn't happen until December, 2020.Uh, 2020. And then NVMe ssd, which didn't end in the cloud until 2017.swyx: I mean, in some ways, like a very big like cloud success story that like you were able to like, uh, put this all together, but also doing things like doing, uh, bind our favor. That that actually is something I've never heard.Simon Hørup Eskildsen: I mean, it's very common when you're a big company, right?You're like connecting your own like data center or whatever. But it's like, it was uniquely just a pain with notion because the, um, the org, like most of the, like if you're buying in Ashburn, Virginia, right? Like US East, the Google, like the GCP and, and AWS data centers are like within a millisecond on, on each other, on the public exchanges.But in Oregon uniquely, the GCP data center sits like a couple hundred kilometers, like east of Portland and the AWS region sits in Portland, but the network exchange they go through is through Seattle. So it's like a full, like 14 milliseconds or something like that. And so anyway, yeah. It's, it's, so we were like, okay, we can't, we have to go through an exchange in Portland.Yeah. Andswyx: you'd rather do this than like run your zookeeper and likeSimon Hørup Eskildsen: Yes. Way rather. It doesn't have state, I don't want state and two systems. Um, and I think all that is just informed by Justine, my co-founder and I had just been on call for so long. And the worst outages are the ones where you have state in multiple places that's not syncing up.So it really came from, from a a, like just a, a very pure source of pain, of just imagining what we would be Okay. Being woken up at 3:00 AM about and having something in zookeeper was not one of them.swyx: You, you're talking to like a notion or something. Do they care or do they just, theySimon Hørup Eskildsen: just, they care about latency.swyx: They latency cost. That's it.Simon Hørup Eskildsen: They just cared about latency. Right. And we just absorbed the cost. We're just like, we have high conviction in this. At some point we can move them to AWS. Right. And so we just, we, we'll buy the fiber, it doesn't matter. Right. Um, and it's like $5,000. Usually when you buy fiber, you buy like multiple lines.And we're like, we can only afford one, but we will just test it that when it goes over the public internet, it's like super smooth. And so we did a lot of, anyway, it's, yeah, it was, that's cool.Alessio: You can imagine talking to the GCP rep and it's like, no, we're gonna buy, because we know we're gonna turn, we're gonna turn from you guys and go to AWS in like six months.But in the meantime we'll do this. It'sSimon Hørup Eskildsen: a, I mean, like they, you know, this workload still runs on GCP for what it's worth. Right? ‘cause it's so, it was just, it was so reliable. So it was never about moving off GCP, it was just about honesty. It was just about giving notion the latency that they deserved.Right. Um, and we didn't want ‘em to have to care about any of this. We also, they were like, oh, egress is gonna be bad. It was like, okay, screw it. Like we're just gonna like vvc, VPC peer with you and AWS we'll eat the cost. Yeah. Whatever needs to be done.Alessio: And what were the actual workloads? Because I think when you think about ai, it's like 14 milliseconds.It's like really doesn't really matter in the scheme of like a model generation.Simon Hørup Eskildsen: Yeah. We were told the latency, right. That we had to beat. Oh, right. So, so we're just looking at the traces. Right. And then sort of like hand draw, like, you know, kind of like looking at the trace and then thinking what are the other extensions of the trace?Right. And there's a lot more to it because it's also when you have, if you have 14 versus seven milliseconds, right. You can fit in another round trip. So we had to tune TCP to try to send as much data in every round trip, prewarm all the connections. And there was, there's a lot of things that compound from having these kinds of round trips, but in the grand scheme it was just like, well, we have to beat the latency of whatever we're up against.swyx: Which is like they, I mean, notion is a database company. They could have done this themselves. They, they do lots of database engineering themselves. How do you even get in the door? Like Yeah, just like talk through that kind of.Simon Hørup Eskildsen: Last time I was in San Francisco, I was talking to one of the engineers actually, who, who was one of our champions, um, at, AT Notion.And they were, they were just trying to make sure that the, you know, per user cost matched the economics that they needed. You know, Uhhuh like, it's like the way I think about, it's like I have to earn a return on whatever the clouds charge me and then my customers have to earn a return on that. And it's like very simple, right?And so there has to be gross margin all the way up and that's how you build the product. And so then our customers have to make the right set of trade off the turbo Puffer makes, and if they're happy with that, that's great.swyx: Do you feel like you're competing with build internally versus buy or buy versus buy?Simon Hørup Eskildsen: Yeah, so, sorry, this was all to build up to your question. So one of the notion engineers told me that they'd sat and probably on a napkin, like drawn out like, why hasn't anyone built this? And then they saw terrible. It was like, well, it literally that. So, and I think AI has also changed the buy versus build equation in terms of, it's not really about can we build it, it's about do we have time to build it?I think they like, I think they felt like, okay, if this is a team that can do that and they, they feel enough like an extension of our team, well then we can go a lot faster, which would be very, very good for them. And I mean, they put us through the, through the test, right? Like we had some very, very long nights to to, to do that POC.And they were really our biggest, our second big customer off the cursor, which also was a lot of late nights. Right.swyx: Yeah. That, I mean, should we go into that story? The, the, the sort of Chris's story, like a lot, um, they credit you a lot for. Working very closely with them. So I just wanna hear, I've heard this, uh, story from Sole's point of view, but like, I'm curious what, what it looks like from your side.Simon Hørup Eskildsen: I actually haven't heard it from Sole's point of view, so maybe you can now cross reference it. The way that I remember it was that, um, the day after we launched, which was just, you know, I'd worked the whole summer on, on the first version. Justine wasn't part of it yet. ‘cause I just, I didn't tell anyone that summer that I was working on this.I was just locked in on building it because it's very easy otherwise to confuse talking about something to actually doing it. And so I was just like, I'm not gonna do that. I'm just gonna do the thing. I launched it and at this point turbo puffer is like a rust binary running on a single eight core machine in a T Marks instance.And me deploying it was like looking at the request log and then like command seeing it or like control seeing it to just like, okay, there's no request. Let's upgrade the binary. Like it was like literally the, the, the, the scrappiest thing. You could imagine it was on purpose because just like at Shopify, we did that all the time.Like, we like move, like we ran things in tux all the time to begin with. Before something had like, at least the inkling of PMF, it was like, okay, is anyone gonna hear about this? Um, and one of the cursor co-founders Arvid reached out and he just, you know, the, the cursor team are like all I-O-I-I-M-O like, um, contenders, right?So they just speak in bullet points and, and facts. It was like this amazing email exchange just of, this is how many QPS we have, this is what we're paying, this is where we're going, blah, blah, blah. And so we're just conversing in bullet points. And I tried to get a call with them a few times, but they were, so, they were like really writing the PMF bowl here, just like late 2023.And one time Swally emails me at like five. What was it like 4:00 AM Pacific time saying like, Hey, are you open for a call now? And I'm on the East coast and I, it was like 7:00 AM I was like, yeah, great, sure, whatever. Um, and we just started talking and something. Then I didn't know anything about sales.It was something that just comp compelled me. I have to go see this team. Like, there's something here. So I, I went to San Francisco and I went to their office and the way that I remember it is that Postgres was down when I showed up at the office. Did SW tell you this? No. Okay. So Postgres was down and so it's like they were distracting with that.And I was trying my best to see if I could, if I could help in any way. Like I knew a little bit about databases back to tuning, auto vacuum. It was like, I think you have to tune out a vacuum. Um, and so we, we talked about that and then, um, that evening just talked about like what would it look like, what would it look like to work with us?And I just said. Look like we're all in, like we will just do what we'll do whatever, whatever you tell us, right? They migrated everything over the next like week or two, and we reduced their cost by 95%, which I think like kind of fixed their per user economics. Um, and it solved a lot of other things. And we were just, Justine, this is also when I asked Justine to come on as my co-founder, she was the best engineer, um, that I ever worked with at Shopify.She lived two blocks away and we were just, okay, we're just gonna get this done. Um, and we did, and so we helped them migrate and we just worked like hell over the next like month or two to make sure that we were never an issue. And that was, that was the cursor story. Yeah.swyx: And, and is code a different workload than normal text?I, I don't know. Is is it just text? Is it the same thing?Simon Hørup Eskildsen: Yeah, so cursor's workload is basically, they, um, they will embed the entire code base, right? So they, they will like chunk it up in whatever they would, they do. They have their own embedding model, um, which they've been public about. Um, and they find that on, on, on their evals.It. There's one of their evals where it's like a 25% improvement on a very particular workload. They have a bunch of blog posts about it. Um, I think it works best on larger code basis, but they've trained their own embedding model to do this. Um, and so you'll see it if you use the cursor agent, it will do searches.And they've also been public around, um, how they've, I think they post trained their model to be very good at semantic search as well. Um, and that's, that's how they use it. And so it's very good at, like, can you find me on the code that's similar to this, or code that does this? And just in, in this queries, they also use GR to supplement it.swyx: Yeah.Simon Hørup Eskildsen: Um, of courseswyx: it's been a big topic of discussion like, is rag dead because gr you know,Simon Hørup Eskildsen: and I mean like, I just, we, we see lots of demand from the coding company to ethicsswyx: search in every part. Yes.Simon Hørup Eskildsen: Uh, we, we, we see demand. And so, I mean, I'm. I like case studies. I don't like, like just doing like thought pieces on this is where it's going.And like trying to be all macroeconomic about ai, that's has turned out to be a giant waste of time because no one can really predict any of this. So I just collect case studies and I mean, cursor has done a great job talking about what they're doing and I hope some of the other coding labs that use Turbo Puffer will do the same.Um, but it does seem to make a difference for particular queries. Um, I mean we can also do text, we can also do RegX, but I should also say that cursors like security posture into Tur Puffer is exceptional, right? They have their own embedding model, which makes it very difficult to reverse engineer. They obfuscate the file paths.They like you. It's very difficult to learn anything about a code base by looking at it. And the other thing they do too is that for their customers, they encrypt it with their encryption keys in turbo puffer's bucket. Um, so it's, it's, it's really, really well designed.swyx: And so this is like extra stuff they did to work with you because you are not part of Cursor.Exactly like, and this is just best practice when working in any database, not just you guys. Okay. Yeah, that makes sense. Yeah. I think for me, like the, the, the learning is kind of like you, like all workloads are hybrid. Like, you know, uh, like you, you want the semantic, you want the text, you want the RegX, you want sql.I dunno. Um, but like, it's silly to like be all in on like one particularly query pattern.Simon Hørup Eskildsen: I think, like I really like the way that, um, um, that swally at cursor talks about it, which is, um, I'm gonna butcher it here. Um, and you know, I'm a, I'm a database scalability person. I'm not a, I, I dunno anything about training models other than, um, what the internet tells me and what.The way he describes is that this is just like cash compute, right? It's like you have a point in time where you're looking at some particular context and focused on some chunk and you say, this is the layer of the neural net at this point in time. That seems fundamentally really useful to do cash compute like that.And, um, how the value of that will change over time. I'm, I'm not sure, but there seems to be a lot of value in that.Alessio: Maybe talk a bit about the evolution of the workload, because even like search, like maybe two years ago it was like one search at the start of like an LLM query to build the context. Now you have a gentech search, however you wanna call it, where like the model is both writing and changing the code and it's searching it again later.Yeah. What are maybe some of the new types of workloads or like changes you've had to make to your architecture for it?Simon Hørup Eskildsen: I think you're right. When I think of rag, I think of, Hey, there's an 8,000 token, uh, context window and you better make it count. Um, and search was a way to do that now. Everything is moving towards the, just let the agent do its thing.Right? And so back to the thing before, right? The LLM is very good at reasoning with the data, and so we're just the tool call, right? And that's increasingly what we see our customers doing. Um, what we're seeing more demand from, from our customers now is to do a lot of concurrency, right? Like Notion does a ridiculous amount of queries in every round trip just because they can't.And I'm also now, when I use the cursor agent, I also see them doing more concurrency than I've ever seen before. So a bit similar to how we designed a database to drive as much concurrency in every round trip as possible. That's also what the agents are doing. So that's new. It means just an enormous amount of queries all at once to the dataset while it's warm in as few turns as possible.swyx: Can I clarify one thing on that?Simon Hørup Eskildsen: Yes.swyx: Is it, are they batching multiple users or one user is driving multiple,Simon Hørup Eskildsen: one user driving multiple, one agent driving.swyx: It's parallel searching a bunch of things.Simon Hørup Eskildsen: Exactly.swyx: Yeah. Yeah, exactly. So yeah, the clinician also did, did this for the fast context thing, like eight parallel at once.Simon Hørup Eskildsen: Yes.swyx: And, and like an interesting problem is, well, how do you make sure you have enough diversity so you're not making the the same request eight times?Simon Hørup Eskildsen: And I think like that's probably also where the hybrid comes in, where. That's another way to diversify. It's a completely different way to, to do the search.That's a big change, right? So before it was really just like one call and then, you know, the LLM took however many seconds to return, but now we just see an enormous amount of queries. So the, um, we just see more queries. So we've like tried to reduce query, we've reduced query pricing. Um, this is probably the first time actually I'm saying that, but the query pricing is being reduced, like five x.Um, and we'll probably try to reduce it even more to accommodate some of these workloads of just doing very large amounts of queries. Um, that's one thing that's changed. I think the right, the right ratio is still very high, right? Like there's still a, an enormous amount of rights per read, but we're starting probably to see that change if people really lean into this pattern.Alessio: Can we talk a little bit about the pricing? I'm curious, uh, because traditionally a database would charge on storage, but now you have the token generation that is so expensive, where like the actual. Value of like a good search query is like much higher because they're like saving inference time down the line.How do you structure that as like, what are people receptive to on the other side too?Simon Hørup Eskildsen: Yeah. I, the, the turbo puffer pricing in the beginning was just very simple. The pricing on these on for search engines before Turbo Puffer was very server full, right? It was like, here's the vm, here's the per hour cost, right?Great. And I just sat down with like a piece of paper and said like, if Turbo Puffer was like really good, this is probably what it would cost with a little bit of margin. And that was the first pricing of Turbo Puffer. And I just like sat down and I was like, okay, like this is like probably the storage amp, but whenever on a piece of paper I, it was vibe pricing.It was very vibe price, and I got it wrong. Oh. Um, well I didn't get it wrong, but like Turbo Puffer wasn't at the first principle pricing, right? So when Cursor came on Turbo Puffer, it was like. Like, I didn't know any VCs. I didn't know, like I was just like, I don't know, I didn't know anything about raising money or anything like that.I just saw that my GCP bill was, was high, was a lot higher than the cursor bill. So Justine and I was just like, well, we have to optimize it. Um, and I mean, to the chagrin now of, of it, of, of the VCs, it now means that we're profitable because we've had so much pricing pressure in the beginning. Because it was running on my credit card and Justine and I had spent like, like tens of thousands of dollars on like compute bills and like spinning off the company and like very like, like bad Canadian lawyers and like things like to like get all of this done because we just like, we didn't know.Right. If you're like steeped in San Francisco, you're just like, you just know. Okay. Like you go out, raise a pre-seed round. I, I never heard a word pre-seed at this point in time.swyx: When you had Cursor, you had Notion you, you had no funding.Simon Hørup Eskildsen: Um, with Cursor we had no funding. Yeah. Um, by the time we had Notion Locke was, Locke was here.Yeah. So it was really just, we vibe priced it 100% from first Principles, but it wasn't, it, it was not performing at first principles, so we just did everything we could to optimize it in the beginning for that, so that at least we could have like a 5% margin or something. So I wasn't freaking out because Cursor's bill was also going like this as they were growing.And so my liability and my credit limit was like actively like calling my bank. It was like, I need a bigger credit. Like it was, yeah. Anyway, that was the beginning. Yeah. But the pricing was, yeah, like storage rights and query. Right. And the, the pricing we have today is basically just that pricing with duct tape and spit to try to approach like, you know, like a, as a margin on the physical underlying hardware.And we're doing this year, you're gonna see more and more pricing changes from us. Yeah.swyx: And like is how much does stuff like VVC peering matter because you're working in AWS land where egress is charged and all that, you know.Simon Hørup Eskildsen: We probably don't like, we have like an enterprise plan that just has like a base fee because we haven't had time to figure out SKU pricing for all of this.Um, but I mean, yeah, you can run turbo puffer either in SaaS, right? That's what Cursor does. You can run it in a single tenant cluster. So it's just you. That's what Notion does. And then you can run it in, in, in BYOC where everything is inside the customer's VPC, that's what an for example, philanthropic does.swyx: What I'm hearing is that this is probably the best CRO job for somebody who can come in and,Simon Hørup Eskildsen: I mean,swyx: help you with this.Simon Hørup Eskildsen: Um, like Turbo Puffer hired, like, I don't know what, what number this was, but we had a full-time CFO as like the 12th hire or something at Turbo Puffer, um, I think I hear are a lot of comp.I don't know how they do it. Like they have a hundred employees and not a CFO. It's like having a CFO is like a runningswyx: business man. Like, you know,Simon Hørup Eskildsen: it's so good. Yeah, like money Mike, like he just, you know, just handles the money and a lot of the business stuff and so he came in and just hopped with a lot of the operational side of the business.So like C-O-O-C-F-O, like somewhere in between.swyx: Just as quick mention of Lucky, just ‘cause I'm curious, I've met Lock and like, he's obviously a very good investor and now on physical intelligence, um, I call it generalist super angel, right? He invests in everything. Um, and I always wonder like, you know, is there something appealing about focusing on developer tooling, focusing on databases, going like, I've invested for 10 years in databases versus being like a lock where he can maybe like connect you to all the customers that you need.Simon Hørup Eskildsen: This is an excellent question. No, no one's asked me this. Um, why lockey? Because. There was a couple of people that we were talking to at the time and when we were raising, we were almost a little, we were like a bit distressed because one of our, one of our peers had just launched something that was very similar to Turbo Puffer.And someone just gave me the advice at the time of just choose the person where you just feel like you can just pick up the phone and not prepare anything. And just be completely honest, and I don't think I've said this publicly before, but I just called Lockey and was like local Lockie. Like if this doesn't have PMF by the end of the year, like we'll just like return all the money to you.But it's just like, I don't really, we, Justine and I don't wanna work on this unless it's really working. So we want to give it the best shot this year and like we're really gonna go for it. We're gonna hire a bunch of people and we're just gonna be honest with everyone. Like when I don't know how to play a game, I just play with open cards and.Lockey was the only person that didn't, that didn't freak out. He was like, I've never heard anyone say that before. As I said, I didn't even know what a seed or pre-seed round was like before, probably even at this time. So I was just like very honest with him. And I asked him like, Lockie, have you ever have, have you ever invested in database company?He was just like, no. And at the time I was like, am I dumb? Like, but I think there was something that just like really drew me to Lockie. He is so authentic, so honest, like, and there was something just like, I just felt like I could just play like, just say everything openly. And that was, that was, I think that that was like a perfect match at the time, and, and, and honestly still is.He was just like, okay, that's great. This is like the most honest, ridiculous thing I've ever heard anyone say to me. But like that, like that, whyswyx: is this ridiculous? Say competitor launch, this may not work out. It wasSimon Hørup Eskildsen: more just like. If this doesn't work out, I'm gonna close up shop by the end of the mo the year, right?Like it was, I don't know, maybe it's common. I, I don't know. He told me it was uncommon. I don't know. Um, that's why we chose him and he'd been phenomenal. The other people were talking at the, at the time were database experts. Like they, you know, knew a lot about databases and Locke didn't, this turned out to be a phenomenal asset.Right. I like Justine and I know a lot about databases. The people that we hire know a lot about databases. What we needed was just someone who didn't know a lot about databases, didn't pretend to know a lot about databases, and just wanted to help us with candidates and customers. And he did. Yeah. And I have a list, right, of the investors that I have a relationship with, and Lockey has just performed excellent in the number of sub bullets of what we can attribute back to him.Just absolutely incredible. And when people talk about like no ego and just the best thing for the founder, I like, I don't think that anyone, like even my lawyer is like, yeah, Lockey is like the most friendly person you will find.swyx: Okay. This is my most glow recommendation I've ever heard.Alessio: He deserves it.He's very special.swyx: Yeah. Yeah. Yeah. Okay. Amazing.Alessio: Since you mentioned candidates, maybe we can talk about team building, you know, like, especially in sf, it feels like it's just easier to start a company than to join a company. Uh, I'm curious your experience, especially not being n SF full-time and doing something that is maybe, you know, a very low level of detail and technical detail.Simon Hørup Eskildsen: Yeah. So joining versus starting, I never thought that I would be a founder. I would start with it, like Turbo Puffer started as a blog post, and then it became a project and then sort of almost accidentally became a company. And now it feels like it's, it's like becoming a bigger company. That was never the intention.The intentions were very pure. It's just like, why hasn't anyone done this? And it's like, I wanna be the, like, I wanna be the first person to do it. I think some founders have this, like, I could never work for anyone else. I, I really don't feel that way. Like, it's just like, I wanna see this happen. And I wanna see it happen with some people that I really enjoy working with and I wanna have fun doing it and this, this, this has all felt very natural on that, on that sense.So it was never a like join versus versus versus found. It was just dis found me at the right moment.Alessio: Well I think there's an argument for, you should have joined Cursor, right? So I'm curious like how you evaluate it. Okay, I should actually go raise money and make this a company versus like, this is like a company that is like growing like crazy.It's like an interesting technical problem. I should just build it within Cursor and then they don't have to encrypt all this stuff. They don't have to obfuscate things. Like was that on your mind at all orSimon Hørup Eskildsen: before taking the, the small check from Lockie, I did have like a hard like look at myself in the mirror of like, okay, do I really want to do this?And because if I take the money, I really have to do it right. And so the way I almost think about it's like you kind of need to ha like you kind of need to be like fucked up enough to want to go all the way. And that was the conversation where I was like, okay, this is gonna be part of my life's journey to build this company and do it in the best way that I possibly can't.Because if I ask people to join me, ask people to get on the cap table, then I have an ultimate responsibility to give it everything. And I don't, I think some people, it doesn't occur to me that everyone takes it that seriously. And maybe I take it too seriously, I don't know. But that was like a very intentional moment.And so then it was very clear like, okay, I'm gonna do this and I'm gonna give it everything.Alessio: A lot of people don't take it this seriously. But,swyx: uh, let's talk about, you have this concept of the P 99 engineer. Uh, people are 10 x saying, everyone's saying, you know, uh, maybe engineers are out of a job. I don't know.But you definitely see a P 99 engineer, and I just want you to talk about it.Simon Hørup Eskildsen: Yeah, so the P 99 engineer was just a term that we started using internally to talk about candidates and talk about how we wanted to build the company. And you know, like everyone else is, like we want a talent dense company.And I think that's almost become trite at this point. What I credit the cursor founders a lot with is that they just arrived there from first principles of like, we just need a talent dense, um, talent dense team. And I think I've seen some teams that weren't talent dense and like seemed a counterfactual run, which if you've run in been in a large company, you will just see that like it's just logically will happen at a large company.Um, and so that was super important to me and Justine and it's very difficult to maintain. And so we just needed, we needed wording for it. And so I have a document called Traits of the P 99 Engineer, and it's a bullet point list. And I look at that list after every single interview that I do, and in every single recap that we do and every recap we end with.End with, um, some version of I'm gonna reject this candidate completely regardless of what the discourse was, because I wanna see people fight for this person because the default should not be, we're gonna hire this person. The default should be, we're definitely not hiring this person. And you know, if everyone was like, ah, maybe throw a punch, then this is not the right.swyx: Do, do you operate, like if there's one cha there must have at least one champion who's like, yes, I will put my career on, on, on the line for this. You know,Simon Hørup Eskildsen: I think career on the line,swyx: maybe a chair, butSimon Hørup Eskildsen: yeah. You know, like, um, I would say so someone needs to like, have both fists up and be like, I'd fight.Right? Yeah. Yeah. And if one person said, then, okay, let's do it. Right?swyx: Yeah.Simon Hørup Eskildsen: Um. It doesn't have to be absolutely everyone. Right? And like the interviews are always the sign that you're checking for different attributes. And if someone is like knocking it outta the park in every single attribute, that's, that's fairly rare.Um, but that's really important. And so the traits of the P 99 engineer, there's lots of them. There's also the traits of the p like triple nine engineer and the quadruple nine engineer. This is like, it's a long list.swyx: Okay.Simon Hørup Eskildsen: Um, I'll give you some samples, right. Of what we, what we look for. I think that the P 99 engineer has some history of having bent, like their trajectory or something to their will.Right? Some moment where it was just, they just, you know, made the computer do what it needed to do. There's something like that, and it will, it will occur to have them at some point in their career. And, uh. Hopefully multiple times. Right.swyx: Gimme an example of one of your engineers that like,Simon Hørup Eskildsen: I'll give an eng.Uh, so we, we, we launched this thing called A and NV three. Um, we could, we're also, we're working on V four and V five right now, but a and NV three can search a hundred billion vectors with a P 50 of around 40 milliseconds and a p 99 of 200 milliseconds. Um, maybe other people have done this, I'm sure Google and others have done this, but, uh, we haven't seen anyone, um, at least not in like a public consumable SaaS that can do this.And that was an engineer, the chief architect of Turbo Puffer, Nathan, um, who more or less just bent this, the software was not capable of this and he just made it capable for a very particular workload in like a, you know, six to eight week period with the help of a lot of the team. Right. It's been, been, there's numerous of examples of that, like at, at turbo puff, but that's like really bending the software and X 86 to your will.It was incredible to watch. Um. You wanna see some moments like that?swyx: Isn't that triple nine?Simon Hørup Eskildsen: Um, I think Nathan, what's calledAlessio: group nine, that was only nine. I feel like this is too high forSimon Hørup Eskildsen: Nathan. Nathan is, uh, Nathan is like, yeah, there's a lot of nines. Okay. After that p So I think that's one trait. I think another trait is that, uh, the P 99 spends a lot of time looking at maps.Generally it's their preferred ux. They just love looking at maps. You ever seen someone who just like, sits on their phone and just like, scrolls around on a map? Or did you not look at maps A lot? You guys don't look atswyx: maps? I guess I'm not feeling there. I don't know, butSimon Hørup Eskildsen: you just dis What about trains?Do you like trains?swyx: Uh, I mean they, not enough. Okay. This is just like weapon nice. Autism is what I call it. Like, like,Simon Hørup Eskildsen: um, I love looking at maps, like, it's like my preferred UX and just like I, you know, I likeswyx: lotsAlessio: of, of like random places, soswyx: like,youswyx: know.Alessio: Yes. Okay. There you go. So instead of like random places, like how do you explore the maps?Simon Hørup Eskildsen: No, it's, it's just a joke.swyx: It's autism laugh. It's like you are just obsessed by something and you like studying a thing.Simon Hørup Eskildsen: The origin of this was that at some point I read an interview with some IOI gold medalistswyx: Uhhuh,Simon Hørup Eskildsen: and it's like, what do you do in your spare time? I was just like, I like looking at maps.I was like, I feel so seen. Like, I just like love, like swirling out. I was like, oh, Canada is so big. Where's Baffin Island? I don't know. I love it. Yeah. Um, anyway, so the traits of P 99, P 99 is obsessive, right? Like, there's just like, you'll, you'll find traits of that we do an interview at, at, at, at turbo puffer or like multiple interviews that just try to screen for some of these things.Um, so. There's lots of others, but these are the kinds of traits that we look for.swyx: I'll tell you, uh, some people listen for like some of my dere stuff. Uh, I do think about derel as maps. Um, you draw a map for people, uh, maps show you the, uh, what is commonly agreed to be the geographical features of what a boundary is.And it shows also shows you what is not doing. And I, I think a lot of like developer tools, companies try to tell you they can do everything, but like, let's, let's be real. Like you, your, your three landmarks are here, everyone comes here, then here, then here, and you draw a map and, and then you draw a journey through the map.And like that. To me, that's what developer relations looks like. So I do think about things that way.Simon Hørup Eskildsen: I think the P 99 thinks in offs, right? The P 99 is very clear about, you know, hey, turbo puffer, you can't run a high transaction workload on turbo puffer, right? It's like the right latency is a hundred milliseconds.That's a clear trade off. I think the P 99 is very good at articulating the trade offs in every decision. Um. Which is exactly what the map is in your case, right?swyx: Uh, yeah, yeah. My, my, my world. My world.Alessio: How, how do you reconcile some of these things when you're saying you bend the will the computer versus like the trade

In this episode, we explore the intersection of AI and Airtable with Rob Weidner. We discuss the current state of AI, its potential impact on productivity, and how Airtable is uniquely positioned to lead the charge. Rob also shares his thoughts on the pros and cons of building on Airtable versus standalone platforms and showcases his work with HyperAgent, a cutting-edge AI tool. Tune in to learn more about the future of work and how AI is changing the game!

Get the guide to create AI Agents: https://clickhubspot.com/wvh Ep. 403 Can you build a team of AI assistants—like a competitive researcher, content strategist, and world-class data analyst—all inside your email inbox? Kieran dives into how AI specialists can supercharge your productivity right from your inbox. Learn more on setting up inbox-native AI agents, why bespoke email-based delegation beats chatbots, and the game-changing workflows for competitive analysis and content repurposing—all done through your email. Mentions Mail Manus https://manus.im/features/mail Airtable https://www.airtable.com/  OpenAI https://openai.com/ Claude https://claude.ai/ Gemini https://gemini.google.com/ Get our guide to build your own Custom GPT: https://clickhubspot.com/customgpt We're creating our next round of content and want to ensure it tackles the challenges you're facing at work or in your business. To understand your biggest challenges we've put together a survey and we'd love to hear from you! https://bit.ly/matg-research 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  Join our community https://landing.connect.com/matg 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.

In this episode, we dive into Airtable's recent outage and the introduction of HyperAgent. We also explore a script that helps manage naming conventions in Airtable, making it easier to keep track of linked records and lookups. Tune in to learn more about the differences between SuperAgent and HyperAgent, and how HyperAgent is more closely tied to Airtable.

You've landed a foothold in a big company, delivered a great project, the client loved it, so why are you still stuck in the same corner six months later winning the same small deals? In this episode, I break down why most consultants stay trapped in one department and how to turn a single project into an enterprise-wide engagement. I share how one Airtable consultant turned a $20,000 clinical trial tracking project at a top-three pharmaceutical company into a $200,000 transformation across three countries, all by making one strategic shift in how he treated his internal champion. If you've got a foothold in a big company and you're watching other consultants land the deals you should be winning, this is your playbook.Resources and LinksApply for a Multiplier CallPrevious episode: 666 - The partner trapCheck out more episodes of the Paul Higgins PodcastSubscribe to our YouTube channel: @PaulHigginsMentoringJoin our newsletterSuggested resources

Ever wonder what actually happens after someone makes a big backend decision?In this episode, I'm giving you a real update on two announcements I made last month:• Hiring a professional Notion strategist to build my marketing team dashboard• Bringing Chelsea on as my fractional CMO for 2026Spoiler: I am not abandoning Airtable. But I did need a better way to coordinate a growing team without becoming the bottleneck.I'm sharing what's working, what surprised me, and how it actually feels to wake up and not have marketing on my to-do list — while everything still moves forward.If you love behind-the-scenes updates, this one's for you.Also Mentioned:Systems in Session (Now Booking for Q2)Email Like You Mean It (next live sprint: April 6-10)Ania my Notion ExpertChelsea my Fractional CMO

Want to learn how to automate repetitive tasks in Airtable? In this episode, Kamille shares a demo of a habit tracker and provides tips and tricks for debugging complex formulas. Learn how to use Airtable to streamline your workflow and increase productivity. From setting up a habit tracker to creating a system for repetitive tasks, this episode covers it all.

Get ready to revolutionize your Airtable workflow with AI-powered interfaces. In this episode, we chat with Aly Elosa about the possibilities of generating custom interfaces using Airtable's AI tools. Learn how to harness the power of AI to create tailored interfaces that meet your specific needs. Tune in to discover the benefits and limitations of this exciting feature.

Get ready to take your Airtable skills to the next level with expert Martin. In this episode, we dive into the world of Airtable webhooks and explore how to build a schema change log, manage cursors, and handle token expiration. Martin shares his experience and expertise on the benefits and challenges of using webhooks, and we discuss some of the limitations of Airtable webhooks. Whether you're an Airtable enthusiast or a developer, this episode is perfect for anyone looking to master Airtable webhooks.

Get ready to take your Airtable skills to the next level! In this episode, we dive into the world of metadata management with expert Ali. Learn how to create a custom script to track field and table changes, and discover tips for optimizing your base for the upcoming Airtable Hackathon. Whether you're a seasoned pro or just starting out, this episode is packed with valuable insights to help you master Airtable metadata.

Please follow us on: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠ or ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Facebook ⁠⁠⁠⁠⁠⁠⁠! In this episode, Kimberly and Tommaso share their experiences after living in Italy for almost a month. They discuss the daily adjustments, from understanding local customs to enjoying Italian cuisine. Key Points: The Italian Tabacchi: More Than Meets the Eye: Kimberly and Tommaso explain how a “tabacchi” in Italy serves multiple purposes beyond selling cigarettes. It is a place to purchase a “Marco da Bolo,” a stamp needed for immigration applications. This discovery highlights the unique role of local establishments in daily Italian life. The Rhythm of Reposo: Kimberly and Tommaso describe the challenge of adapting to store closing times for “riposo” or “pausa,” the Italian equivalent of a siesta. Store hours vary, making it tricky to plan errands. They joke about needing a spreadsheet or an “Airtable database” to keep track of business hours. These closures offer a peaceful atmosphere, especially during midday, creating a quiet charm in the streets. Grocery Shopping Adventures: A humorous incident occurs when Kimberly attempts to bring a two-wheel shopping cart into a grocery store. She learns that these carts are not allowed inside due to unspoken rules. Kimberly ‘s New York City instincts made her hesitant to leave her cart unattended. The grocery manager's reaction to her concern about theft provides a moment of cultural contrast. A Culinary Awakening: Kimberly and express their delight in the quality and accessibility of Italian food. Small “alimentaries” (local markets) specialize in different products, from prosciutto to Parmigiano. Even simple roasted vegetables become a culinary revelation due to the fresh ingredients and olive oil. They highlight the artistic display of food in shops, which makes shopping a visually appealing experience. The Echoes of History: Living in a village with roots dating back to the Bronze Age give Kimberly and Tommaso a deeper appreciation for history. The Venetian architecture in their village adds to its charm. Tommaso Il Favoloso reflects on his lifelong dream of living in Europe and the magical feeling of making Italy his home. Ciao!

This episode focuses on the exciting custom clustering feature now available in Ancestry's Pro Tools. Diana introduces the tool, explaining how it allows for the strategic targeting of specific ancestral lines, offering more flexibility than the original clustering tool. She describes Ancestry's process, which looks for matches sharing 65 cM to 1,300 cM with the user, and then finds those matches that also share at least 20 cM with each other. Nicole discusses the key benefits of using custom clusters: they help you hone in on specific ancestral lines, quickly identify groups descending from common ancestors, and work more efficiently at distant generations. Before creating a cluster, Diana reviews critical points from Ancestry, noting that clusters expire after 30 days unless saved to a group and you are limited to 25 clusters in your history. Nicole shares Ancestry's recommended centimorgan ranges based on the generational distance of the ancestor you are researching. She then walks through the four steps for creating a cluster: choosing a target match, selecting four additional "sidekick" matches, setting the centimorgan range, and generating the cluster. Diana provides a real-world example from her Cline family research, detailing how she used a custom cluster with a 20-50 cM range to test a hypothesis about the parentage of John C. Cline. The results successfully separated her matches into distinct sub-clusters that provide additional evidence for her research. Listeners learn practical tips for success, including saving clusters strategically, trying different target and sidekick match combinations, and systematically tracking all experiments in a research log like Airtable. This powerful strategy helps you apply a new approach to breaking down your DNA research brick walls. This summary was generated by Google Gemini. Links How to Use Ancestry DNA Custom Clusters in Your Research – with Video - https://familylocket.com/how-to-use-ancestry-dna-custom-clusters-in-your-research-with-video/ Ancestry Support Article - Matches by Cluster https://support.ancestry.com/s/article/Matches-by-Cluster?language=en_US Ancestry Support Article - Custom Match Clusters https://support.ancestry.com/s/article/Custom-Match-Clusters?language=en_US  Sponsor – Newspapers.com For listeners of this podcast, Newspapers.com is offering new subscribers 20% off a Publisher Extra subscription so you can start exploring today. Just use the code "FamilyLocket" at checkout.  Research Like a Pro Resources Airtable Universe - Nicole's Airtable Templates - https://www.airtable.com/universe/creator/usrsBSDhwHyLNnP4O/nicole-dyer Airtable Research Logs Quick Reference - by Nicole Dyer - https://familylocket.com/product-tag/airtable/ Research Like a Pro: A Genealogist's Guide book by Diana Elder with Nicole Dyer on Amazon.com - https://amzn.to/2x0ku3d 14-Day Research Like a Pro Challenge Workbook - digital - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-digital-only/ and spiral bound - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-spiral-bound/ Research Like a Pro Webinar Series - monthly case study webinars including documentary evidence and many with DNA evidence - https://familylocket.com/product-category/webinars/ Research Like a Pro eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-e-course/ RLP Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-study-group/ Research Like a Pro Institute Courses - https://familylocket.com/product-category/institute-course/ Research Like a Pro with DNA Resources Research Like a Pro with DNA: A Genealogist's Guide to Finding and Confirming Ancestors with DNA Evidence book by Diana Elder, Nicole Dyer, and Robin Wirthlin - https://amzn.to/3gn0hKx Research Like a Pro with DNA eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-with-dna-ecourse/ RLP with DNA Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-with-dna-study-group/ Thank you Thanks for listening! We hope that you will share your thoughts about our podcast and help us out by doing the following: Write a review on iTunes or Apple Podcasts. If you leave a review, we will read it on the podcast and answer any questions that you bring up in your review. Thank you! Leave a comment in the comment or question in the comment section below. Share the episode on Twitter, Facebook, or Pinterest. Subscribe on iTunes or your favorite podcast app. Sign up for our newsletter to receive notifications of new episodes - https://familylocket.com/sign-up/ Check out this list of genealogy podcasts from Feedspot: Best Genealogy Podcasts - https://blog.feedspot.com/genealogy_podcasts/

In this episode recorded at the Presales Collective Leadership Next Summit in November of 2025, Jack Cochran sits down with Gretchen Fitzgibbons, Senior Manager of Strategic Solutions Consulting at Airtable, to discuss what it means to be a courageous leader in presales. They explore how to make difficult decisions under pressure, navigate organizational politics with integrity, and build the support systems that enable consistent leadership. Gretchen shares powerful stories from her two decades of experience advising Fortune 500 customers and leading presales teams, including standing up for a team member being unfairly assessed and creating win-win solutions in challenging situations. Follow Us Connect with Jack Cochran: https://www.linkedin.com/in/jackcochran/ Connect with Gretchen Fitzgibbons: https://www.linkedin.com/in/gretchenfitzgibbons/ Links and Resources Mentioned Join Presales Collective Slack: https://www.presalescollective.com/slack Sol/Con 2026: https://www.presalescollective.com/solcon-2026  Book mentioned: Think Again by Adam Grant: https://adamgrant.net/book/think-again/  Book mentioned: Thinking, Fast and Slow by Daniel Kahneman: https://www.goodreads.com/book/show/11468377-thinking-fast-and-slow  Key Topics Covered Redefining Courage and Leadership Making Tough Calls: Standing Up for Team Members Focusing on Your Team rather than on Yourself How to Prepare for a Leadership Role It's OK to be Wrong Developing Your Leadership Skills Grounding Principles for Leadership Timestamps 00:00 Welcome and Introduction 02:14 Defining Courage and Leadership in Presales 05:15 Making Tough Calls: A Story of Standing Up for What's Right 11:20 Focusing on Your Team rather than on Yourself 22:07 How to Prepare for a Leadership Role 27:40 It's OK to be Wrong 30:30 Developing Leadership Skills 37:42 Final Takeaways and Grounding Principles

This is a story of growth through creativity, experimentation, and using technology to stay lean.Carlo Pandian (LinkedIn) is the founder of Slow Travel Italia. Four years ago he started with a single wine tasting in Verona, and today runs 160 experiences across 12 Italian cities, serving 15,000 guests a year with a very small team.In this episode, he talks to TP host Mitch Bach about exactly how he did it: experimenting with neglected time slots (like 6pm) that competitors ignore, launching five tours at once instead of one to multiply his chances of finding a niche, using Airtable and automations to eliminate manual booking assignments and personalize communication at scale, and treating OTAs as a launchpad rather than a long-term home. Carlo shares how he identifies gaps in crowded markets by studying what's missing—not just in Italy but in places like Japan—and why he pulled out of Milan when the math didn't work. He explains his "requirements manifesto" for vetting partners, how he coaches food producers on storytelling for international audiences, and why the biggest trend he's seeing is travelers willing to spend half a day outside the city for a single product done deeply—visiting the olive grove, watching mozzarella pulled from boiling water, understanding one thing fully rather than tasting nine things superficially.As always, more info and takeaways on tourpreneur.com.

Zevi Arnovitz is a product manager at Meta with no technical background who has figured out how to build and ship real products using AI. His engineering team at Meta asks him to teach them how he does what he does. In this episode, Zevi breaks down his complete AI workflow that allows non-technical people to build sophisticated products with Cursor.We discuss:1. The complete AI workflow that lets non-technical people build real products in Cursor2. How to use multiple AI models for different tasks (Claude for planning, Gemini for UI)3. Using slash commands to automate prompts4. Zevi's “peer review” technique, which uses different AI models to review each other's code5. Why this might be the best time to be a junior in tech, despite the challenging job market6. How Zevi used AI to prepare for his Meta PM interviews—Brought to you by:10Web—Vibe coding platform as an APIDX—The developer intelligence platform designed by leading researchersFramer—Build better websites faster—Episode transcript: https://www.lennysnewsletter.com/p/the-non-technical-pms-guide-to-building-with-cursor—Archive of all Lenny's Podcast transcripts:https://www.dropbox.com/scl/fo/yxi4s2w998p1gvtpu4193/AMdNPR8AOw0lMklwtnC0TrQ?rlkey=j06x0nipoti519e0xgm23zsn9&st=ahz0fj11&dl=0—Where to find Zevi Arnovitz• X: https://x.com/ArnovitzZevi• LinkedIn: https://www.linkedin.com/in/zev-arnovitz• Website: https://zeviarnovitz.com—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Zevi Arnovitz(04:48) Zevi's background and journey into AI(07:41) Overview of Zevi's AI workflow(14:41) Screenshare: Exploring Zevi's workflow in detail(17:18) Building a feature live: StudyMate app(30:52) Executing the plan with Cursor(38:32) Using multiple AI models for code review(40:40) Personifying AI models(43:37) Peer review process(45:40) The importance of postmortems(51:05) Integrating AI in large companies(53:42) How AI has impacted the PM role(57:02) How to improve AI outputs(58:15) AI-assisted job interviews(01:02:57) Failure corner(01:06:20) Lightning round and final thoughts—Referenced:• Becoming a super IC: Lessons from 12 years as a PM individual contributor | Tal Raviv (Product Lead at Riverside): https://www.lennysnewsletter.com/p/the-super-ic-pm-tal-raviv• Wix: https://www.wix.com• Building AI Apps: From Idea to Viral in 30 Days: https://www.youtube.com/watch?v=j2w4y7pDi8w• Riley Brown on YouTube: https://www.youtube.com/channel/UCMcoud_ZW7cfxeIugBflSBw• Greg Isenberg on YouTube: https://www.youtube.com/@GregIsenberg• Bolt: https://bolt.new• Inside Bolt: From near-death to ~$40m ARR in 5 months—one of the fastest-growing products in history | Eric Simons (founder and CEO of StackBlitz): https://www.lennysnewsletter.com/p/inside-bolt-eric-simons• Lovable: https://lovable.dev• Building Lovable: $10M ARR in 60 days with 15 people | Anton Osika (co-founder and CEO): https://www.lennysnewsletter.com/p/building-lovable-anton-osika• StudyMate: https://studymate.live• Dibur2text: https://dibur2text.app• Claude: https://claude.ai• Everyone should be using Claude Code more: https://www.lennysnewsletter.com/p/everyone-should-be-using-claude-code• Bun: https://bun.com• Zustand: https://zustand.docs.pmnd.rs/getting-started/introduction• Cursor: https://cursor.com• The rise of Cursor: The $300M ARR AI tool that engineers can't stop using | Michael Truell (co-founder and CEO): https://www.lennysnewsletter.com/p/the-rise-of-cursor-michael-truell• Wispr Flow: https://wisprflow.ai• Linear: https://linear.app• Linear's secret to building beloved B2B products | Nan Yu (Head of Product): https://www.lennysnewsletter.com/p/linears-secret-to-building-beloved-b2b-products-nan-yu• Cursor Composer: https://cursor.com/blog/composer• Replit: https://replit.com• Behind the product: Replit | Amjad Masad (co-founder and CEO): https://www.lennysnewsletter.com/p/behind-the-product-replit-amjad-masad• Base44: https://base44.com• Solo founder, $80M exit, 6 months: The Base44 bootstrapped startup success story | Maor Shlomo: https://www.lennysnewsletter.com/p/the-base44-bootstrapped-startup-success-story-maor-shlomo• v0: https://v0.app• Everyone's an engineer now: Inside v0's mission to create a hundred million builders | Guillermo Rauch (founder & CEO of Vercel, creators of v0 and Next.js): https://www.lennysnewsletter.com/p/everyones-an-engineer-now-guillermo-rauch• Cursor Browser mode: https://cursor.com/docs/agent/browser• Google Antigravity: https://antigravity.google• Grok: https://grok.com• Zapier: https://zapier.com• Airtable: https://www.airtable.com• Build Your Personal PM Productivity System & AI Copilot: https://maven.com/tal-raviv/product-manager-productivity-system• The definitive guide to mastering analytical thinking interviews: https://www.lennysnewsletter.com/p/the-definitive-guide-to-mastering-f81• AI tools are overdelivering: results from our large-scale AI productivity survey: https://www.lennysnewsletter.com/p/ai-tools-are-overdelivering-results-c08• Yaara Asaf on LinkedIn: https://www.linkedin.com/in/yaarasaf• The Pitt on Prime Video: https://www.amazon.com/The-Pitt-Season-1/dp/B0DNRR8QWD• Severance on AppleTV+: https://tv.apple.com/us/show/severance/umc.cmc.1srk2goyh2q2zdxcx605w8vtx• Loom: https://www.loom.com• Cap: https://cap.so• Supercut: https://supercut.ai...References continued at: https://www.lennysnewsletter.com/p/the-non-technical-pms-guide-to-building-with-cursor—Recommended books:• The Fountainhead: https://www.amazon.com/Fountainhead-Ayn-Rand/dp/0451191153• Shoe Dog: A Memoir by the Creator of Nike: https://www.amazon.com/Shoe-Dog-Memoir-Creator-Nike/dp/1501135910• Mindset: The New Psychology of Success: https://www.amazon.com/Mindset-Psychology-Carol-S-Dweck/dp/0345472322—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com