Podcasts about supabase

In this episode of In Depth, Brett sits down with Paul Copplestone, co-founder and CEO of Supabase, the open-source Postgres platform now serving more than seven million developers. Before Supabase, Paul launched a Thumbtack-style marketplace in Southeast Asia and co-founded an office-management startup called Nimbus, experiences that taught him to separate fundraising from building and to find product-market fit before blitzscaling. He breaks down how a single tagline change for Supabase unlocked product-market fit, why he runs a fully distributed async team with near-zero attrition, and how he turned PLG signals into a product-led sales motion comped only on incremental uplift. In today's episode, we discuss: How changing one tagline helped Supabase go to #1 in Hacker News - an early sign of product market fit Why Paul ran Supabase like it had only $100K in the bank despite raising real money How Supabase rode three distinct AI waves, from pgvector to Bolt and Lovable, to Claude Code Why Supabase built a sales team comped only on the incremental uplift over a control group What the Toyota production system's "kaizen" taught Paul about unblocking a scaling team References: Ant Wilson: https://www.linkedin.com/in/ant-wilson-46179937 Bolt: https://bolt.new/ Claude Code: https://www.anthropic.com/claude-code Codex: https://openai.com/codex/ Entrepreneurs First: https://www.joinef.com/ Firebase: https://firebase.google.com/ Lovable: https://lovable.dev/ MongoDB: https://www.mongodb.com/ Next.js: https://nextjs.org/ PostgreSQL: https://www.postgresql.org/ Supabase: https://supabase.com/ Thumbtack: https://www.thumbtack.com/ Y Combinator: https://www.ycombinator.com/ Where to find Paul: LinkedIn: https://www.linkedin.com/in/paulcopplestone Twitter/X: https://x.com/kiwicopple Where to find Brett: LinkedIn: https://www.linkedin.com/in/brett-berson-9986094/ Twitter/X: https://twitter.com/brettberson Where to find First Round Capital: Website: https://firstround.com/ First Round Review: https://review.firstround.com/ Twitter/X: https://twitter.com/firstround YouTube: https://www.youtube.com/@FirstRoundCapital This podcast on all platforms: https://review.firstround.com/podcast Timestamps: 00:00 Introduction 01:32 Why Paul's earlier startups were never destined to be huge 07:14 Unlearning the "tall poppy" mindset and going all-in on async 09:54 Reverse-engineering why Supabase was an outstanding idea 12:04 The accidental Hacker News launch and tagline lesson 13:58 Where the early roadmap came from: demand vs. technical taste 17:28 Skill vs. luck, and operating like you have $100K in the bank 21:42 What actually makes a great developer experience 23:10 Solving the "graduation problem" Firebase never could 24:58 The role of open source in Supabase's success 26:10 The three distinct AI tailwinds: From pgvector to Claude Code 35:24 Supabase's egoless, hyper-competitive open-source culture 42:58 A tactical playbook for raising capital 48:37 Product-led sales comped on incremental uplift only 59:27 The production philosophy behind Supabase's operations

This week, we discuss the Fable ban, SpaceX's $60B Cursor buy, and why Lovable wins when AI picks your stack. Plus, Europeans are at the World Cup and already drank Boston dry. Watch the YouTube Live Recording of Episode 577 Runner-up Titles Waited out the storm Maybe we should build some castles or something Years of lawsuits ahead of us The ultimate dream AI SEO I hope you're paid by the hour Always be monitoring to me Rundown Anthropic How Amazon and the White House ended Anthropic's Fable Statement on the US government directive to suspend access to Fable 5 and Mythos 5 Dario Amodei — Policy on the AI Exponential Cursor Live Updates: Elon Musk Becomes World's First Trillionaire as SpaceX Starts Trading SpaceX to acquire Cursor for $60B in stock, days after blockbuster IPO Vibe Coding Lovable says it has hit $500M in annualized revenue, with 1 million new projects a week Vibe-coding phenomenon lifts AI startup Supabase to $10.5 billion valuation Database startup Supabase raises $500 million $10.5 billion valuation curl summer of bliss Relevant to your Interests Grep this: Microsoft grafts (most) Linux commands onto Windows apple/container The Virtual OS Museum YouTube has eclipsed Netflix in viewership via (@lucas_shaw) OpenAI to acquire Ona Keycap Quarry – Artisan Keycaps for Mechanical Keyboards Mark Zuckerberg Orders His Employees to Start Having Fun Again Why is Meta destroying its engineering organization? VCs behaving badly Databricks Agrees to Acquire Panther Sponsors Sentry - Quit Buggin': use code sdt26 for $100 in credit for new customers Nonsense The AI coding agent that runs on stolen Chipotle compute Minesweeper 3D No Guess – Free 3D Browser Game | Logic Solver Fly around the world (Experimental) | Google Earth | Google for Developers Commodore's newest gadget is a flip phone that blocks social media and browsers Conferences WeAreDevelopers Europe, July 8-10, 2026 Berlin, Coté speaking. DevOpsDays Graz, Sept 4-5, 2026 Cloud Foundry Summit, Sept. 21st to 22nd, Germany. DevOpsDays Rockies, Sept. 22 – 23, 2026, Discount Code: 26DODSWEDEFTALK WeAreDevelopers NA, Sept 23-25, 2026, Discount Code: DEVPOD26 25 Free Tickets DevOpsDays Dallas, Sept 28-29, 2026 DevOpsDays Vilnius, Sep 30 - Oct 1, 2006 DevOpsDays Istanbul, Oct 24th, 2026, Coté keynoting. VMware User Group, Orlando, Oct 20-22, 2026 SDT News & Community Join our Slack community Email the show: questions@softwaredefinedtalk.com Free stickers: Email your address to stickers@softwaredefinedtalk.com Follow us on social media: Twitter, Threads, Mastodon, LinkedIn, BlueSky Watch us on: Twitch, YouTube, Instagram, TikTok Book offer: Use code SDT for $20 off "Digital WTF" by Coté Sponsor the show Sponsor more podcasts with Failover Media Recommendations Brandon: Digital ID Matt: Murderbot Diaries: Platform Decay Coté: WordPress.com. Tetilla cheese from the Camino de Santiago.

Database branching has, for a long time, been a troublesome piece in the modern developer workflow puzzle: a good idea in principle but in practice a slow and often expensive challenge. Get it right and you can accelerate productivity and remove bottlenecks; get it wrong and you're potentially creating all sorts of trouble for yourself, from privacy risks to additional complexity. However, things are changing. Thanks to the emergence of new platforms such as Neon, Supabase and Databricks Lakebase, branching a database can become as familiar to developers as managing code branches and multiple environments with, say, Git and Terraform.  On this episode of the Technology Podcast, host Ken Mugrage is joined by his Thoughtworks colleague Cam Casher and Databricks' Kevin Hartman to discuss the work Thoughtworks and Databricks have been doing together on Lakebase. They discuss the platform, their experience using it with Spotify's Backstage and the opportunities database branching can offer software engineering teams in an increasingly AI-assisted and agentic world. Read Cam and Kevin's recent series on using Databricks Lakebase with Backstage: https://www.thoughtworks.com/insights/blog/data-engineering/backstage-lakebase-databricks

2026年6月、テック業界が1週間で大きく動きました。SpaceXの史上最大IPO、Microsoftの自社AI「MAI」、OpenAI Codexの新機能、そして世界一になったばかりのAnthropicが「AI開発を止めろ」と提言。いま世界と日本のビルダーが話題にしているニュースを、ShinとKboyが一気に解説します。KK Tech Digest、記念すべき第1回。▼チャプター オープニング・今週の構図「実装の週」SpaceX 史上最大IPOへ（時価総額1.77兆ドル） Apple 初の他社AIエージェントを承認Microsoft 自社AI「MAI」7モデルでOpenAI脱却OpenAI Codex「Sites」非エンジニアがアプリを作るAirbnb CEOがAIラボ設立へ核融合 Helion が465億円調達Supabase 800億円調達Deel ステーブルコイン給与を実装Anthropic AI開発の減速を提言国内：トレンドマイクロ × Claude Mythos国内：PayPay 生保参入（T&D子会社化）国内：創業期スタートアップの調達が4割減一番気になったニュースと、次に深掘りしてほしいテーマをコメントで教えてください。面白かったら高評価とチャンネル登録をお願いします。

You're tired of hearing “just build a SaaS” like it's easy, especially when you don't code, don't have a team, and still want something real that can actually make money. It can feel like everyone else has access to some secret playbook while you're stuck trying to figure out where to even begin. In this episode, Omar completely removes the gatekeeping and shows you what it actually looks like to build a real software business in a ridiculously short timeframe using AI. Nothing is hidden. He walks you through the exact tools, decisions, and steps he takes so you're not left guessing or piecing things together on your own. It's clear, practical, and designed to make you feel like this isn't some exclusive club, it's something you can dive into right now. If you've been waiting for proof that you can pull off your own AI-powered software build in a matter of hours, this is it. Click play at the top of the page and see how you can turn your idea into a real product faster than you thought possible. MBA2790 How To Build A Software Business With AI This Weekend. Zero Coding Skills Required. Must-Have Stack to Build Your Own AI App 1. Supabase 2. GitHub 3. Windsurf 4. Vercel 5. Claude 6. GoDaddy 7. Stripe 8. Kit Helper / Optional Tools to support your workflow 1. Wispr Flow 2. Google Forms 3. Chrome DevTools (Inspect Element) Recommended episode to explore: Can You Build A Profitable SaaS In 7 Days With Just AI? My Experiment With Proof! Watch the episodes on YouTube: https://lm.fm/GgRPPHi SUBSCRIBE YouTube | Apple Podcast | Spotify | Podcast Feed Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

NIO is executing. The ES9 flagship is already on pace for 10,000 deliveries this month with strong waitlists on higher trims. Fresh today: partnership with GigaDevice on next-gen automotive chips and another smart financing move through Mirattery at ultra-low rates.We also check XPENG — strong demand on the GX SUV but a notable loss in their robotics team. Plus the hot US jobs report, Supabase hitting $10B valuation, Mira Murati speaking out, GM's battery push, and a quick SpaceX/NASA moment.Real talk: NIO's steady progress in the premium segment stands out while competition stays intense and macro throws some short-term pressure. The affluent buyer thesis and tech integration moves are what matter long-term.Dial Tone: A Modern Salesman's Story — my debut novel is now available for pre-order on Amazon. E-book ready now, hard copy June 12th.

Hannah Hoffmaster went from a self-described two-out-of-seven in technical skill to building multi-agent AI tools in a single year at Foster. This episode is for anyone — technical or not — trying to understand what genuine AI fluency looks like and how to build it. Hannah Hoffmaster is a student completing the one-year MSIS program at the University of Washington Foster School of Business. She came to the program with some knowledge of statistics and R, but little coding experience. Through her coursework — including Prof. Leo Bousioux's AI and Generative AI in Business class — she developed the ability to design and build AI-powered tools, including a charity comparison platform and an ADHD-focused scheduling app. She describes experimenting with AI as something she now does for fun. We covered alot of ground in this episode: How to think about AI as a build tool when you have no coding background Why "trust but verify" is the core discipline of working with AI, and how to operationalize it How to design a multi-agent workflow around the parts of a task you don't want to do What a deliberate, build-first job search looks like in a fast-moving field How to stay current as tools change — by building, researching versions, and talking to peers Why holding your career goals loosely can be an advantage in an uncertain market Resources mentioned: GiveWise (Hannah's project); Offload and the "Nudge" chatbot (Hannah's project); Claude Code; Supabase; GitHub; Vercel; Lovable; ChatGPT; Gemini; Codex; Prof. Leo Bousioux's AI and Generative AI in Business course; Foster's AI club.

Watch the YouTube version of this episode HEREIn this episode of Maximum Lawyer Live, Tyson Mutrux riffs on a short clip from Marc Andreessen to show you exactly what the near future of legal work looks like: you managing 20+ AI agents instead of a bloated human team.Tyson shares how he and Kashef became “AI vampires” while building Foxy, their new case management system, taking shifts in Bolt, wiring up back-end tools like Supabase and GitHub, and literally waking up in the middle of the night to see what the agents had shipped.Tyson also uses a wild example from the Los Angeles mayoral race to show how a lesser-known candidate is using AI to close the gap on an incumbent with more money and name recognition, and why the same thing is about to happen in your market if you don't level up.If you want a real-time window into the future of law firm operations, months, not years, away and what it means for your hiring, compensation, and leadership, this episode will give you the play-by-play.AI isn't just making knowledge workers more efficient; it's creating “AI vampires” who are so productive with agents that they don't want to stop working and law firms are next. The job of the law firm owner is shifting from managing people who do tasks to managing fleets of agents that run entire workflows.In this episode, you'll learn:The “AI vampire” phenomenon in Silicon Valley and why lawyers should careHow building Foxy turned Tyson and Kashef into round‑the‑clock AI tinkerersWhy AI has unlocked a backlog of “someday” projects that used to require an armyHow AI is already leveling up political campaigns, and why that matters for your marketingThe coming split between AI‑fluent team members and everyone elseWhy top performers who master AI will see their compensation go up while total headcount goes downThe next 12–24 months of legal work: people managing agents, and then agents managing agentsHighlights0:00 – Tyson tosses the original topic and pivots to Marc Andreessen's “AI vampire” clip1:30 – How Emma, Jackson, and Hudson's school transitions mirror the transitions coming to your firm2:40 – Andreessen on coders becoming four to twenty times more productive with AI4:30 – Tyson's Foxy build: taking shifts in Bolt, wiring up Supabase and GitHub, and waking up at night to check the agents6:00 – The physical toll: exhaustion, bags under the eyes, and why Tyson finally pulled back8:30 – The Wall Street friend who used AI to generate 500,000 lines of code and fully automate his home10:00 – Why AI is for idea people: shipping long‑stalled projects with a few prompts12:45 – The elasticity of demand: when code (or legal work) becomes cheap, demand explodes15:00 – What this means for law firms: massive improvements in marketing, intake, litigation, and operations17:40 – The LA mayoral race example and how AI helps underdogs punch above their weight19:00 – The salary shakeup: AI‑effective team members vs. everyone else20:20 – The true “window into the future”: managing 20 agents for discovery, service, med records, and more21:00 – Tough calls: do you eliminate roles or shift people into high‑touch client service?22:00 – Final takeaway: your future job is managing agents and investing in the humans who can do the same

Steve Holmberg is one of our favorite recurring guests, and this time, he showed up with something nobody expected. Over the holidays, Steve went from zero coding experience to a fully functional AI-powered app called Field Check, built using the vibe coding platform Lovable. The app connects retail store associates directly to brand product and marketing teams through AI-driven chats that go deeper than any survey can — and he built the whole thing in about a month. In this conversation, Steve walks through exactly how he did it, what he wishes he'd known before starting, and why AI is "a tool masquerading as a solution." He also deployed Field Check live on the Second Nature Slack channel to surface what the audience actually wants — and the results are fascinating. Plus: a halftime check-in on Second Nature's 2026 predictions, what happened at Sea Otter with Chinese bike brands, why Adidas is having a moment, and the 32-inch wheel debate that nobody asked for. Show Notes: Popfly for Creators: https://popf.ly/secondnaturecreators Popfly for Brands: https://popf.ly/secondnaturebrands Steve Holmberg: https://www.linkedin.com/in/stephenholmberg/ Insight Accelerator: https://insight-accelerator.com/ Lovable: https://lovable.dev/ Field Check: https://fieldcheck.app/ Supabase: https://supabase.com/ Cloudflare: https://www.cloudflare.com/ Github: https://www.github.com 2026 Predictions Episode: https://www.youtube.com/watch?v=k0G3OpDVnyA Steve's Prediction Post: https://www.linkedin.com/posts/stephenholmberg_2026-sport-and-outdoor-industry-trends-activity-7414293417557626880-AXy7 Trailcon: https://www.trailconference.com BPC - Brand, Product, Content Jason Fried - David Senra Podcast: https://www.youtube.com/watch?v=BdDCtMA1gSw Adventure Bucket List: https://reachinternationaloutfitters.com/collections/state-bucket-lists Join us on LinkedIn: https://www.linkedin.com/company/second-nature-media Meet us on Slack: https://www.launchpass.com/second-nature Follow us on Instagram: https://www.instagram.com/secondnature.media Subscribe to our newsletter: https://www.secondnature.media Subscribe to the YouTube channel: https://www.youtube.com/@secondnaturemedia

In this episode of Brave New Bookshelf, we are joined by author and "vibe coder" Cassie Alexander to discuss how high-level AI automations can revolutionize an author's business operations. Cassie shares her fascinating journey of building a cloud-based "command center" using Supabase and slashing her monthly overhead by replacing expensive subscriptions with custom-coded tools. From scaling a single nonfiction book into 50 different languages to developing bespoke AI "skills" that handle the tedious grunt work of retailer uploads and ISBN registration, Cassie provides a roadmap for authors looking to reclaim their creative time and maximize their global reach. Visit our website https://bravenewbookshelf.com to view the full episode notes, links and apps mentioned in the episode, and the full transcript.

Why Your Amazon Dashboard Is Lying to You + Remotion & Voice Cloning Reality Check | Claude Sessions Amazon Dashboard Brain, Remotion Video & ElevenLabs Voice Cloning | Claude Sessions SEO Description Shubhash Sharma on building a data brain behind your Amazon dashboard. Danny McMillan on Remotion video and ElevenLabs voice cloning realities. Episode Summary Week 3 of the month means Claude Sessions, and Danny McMillan and Shubhash Sharma are back with a double feature for Amazon and TikTok Shop sellers building their own AI tooling. Shubhash picks up from last episode's SP API and Ads API walkthrough with a hard lesson learned the wrong way: a polished dashboard wired straight into Amazon is a window with no room behind it. The numbers will lie, and you will not know when a feed silently dies. He walks through the fix: a "brain" sitting between the data sources and the dashboard. Supabase as the long term store, pgvector for unstructured stuff like contracts and reviews, n8n as the orchestration layer. Six core domains every seller shares (orders, products, analytics, ads, finance, affiliates and creators) plus an optional documents layer. He closes with a dual write migration pattern so you can flip between old and new without taking the business offline. Then Danny turns to video and voice. Remotion looks like toy town out of the box, but with the right plugins (motion blur, transitions, captions, shapes, fonts, rendering) and Claude doing the orchestration, it becomes a serious production tool that can pull in your footage, branding and design system. On the voice side, he has tested VoiceBox and F5TTS and come back to ElevenLabs Multilingual v2 at £22 a month. The missing gap everywhere is cadence. He also names the deeper bet: as the market floods with AI generated content, authentic voice becomes the differentiator that cannot be cloned. Key Topics Why dashboards lie when wired straight into Amazon, TikTok and Shopify The "brain" pattern: Supabase, pgvector and n8n as a centralised data layer The six core data domains every seller needs (plus a 7th for documents) Dual write migration so the old system and brain run in parallel Remotion as a code based video tool, and what it needs to stop looking toy town The four layer creative workflow: brief, story skeleton, treatment, scene by scene ElevenLabs vs VoiceBox vs F5TTS for voice cloning your own voice Why cadence is the last hard problem in synthetic voice The authenticity premium in an AI flooded market Timestamps [00:00] Intro and welcome back to Claude Sessions [00:34] Shubhash kicks off: where to put the data you pulled last week [01:04] "Your dashboard is lying to you" and the polished dashboard pitfall [02:32] Dashboard is a window. The brain is the room behind it [04:54] Tech stack: Supabase (Postgres), pgvector, n8n [05:54] The six fundamental data domains [06:26] Orders, products, analytics, ads, finance, affiliates and creators [08:30] The optional 7th layer: unstructured documents via pgvector [09:44] Dual write pattern for safe migration [10:48] Three takeaways: audit, list domains, build one table at a time [12:28] Danny on Remotion: code based video and why it is toy town out of the box [13:51] What is missing: motion blur, transitions, captions, shapes, beat detection [14:54] The 80+ plugin packages that turn it into a real tool [16:56] Pulling in footage, logos, design systems and free music from Pixabay [18:30] The 4 layer creative workflow: brief, story skeleton, treatment, scenes [21:15] Voiceovers: ElevenLabs Pro setup and why the £22 is worth it [22:12] VoiceBox and F5TTS field test: garbage and 5 rounds of tuning later [23:22] Why cadence is the hardest thing for AI voice to fake [25:42] How much reference audio you actually need (30 min min, 2 hours ideal) [27:25] ElevenLabs UI parameters: speed, stability, similarity, exaggeration [28:52] The authenticity premium when the market floods with AI [30:30] Key takeaways, ElevenLabs API usage and locking in your voice once [34:24] Aside: "insane" and "most" as the new AI tells [36:31] SSL 2026 wrap, 18 days out, Ritu returns next week with Japan Key Takeaways Build a brain, not just a window. A dashboard wired straight to Amazon, TikTok or Shopify has no memory. When a feed silently fails, the dashboard happily lies. Sit a Supabase + pgvector + n8n layer in between, and your dashboard becomes a view on top of a real source of truth. Six domains cover almost every seller. Orders, products, analytics, ads, finance, and affiliates / creators. Map every place each one currently lives, then consolidate one domain at a time. Start with one table (orders) and let Claude do the heavy lifting. Use dual write when migrating. Write to the old store and the new brain in parallel for a week. Compare. Flip the dashboard's read side via a feature flag. If something breaks, flip back. Zero downtime, zero fear. Remotion is a system, not a tool. Out of the box it is bare. Add the plugins (motion blur, transitions, captions, fonts, rendering), bring your own footage and design system, and let Claude orchestrate the four layer workflow: brief, story skeleton, treatment, scene by scene. ElevenLabs Multilingual v2 still wins for voice cloning. VoiceBox and F5TTS were not close. Pay the £22, use Model 2, feed it 30 minutes minimum (2 hours ideal) of clean reference audio, and lock the setup in once. Cadence is the last mile. AI can match tone and timbre. It still cannot match the rises, falls and micro pauses that make a sentence sound like you. Use scripts split into short paragraphs, generate three variants, and tune the language you use to talk to Claude until the cadence lands. Authenticity becomes the moat. As written, visual and audio AI floods every channel, the brand voice that is unmistakably human becomes the differentiator. Do not give that away to save 22 dollars a month on a podcast. Notable Quotes "Dashboard is a window. We need a room behind the window. So the brain is going to be the room behind this window." Shubhash Sharma "If any of our SaaS went offline tomorrow, will our business still have its memory? The answer is no, because we haven't stored it. All we have is rented attention." Shubhash Sharma "When you migrate to your brain, don't rip out your old system. Use dual write. Run them in parallel for a week. If something breaks, flip it back. Zero downtime, zero fear." Shubhash Sharma "Remotion out of the box isn't great. It's almost like building some slides, just one step up. You have to build it as a system of what you need." Danny McMillan "The hardest part for AI to represent is cadence. It can get the tone of your voice. That's the easy bit. But the speed and the up and down of how you talk, that's where these models still fail." Danny McMillan "In our rush to use AI, you've got to remember the market floods with it. When everything sounds like AI, the only thing left is the authentic voice for your brand." Danny McMillan Resources Mentioned Supabase : Postgres backend used as the long term data store for the seller "brain" pgvector : Postgres extension for semantic search over unstructured data (contracts, reviews, supplier emails) n8n : Orchestration layer for scheduled pulls and cron jobs with a UI Amazon Selling Partner API (SP API) : Source for orders, inventory and finance data (covered in last episode) Amazon Ads API : Source for ad spend, campaign and keyword data Remotion : Code based, React powered video creation framework ElevenLabs : Voice cloning and text to speech. Model used: Multilingual v2 (Pro plan, £22 / month) F5 TTS : Open source text to speech model tested for voice cloning VoiceBox by Jamie Pine : GitHub voice cloning desktop app tested by Danny Pixabay : Free music and sound effects used inside the Remotion workflow Loom : Source of clean voice reference audio if you record team walkthroughs Seller Sessions Live 2026 : Conference 9 May 2026, 18 days out at recording Hosts Danny McMillan : Host of Seller Sessions and Claude Sessions, founder of DataBrill, building AI native tooling for Amazon sellers. Website: https://sellersessions.com LinkedIn: https://www.linkedin.com/in/dannymcmillan Shubhash Sharma : Engineer building data infrastructure for Amazon and TikTok Shop sellers. Returning Claude Sessions co host. What's Next Next week: Ritu returns from Japan with three subjects covered in this month's rotation. In 18 days: Seller Sessions Live 2026 in London on 9 May. Modular format, new venue confirmed. About Seller Sessions Seller Sessions is the leading podcast for serious Amazon sellers, hosted by Danny McMillan since 2017. Claude Sessions is the AI focused monthly strand where Danny and rotating co hosts work through the practical wins, false starts and engineering reality of building with Claude, MCPs and the wider AI stack inside real seller businesses.

In this episode of the Liquid Weekly Podcast, hosts Karl Meisterheim and Taylor Page are joined by Anne Thomas, co-founder of Design Packs. Anne shares her journey in the Shopify ecosystem, her recent foray into backend development with Supabase and Claude AI, and the launch of her new podcast, Cart to Cart.The conversation dives into the nuances of building with Shopify's flexible theme blocks, managing design systems, and the realities of using AI for coding and QA. Anne also discusses her community-building efforts with "Women Unified in Commerce".STAY CONNECTEDSubscribe to Liquid Weekly for more expert insights: https://liquidweekly.com/EPISODE HIGHLIGHTS Anne's Background & Side Projects: From starting with Shopify themes in 2014 to building a horse-riding tracking app. Cart to Cart Podcast: Anne introduces her new podcast co-hosted with Trudy McNabb, Brenda Storer, and Diana Birsan. Women Unified in Commerce: Insights into the grassroots community meetups Anne and Trudy host in Toronto. Developer vs. Merchant Feedback: How the Design Packs team navigates and balances feedback. Theme Blocks & Design Systems: A deep dive into Shopify's flexible blocks, modern theme architecture, and CSS overrides. AI in the Dev Workflow: The realities of using AI tools like Claude and Cursor's Bugbot for writing code and PR reviews.FIND ANNE ONLINE & RESOURCES LinkedIn: https://www.linkedin.com/in/annethomas8/ Twitter(X): https://x.com/alfalfaanne Design Packs: https://design-packs.com/ Cart to Cart Podcast: https://cart2cartpodcast.com Women Unified in Commerce: LinkedIn Group TIMESTAMPS 00:00 - Introduction & Anne's Background 03:30 - Building with Supabase & Claude AI 08:40 - The "Cart to Cart" Podcast 30:30 - "Women Unified in Commerce" Meetups 37:50 - Balancing Merchant and Developer Feedback 43:30 - Navigating Shopify's Flexible Theme Blocks 50:15 - Design Systems & CSS Overrides in Themes 58:15 - AI Realities: Coding, QA, and Automated PR Reviews 01:09:40 - Dev Changelog Highlights 01:14:10 - Picks of the WeekDEV CHANGELOG ActionBar removed on mobile: TitleBar primary action now renders as an icon button - https://shopify.dev/changelog/primary-action-icon-replaces-actionbar-on-mobile New CSS variable for mobile safe area insets - https://shopify.dev/changelog/new-css-variable-for-mobile-safe-area-insets Automated testing for Shopify UI extensions with @shopify/ui-extensions-tester - https://shopify.dev/changelog/automated-testing-for-shopify-ui-extensions-with-shopify-ui-extensions-tester New discount fields in the Storefront API's cart types - https://shopify.dev/changelog/new-discount-fields-in-the-storefront-cart-graphql-api Shopify AI Toolkit: Connect your AI tools to the Shopify platform - https://shopify.dev/changelog/shopify-ai-toolkit-connect-your-ai-tools-to-the-shopify-platform Shopify Scripts will be deprecated on June 30, 2026 - https://shopify.dev/changelog/shopify-scripts-will-be-deprecated-on-june-30-2026 (non-dev) Checkout Blocks: Order value limits available on all plans - https://changelog.shopify.com/posts/checkout-blocks-order-value-limits-available-on-all-plansPICKS OF THE WEEK Karl: Simple Truth low-carb crisp crackers and reading the book Dune. Anne: Swapping the morning doomscroll for a daily crossword puzzle. Try https://www.dictionary.com/games/crossword to start. Taylor: Taking the kids to see The Super Mario Bros. Movie.

Coraz więcej ludzi traktuje AI jak wyrocznię – wejdę, zapytam i mam gotową odpowiedź. Niestety, sztuczna inteligencja karmiona ogólnodostępną wiedzą z sieci sprowadza ekspertów na manowce. Mój dzisiejszy gość pokazuje alternatywną drogę. Wojtek Plona (https://plonaconsulting.pl/), zamiast podłączać AI do kolejnych connectorów wyżej ceni własnego RAGa – osobistą bazę wiedzy finansowej, do której sięga Claude.W tym odcinku rozmawiamy o tym, dlaczego jakość źródeł jest ważniejsza niż ilość, kiedy AI najgroźniej halucynuje i z perspektywy dwóch nietechnicznych gości poruszamy wątki serwerów MCP, Supabase i wyszukiwania wektorowego. Wojtek pokazuje też krok po kroku, jak zbudował swoją bazę i jak z niej korzysta przy projektowaniu zarządczego rachunku wyników.Z tego odcinka dowiesz się:

Até onde o low-code realmente pode chegar em sistemas reais?Neste episódio, falamos sobre como o Bubble e ferramentas similares vão além de MVPs, atuando como complemento a sistemas existentes, integrando com APIs — inclusive fiscais — e acelerando entregas com uma arquitetura bem definida.Uma conversa prática sobre aplicação responsável de low-code, combinando automação com n8n e backends modernos como Supabase e Xano.Ouça agora e transforme sua forma de programar com ACBr!Convidados: Marcus Ribeiro é empreendedor tech e cofundador da Ison. Atua há mais de 10 anos com desenvolvimento de soluções empresariais, hoje focado na construção de Módulos sob demanda, automações e integrações — principalmente conectando sistemas com APIs e estruturas fiscais, usando uma abordagem híbrida entre low-code e desenvolvimento tradicional.

Tu es solopreneur / freelance et tu veux créer des revenus passifs ?Créer une formation pendant 6 mois, écrire un ebook que personne n'achète, faire de l'affiliation classique... Ne perds plus ton temps sur des modèles qui ne scalent plus aussi bien qu'en 2020.Dans ce nouveau Solo Nation, on décortique la stratégie passive qui va exploser en 2026 avec 3 solopreneurs qui ont pris 2 ans d'avance grâce au vibe coding :

AGENDA: 03:59 — Anthropic Surpasses OpenAI in Revenue 12:43 — OpenAI Management Reboot 18:24 — OpenAI Buys TBPN 29:00 — SpaceX Files for IPO Targeting $2 Trillion Valuation 37:21 — Doug Leone Returns to Sequoia Capital 41:14 — YC Kicks Out Delve 45:21 — The Rise of Open Router 57:59 — Supabase Targeting $10B Valuation 01:08:18 — The Mercor Hack and AI Cyber Threats Moving Forward 01:17:25 — The $1.8B Two-Person Company  

Hey yall, Alex here, writing this from sunny London, at the first ever AI Engineer conference in Europe!What a show we have for you today! First, let me catch you up on what's important: Anthropic, this week announced a whopping $30B ARR up from 19B in Feb, while also telling us about Claude Mythos Preview their next gen HUGE model that they won't release to the public (yet?) that finds crazy vulnerabilities in existing code bases. Apparently OpenAI will follow up with a similar non-public model soon.The Meta Superintelligence Lab led by Alex Wang finally showed what they were working on, Muse Spark, the smaller of their upcoming models on a complete new infrastructure (MSL announcement, Simon Willison's deep dive on the 16 hidden tools).In other news:Z.AI released GLM 5.1 in OSS finally (HF weights), Seedance 2.0 finally available in US on Replicate, OpenAI testing out GPT-image-2 on LM Arena under codenames, HappyHorse from Alibaba takes the video crown, and Mila Jovovich (5th Element, Resident Evil) releases agentic memory plugin called MemPalace (Ben Sigman's transparent correction thread is worth reading).We had 5 guests today on the show, we kick off with @swyx the founder of AI Engineer and host of Latent Space. We then chatted with @petergostev from Arena (formerly LMArena) about Mythos and the compute wars, then Vincent Koc, the second most prolific contributor to OpenClaw, then our friends VB from OpenAI and Omar from DeepMind, both previously at HuggingFace. This is a busy busy show, and given the time-zones, I unfortunately don't have time for a full weekly writeup, but as always, I will share the raw notes and post the video (lightly edited).ThursdAI - Highest signal weekly AI news show is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.AI Engineer - LondonThursdAI came a long way since the first AI Engineer conference, but many who read this don't know, that was my big break. Swyx invited me to cover the first AIE in San Francisco in 2023, and I remember, I was in an Uber to the airport, the driver asked me what I do, and I, for the first time said “I host a podcast”. I (and ThursdAI) owe a lot to Swyx, and AIE team, and it's been incredible to see how big they've grown and how many great speakers this event hosts! The term AI Engineer has drifted in those 3 years, but also has the term Software Engineer. Swyx predicted this nearly 3 years ago, what I don't think he predicted, is that all engineers are now AI Engineers, and this includes domains like Agens (OpenClaw), Context and Harness Engineering, Evals and Observability, Voice & Vision all of which are tracks in this conference. I was really surprised to see how many of the talks/speakers here are native to London (after all, Deepmind is from here, OAI, Anthropic, Meta have offices here) and the latest boom in agents, OpenClaw, Pi were all Europe based as well, and they are joined the AI Engineer stage. Oh, and there's also a Giant Inflatable Claw at the entrance, yup, for pictures and vibes, and to show off how quickly the OpenClaw took over the mind-share. Anthropic announces $30B ARR and Mythos, their next model, will not be released to the public. The thing that everyone will tell you, is that Anthropic is on a roll, this is obviously connected to their upcoming IPO this year. We've been covering many issues on their part, but this week we saw them posting about a HUGE increase in ARR, from 19B in February to 30B in April, passing OpenAI at $25B. That last fact though, is kind of disproven because they report on ARR differently, OpenAI apparently only counts their cloud revenue from Microsoft per the information. The growth is undeniable though, and so is the most unprecedented release announcement, Claude Mythos Preview, which was rumored for a bit and now was announced proper. With project Project GlassWing, Anthropic has announced that this model is SO good at cyber security and finding bugs in code, that they cannot share it with the public, and through GlassWing they will share it with companies like Microsoft, Linux, CrowdStrike and a bunch of others, to harden their security. This is it folks, this is the first time, where a model was “announced” but deemed too risky to release. Now, is it truly “too risky”? Previously, folks thought that DALL-E is too risky, or cloning voice tech is too risky, and now it's everywhere. The capabilities catch up even in OpenSource. But the facts are, Anthropic says they've found a 27-year old bug in OpenBSD (famously very secure), and that this model is very very good at connecting the dots between several, seemingly inacuous bugs, to string them together into one coheren exploit. This is, indeed scary. Just last week, one of the top security researchers in the world, Nicolas Carlini, now at Anthropic, gave a talk at Black Hat, showing off these results, and saying that these models since December and definitely recently have passed him as a security engineer. If you haven't seen this talk, watch it, then try to estimate if Anthropic did the right thing by only releasing this model to enterprises first. But on the show, Peter Gostev from Arena gave me a take on this that I haven't been able to shake. Peter pulled up his Compute Wars chart live on the show — and the picture is that OpenAI is way ahead of Anthropic on compute, with Anthropic only recently getting a noticeable bump (which lines up suspiciously well with Mythos being trainable in the first place). His read: “it sounds cooler to say it's too risky to release than ‘we can't serve it.'” The official partner pricing is $25 / $125 per million tokens — 5x Opus 4.6 — but if you don't have the GPUs to serve it broadly, the price doesn't matter. In the year of the IPO, the company that cannot serve a model says the model is too dangerous to serve. Make of that what you will.This also reframes the whole rate-limit drama with OpenClaw. Anthropic didn't ban OpenClaw — I want to be very clear about this because the discourse went sideways. What they did is they made it significantly more expensive for Max-tier subscribers to use Opus through OpenClaw, which pushed a lot of people over to GPT-5.4 via Codex. Same root cause: they're out of compute. The freshly announced Anthropic + Google TPU deal (Google already owns ~10% of Anthropic) is them trying to fix this — though as Peter noted, it's pretty wild that Google is propping up a direct competitor to their own DeepMind team. Same pattern as their original $2B Anthropic investment ending up propping AWS Bedrock against Google Cloud. Big Google contains multitudes.Meta Superintelligence Labs ships Muse Spark — Llama is dead, long live MuseLlama is dead, long live Muse. This week Meta finally showed what the very expensive Meta Superintelligence Labs under Alexandr Wang has been cooking, and the answer is Muse Spark — the smaller of their new model family, built on a fully rebuilt AI stack from scratch in just 9 months. Nine months is wild for that kind of overhaul, and the headline number people are quoting is that they reach Llama 4 Maverick capability with over 10x less compute.Spark is intentionally small and latency-optimized — it's not trying to be the biggest, it's trying to be the first step on Meta's new scaling ladder. But the benchmarks in certain areas are nuts: 86.4 on CharXiv Reasoning (beats Opus, Gemini, GPT-5.4), and the one that really got me — 42.8 on HealthBench Hard vs Opus at 14.8 and Gemini at 20.6. They trained it with data curated by over 1,000 physicians and it shows. They also shipped a Contemplating mode which is parallel multi-agent reasoning, hitting 58.4% on Humanity's Last Exam with tools. Coding is the acknowledged weak point (77.4 on SWE-Bench Verified vs Opus 80.8) but for v1 from a brand new stack, this is extremely respectable.Meta is Back!The real story isn't any single benchmark though, it's distribution. Spark is rolling out across meta.ai, WhatsApp, Instagram, Threads, Messenger, and Ray-Ban Meta glasses — billions of users. Meta went from open Llama to a closed consumer model and they're clearly playing a different game now (though Wang says future Muse versions might be open-sourced).The deep-dive that's really worth your time is Simon Willison's post where he poked at the meta.ai chat UI and got the model to spit out descriptions of 16 hidden tools behind the scenes — full Code Interpreter with persistent Python 3.9, a visual grounding tool that does pixel-precise object detection (bounding boxes, point coordinates, counting — it located 8 objects including individual whiskers and claws on a generated raccoon), sub-agent spawning, file editing, and semantic search across Instagram/Threads/Facebook posts. It's basically an entire agentic harness baked into the chat UI. Jack Wu from MSL confirmed the tools are part of a new harness built specifically for Spark's launch. Meta stock went up 7% on this. They are very much back in the frontier game.Guest highlights We had an unprecedented packed show with 5 guests (also this is the shortest show we've everSwyx kicked us off with vibes from the AI Engineer floor — harness engineering as the dominant theme (gains are coming from the harness, not the weights), the rise of skills (English-as-programming-language) absorbing more of that harness work, and his thesis that supply-chain attacks like the recent light LLM and Axios incidents mean you should basically vendor everything — pip fork instead of pip install. We also chatted about how MCP has gone from “the most exciting protocol” to “settled and stable, therefore less interesting,” which is a great problem to have.Peter Gostev from Arena (you saw a lot of him in the Mythos section above) also dropped a bonus on us: Arena just released 3 years of historical leaderboard data and actual prompt datasets on Hugging Face. He used to literally scrape the arena website by hand into Google sheets to make those overtime leaderboards we all loved — now it's all public. Also: he confirmed that Seedance 2.0 jumped ~80 ELO points above the next video model on Arena, which is unprecedented — video models normally cluster within 10 points of each other.Vincent Koc — the #2 OpenClaw maintainer after Peter Steinberger — joined us fresh off the OpenClaw track stage. The OpenClaw codebase is now ~1.5 million lines of code including unreleased iOS and Android native apps. GitHub literally caps the issue/PR counter at “5K+” and they hit the ceiling. We talked about OpenClaw 2026.4.5 which ships /dreaming GA (Light/Deep/REM phases that defrag agent memory and write a human-readable Dream Diary to DREAMS.md), built-in video and music generation across 4 backends, GPT-5.4 as the new default, prompt-cache reuse improvements, and Control UI + docs in 12 new languages. Vincent's framing of dreaming was beautiful — “how do you explain agent memory to a mom? You call it dreaming.” He also gave my favorite line of the show on the GPT-5.4 personality problem: incredible at coding, but soulless. (For what it's worth, I came home after watching Project Hail Mary, cloned the Rocky voice, dropped it into my OpenClaw, and it was magical. That's the kind of thing you can only do when the harness and the model are decoupled.)VB from OpenAI told us Codex just hit 3 million weekly active users — up from 2 million last month. We talked plugins (the Stripe / Supabase / shadcn ones that ship as packages), sub-agents (yes, one is named Jason), and Guardian Approvals — an experimental mode that classifies each tool call by risk and only escalates the dangerous ones to you, so you don't have to YOLO-mode everything. The story that stuck with me though is his 9 AM Codex automation: every morning it reads his Slack mentions, cross-references Gmail and Calendar, and creates 5-minute pre-brief calendar events for upcoming meetings. None of that is “coding.” That's the super-app future hiding inside a “developer tool.” I'm stealing this workflow.Omar Sanseviero from Google DeepMind came on to celebrate Gemma 4 crossing 10M+ downloads with 1,000+ Gemma-4-based fine-tunes already on HF (and Gemma family total is now over 500M downloads). Gemma 4 is also the foundation for the next generation of Gemini Nano on Pixel/Samsung devices. Lama.cpp vision capability fixes are landing. Gemma 4 is also live on W&B Inference if you want to play. Wolfram (whose entire household runs on Pixel + Google AI Studio, including his 70-year-old mother on voice unlock) was in heaven.This Week's BuzzA short but spicy week from Weights & Biases:* W&B Automations are LIVE. You can now wire event triggers from your training runs (completion, eval thresholds, drift) into notifications, GitHub Actions, deployments, infra shutdowns — closing the loop from experiment to production. Pairs really well with the iOS app we recently shipped, so you can get a ping on your phone the moment something interesting happens on a run.* GLM 5.1 is live on W&B Inference (alongside Gemma 4 from last week) — the team is moving fast to host the best open models the moment they drop.* Wolfram published a deep dive on “more reasoning is not always better” on the W&B blog — the research behind his finding that giving models more thinking tokens can actually make them dumber on certain tasks. It's the in-depth version of what we discussed on the show last week, with all the data. Go read it on wandb.com.Also: shout out to everyone who came up to me at AI Engineer and said hi. The Wolf Bench mentions in particular made my day. If you're listening to this and you're at AIE — come find us, we'll be around tomorrow too.That's it for this week — newsletter is short because the show was long and London is calling. As always, thanks for reading and listening

Send us Fan Mail** For various reasons ... I used HeyGen to create the video and audio file this week. Text-to-video/audio. I don't like the results. If anyone has tips on how to improve this AI output please reach out. I'm keen to learn here. **Invest in pre-IPO stocks with AG Dillon & Co. Contact aaron.dillon@agdillon.com to learn more. Financial advisors only. www.agdillon.com00:00 - Intro00:50 - SpaceX Is Targeting the Largest IPO in Stock Market History at $2 Trillion01:41 - Tether Is One of the Most Profitable Financial Companies Per Employee in the World and Almost Nobody Knows It02:23 - Supabase Just Doubled Its Valuation to $10 Billion in a Matter of Months03:03 - 103% Subscription Growth and $1.1B in Bookings: Whoop May Be Done Raising Private Capital03:49 - Saronic Has a $1.75 Billion Raise, a $392M Navy Contract, and Is Rethinking Warfare at Sea04:39 - Starcloud Went From Y Combinator to $1.1 Billion Unicorn in Just 17 Months by Putting Data Centers in Orbit05:39 - Rebellions Raised $650 Million in Six Months and South Korea's AI Chip Contender Is Heading for an IPO06:30 - Nuclear Power Is Back and Valar Atomics Just Raised $450 Million to Power the AI Industry07:33 - Medvi Generated $401 Million in Revenue in Its First Year With Two Full-Time Employees08:25 - Sarvam Is Chasing the Largest Indian AI Fundraise Ever With 22 Languages and 1.4 Billion People09:16 - OpenAI Is Now the Most Valuable Startup in History After Raising $122 Billion at $852 Billion10:15 - OpenAI Just Bought TBPN, a $30M Revenue Media Company, and It Is Only Getting Started10:59 - Anthropic Just Paid $400 Million for an 8-Month-Old Company With Fewer Than 10 People11:51 - Mistral Just Secured $830 Million From Seven Banks to Build Europe's Own AI Infrastructure12:51 - ElevenLabs Hit an $11 Billion Valuation and Is Now Taking Aim at Suno and Udio in AI MusicNOTE: AG Dillon ("AGD") is not affiliated with Anduril. Anduril may require company approval for purchases (aka transfers). AGD has not been pre-approved by Anduril to purchase their stock. AGD purchases pre-IPO stocks in the secondary market and may gain exposure by directly purchasing the stock (on the company's capitalization table) and/or through a third-party fund (aka special purpose vehicle, or SPV).

James and Kieran get into the practical, unglamorous side of building software with AI that nobody seems to talk about.After a HubSpot integration silently broke his video testimonial app in front of a client, Kieran shares his journey into writing automated tests, and how Claude wrote a full test suite in five minutes that would have taken a developer a week.They also cover replacing paid SaaS tools with custom-built alternatives (blogging platforms, course hosting, even a video-to-scope tool for freelance clients), why Convex is generating buzz as a Supabase alternative, how Apple and Shopify app stores are buckling under the wave of AI-generated submissions, and running OpenClaw agents autonomously in Slack as a marketing team of one.Plus a first look at Anthropic's brand new scheduled tasks feature and what it means for running AI workflows without keeping your laptop open.Topics covered:Writing tests for vibe-coded appsConvex vs SupabaseApp store review bottlenecksReplacing SaaS subscriptions with your own buildsOpenClaw as an autonomous marketing agentAnthropic's scheduled tasksThe rise of solo founders

Link to episode page This week's Department of Know is hosted by Rich Stroffolino with guests Bil Harmer, CISO, Supabase, and Chris Ray, Field CTO, GigaOm Thanks to our show sponsor, ThreatLocker Many security strategies still assume everything is allowed until proven malicious. Attackers understand that model well. That's why more organizations are rethinking endpoint security — shifting from detection-first tools to control-first approaches that reduce attack surface before an incident occurs. Learn more at ThreatLocker.com All links and the video of this episode can be found on CISO Series.com  

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    

The agentic AI revolution is finally escaping the coding bubble. What does that mean for startup founders?Just 13 days after recording his first conversation with Yaniv, Gary Lo called to re-record. The reason? OpenClaw and Claude Cowork dropped some huge AI agent updates, and it shifted Gary's perspective enough to change the whole conversation.In this episode, Yaniv Bernstein sits down with Gary Lo – founder of OpenBA, one of Australia's most compelling pre-seed AI startups – to unpack why OpenClaw and Claude Cowork news marks a 'Cursor moment' for the rest of the world: the inflection point where AI stops being a productivity tool for tech teams and starts fundamentally reshaping how every industry works.They break down why tool use will make LLMs genuinely transformative, why non-technical business owners are already buying Mac Minis to run AI agents, and what the shift from 'human-first' to 'LLM-first' product design means for how you build and position your startup today. This episode is essential listening for any founder trying to figure out where to place their bets in an agentic world.In this episode, you'll learn:Why OpenClaw and Claude Cowork signal a 'Cursor moment' beyond software engineeringHow tool use transforms LLM weaknesses into strengthsWhy the long-promised vision of "everything as an API" is finally becoming realHow to think about building for agents vs. humans, and why most current tools aren't optimized for eitherThe "done list" mental model: how agentic coding is collapsing the coordination layers in software workflowsWhy being "a tool worth calling" – like Supabase – is a smarter bet than competing directly with AI modelsHow Gary is applying LLM-first thinking to OpenBA's roadmap right nowResources mentioned in this episode:OpenClaw: https://openclaw.ai/Claude Cowork (Anthropic's agentic desktop tool): https://www.anthropic.com/news/claude-coworkCursor (AI-native code editor, referenced as the original 'Cursor moment' for coding): https://www.cursor.comSupabase (referenced as an example of a tool that rides the agentic AI wave): https://supabase.comOpenBA (Gary Lo's startup - AI platform for buyer's agents): https://openba.com.auGary Lo on LinkedIn: https://www.linkedin.com/in/gary-lo-engineer/The Pact Honor the Startup Podcast Pact! If you have listened to TSP and gotten value from it, please:Follow, rate, and review us in your listening appSubscribe to the TSP Mailing List to gain access to exclusive newsletter-only content and early access to information on upcoming episodes: https://thestartuppodcast.beehiiv.com/subscribe Secure your official TSP merchandise at https://shop.tsp.show/ Follow us here on YouTube for full-video episodes: https://www.youtube.com/channel/UCNjm1MTdjysRRV07fSf0yGg Give us a public shout-out on LinkedIn or anywhere you have a social media followingKey linksThis episode of the Startup Podcast is sponsored by .tech domains. Forget weird prefixes and creative misspellings; the availability for .tech domains is simply way better than .com. For a clean name that highlights your tech credentials, get a .tech domain at your favorite registrar.Get your question in for our next Q&A episode: https://forms.gle/NZzgNWVLiFmwvFA2A The Startup Podcast website: https://www.tsp.show/episodes/Learn more about Chris and YanivWork 1:1 with Chris: http://chrissaad.com/advisory/ Follow Chris on Linkedin: https://www.linkedin.com/in/chrissaad/ Follow Yaniv on Linkedin: https://www.linkedin.com/in/ybernstein/Producer: Justin McArthur https://www.linkedin.com/in/justin-mcarthurIntro Voice: Jeremiah Owyang https://web-strategist.com/

In this episode, I sit down with Prashant Sridharan, a 30-year veteran of developer marketing who has shaped go-to-market strategies for tech giants like Sun Microsystems, Microsoft, AWS, Facebook, and Twitter, and currently runs product marketing at Supabase. We dive deep into the origins of DevRel and how marketing to developers has evolved in an increasingly noisy, AI-saturated landscape.Topics covered:- Transitioning from massive tech companies to the fast-paced startup world - How to genuinely measure the success of Developer Relations without ruining communities - Using AI tools like Claude to accelerate mechanical marketing tasks while preserving authentic storytelling - The shift from traditional SEO to GEO (Generative Engine Optimization) for developer tools - The thrill of live, unscripted coding demos and stories from sharing the stage with Steve Ballmer - Prashant's upcoming fiction novel, The Midnight Coders Children, and the craft of writing Find more from Prashant at StrategicNerds.com and check out his non-fiction book, Picks and Shovels: https://amzn.to/4cJ2TRO

Google has confirmed that state-backed threat actors are operationally using Gemini across the intrusion lifecycle — not experimentally, but strategically. In this episode of Security Squawk, we break down how AI is being integrated into reconnaissance, phishing refinement, vulnerability research, and even dynamic malware generation. According to Google's Threat Intelligence Group, multiple clusters — including DPRK-linked actors — are using Gemini to synthesize OSINT, map organizational structures, refine recruiter impersonation campaigns, and research exploit paths. In one case, malware known as HONESTCUE leveraged Gemini's API to dynamically generate C# code for stage-two payload behavior, compile it in memory using legitimate .NET tooling, and execute filelessly. This isn't a zero-day story. It's a friction story. At the same time, two individuals in Connecticut were charged for allegedly using thousands of stolen identities to exploit FanDuel's onboarding and promotional systems. No exotic exploit. No advanced intrusion chain. Just automated workflow abuse at scale. The pattern is clear: AI is compressing attacker timelines, and identity-driven fraud is industrializing predictable processes. We examine: How AI-enhanced phishing eliminates traditional grammar-based red flags Why trusted SaaS domains (Gemini share links, Discord CDNs, Cloudflare fronting, Supabase backends) are weakening reputation-based defenses What model distillation attempts (100,000+ structured prompts) signal about API abuse and intellectual property risk How fileless malware compiled with legitimate developer tooling challenges signature-based detection Why onboarding workflows and recruiting processes are now primary attack surfaces For CEOs, this is about erosion of trust anchors and shifting insurability expectations. For IT Directors and SOC leaders, this means reevaluating fileless execution visibility, API anomaly detection, and the reliability of reputation filtering models. For MSPs and risk managers, breaches will increasingly originate from workflow exploitation rather than perimeter misconfiguration. AI didn't invent new attack types. It removed friction from existing ones. And when friction disappears, scale compounds. If your recruiting, onboarding, verification, or AI product interfaces can be scripted — they can be weaponized. This episode is about operational clarity in a rapidly compressing threat landscape. Keywords: Google Gemini, HONESTCUE malware, AI phishing, state-backed threat actors, DPRK cyber operations, model distillation attacks, API abuse detection, fileless malware, .NET in-memory compilation, identity fraud, FanDuel fraud case, workflow exploitation, SaaS infrastructure abuse, Cloudflare phishing, Discord CDN payloads, Supabase backend abuse. Support the show https://buymeacoffee.com/securitysquawk

In this episode, Alex Hillman, co-founder of Philadelphia's legendary coworking space Indy Hall, takes us through his journey building a sophisticated AI executive assistant using Claude Code. What started as a simple terminal experiment in October 2025 has evolved into a full production system that autonomously manages network diagnostics, email workflows, relationship tracking, and newsletter automation. Alex shares the technical architecture, real-world stories of AI-powered problem solving, cost insights, and his thoughtful approach to building trust with AI while maintaining strong ethical guardrails.## Chapters- 00:00 Coming Up...- 02:01 Introductions- 03:57 The Origins of PhillyCocoa and Indie Hall- 06:12 The Evolution of AI and Personal Assistants- 07:35 Building a Personal Assistant with Claude Code- 10:26 The Architecture of the Personal Assistant- 14:04 Creating a Web App Interface for the Assistant- 16:10 Using Tailscale for Secure Access- 19:01 Mitigating Risks with AI Autonomy- 29:24 Backup Protocols and Data Management- 31:23 Emergent Behavior in AI Systems- 34:10 Flow State and Productivity in Programming- 37:56 Understanding AI Behavior and User Education- 39:45 Cost Management in AI Development- 45:37 Building Trust with AI Systems- 53:53 Navigating Trust in Skill Utilization- 55:23 Technical Applications for Non-Developers- 01:00:17 Innovative Personal and Business Management- 01:09:03 Transforming Workflows with AI- 01:12:56 Ethics and Responsibility in AI Usage- 01:18:25 Community Building Through Meetups- 01:21:55 Tag## Highlights**Architecture:** Claude Code headless via CLI with WebSocket communication, Docker on Hetzner VPS, Tailscale networking, hourly snapshots, git hooks for destructive commands, multi-layered security.**Real Use Cases:**- Network monitoring that diagnosed an overheating router fan from a screenshot- Email sorted by "easiest to hardest" instead of chronological- Date night tracking with restaurant and wine pairing suggestions- Organized 51 wine bottles via photos into ASCII grid layout- Newsletter reduced from 4 hours to 30 minutes while preserving human writing**Costs:** $20/month plan lasted 20 minutes. Now at $200/month. One Thanksgiving week hit $1,500 in overages during heavy development.**Philosophy:** "Modest YOLO" approach—autonomous but controlled. AI enhances human work, doesn't replace it. The system can modify itself: type "add a button," refresh, it works.**Open Source:**- **Kuato**: Session search for Claude Code- **Smaug**: Twitter bookmark archiver with AI analysis- **Andy Timeline**: Auto-generated weekly narrative of the AI's evolution## Event**Big Philly Meetup Mashup** - March 15, 2026Hackathon for Philadelphia's tech and creative communities. Theme: "Good Neighbors." Sponsored by Supabase.https://indyhall.org/goodneighbors/## Links**Alex Hillman**YouTube: https://www.youtube.com/@AlexHillman | Website: https://dangerouslyawesome.com | GitHub: https://github.com/alexknowshtml**Open Source Projects**Kuato: https://github.com/alexknowshtml/kuato | Smaug: https://github.com/alexknowshtml/smaug | Andy Timeline: https://github.com/alexknowshtml/andy-timeline**Tools & Resources**Indy Hall: https://indyhall.org | Claude Code: https://claude.com/product/claude-code | OpenClaw: https://openclaw.ai | Brian Casel: https://www.youtube.com/@briancasel | Termius: https://termius.com | Point-Free: https://www.pointfree.co/the-way**PhillyCocoa:** http://phillycocoa.orgIntro music: "When I Hit the Floor", © 2021 Lorne Behrman. Used with permission of the artist.

Scott and Wes break down how they built SynHax, the real-time CSS Battle app powering the upcoming Mad CSS tournament. From SvelteKit and Zero to diffing algorithms, sync conflicts, and a last-minute hackweek glow-up, this one's a deep dive into shipping ambitious web apps fast. Show Notes 00:00 Welcome to Syntax! 00:50 March Mad CSS Tournament. 03:19 Brought to you by Sentry.io. 03:59 What the heck is a CSS Battle? 05:34 The tech stack. 06:30 Svelte Kit. 06:44 Zero Sync. Zero Docs Zero Svelte. 07:32 Drizzle. 07:58 Supabase. 08:23 Graffiti. 10:45 Sync Server. 12:10 Cloudflare Workers. 12:23 Local File System. 13:26 How Zero Works. 13:48 Zero Sync Client. 15:39 API server. 19:34 Dealing with states and conflicts. 24:25 The Hackweek Project. 25:29 The Diffing Algorithm. 35:22 The bugs. Hit us up on Socials! Syntax: X Instagram Tiktok LinkedIn Threads Wes: X Instagram Tiktok LinkedIn Threads Scott: X Instagram Tiktok LinkedIn Threads Randy: X Instagram YouTube Threads

Jason William Johnson, PhD, Founder of SoundStrategist, is driven by two lifelong passions: creating and teaching. Through SoundStrategist, Jason designs AI-powered learning experiences and intelligent coaching systems that blend music, gamification, and experiential learning to drive real skill development and engagement for enterprises and entrepreneur support organizations. We explore Jason's journey as a musician, educator, and business coach, and how he fused those disciplines into an AI-first company. Jason shares his AI for Deep Experts Framework, showing how subject-matter experts can identify an industry pain point, envision a solution, brainstorm with AI, leverage AI tools to build it, and go after high-value impact—turning deep expertise into scalable products and platforms without needing to be technical. He also explains how AI accelerates research and product design, how “vibe coding” enables rapid MVP development, and why focusing on high-value B2B impact creates faster traction with less complexity. — Turn Your Expertise Into Software with Jason W. Johnson Good day, dear listeners. Steve Preda here, the Founder of the Summit OS Group, developing the Summit OS Business Operating System. And my guest today is Jason William Johnson, PhD, the Founder of SoundStrategist. His team designs AI-powered learning experiences and deploys intelligent coaching systems for enterprises and entrepreneur support organizations blending music, gamification, and experiential learning to drive real skill development and engagement. Jason, welcome to the show.  Thanks for having me, Steve.  I’m excited to have you and to learn about how you blend music and learning and all that together. But to start with, I’d like to ask you my favorite question. What is your personal ‘Why’ and how are you manifesting it in your business?  I would say my personal ‘Why’ is creating and teaching. Those are my two passions. So when I was younger, I was always a creative. I did music, writing, and a variety of other things. So I was always been passionate about creating, but I’ve also been passionate about teaching. I've been informally a teacher for my entire adult life—coaching, training. I've also been an actual professor. So through  SoundStrategist, I’m kind of combining those two passions: the passion for teaching and imparting wisdom, along with the passion for creating through music, AI-powered experiences, gamification, and all of those different things. So I'm really in my happy place.Share on X  Yeah, sounds like it. It sounds like you're very excited talking about this. So this is quite an unusual type of business, and I wonder how do you stumbled upon this kind of combination, this portfolio of activities and put them all into a business. How did that come about? So Liam Neeson says, “I have a unique combination of skills,” like in Taken. I guess that's kind of how I came up with SoundStrategist. I've pretty much been in music forever. I've been a musician, songwriter, producer, and rapper since I was a child. My father was a musician, so it was kind of like a genetic skill that I kind of adopted and was cultivated at an early age. So I was always passionate about music. Then got older, grew up, got into business, and really became passionate about training and educating. So I pretty much started off running entrepreneurship centers. My whole career has been in small business and economic development. SoundStrategist was a happy marriage of the two when I realized, oh, I can actually use rap to teach entrepreneurship, to teach leadership skills, and now to teach AI and a variety of other things.Share on X So pretty much it was just that fusion of things. And then when we launched the company, it was around the time ChatGPT came out. So we really wanted to make sure we were building it to be AI-first. At first, we were just using AI in our business operations, but then we started experimenting  with it for client work—like integrating AI-powered coaches in some of the training programs we were running and things like that. And that really proved to be really valuable, because one of the things I learned when I was running programs throughout my career was you always wanted to have the learning side and the coaching side. Because the learning side generalizes the knowledge for everybody and kind of level-sets everybody.Share on X But everybody’s business, or everybody’s situation, is extremely unique, so you need to have that personalized support and assistance. And when we were running programs in the entrepreneurship centers I were running and things like that, we would always have human coaches. AI enabled us to kind of scale coaching for some of the programs we’re building at SoundStrategist through AI. So with me having been a business coach for over 15 years, I knew how to train the AI chatbots. It started off as simple chatbots, and now it's evolved into full agents that use voice and all those other capabilities. But it really started as, let's put some chatbots into some of our courses and some of our programs to kind of reinforce the learning, personalize it, and then it just developed from there. Okay, so there's a lot in there, and I'd like to unpack some of it. When you say use rap to teach, I’m thinking about rap is kind of a form of poetry. So how do you use poetry, or how do you use rap to teach people? Is it more catchy if it is delivered in the form of a rap song? How does it work? So you kind of want to make it catchy. Our philosophy is this: when you listen to it, it should sound like a good song.Share on X Because there’s this real risk of it sounding corny if it's done wrong, right? So we always focus on creating good music first and foremost when we’re creating a music-based lesson. So it should be a good song. It should be something you hear and think, oh, between the chorus and the music, this actually sounds good. But then, the value of music is that once you learn the song, you learn the concept, right? Because once you memorize the song, you memorize the lyrics, which means you memorize the concept. One of the things we also make sure to do is introduce concepts. The best way I could describe this is this, and this might be funny, but I grew up in the nineties, and a lot of rappers talked about selling dr*gs and things like that. I never sold dr*gs in my life. But just by listening to rap music and hearing them introduce those concepts, if I ever decided to go bad, I would have a working theory, right? So the same thing with entrepreneurship, and the same thing with business principles. You can create songs that introduce the concepts in a way where if a person's never done it, they're introduced to the vocabulary.Share on X They’re introduced to the lived experiences. They’re introduced to the core principles. And then they can take that, and then they can go apply it and have a working theory on how to execute in their business. So that’s kind of the philosophy that we took, let’s make it memorable music, but also introduce key vocabulary. Let’s introduce lived experiences. Let’s introduce key concepts so that when people are done listening to the song, they memorize it, they embody it, and they connect with it. Now they have a working theory for whatever the song is about.  And are you using AI to actually write the song?  No, we're not. That’s one of the things we haven’t really integrated on the AI front, because the AI is not good enough to take what’s exactly in my head and turn it into a song. It’s good for somebody who doesn’t have any songwriting capability or musical capability to create something that’s cool. But as a musician, as somebody who writes, you have a vision in your head on how something should sound sonically, and the AI is not good enough to take what’s in my head and put it into a song. Now, what we are using are some of the AI tools like Suno for background music. So at first, we used that to create all our background music for our courses from scratch. We are using some of the AI to help with some of the background music and everything and all of that so that we can have original stuffShare on X as opposed to having to use licensed music from places like Epidemic Sound. So we are using it for like the background music. But for the actual music-based lessons, we're still doing those old school.  Okay, that's pretty good. We are going to dive in a little bit deeper here, but before we go there, I’d like to talk about the framework that you’re bringing to the show. I think we called it the AI for Deep Experts Framework. That's the working title right now, but yeah, we're still finalizing it. But that’s the working title. Yeah.  But the idea—at least the way I'm understanding it—is that if someone has deep domain expertise, AI can be a real accelerator and amplifier of that expertise. Yep.  So people who are listening to this and they have domain expertise and they want to do AI so that they can deliver it to more people, reach more people, create more value, what is the framework? What is the five-step framework to get them there?  Number one: provided that you have deep expertise, you should be able to identify a core pain point in your respective industry that needs solving.Share on X Maybe it’s something that, throughout your career, you wanted to solve, but you weren’t able to get the resources allocated to get it done in your job. Or maybe it required some technical talent and you weren’t a developer, or whatever, right? But you should be able to identify what’s the pain point, a sticking pain point that needs to be solved—and if it's solved, it could really create value for customers. That's just old-school opportunity recognition. Number two: now, the great thing about AI is that you can leverage AI to do a lot of deep research on the problem. So obviously, you're still going to have conversations to better understand the pain point further. You're going to look at your own lived experiences and things like that. But now you can also leverage AI tools—using Perplexity or Claude—to do deep research on a market opportunity. So whether or not you have experience in market research, you can use an AI tool to help identify the total addressable market. You can brainstorm with it to uncover additional pain points, and it help you flesh out your value proposition, your concept statement, and all of those things that are critical to communicating the offering. Because before we transact in money, we always transact in language, right? So pretty much, AI can help you articulate the value proposition, understand the pain point, all of those different things. And then also if you have like deep expertise and you haven't really turned it into a framework, the AI can help you framework it and then develop a workflow to deliver value.Share on X So now you have the framework, you have the market understanding, and all of those different things. AI can even help you think through what the product would look like—the user experience, the workflow, things like that. Now you can use the AI-powered tool to help you build that. You can use something like Lovable. You can use something like Bolt. You could use something like Cursor, all different AI-powered tools. For people who are newer to development and have never done development before, I would recommend something like Lovable or maybe Bolt. But once you get more comfortable and want to make sure you're building production-ready software, then you move to something like Cursor.  Cursor has a large enough context window—the context window is basically the memory of an AI tool. It has a large enough context window to deal with complex codebases. A lot of engineers are using it to build real, production-ready platforms. But for an MVP, Bolt and Lovable are more than good enough. So one of the things I recommend when building with one of these tools is to do what's called a PRD prompt. PRD stands for Product Requirements Document.Share on X For those who aren’t familiar with software development, typically, and this is not even really happening anymore, but traditionally with software development, you would have the product manager create a Product Requirements Document. So this basically outlines the goals of the platform, target audience, core features, database, architecture, technology stack, all of the different things that engineers would need to do in order to build the platform. So you can go to something like Claude, or ChatGPT, and you can say: “Create a PRD prompt for this app idea,” and then give as much detail as possible—the features, how it works, brand colors, all of those different things. Then the AI tool—whether you're using ChatGPT, Claude, or Gemini—will generate your PRD prompt. So it’s going to be like this really, really long prompt. But it’s going to have all of the things that the AI tool, web-building or app-building tool needs to know in order to build the platform. It’s going to have all the specifications. So you copy and paste.  Is this what people call vibe coding?  Yeah, this is vibe coding. But the PRD prompt helps you become more effective at vibe coding because it gives the AI the specifications it needs and the language that it understands to increase the likelihood that you build your platform correctly. Because once you build the PRD prompt, the AI is going to know, okay, this is the database structure. It's going to know whether this is a React app versus a Next.js app. It's going to know, okay, we're building a frontend with Netlify. The stuff that you may not know, the AI will know, and it will build the platform for that. So then you take that prompt, you paste it into Lovable, paste it into Cursor, and then you can kind of get into your vibe coding flow. Don't let the hype fool you, though, because a lot of people will say, “Oh, I built this app in 15 minutes using Lovable.” No—it still requires time. But if you can build a full-stack application in two weeks when it typically takes several months, that’s still like super fast. So pretty much, on average, you can build something in a couple of weeks—especially once you get familiar with the process, you can build something in a couple of weeks. But if this is your first time ever doing this, pay attention to things like when the app debugs and some of the other issues that come up.  Start paying attention because you’re going to learn certain things by doing. As you go through the process, you'll begin to understand things like, okay, this is what an edge function is, this is what a backend is. You’ll start learning these different things as you’re going through the process, right? So you get the platform built. Now the next step is you want to distribute the platform. So obviously, if you’ve been in your industry for a while and you have some expertise, you should have some distribution. You should have some folks in your space who are your ICP that you can kind of start having some customer conversations with and start trying to sell the platform. One of the things that I always recommend is going B2B and selling something for significant valueShare on X as opposed to going B2C and selling a bunch of $19.99 subscriptions. And the reason for that is a couple of different things. Number one, when you have to do a lot of volume, your business model becomes more complicated. And then you have to introduce things to manage that volume. Whereas if you’re selling a solution that’s a five-figure to six-figure offering, like 10 clients, 15 clients, the amount of money that you can get to with less complexity in your business model. So I always say go B2B, at least a five-figure annual offering, because I know most of the offerings that we offer are at least high five figures, low six figures—subscriptions, SaaS licensing, or whatever. And that way it just introduces less complexity to your business model, and it allows you to get as much revenue as possible. And then as you go to market, you’re going to learn. So the learning aspect, you’re going to learn maybe customers want this or this feature. We thought the people were going to use the platform this way, but they’re actually using it this way. So you’re always learning, always evolving, and adjusting the offering. Okay, so let's say I have deep expertise in some area—maybe investment banking or whatever. I want to use AI. I identify an industry pain point that I've addressed or maybe I personally experienced. I visualize a solution, then I brainstorm with ChatGPT or Claude or whatever, figure out what to do, and then I leverage AI tools like Cursor, Lovable, or Bolt. I set the price point. I go B2B. Is this something that, as a subject-matter expert, is efficient for me to do myself because I have the expertise and the vision? Or is it better for me to hire someone to do this?  It depends on what your bandwidth is. I mean, pretty much I’m of the firm belief that like these are skills that you probably want to unlock anyway. So it might be worth going through the process of learning the tools, leveraging them, and everything, and all of that. And that’s kind of how you future-proof yourself. Now, obviously, if you have bandwidth limitations, there are firms and organizations that you could hire, et cetera, et cetera, that can do it for you. Obviously, developers and things like that. But the funny thing about a lot of developers is, even though they're using AI, they're still charging the prices they charged before AI, right? They’re just getting it done faster, and their margins are a lot lower. So you're still going to pay, in a lot of instances, developer pricing for a platform. Those are the things that you have to consider as far as your own personal situation. But me personally, I believe these are skills worth unlocking.Share on X Because one of the things is, if you get very senior in your career—let's say you've been there 15, 16 years, 20 years—we all know there's this point where you either move up to the C-suite or you get caught in upper-middle-management purgatory, where you're kind of in that VP, senior director space, et cetera, et cetera, and you just kind of hover there. At that point, your career moves tend to be lateral—going from one VP role to another VP role, one senior director role to another senior director role, right? At that point, your income potential starts to get limited. So unlocking one of these skills and becoming more entrepreneurial is something I genuinely believe is worth developing personally. And what would you say is the time requirement for someone to get competent in vibe coding?  Three months minimal. You could be pretty solid in three months.  But three months full-time or three months part-time?  Three months part-time.  So three months. That's about 143 working hours in a regular month. So that's basically around 420–430 hours if you were full-time.  If you spend weekends working on your project, learning how to build it, taking notes, and actually going through the process, you can get pretty decent in a couple of months. Now, obviously, there are still levels as you continue and to progress and things like that, but you can get pretty solid in a couple months. Another thing you want to consider is who you're selling to. You obviously wanna make sure that your platform security is really well, is really done. So even if you build it yourself and then you have an engineer do code review, that’s cheaper than having them build it. I think if you spend three months, you can get really good at building solutions for what you need to get done. And then from there, you just get better and better and better and better.  How do I know that, let's say I hire someone in Serbia to do a code review for me? Let's say I learn the vibe coding thing and create the prototype, then I have someone to clean the code. How do I know that they did a good job or not?  You really don’t. You really don’t know until the platform’s in the wild, and it’s like, okay, it’s secure. So there are some things that you can do to check behind people. Let's say you don't have the money to do a full security audit or hire someone specifically for a security review, a developer for security review. One of the things that you can do is you can do multi-agent review. Like you take your codebase, have Claude review it, have OpenAI Codex review it, have a Cursor agent review it. You have multiple agents do a review. Then they kind of check each other’s work, if you will.  They kinda identify things that others may not have identified, so you can get the collective wisdom of those three to be able to be like, “Okay, I need to shore this up. I need to fix this. I need to address that.” That gives you more confidence. It still doesn’t replace a person who has deep expertise and making sure they build secure code, but it will catch common issues, like hard-coding API keys, which is a risk, right? It’ll catch those type of things that typically happen. But let’s say you do have a security, a code review, you could just kind of take that same approach also to check their work. Because they shouldn’t find any major vulnerabilities. The AI agents that come in after it shouldn’t really find any major vulnerabilities if it was like done securely securely. Another thing to consider is that a lot of these tools use Supabase for the backend and database. Supabase also has a built-in security advisor, including an AI security advisor, that points out security issues, performance problems, and configuration errors. So like you do have some AI-powered check and balances to check behind people.Share on X  Interesting. So basically, I can audit their applications, and the AI will check the code and tell me what needs to be improved?  Yeah. And they can make the fixes for you.  Yeah. Wow, that’s amazing. It still sounds a little bit overwhelming. It’s basically a language, a new language to learn, isn’t it?  It’s not really — it’s English. That’s the amazing thing about it—it’s English. I mean, you literally talk to AI in natural language, and it builds stuff for you, which is, if somebody is like, had a idea for a minute, because I mean, pretty much running entrepreneurship centers, I’ve known so many people who’ve had ideas that they were never able to launch or build, and then they see somebody build it later. If you learn these skills, you get to the point where anything that's in your head, you can kind of start bringing it to life in reality.Share on X And even if you've got to bring somebody in to make sure it's secure and production-ready, it's way cheaper than having them build it from scratch. And then another thing that you’ll find also is if you’re able to build something, let’s say you want to turn it into a startup or something, right? It’s a lot easier to bring in a technical co-founder when they don’t got to build the thing from scratch, and then they also see that you were able to build something, they’re able to see your product vision, et cetera, et cetera. It becomes a lot more easier to recruit people who actually have that expertise into the company because you’ve already handled the hard part. You got something and it works. And all they got to do is just come in, make it safe, and make it work better.  Yeah, that is very interesting. It feels analogous to writing a book yourself or having a ghostwriter. Because essentially, you are vibe coding with a ghostwriter, right? You tell the stories, and then the ghostwriter writes the book for you. Probably now you can use  AI to do that. Yep.  But that's a skill. Not everyone has the skill to write it themselves, and then they need to go to the ghostwriter, but still is their book, right?  Yep.  So it sounds a little bit similar. That’s fascinating. So what’s the path to launching an MVP? So let’s say I’m a subject matter expert, and I want to launch an MVP within a few weeks. Is there a path for me to go there?  Once you get good with the platform, once you get comfortable with the tools, yeah. So for example, we're launching an AI platform. It's an AI coaching platform, but it's also a data analytics platform. Basically, it's targeted to entrepreneur support organizations and municipalities supporting small businesses. So on the front end, it's an AI-powered advisor — it's a hotline that people can call 24/7. But on the back end, the municipalities and entrepreneur support organizations get access to analytics from each of those calls. We built this in two weeks. We’re already talking to customers, we’re already having conversations, and all of those things. We literally brought it to market in two weeks. So the thing is, once you kind of get caught up with the tools—and I'm not a developer, I'm not a developer by trade at all. I had a tech startup before, but I was a non-technical founder. I just know how to put together a product. But once you get good with the tools, that's very conceivable. And then you just go out there, and you go in the market, you start having conversations with your ideal customer profile.Share on X As you’re going through that process, you’re learning, okay, maybe this isn’t my ideal customer profile, this is their pain point. Or maybe instead of this being the feature they want, this is the feature they want. And the crazy thing about it is in the past you had to really get that ICP real tight and the feature set real tight because it cost so much money to go back and have to make tweaks and changes and to get it to market in the first place. Now, you can get a new feature added in the afternoon. It allows you to go to market a little bit faster. You don’t have to have the ideal feature set. You don’t have to have the ICP figured out. You get out there, you learn, and then you’re able to iterate a lot faster because the cost of development is super cheap now, and the speed in which like new features can be added or deprecated is a lot faster. So it allows you to go to market a lot faster than in the past.  Okay, I got it. You can do this, you can code. What do you recommend for someone who’s starting out? You mentioned Lovable, Bolt, and then Cursor. Is Cursor like an advanced product?  Cursor’s a little bit more advanced, but if you want to build production-ready software, it's something you're going to eventually have to use. But can you convert from Lovable to Cursor?  Yes, you can. Yep. So what you typically do — and I still do this to this day — is every time I launch a product, I build it in Bolt first. You could use Bolt or Lovable, either one's fine. I use Bolt because Bolt came out first, and that's what I started using. Then Lovable came out like a month later. But I use Bolt. I’ll spin up the idea in Bolt. And the reason I like doing it in Bolt or Lovable is that it's really good at doing two things. It's really good at quickly launching your initial feature set, and then spinning up your backend. Your database — it's really good at that. So I start off in Bolt, then I connect it to a repository.  For those who aren't familiar with GitHub, there's a button in Bolt or Lovable where you can easily connect it to a GitHub repository. So then once I kind of get the app to a point where the basic skeleton is set, then I go into Cursor. Then I pull the repository into Cursor and do the heavy work. The reason Cursor has a learning curve is because there are still some traditional developer things you need to know to spin up a project. Your initial database — it's a lot harder to spin up your initial database and backend in Cursor. It's also harder to identify your initial libraries and all of those things. If you're a developer, it's not difficult. But if you're new, it is. Bolt and Lovable abstract those things out for you. So you start it off in Bolt or Lovable. Basically, since they're limited in their context windows, when you're trying to build something complex, eventually they start making a whole bunch of errors. They basically start getting stup*d. That's when you know it's time to move to Cursor, because Cursor can handle the heavy lifting. So if you build in Bolt or Lovable until it gets stup*d, then you move to Cursor for the heavy lifting.  And then is there a point where Cursor gets stup*d as well? No. Cursor has a couple of different things that allow it to extend its context window, which is his memory. You can put documentation into Cursor. For example, whatever your PRD prompt was, you can save that as a document in Cursor. You can also set rules. One of my rules in Cursor is: I'm not technical, so explain everything in layman's terms. And then as you’re starting to build code, you can save that code or you can point it to that repository. So there's some more flexibility with Cursor as far as managing your context window.Share on X But with Bolt and Lovable, the context window is more limited right now. So I start off in those, and then once I kind of get the skeleton up, then I move to Cursor. And at that point, a lot of the complicated things like spinning up your dev environment and all those things are kind of abstracted out. Then you can just jump in and use it the same way you use Bolt and Lovable. Fantastic. Fantastic. So, Jason, super helpful information for domain experts who want to build an application that will help them promote their product or manifest their ideas in product form. I think that’s super powerful. So if someone would like to learn about SoundStrategist and what SoundStrategist can do for them in terms of learning and experiential products, incorporating music, or building curriculum, or they would just like to connect with you to learn more about what you can do for them, where should they go?  Jason William Johnson, PhD, on LinkedIn, or www.getsoundstrategies.com.  Okay. Well, Jason William Johnson, you are really ahead of the curve, especially connecting this whole idea of vibe coding to people who are subject matter experts and not technical. And you know it because you don't come from a technical background, yet you've mastered it. I’m living it. Everything I’m sharing—this is not like a theoretical framework. I'm living all of this. So everything I’m saying. Super authentic. And especially coming from you—you understand what it's like to not be technical person, learning this, applying this.  So if you'd like to do this, learn more, or maybe have Jason guide you, reach out to him. You can find him on LinkedIn at Jason William Johnson, PhD, or visit www.getsoundstrategies.com. And if you enjoyed this episode, make sure you follow us and subscribe on YouTube, follow us on LinkedIn, and on Apple Podcasts. Because every week I bring a super interesting entrepreneur, subject matter expert, or a combination of the two—like Jason—to the show, who will help you accelerate your journey with frameworks and AI frameworks in that gear. So thank you for coming, Jason, and thank you for listening. Important Links: Jason's LinkedIn Jason's website

Amir (Co-Founder at Humblytics) shares how he builds an “AI-native” company by focusing less on shiny tools and more on change management: assessing AI fluency across roles, setting the right success metrics, and creating shared context so AI can reliably ship work. The big theme is convergence—engineering, product, and design are collapsing into tighter loops thanks to tools like Cursor, MCP connectors, and Figma Make. Amir demos workflows like: AI-generated context files + auto-updated documentation, scraping customer domains to infer ICPs, turning screenshots into layered Figma designs, then converting Figma to working React code in minutes, and even running an “AI co-founder” Slack bot that files Linear tickets and can hand work to agents.Timestamps0:00 Introduction0:06 Amir's stance: “no AI experts” — it's constant learning in a fast-changing field.1:59 Cursor as the unlock: not just coding, but PM/strategy/design work via MCPs.4:17 The real problem: AI adoption is mostly change management + fluency assessment.5:18 The AI fluency rubric (helper → automator → augmentor → agentic) and why it matters.8:13 Cursor analytics: measuring AI-generated code and usage across the team.9:24 “New code is ~99% AI-generated” + how they keep quality via tight review + incremental changes.10:58 Docs workflow: GitBook connected to repo → AI edits docs and pushes live fast.14:02 ICP building: export Stripe customers → scrape domains with Firecrawl → cluster personas.17:45 Hallucination in the wild: AI misclassifies a company; human correction loop matters.34:43 Wild move: they often design in code and use an AI-generated style guide to stay consistent.38:10 Best demo: screenshot → Figma Make → layered design → Figma MCP → React code in minutes.45:29 “AI co-founder” Slack bot (Pixel): turns a bug report into a Linear ticket and can hand off to agents.48:46 Amir's wish list: we “solved dev”; now we need Cursor for marketing/sales → path to $1M ARR.Tools & technologies mentionedCursor — AI-first IDE used for coding and product/design/strategy workflows; includes team analytics.MCP (Model Context Protocol) — “connector” layer (Anthropic-origin) that lets LLMs interface with external tools/services.ChatGPT — used as a common baseline tool; discussed in the context of prompting practices and workflows.Microsoft Copilot — referenced via the law firm incentive story; used as an example of “usage metrics” gone wrong.Anthropic (AI fluency framework) — inspiration source for the helper/automator/augmentor/agentic rubric.GitBook — documentation platform connected to the repo so docs can be updated and published quickly.Firecrawl (MCP) — agentic web scraper used to analyze customer domains and infer ICP/personas.Stripe — source of customer export data (domains) to build ICP clustering.Figma — design collaboration tool; used here with Make + MCP to move from design → code.Figma Make — feature to recreate UI from an image/screenshot into editable, layered designs.Figma MCP — connector that allows Cursor/LLMs to pull Figma components/designs and generate code.React — front-end framework used in the demo for generating functional UI components.Supabase — mentioned as part of a sample stack when generating a PRD.React Router — mentioned as part of the sample stack in PRD generation.Slack — where Amir runs internal agents (including the “AI co-founder” bot).Linear — project management tool used for creating tickets from Slack/agent workflows.CI/CD — their deployment/review pipeline; emphasized as the human accountability layer.Subscribe at⁠ thisnewway.com⁠ to get the step-by-step playbooks, tools, and workflows.

Here's what I'm building with as of Dec 2025.Lovable - https://lovable.dev/Cursor - https://www.cursor.comClaude Code - https://claude.ai/ (Sonnet/Ops 4.5)Vercel - https://vercel.com/Railway - https://railway.com/Supabase - https://supabase.com/ Free Email Course - https://bootstrappersparadise.com/courseOnline Community - https://bootstrappersparadise.com/communityBootstrapper's Paradise - https://bootstrappersparadise.com/

We're excited to bring on Elena Levi, Director of Product Management at Payoneer, data analytics veteran, and passionate advocate for product-driven teams, for a special episode exploring what it's really like to use Lovable and other AI-powered vibe coding tools in product development.Elena shares insights from 15 years in data analytics and product, with the journey from data analyst to product leadership fueling her curiosity about how AI can reshape prototyping, design, and collaboration. Drawing from hands-on experience building predictive analytics solutions, Elena reveals why she chose Lovable for fast prototyping, user testing, product sense interviews, and collaborating with both developers and designers.Join Matt, Moshe, and Elena as they explore:The strengths and limitations of Lovable for prototyping: rapid iteration, easy sharing, changing flows on the fly, user testing, and developer handoffWhen vibe coding works, and where you still need engineering and design expertiseThe realities of code generation, versioning, Supabase integration, and why Lovable stood out from the competition at the time she chose itUsing Lovable for product sense interviewsPractical tips: breaking tasks into smaller prompts, saving tokens with up-front documents, and why the first prompt is the most importantThe trade-offs of using AI tools for MVPs, B2B vs. B2C products, and where privacy and maintainability concerns come inResponses from engineers and designers, what these tools mean for their work, learning curves, and whether they help or hinder junior team membersExpectations vs. reality: how close AI tools get you to the finish line, and why “the last mile” is the toughestConundrums, gotchas, frustrations, and how to keep flexibility in your workflowWhy do PMs must always ask “Why?”, and why AI alone can't replace a critical data mindsetAnd much more!Want to connect with Elena or learn more?LinkedIn: https://www.linkedin.com/in/elena-levi-dataYou can also connect with us and find more episodes:Product for Product Podcast: http://linkedin.com/company/product-for-product-podcastMatt Green: https://www.linkedin.com/in/mattgreenproductMoshe Mikanovsky: http://www.linkedin.com/in/mikanovskyNote: Any views mentioned in the podcast are the sole views of our hosts and guests, and do not represent the products mentioned in any way.Please leave us a review and feedback ⭐️⭐️⭐️⭐️⭐️

Lovable leaps to $6.6B on $330M wings for no-expertise app building. Supabase backend pairs perfectly. Enterprise ARR ramps.Get the top 40+ AI Models for $20 at AI Box: ⁠⁠https://aibox.aiAI Chat YouTube Channel: https://www.youtube.com/@JaedenSchaferJoin my AI Hustle Community: https://www.skool.com/aihustleSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

AGENDA: 04:20 Thrive and OpenAI Partnership  07:14 Databricks Raising $5BN at $134BN Valuation: Cheap or Not? 17:39 Eventbrite Acquired by Bending Spoons for $500M 21:39 Pagerduty's $1BN Market Cap, Just 2x Revenue 26:59 The TAM Trap: Why SaaS Is Like Japan 37:42 Lessons from Companies Hitting $100M ARR 44:57 The Future of Labour Markets is F****** 52:10 The Importance of Compounding in Investments 56:45 The Relevance Game in Venture Capital 01:05:01 Supabase at $5BN or Lovable at $6BN: Which One?  

In this episode, Prashant Sridharan, Head of Product Marketing at Supabase, joins Louise Liu to share insights on building trust and winning with developer marketing—from feature‑first messaging and PLG strategies to aligning product, DevRel, and marketing for go‑to‑market success. Prashant also discusses why transparency beats hype and how AI is reshaping the way product marketers work.For more information on AI and product marketing workflows, read Prashant Sridharan's article “How I Use Claude To Build Launch Plans From Chaos“.All rights reserved. © Product Marketing Hive.

In this episode, Prashant Sridharan, Head of Product Marketing at Supabase, joins Louise Liu to share insights on building trust and winning with developer marketing—from feature‑first messaging and PLG strategies to aligning product, DevRel, and marketing for go‑to‑market success. Prashant also discusses why transparency beats hype and how AI is reshaping the way product marketers work.For more information on AI and product marketing workflows, read Prashant Sridharan's article “How I Use Claude To Build Launch Plans From Chaos“.All rights reserved. © Product Marketing Hive.

In this episode, Aydin sits down with Ryan McCready, who went from hating AI to becoming one of the most creative AI-powered content builders on the internet. After getting laid off in mid-2025, Ryan realized that every job interview demanded AI fluency. So he went all-in, teaching himself Zapier, Lovable, Supabase, and advanced prompting to engineer a “Content Factory” that turns a webinar into blog posts, clips, and social content in minutes.He shares the mindset shift from “AI is plagiarism” to “AI is an input-output engine,” why content engineering is the future, what makes AI workflows actually work, and how breaking big tasks into many small steps is the secret to non-sloppy AI content.You'll see how he built a 30-step Zapier workflow that analyzes a webinar transcript, extracts frameworks and insights, turns them into pitches, builds outlines, writes social posts, and even generates clip candidates for Descript. If you create content or run marketing—this one is a masterclass.Timestamps0:23.00 – Why he believed AI was a “plagiarism machine”2:04.00 – Getting laid off and realizing every employer wanted AI skills4:37.00 – The workflow that kickstarted his learning (LinkedIn voice extraction + employee advocacy shares)5:40.00 – Learning Lovable and Supabase by building real projects6:51.00 – Why “everyone is a builder now” because of AI tools7:52.00 – Introducing “Content Engineering” and why most marketers can't do it9:03.00 – Example: turning a webinar into 10+ pieces of content10:58.00 – Why webinars usually die after they're aired—and why that's a waste11:43.00 – The “Webinar Content Flywheel” teaser16:30.00 – Why Ryan moved back from n8n to Zapier17:55.00 – Zapier vs. n8n: simplicity, stability, and architecture19:03.00 – “Start small”: a two-step Zap example20:09.00 – Interface demo: uploading a transcript and hitting “Go”21:22.00 – Why Zapier Interfaces make deployment easy22:40.00 – Step-by-step breakdown of the workflow24:06.00 – Example: webinar analysis output (themes, chapters, frameworks)27:02.00 – Creating three blog pitches from the transcript30:43.00 – Sending the pitches to Slack for review31:03.00 – Clip extraction workflow + Descript integration32:14.00 – How he uses Descript's “Underlord” to auto-cut clips33:20.00 – Why this beats automated clip tools like Riverside for B2B35:02.00 – Social content workflow (framework angle, data angle, hot take, wildcard)37:12.00 – Why prompting manually is wasteful—build once, automate forever40:11.00 – “Big → small → big” framework: the secret to non-sloppy AI content41:21.00 – Google's “AI content penalty” myth, according to Ryan42:47.00 – Why your input quality determines whether your AI output is good43:44.00 – What excites him most in the next 12 monthsTools & Technologies MentionedZapier: Automation platform used to chain 30+ steps together: analysis, pitch creation, clip extraction, social content, Notion updates, etc.AI by Zapier: Zapier's built-in LLM module used for analysis, extraction, outline generation, and writing.n8n: Open-source workflow automation platform. Ryan tested it, but ultimately moved back to Zapier for stability and structure.Lovable: AI-enabled “vibe coding” tool that turns prompts into functional web apps.Supabase: A database + backend platform used for storing structured content data from builds.Descript (Underlord): Video editing tool with an AI agent that cuts clips based on transcript timecodes generated by the workflow.Notion: Used as the source of truth for storing transcripts, outlines, clip docs, and the full content tracker.Claude / ChatGPT: Used for second-pass expansion—turning outlines or social angles into fully polished blog posts and posts.Fellow.ai: AI meeting assistant—summarizes meetings, tracks decisions, and generates insights and performance summaries.Subscribe at⁠ thisnewway.com⁠ to get the step-by-step playbooks, tools, and workflows.

In this episode, Katerina Skroumpelou joins us to talk all things Supabase — from what it is and how it simplifies life for everyday developers to why Angular devs are starting to love it. We chat about real-world use cases, security best practices, and how Katerina keeps learning new tools with confidence and curiosity. She also opens up about standing out in a tough job market and the mindset that got her where she is today — no “auth” required.https://supabase.com/docs/guides/getting-started/tutorials/with-angularMore about Katerina:https://twitter.com/psybercityhttps://bsky.app/profile/psyber.cityhttps://github.com/mandarinihttps://psyber.city/https://github.com/supabase/supabase-jsFollow us on X: The Angular Plus ShowBluesky: @theangularplusshow.bsky.social  The Angular Plus Show is a part of ng-conf. ng-conf is a multi-day Angular conference focused on delivering the highest quality training in the Angular JavaScript framework. Developers from across the globe converge  every year to attend talks and workshops by the Angular team and community experts.JoinAttendXBluesky        ReadWatchEdited by Patrick HayesStock media provided by JUQBOXMUSIC/ Pond5

Our 223st episode with a summary and discussion of last week's big AI news!Recorded on 10/17/2025Hosted by Andrey Kurenkov and co-hosted by Erik SchnultzFeel free to email us your questions and feedback at contact@lastweekinai.com and/or hello@gladstone.aiRead out our text newsletter and comment on the podcast at https://lastweekin.ai/In this episode:Anthropic and OpenAI have announced updates to their AI models and tools, including Haiku 4.5 and various business collaborations.Multiple companies like Slack and Salesforce are integrating AI assistants and agents into their platforms, enhancing task management and business operations.Recent research in reinforcement learning and agent memory curation highlights new methods for improving AI model performance and context management.California has passed a law to regulate AI chatbots for children and vulnerable users, and there are rising concerns over the increasing amount of AI-generated content on the internet.Timestamps:(00:00:10) Intro / Banter(00:01:31) News PreviewTools & Apps(00:02:18) Anthropic launches new version of scaled-down ‘Haiku' model(00:04:52) Everything OpenAI announced at DevDay 2025: Agent Kit, Apps SDK, ChatGPT, and more | ZDNET(00:09:11) Anthropic turns to ‘skills' to make Claude more useful at work | The Verge(00:13:20) Microsoft launches ‘vibe working' in Excel and Word | The Verge(00:17:22) Google releases Veo 3.1, adds it to Flow video editor | TechCrunch(00:19:40) Slack is turning Slackbot into an AI assistant | The Verge(00:22:52) Salesforce announces Agentforce 360 as enterprise AI competition heats up | TechCrunchApplications & Business(00:24:58) Broadcom stock pops 9% on OpenAI custom chip deal, adding to Nvidia and AMD agreements(00:27:58) How ByteDance Made China's Most Popular AI Chatbot | WIRED(00:30:08) Amazon's Zoox Robotaxis Have Arrived In Las Vegas - Here's What Riders Are Experiencing(00:32:43) Waymo's robotaxis are coming to London | The Verge(00:34:14) Reflection AI raises $2B to be America's open frontier AI lab, challenging DeepSeek | TechCrunch(00:35:58) General Intuition lands $134M seed to teach agents spatial reasoning using video game clips | TechCrunch(00:38:36) Supabase nabs $5B valuation, four months after hitting $2B | TechCrunchProjects & Open Source(00:40:58) Neuphonic Open-Sources NeuTTS Air: A 748M-Parameter On-Device Speech Language Model with Instant Voice Cloning - MarkTechPost(00:43:06) Anthropic AI Releases Petri: An Open-Source Framework for Automated Auditing by Using AI Agents to Test the Behaviors of Target Models on Diverse Scenarios - MarkTechPostResearch & Advancements(00:44:25) [2510.13786] The Art of Scaling Reinforcement Learning Compute for LLMs(00:48:51) [2510.01171] Verbalized Sampling: How to Mitigate Mode Collapse and Unlock LLM Diversity(00:51:22) [2510.12635] Memory as Action: Autonomous Context Curation for Long-Horizon Agentic Tasks(00:54:31) [2510.07364] Base Models Know How to Reason, Thinking Models Learn When(00:57:24) [2510.12402] Cautious Weight DecayPolicy & Safety(01:02:03) California becomes first state to regulate AI companion chatbots | TechCrunch(01:04:13) Over 50 Percent of the Internet Is Now AI Slop, New Data FindsSynthetic Media & Art(01:06:31) OpenAI Reverses Stance on Use of Copyright Works in Sora - WSJ(01:08:29) Character.AI removes Disney characters from platform after studio issues warningSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

AGENDA:  03:29 OpenAI and AMD's Major Partnership 07:35 Microsoft Have F***** Up the OpenAI Partnership  17:08 OpenAI's Developer Day Announcements 20:45 Why VC is the Most Forgiving Asset Class on Price and Valuation 29:10 What Does it Take to IPO in 2025: Why Snyk Will Not IPO 42:30 Four Strategies Companies Need to Take to Own Their Own Destiny 49:31 Vercel Raises $300M at $9BN: Suicide Round or Strategic 55:39 Does King Making Really Work in Venture Capital: Legora vs Harvey 01:08:11 Chamath Raises Latest SPAC: SPACs are Back 01:10:56 Polymarket Raises $2BN at a $9BN Valuation 01:14:53 Quick Fire Questions and Wrap-Up  

In the episode, we sat down with ClickHouse Co-Founder Yury Izrailevsky to unpack how one of the fastest open-source databases in the world became the analytics engine of choice for 2,000 customers including Harvey, Canva, HP, and Supabase. From its Yandex origins to powering AI observability, Yury shares how ClickHouse balances open-source roots, cloud innovation, and a remote-first culture moving at breakneck speed.ClickHouse's Series C valued the company at $6.35B earlier this year, and just yesterday they announced an extension to that round, just months after it was raised. In this episode, we dig into:Origins & Founding StoryClickHouse began as an internal project at Yandex to power a Google Analytics–style platform, focused on performance and scale.Open-sourced in 2016 - rapid global adoption laid the foundation for ClickHouse the company. Yury first discovered ClickHouse while at Google; impressed by its speed, he later co-founded the company in 2021 alongside Aaron Katz (ex-Elastic) and the original creator Alexey Milovidov.Why ClickHouse Stands OutColumn-oriented, open source OLAP database designed for massive-scale analytical processing.Excels in performance, efficiency, and cost - ideal for large data volumes and real-time analytics (and now AI workloads). Architectural choices:Columnar storage = better compression and faster execution.Separation of compute and storage enables elasticity, scalability, and resilience in the cloud.Open Source vs. CloudOpen-source version offers freedom and flexibility.Cloud product delivers much lower total cost of ownership and fully managed experience.Architectural parity between the two ensuring no vendor lock-in for customers. Customers can run the same queries on both; most stay with cloud due to simplicity and cost efficiency.Use Cases & Ecosystem4 main use cases:Real-time analyticsData WarehousingObservability AI / ML WorkloadsCompany Building & CultureFully remote from day one.Prioritized experienced, self-sufficient engineers over early-career hires.Built and launched GA version in less than a year - insane pace of innovation.Innovation & CommunityMonthly release cadence.Hundreds of integrations and connectors.Strong open-source and commercial communityAdvice for FoundersFocus on what matters most Hire mature, independent thinkers.Move fast but maintain quality; ClickHouse Cloud achieved production-grade quality in record time.

```html join wall-e for today's tech briefing on monday, october 6th, as we explore the latest tech dynamics: openai's strategic acqui-hire: acquisition of roi, a pioneering ai-driven personal finance app, with only ceo sujith vishwajith joining. highlights openai's pivot towards personalized ai solutions and is spearheaded by former instacart ceo fidji simo. anticipation for openai devday 2025: a major event featuring over 1,500 attendees, discussions between ceo sam altman and apple's jony ive, and potential ai product launches that may reshape consumer tech. sora app's rapid ascent: openai's invite-only ai video app achieves top spot on apple's u.s. app store, surpassing competitors like google's gemini, showcasing high demand for new ai tools. supabase's impressive growth: open-source database service hits a $5 billion valuation following a $100 million series e round, driven by demand for scalable solutions in tech ecosystems. naveen rao's new venture: former databricks ai head launches unconventional, inc., aiming for a $5 billion valuation with backing from andreessen horowitz, set to revolutionize ai computing and challenge nvidia. tune in tomorrow for more tech insights! ```

Welcome to First Block, a Notion series where founders from the world's leading companies tell us what it was like to navigate the many firsts of their startup journey—and what they learned from that experience.In this episode, we spoke with Ant Wilson, Co-Founder and CTO of Supabase. Supabase is the Postgres development platform that has become one of the world's fastest growing open source communities.Ant shares his journey about previous founder experiences, the power of solving your own problem, and why building authentic relationships with your community matters.Chapters:00:00 Intro02:56 Supabase Explained07:04 The Positioning Shift09:25 Memes & Marketing13:08 Scaling the Community15:09 Winning Enterprises17:09 Remote-First Culture22:49 AI in Action26:10 Advice BlockFor video, transcripts, and custom Notion Mercor templates, please visit: https://ntn.so/aow225To learn more about how Notion is supporting startups, please visit: ⁠https://ntn.so/cwep6x

Want to build your own apps with AI? Get the prompts here: https://clickhubspot.com/gfb Episode 75: What if you could turn your app idea into a fully functional web application—without writing a single line of code—in under 60 seconds? Nathan Lands (https://x.com/NathanLands) welcomes Eric Simons (https://x.com/ericsimons), co-founder of Bolt, one of the hottest AI startups revolutionizing how apps are built. In this episode, Eric reveals how Bolt makes it possible for anyone, regardless of technical skill, to go from idea to live, production-ready web or mobile apps—complete with authentication, databases, and hosting. He shares Bolt's unique approach that enables rapid prototyping, real business-grade deployments, and makes high-fidelity MVPs accessible to entrepreneurs, product managers, and non-coders everywhere. The conversation covers Bolt's founding story, its growth, and details from their record-breaking hackathon that empowered 130,000+ makers. Check out The Next Wave YouTube Channel if you want to see Matt and Nathan on screen: https://lnk.to/thenextwavepd — Show Notes: (00:00) High Fidelity Prototyping Essentials (04:32) Revolutionary Prototyping and Collaboration Tool (06:33) Rapid Prototyping Tool Focus (11:35) Empowering Non-Tech Entrepreneurs (13:34) Fast MVP Development with Bolt (18:19) AI-Powered Personalized Weight Coach (22:10) Launching Stackblitz: Web IDE Vision (22:48) Browser-Based Dev Environments Revolution (28:05) Advancements in Coding and AI (29:28) Critical Thinking in AI Development (34:08) Teaching Kids Future Skills (37:05) Bay Area's Autonomous Transport Future — Mentions: Eric Simons: ​​https://www.linkedin.com/in/eric-simons-a464a664/ Bolt: https://bolt.new/ Figma: https://www.figma.com/ Netlify: https://www.netlify.com/ Supabase: https://supabase.com/ Cursor: https://cursor.com/ Lovable: https://lovable.dev/ Get the guide to build your own Custom GPT: https://clickhubspot.com/tnw — Check Out Matt's Stuff: • Future Tools - https://futuretools.beehiiv.com/ • Blog - https://www.mattwolfe.com/ • YouTube- https://www.youtube.com/@mreflow — Check Out Nathan's Stuff: Newsletter: https://news.lore.com/ Blog - https://lore.com/ The Next Wave is a HubSpot Original Podcast // Brought to you by Hubspot Media // Production by Darren Clarke // Editing by Ezra Bakker Trupiano

Nik and Michael discuss when not to use Postgres — specifically use cases where it still makes sense to store data in another system. Here are some links to things they mentioned:Just use Postgres (blog post by Ethan McCue) https://mccue.dev/pages/8-16-24-just-use-postgresJust Use Postgres for Everything (blog post by Stephan Schmidt) https://www.amazingcto.com/postgres-for-everythingReal-time analytics episode https://postgres.fm/episodes/real-time-analyticsCrunchy Data Joins Snowflake https://www.crunchydata.com/blog/crunchy-data-joins-snowflakeTwo sizes fit most: PostgreSQL and Clickhouse (blog post by Sid Sijbrandij) https://about.gitlab.com/blog/two-sizes-fit-most-postgresql-and-clickhousepg_duckdb episode https://postgres.fm/episodes/pg_duckdbCloudberry https://github.com/apache/cloudberryTime-series considerations episode https://postgres.fm/episodes/time-series-considerationsQueues in Postgres episode https://postgres.fm/episodes/queues-in-postgresLarge Objects https://www.postgresql.org/docs/current/largeobjects.html PGlite https://pglite.devParadeDB https://www.paradedb.comZomboDB https://github.com/zombodb/zombodbturbopuffer https://turbopuffer.comHNSW vs. DiskANN (blog post by Haziqa Sajid) https://www.tigerdata.com/learn/hnsw-vs-diskannSPANN: Highly-efficient Billion-scale Approximate Nearest Neighbor Search (paper) https://www.microsoft.com/en-us/research/wp-content/uploads/2021/11/SPANN_finalversion1.pdfAmazon S3 Vectors https://aws.amazon.com/s3/features/vectorsIterative Index Scans added to pgvector in 0.8.0 https://github.com/pgvector/pgvector/issues/678S3 FDW from Supabase https://github.com/supabase/wrappers/tree/main/wrappers/src/fdw/s3_fdw~~~What did you like or not like? What should we discuss next time? Let us know via a YouTube comment, on social media, or by commenting on our Google doc!~~~Postgres FM is produced by:Michael Christofides, founder of pgMustardNikolay Samokhvalov, founder of Postgres.aiWith credit to:Jessie Draws for the elephant artwork

Reuniting after more than a decade since their days in This Week in Asia Podcast from 2009, Michael Smith Jr., co-host of The Generalist podcast, and Daniel Cerventus Lim, semi-retired entrepreneur and community builder in Malaysia, join us for a candid assessment of Southeast Asia's tech ecosystem evolution. In this raw conversation, Michael offers his unflinching perspective on what he calls the 'broken windows era' of Southeast Asian tech, arguing that recent alleged fraud cases like E-Fishery and Tanihub require serious consequences to restore investor confidence, while questioning whether the region was ever correctly modelled for Silicon Valley-style outcomes. Daniel shares his pivot from startup founder to search fund advocate, explaining his bullish view on acquiring profitable traditional businesses and reflects on whether the region's potential was genuinely unrealized or simply impossible to achieve. Together, they explore the shift from venture-backed unicorn dreams to bootstrap realities, debate work ethic of Southeast Asia founders in comparison with Chinese and Indian founders, and discuss why the future of Southeast Asian tech may lie in smaller, profitable exits rather than the massive IPOs once envisioned. "I think wealth creation here is very SME-focused." - Daniel Cerventus Lim "Basically whether, it's SME or startup, to me now it's just: can you build a profitable business?" - Bernard Leong "I have this philosophy that I think people don't agree with me, but we're in a broken Windows era of Southeast Asia and the only way in my opinion, the windows get fixed is if some of these people are behind bars." - Michael Smith Jr. Episode Highlights: [00:00] Quote of the Day by Daniel Cerventus, Bernard Leong & Michael Smith JR [00:59] Introduction: Daniel Cerventus and Michael Smith Jr. from the Generalists Podcast [06:00] Multiple alleged frauds in Southeast Asia: E-Fishery, Tanihub [09:57] Southeast Asia in "broken windows era" [11:26] Only exits from seed to Series A [11:47] B rounds virtually gone, A rounds endangered. [14:00] 50-100 million exits still viable [16:30] Malaysian crypto companies globally focused [19:25] Country expansion model in ASEAN doesn't work [23:02] Israel model: never think local market [24:15] Razer story: HP Mafia network backing [25:07] Supabase: not really Singapore capital, but globally successful [30:18] Chinese founders arriving with speed [31:19] Work ethic comparisons with India [32:34] Search funds emerging in Singapore [37:25] Mainstream media ignores bootstrap success [39:50] Search fund model targeting aging operators [41:21] SME vs startup distinction blurring [46:20] Hedge funds questioning regional companies [49:32] Unrealized vs impossible potential debate [51:07] Bangladesh ecosystem showing promise [53:20] Structural exit issues remain unsolved [54:31] Reset creating better founder discipline [55:40] Optimistic on Southeast Asia's startup ecosystem [57:21] Closing Profile: Michael Smith Jr., Tech Evangelist from Oracle & Co-Host, LinkedIn: https://www.linkedin.com/in/smittysgp/ YouTube: https://www.youtube.com/@TheGeneralistsPodcast   Daniel Cerventus Lim, semi-retired entrepreneur, Community Builder in Malaysia and TEDxKL founder. LinkedIn: https://www.linkedin.com/in/cerventus/ Facebook: https://www.facebook.com/groups/80164351656   Podcast Information: Bernard Leong hosts and produces the show. The proper credits for the intro and end music are "Energetic Sports Drive." G. Thomas Craig mixed and edited the episode in both video and audio format. Here are the links to watch or listen to our podcast. Analyse Asia Main Site: https://analyse.asia Analyse Asia Spotify: https://open.spotify.com/show/1kkRwzRZa4JCICr2vm0vGl Analyse Asia Apple Podcasts: https://podcasts.apple.com/us/podcast/analyse-asia-with-bernard-leong/id914868245 Analyse Asia LinkedIn: https://www.linkedin.com/company/analyse-asia/ Analyse Asia X (formerly known as Twitter): https://twitter.com/analyseasia Sign Up for Our This Week in Asia Newsletter: https://www.analyse.asia/#/portal/signup Subscribe Newsletter on LinkedIn https://www.linkedin.com/build-relation/newsletter-follow?entityUrn=7149559878934540288

Want better results from AI tools? Get the Advanced Prompt Engineering guide: https://clickhubspot.com/mgv Episode 71: What if you could turn your Figma designs into fully functioning apps—just by asking? Host Nathan Lands (https://x.com/NathanLands) is joined by David Kossnick (https://x.com/DKossnick), a key leader at Figma working on the cutting edge of AI-powered design tools. David is part of the team behind Figma Make, Figma's groundbreaking new tool that takes your sketches, mockups, or even simple prompts and instantly transforms them into interactive, code-backed applications. In this episode, David demonstrates how Figma Make builds real apps—like dashboards, games, and data-powered prototypes—right before your eyes. The discussion goes deep into Figma's AI journey: from their first AI-powered features to the vision for democratizing software creation in a truly collaborative, multiplayer environment. Whether you're a designer, entrepreneur, or just someone with big ideas, this episode is a glimpse into the AI-native future of how products will be built. Check out The Next Wave YouTube Channel if you want to see Matt and Nathan on screen: https://lnk.to/thenextwavepd — Show Notes: (00:00) Multiplayer Code-Generating Dashboard Tool (04:29) Collaborative Project Creation with Supabase (09:29) Prompt Management Overview (10:46) Emerging Interactive Design Space (14:57) Designing with AI: Complement, Not Replace (18:24) Figma: A Collaborative Design Hub (22:42) Empowering Designers with New Superpowers (25:35) Future of Design and Innovation (28:37) AI's Impact on Future Society (29:48) AI's Future in Healthcare (33:19) Figma AI's Exciting Future — Mentions: David Kossnick: https://www.linkedin.com/in/davidkossnick Figma: https://www.figma.com/ Figma Make: https://www.figma.com/make/ Supabase: https://supabase.com/ Claude: https://claude.ai/ Waymo: https://waymo.com/ Duolingo: https://www.duolingo.com/ Get the guide to build your own Custom GPT: https://clickhubspot.com/tnw — Check Out Matt's Stuff: • Future Tools - https://futuretools.beehiiv.com/ • Blog - https://www.mattwolfe.com/ • YouTube- https://www.youtube.com/@mreflow — Check Out Nathan's Stuff: Newsletter: https://news.lore.com/ Blog - https://lore.com/ The Next Wave is a HubSpot Original Podcast // Brought to you by Hubspot Media // Production by Darren Clarke // Editing by Ezra Bakker Trupiano

Alex Lee joins the show to walk us through an end-to-end automated newsletter generator built using N8N, Airtable, and generative AI. From aggregating news and generating summaries to crafting branded HTML and distributing it via email, Alex shows how businesses can reduce newsletter production from 6 hours to 30 minutes. He also shares how Model Context Protocol (MCP) is enabling real-time access to company data, explains his decision-making process between using workflow automation tools vs. vibe coding, and previews what's next in AI-powered business automation.Timestamps:00:23 – Welcome Alex Lee: Career journey from SAP to Google to AI consulting01:31 – How ChatGPT changed his mind about NLP02:38 – Why Alex is focused on AI enablement for businesses03:36 – Use case #1: AI-powered newsletter generator04:49 – The manual pain of newsletter creation06:12 – Why email is the best owned marketing channel07:25 – Step-by-step demo: Aggregating articles, adding context, and generating drafts09:09 – Human-in-the-loop editing and brand tone tuning10:01 – HTML generation and branded email output11:03 – Use cases beyond marketing: Internal custom newsletters15:26 – Why Airtable powers the backend of the workflow17:27 – Behind the scenes: N8N automation workflow overview20:26 – Tool selection: When to use N8N vs. Zapier vs. Make21:49 – Hosting your own N8N instance for cost efficiency24:04 – How clients send the generated newsletter (Mailchimp, HubSpot, EasyMail)27:12 – Vibe coding vs. workflow automation: which path to choose?28:41 – Why Lovable stands out among V0, Replit, Cursor30:19 – Benefits of prototyping and vibe coding for non-technical folks31:24 – What is MCP and why it matters33:05 – Example: Using Claude + MCP to search Google Drive and draft an executive summary38:59 – AI-powered time tracking via calendar and file analysis40:58 – What's next: legacy system integration, coding agents, MCP standardization42:39 – How to contact AlexTools and Technologies Mentioned:N8N – Open-source workflow automation platform used to orchestrate the newsletter processAirtable – Serves as the data layer and user interface for non-technical usersClaude (Anthropic) – Used for summarization, HTML generation, and MCP interactionMCP (Model Context Protocol) – Enables AI models to access external systems like Drive and calendars in real timeZapier, Make – Workflow automation tools considered depending on client preferenceLovable – No-code/low-code app builder that successfully integrates with Supabase and OpenAIHubSpot, Mailchimp, EasyMail – Email service providers used to distribute the newslettersSupabase – Backend database often used in vibe-coded appsSubscribe at⁠ thisnewway.com⁠ to get the step-by-step playbooks, tools, and workflows.

Lukas Mathis tells us to stop uploading our data to Google, Robert Vitonsky wants web devs to not guess his language using his IP, Tom from GameTorch reminds us that software talent is gold right now, Austin Parker from Honeycomb describes how LLMs are upending the observability industry, and Vitess co-creator, Sugu Sougoumarane, joins Supabase to lead their Multigres effort to bring Vitess to Postgres.

Episode 714: Shaan Puri ( https://x.com/ShaanVP ) sits down with Matt Mazzeo ( https://x.com/Mazzeo ) about using AI agents as your go-to-market.  — Show Notes: (0:00) Intro  (3:30) AI as the Go-to-Market (8:50) The Billion Dollar Secret  (12:03) Mario Kart Theory (18:55) Being a Tinkerer/Supabase (25:38) Amjad Masad/Replt (28: 41) Taste (36:44) Agents replacing VCs (37:57) Agent Employees (42:28) Story Game — Links: • Want Sam's guide to use ChatGPT? Get it here: https://clickhubspot.com/wpv • Supabase - https://supabase.com/  • Replit - https://replit.com/  • Clay - https://www.clay.com/  • Alpha Go Movie - https://www.youtube.com/watch?v=WXuK6gekU1Y  — Check Out Shaan's Stuff: • Shaan's weekly email - https://www.shaanpuri.com  • Visit https://www.somewhere.com/mfm to hire worldwide talent like Shaan and get $500 off for being an MFM listener. Hire developers, assistants, marketing pros, sales teams and more for 80% less than US equivalents. • Mercury - Need a bank for your company? Go check out Mercury (mercury.com). Shaan uses it for all of his companies! Mercury is a financial technology company, not an FDIC-insured bank. Banking services provided by Choice Financial Group, Column, N.A., and Evolve Bank & Trust, Members FDIC

For the full experience, watch this episode on YouTube: https://www.youtube.com/watch?v=d0j_n3OOM7c Episode 712: Sam Parr ( https://x.com/theSamParr ) talks to Greg Isenberg ( https://x.com/gregisenberg ) talk about how to find a startup idea and build it in a couple hours using AI.  — Show Notes: (0:00) Step 1: Find an idea (7:57) Step 2: Sketch out the idea (9:48) Step 3: Scope out the MVP (18:25) Step 4: Vibe code a prototype (36:06) Step 5: Vibe marketing the business (49:14) Step 6: AI agent product manager — Links: • Want Greg's guide to Build an AI Startup in 3 Hours with

Rahul Vohra is the founder and CEO of Superhuman. Prior to Superhuman, Rahul founded Rapportive, the first Gmail plug-in to scale to millions of users, which he sold to LinkedIn in 2012. He is also a prominent angel investor, and his fund has invested $50 million in over 120 companies, including Placer, Supabase, Mercury, Zip, ClassDojo, and Writer.What you'll learn:• The unexpected insight about virality Rahul gained from LinkedIn's head of growth.• Why Rahul restructured his entire executive team to spend 60% to 70% of his time on product, design, and marketing instead of the typical CEO responsibilities.• The counterintuitive approach to finding product-market fit using a methodical system inspired by Sean Ellis, and how this algorithmically determines your roadmap.• How manually onboarding every user (Superhuman had 20 full-time people doing this at peak) created superfans and allowed engineers to focus on product rather than onboarding flows.• The “Single Decisive Reason” framework for making better decisions by avoiding collections of weak justifications.• How Superhuman's AI features have evolved to create a truly intelligent email experience that works while you sleep.—Brought to you by:• Eppo—Run reliable, impactful experiments• Fundrise Flagship Fund—Invest in $1.1 billion of real estate• OneSchema—Import CSV data 10x faster—Find the transcript at: https://www.lennysnewsletter.com/p/superhumans-secret-to-success-rahul-vohra—Where to find Rahul Vohra:• X: https://x.com/rahulvohra• LinkedIn: https://www.linkedin.com/in/rahulvohra/• Email: Rahul@superhuman.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 Rahul and Superhuman(05:00) The most pivotal moment in Rahul's career(07:01) The secret to virality(11:02) Superhuman's product evolution and core values(13:32) Overcoming slowdowns at scale(18:06) Time management and meditation(27:35) The role of a president(30:56) Attention to detail(43:00) Finding your unique position(47:32) The power of manual onboarding(52:37) Mastering product-market fit(59:33) Game design in business software(01:05:35) Contrarian pricing strategies(01:09:29) Leveraging AI(01:15:40) Transitioning to enterprise solutions(01:19:08) The Single Decisive Reason framework(01:22:32) Conclusion and final thoughts—Referenced:• Superhuman: https://superhuman.com/• Rapportive: https://techcrunch.com/2012/02/22/rapportive-linkedin-acquisition/• Elliot Shmukler on LinkedIn: https://www.linkedin.com/in/eshmu/• What Are ‘Whales' in Video Games: https://gamerant.com/video-games-whales-concept-term-explained/• Figma: https://www.figma.com/• Notion: https://www.notion.com/• Loom: https://www.loom.com/• How to use Team Comments to reimagine email collaboration: https://blog.superhuman.com/how-to-use-team-comments-to-reimagine-email-collaboration/• Rajiv Ayyangar's post on X about Superhuman: https://x.com/rajivayyangar/status/1816176308130570385• Transcendental Meditation: https://www.tm.org/• Laurent Valosek on LinkedIn: https://www.linkedin.com/in/laurent-valosek-18708b5a/• Peak Leadership Institute: https://www.peakleadershipinstitute.com/• Ed Sim's website: https://edsim.net/• Adelle Sans: https://fonts.adobe.com/fonts/adelle-sans• Comic Sans: https://en.wikipedia.org/wiki/Comic_Sans• Greenfield project: https://en.wikipedia.org/wiki/Greenfield_project• Why Mailbox died: https://www.theverge.com/2015/12/8/9873268/why-dropbox-mailbox-shutdown• Bill Trenchard on X: https://x.com/btrenchard• How Superhuman Built an Engine to Find Product-Market Fit: https://review.firstround.com/how-superhuman-built-an-engine-to-find-product-market-fit/• Using the Sean Ellis Test for Measuring Your Product-Market Fit: https://medium.productcoalition.com/using-sean-ellis-test-for-measuring-your-product-market-fit-c8ac98053c2c• Sean Ellis on LinkedIn: https://www.linkedin.com/in/seanellis/• The original growth hacker reveals his secrets | Sean Ellis (author of “Hacking Growth”): https://www.lennysnewsletter.com/p/the-original-growth-hacker-sean-ellis• The Trouble with Rewards: https://www.kornferry.com/insights/briefings-magazine/issue-13/519-the-trouble-with-rewards• The art and science of pricing | Madhavan Ramanujam (Monetizing Innovation, Simon-Kucher): https://www.lennysnewsletter.com/p/the-art-and-science-of-pricing-madhavan•  Van Westendorp Price Sensitivity Meter: https://en.wikipedia.org/wiki/Van_Westendorp%27s_Price_Sensitivity_Meter• AI-powered email for high-performing teams: https://superhuman.com/ai• 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• Single Decisive Reason: decision-making for fast-scaling startups: https://blog.superhuman.com/single-decisive-reason-decision-making-for-fast-scaling-startups/• Reid Hoffman on LinkedIn: https://www.linkedin.com/in/reidhoffman/—Recommended books:• Positioning: The Battle for Your Mind: https://www.amazon.com/Positioning-Battle-Your-Al-Ries/dp/0071373586• Monetizing Innovation: How Smart Companies Design the Product Around the Price: https://www.amazon.com/Monetizing-Innovation-Companies-Design-Product/dp/1119240867—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. Get full access to Lenny's Newsletter at www.lennysnewsletter.com/subscribe