Podcasts about Airtable

This episode explores the ongoing genealogical project to identify the biological father of Cynthia (Dillard) Royston, an ancestor who remains a mystery after years of research. Diana and Nicole focus on the fifth phase of this investigation, which involves utilizing DNA and documentary evidence to connect Cynthia to potential candidates among the Dillard men who drew lots in the 1832 Georgia Gold Lottery. Diana explains how she organizes this project using Airtable to track timelines and research logs while eliminating data duplication. She also shares her strategies for managing and selecting records, such as census data from 1840 to 1880, to establish a baseline for Cynthia's birth between 1815 and 1818.  Listeners learn about the practical application of locality research in genealogy as Diana investigates the counties associated with the Dillard candidates. She contrasts the availability of records in Pulaski and Oglethorpe counties, which have extant records and no major courthouse disasters, with the challenges of Burke County, where fires destroyed many documents. Diana describes how she uses the FamilySearch Wiki and 1832 maps to contextualize the migration of these men relative to Cass County. By walking through her research process, the hosts demonstrate how to combine timeline creation, map analysis, and targeted locality research to build a strategy for complex DNA projects. This summary was generated by Google Gemini. Links Finding a Father for Cynthia: Phase 5 – Part 2: Timeline and Locality Research - https://familylocket.com/finding-a-father-for-cynthia-phase-5-part-2-timeline-and-locality-research/ Sponsor – Newspapers.com For listeners of this podcast, Newspapers.com is offering new subscribers 20% off a Publisher Extra subscription so you can start exploring today. Just use the code "FamilyLocket" at checkout.  Research Like a Pro Resources Airtable Universe - Nicole's Airtable Templates - https://www.airtable.com/universe/creator/usrsBSDhwHyLNnP4O/nicole-dyer Airtable Research Logs Quick Reference - by Nicole Dyer - https://familylocket.com/product-tag/airtable/ Research Like a Pro: A Genealogist's Guide book by Diana Elder with Nicole Dyer on Amazon.com - https://amzn.to/2x0ku3d Research Like a Pro with AI Workbook – Second Edition (eBook) - https://familylocket.com/product/research-like-a-pro-with-ai-workbook-second-edition-ebook/ 14-Day Research Like a Pro Challenge Workbook - digital - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-digital-only/ and spiral bound - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-spiral-bound/ Research Like a Pro Webinar Series - monthly case study webinars including documentary evidence and many with DNA evidence - https://familylocket.com/product-category/webinars/ Research Like a Pro eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-e-course/ RLP Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-study-group/ Research Like a Pro Institute Courses - https://familylocket.com/product-category/institute-course/ Research Like a Pro with DNA Resources Research Like a Pro with DNA: A Genealogist's Guide to Finding and Confirming Ancestors with DNA Evidence book by Diana Elder, Nicole Dyer, and Robin Wirthlin - https://amzn.to/3gn0hKx Research Like a Pro with DNA eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-with-dna-ecourse/ RLP with DNA Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-with-dna-study-group/ Thank you Thanks for listening! We hope that you will share your thoughts about our podcast and help us out by doing the following: Write a review on iTunes or Apple Podcasts. If you leave a review, we will read it on the podcast and answer any questions that you bring up in your review. Thank you! Leave a comment in the comment or question in the comment section below. Share the episode on Twitter, Facebook, or Pinterest. Subscribe on iTunes or your favorite podcast app. Sign up for our newsletter to receive notifications of new episodes - https://familylocket.com/sign-up/ Check out this list of genealogy podcasts from Feedspot: Best Genealogy Podcasts - https://blog.feedspot.com/genealogy_podcasts/

276 | Airtable, das Rückgrat meines gesamten Business, wurde für ein Zehntel seines früheren Werts an Bending Spoons aus Italien verkauft, die mit dem Aufkaufen alternder Software zum Milliardenkonzern geworden ist. Ich erkläre, was hinter diesem Deal steckt, warum kein Unternehmen gleichzeitig alt und neu sein kann - und welche drei Geschäftsideen für dich daraus entstehen.Partner dieser Folge:PlaudRichtig gute Transkriptionen für Offline Meetings mit Plaud. Geh auf: https://de.plaud.ai/dpt10% Discount code: OPT10Mach das 1-minütige Quiz und finde eine Geschäftsidee, die zu dir passt: digitaleoptimisten.de/quiz. Mich erreichst du unter alexander@digitaleoptimisten.deKapitel(01:34) Airtable wurde verkauft – und was das über den Preis von Software verrät (05:23) Bending Spoons: das brutalste Geschäftsmodell im Software-Markt (11:04) Der versteckte Teil des Deals (12:22) Warum keine Firma gleichzeitig alt und neu kann (19:46) Drei Geschäftsideen aus diesem DealSo erreichst du uns:Sprachnachricht senden: https://www.speakpipe.com/digitaleoptimistenEmail schreiben: alexander@digitaleoptimisten.de

Kamille Parks demonstrates how to use the Model Context Protocol (MCP) to manage Airtable automations via Claude. She walks through updating an existing automation by adding placeholder email addresses to a notification step, showing how the AI can modify specific parameters while preserving existing context. The demo also covers management tasks like deleting an automation and using the "undo" feature to revert actions. By leveraging action IDs tracked through the MCP, the AI can effectively restore what was previously deleted. Finally, the segment explores creating new scheduled automations from scratch and exporting all base automations as JSON for auditing and configuration reviews. ⏱ In this cut: 01:58 — Updating an existing automation 06:52 — Deleting and undoing actions 08:36 — Creating new scheduled automations 16:11 — Exporting automations as JSON

A very special edition of More or Less, featuring Josh Wolfe (Founder, Lux Capital), Rachel Holt (Founder, Construct Capital; former Head of North America at Uber), Scott Belsky (Partner, A24; Founder, Behance), Scott Stanford (Founder, Acme Capital), and Peter Deng (GP, Felicis; formerly Google, Facebook, Instagram, Uber, Airtable, and OpenAI). Sam takes over hosting duties and assembles an overqualified group of investor friends to argue about where AI goes from here, from agents, Grok, Claude, and the shift from “help me do this” to “just do it,” to trust, data ownership, Apple's AI advantage, open vs. closed models, model routing, and why proprietary data may become the real moat. They also dig into NVIDIA's massive compute financing strategy, the risks of securitizing GPUs like long-lived infrastructure, what the OpenAI executive exodus says about the AI talent market, and the bigger question hanging over all of it: if AI really changes work, who actually participates in the upside?Chapters0:00 Episode trailer1:24 Episode start1:59 Meet the panel, every flavor of venture capital5:14 Consumer AI agents cross the Rubicon7:24 The end of websites, when agents talk to agents8:32 Which AI companies do you actually trust?11:41 Why Apple could win AI by doing nothing16:40 If models commoditize, unique data becomes the moat22:15 Open vs. closed AI, and who owns your data27:06 NVIDIA's balance sheet shenanigans31:26 NVIDIA gets the upside, who gets the risk?34:31 Nobody has ever securitized compute35:02 Who owns the wealth AI creates?39:38 What happens when economic opportunity runs out?42:23 Why OpenAI's best people keep leaving47:23 Why AI may look more like GPS than Facebook49:14 What actually happened with Airtable50:30 Lightning Round: Rachel Holt on physical-world investing53:00 Scott Belsky on AI watermarks, provenance & deepfakes54:15 Josh Wolfe on socialism, Europe & defense57:15 Final thoughts & sign-offWe're also on ↓X: https://twitter.com/moreorlesspodInstagram: https://instagram.com/moreorlessSpotify: https://podcasters.spotify.com/pod/show/moreorlesspodConnect with us here:1) Sam Lessin: https://x.com/lessin2) Dave Morin: https://x.com/davemorin3) Jessica Lessin: https://x.com/Jessicalessin4) Brit Morin: https://x.com/brit

גיא קצוביץ' מארח את עמית קרפ (Bessemer Venture Partners), ברק שוסטר (Battery Ventures) וינאי אורון (Vertex Ventures Israel) למהדורת מוסף בה ננתח את טלטלות השוק המשמעותיות ביותר של התקופה האחרונה. התחלנו עם הדרמה ב- Monday סביב חבילות התגמול של המנכ"לים, והמשכנו לסטארטאפ הישראלי Decart שגייס במאי האחרון 300 מיליון דולר, מה עומד מאחורי השמועות על הרכישה של ב-$6?השוונו את צמיחת הענק הזו להתרסקות השווי הכואבת של חברת Airtable, כדוגמה מובהקת לאיך מהפכת ה-AI פוגעת במכפילים של חברות תוכנה שלא מסתגלות מהר למציאות. לסיום, צללנו אל המגמה בה חברות משתמשות בשבבי אנבידיה כעירבון לקבלת הלוואות ענק להקמת חוות שרתים, והסברנו מדוע מחירי השכירות של כרטיסי מסך ישנים של החברה ממשיכים לזנק מעלה.(00:00) פתיחה ועדכונים(01:14) התגמולים בחברת מאנדיי(04:02) איך מתוגמלים מנכ"לים לקראת הנפקה?(13:25) מה עומד מאחורי השמועות על הרכישה של דקארט ב-$6(22:42) התרסקות השווי של Airtable(35:07) אפוקליפסת ה-SaaS ושינוי המכפילים בוול סטריט(47:09) שימוש בשבבי אנבידיה כעירבון להלוואות לחוות שרתים(51:27) שוק השבבים המשומשים: למה ה-GPU הוא הרולקס החדש?

Alli Alosa demonstrates how to use the 'Insert as JSON' feature in Airtable automations to reliably handle incoming data from external webhooks, such as Fillout. She explains why this method is more robust than traditional field mapping, especially when dealing with inconsistent data. The discussion covers a practical use case involving event feedback collection. By passing the entire payload as a JSON object, you can prevent automations from failing when certain form fields are left empty or missing from the payload. Finally, the team explores how to use this JSON data within a script action. Instead of manually mapping every individual field as an input, you can pass the entire object into a script, allowing for much more scalable and maintainable automation logic. ⏱ In this cut: 01:03 — Using feedback collection as a use case 12:38 — The benefits of using Insert as JSON 13:37 — Solving errors caused by empty field values 17:00 — Passing JSON data into a script action 25:09 — Conditional filters and advanced integrations

AGENDA: 05:00 Canva's Growth Gets Slashed as AI Costs Explode 20:00 The Great Software Reset: Why 2026 Will Punish AI Hesitancy 29:00 Canva's Valuation Reality Check—and the LP Liquidity Trap 35:00 Google's AI Brain Drain: Jeff Dean Leaves, Demis Steps Back 43:00 Why Google Can't Afford to Cure Alzheimer's 50:00 The Data-Centre Revolt: Can AI Survive the Political Backlash? 55:00 Elon Musk's $55BN Terrafab Bet to Break Free from TSMC 57:00 Revolut's $50BN CEO Pay Package—and the Return of Founder Control 01:13 AI Shopping, Atlassian's Revival, and Airtable's Brutal Sale Reality  

Connect with Early Riders — https://www.earlyriders.com/contactConnect with Onramp — https://onrampbitcoin.com/contact-us/Presented collaboratively by Early Riders & Onramp Media…Final Settlement is a weekly podcast covering capital markets, dealmaking, early-stage venture, bitcoin applications and protocol development.The CLARITY Act has slipped to a September 15 Senate vote, and Bitcoin did not move. This week Michael, Liam, and Brian make the case that stalled legislation on top of the Coldcard fallout, BIP-110 infighting, and Saylor selling, with the price still holding, is what a bottom looks like rather than a top. They run through a brutal week for Bitcoin infrastructure: BTCPay Server, Zeus, and Boltz all disclosing vulnerabilities or going dark, with Boltz warning that attackers now iterate faster than a team its size can patch. On the AI side they cover Kimi K3 escaping an isolated sandbox, Sam Altman's comments on Astra and who gets frontier access, an agent that cancelled a stranger's gym reservation to move its owner up the waitlist, and Cloudflare Wallets arriving as agent requests climb 1,700% and cross half of all network traffic. They close on the deals: Yellow Card's $40M round, Sapium's $35M Series A for the agent routing layer, Coinbase losing BVNK to Mastercard despite bidding $700M more, Airtable selling for $1.29B after an $11.7B peak, and what Block's Buzz did during the Coldcard incident.Chapters00:00 - Coldcard update: thefts slow, 2,000 BTC still gone01:00 - BTCPay Server, Zeus, and Boltz all disclose vulnerabilities02:51 - Why open source Bitcoin code became the target04:11 - Boltz: attackers now iterate faster than we can patch05:22 - Liam: Bitcoin itself is not the vulnerability06:40 - Good actors handicapped when US frontier models refuse10:04 - Sam Altman on Astra and keeping powerful models from the few11:12 - Only 2% of US households pay for AI13:34 - Kimi K3 escapes its isolated sandbox14:34 - Why non-deterministic models cannot be reliably contained19:35 - An agent cancels a stranger's gym reservation20:58 - Cloudflare Wallets and the programmable agentic internet23:45 - Agent traffic passes human traffic26:42 - ARK on Cloudflare's earnings: agent requests up 1,700%31:07 - Privy's CRM breach and the limits of mobile wallets32:13 - The CLARITY Act slips to September 1533:45 - Why stalled legislation plus a flat price looks like a bottom35:56 - Yellow Card raises $40M for African stablecoin rails37:40 - Sapium raises $35M for the AI agent routing layer40:14 - Coinbase bid $2.5B for BVNK and lost to Mastercard at $1.8B42:17 - Airtable sells for $1.29B after an $11.7B peak45:32 - The Architecture Problem and where custody goes next47:48 - Why every firm ends up at multi-institution custody49:22 - Buzz, Goose, and how Block moved in hours on Coldcard54:45 - GPU hours as crude oil: an open source AI analogy55:34 - Sergey Brin returns to Gemini, Meta ships Muse CodeIf you found this valuable, please subscribe to Early Riders Insights for access to the best content in the ecosystem weekly: https://www.earlyriders.com/researchKeep up with Michael:https://x.com/MTangumaKeep up with Liam:https://x.com/Lnelson_21Keep up with Brian:https://x.com/BackslashBTC

Justin cuts 4140 steel for the first time for PDX CNC products while Jem battles venomous spiders and pallet racking inspections. They discuss organizing shop kits with gridfinity bins, Airtable's uncertain future, local file storage versus cloud chaos, and surviving wildfire smoke. Plus: Christopher Nolan's massive IMAX camera and the eternal struggle of documentation.Watch on YoutubeDISCUSSED:✍️ Comment or Suggest a TopicSteel!Work SafeAirtable bought for 8x less than top valueSuper SmokyBig Summer Movie this summmmmerFU Assembly Bins - video?Google Search Console - Instagram, Tiktok, Youtube now!Tool-tags.com---Profit First PlaylistClassic Episodes Playlist---SUPPORT THE SHOWBecome a Patreon - Get the Secret ShowReview on Apple Podcast Share with a FriendDiscuss on Show SubredditShow InfoShow WebsiteContact Jem & JustinInstagram | Tiktok | Facebook | YoutubePlease note: Show notes contains affiliate links.HOSTSJem FreemanCastlemaine, Victoria, AustraliaLike Butter | Instagram | More LinksJustin BrouillettePortland, Oregon, USAPDX CNC | Instagram | More Links

Autonomous AIs are hacking, collaborating, and outpacing human defenders, raising urgent questions about what happens when the machines start breaking into each other (and potentially us). Plus, a Tucson coder is using AI to reinvent local journalism, exposing how automation could fill the gaps left by shrinking newsrooms. Tucson Daily Brief uses AI to revive local news coverage Data centers boom in Arizona, with harsh environmental impact Amazon's Texas data center to run on polluting natural gas Nuclear and solar debates for sustainable data center power Black Hat and DEF CON: Security pros, hackers, and mohawks OpenAI's runaway AI hack at Black Hat stuns security community AI agents collaborate, evade controls, and break into real-world systems Industry struggles to regulate AI, and defense lags behind automated attackers White House, Congress, and AI execs clash over regulation proposals AI "kill switch" and model bans: pipe dreams in a global race Google's DeepMind shakeup, Demis Hassabis moves upstairs Jeff Dean and key talent exit Google for self-improving AI startup Google, Meta, Apple: AI brain drain and market repercussions Phones stagnate as hardware innovation slows, AI devours chip supply OpenAI teams with Jony Ive on strange new AI-first device Smart glasses privacy backlash and DuckDuckGo's tongue-in-cheek sunglasses Meta fined $942 million by New Mexico court for youth harms Apple sues OpenAI over alleged stolen secrets, countersuits ensue UK revives "Snooper's Charter" for backdoors, Apple fights in secret court License plate readers spark local backlash and privacy activism U.S. water systems face cyber sabotage as critical infrastructure weakens Bending Spoons buys Airtable, fueling SaaS layoffs and AI data grabs Nicholas DeLeon uses AI tools to get fit NASA hacks keep aging Voyager probes alive for another year Host: Leo Laporte Guests: Iain Thomson and Nicholas De Leon Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: bitwarden.com/twit NetSuite.AI/TWIT ZipRecruiter.com/twit adaptivesecurity.com superhuman.com

Autonomous AIs are hacking, collaborating, and outpacing human defenders, raising urgent questions about what happens when the machines start breaking into each other (and potentially us). Plus, a Tucson coder is using AI to reinvent local journalism, exposing how automation could fill the gaps left by shrinking newsrooms. Tucson Daily Brief uses AI to revive local news coverage Data centers boom in Arizona, with harsh environmental impact Amazon's Texas data center to run on polluting natural gas Nuclear and solar debates for sustainable data center power Black Hat and DEF CON: Security pros, hackers, and mohawks OpenAI's runaway AI hack at Black Hat stuns security community AI agents collaborate, evade controls, and break into real-world systems Industry struggles to regulate AI, and defense lags behind automated attackers White House, Congress, and AI execs clash over regulation proposals AI "kill switch" and model bans: pipe dreams in a global race Google's DeepMind shakeup, Demis Hassabis moves upstairs Jeff Dean and key talent exit Google for self-improving AI startup Google, Meta, Apple: AI brain drain and market repercussions Phones stagnate as hardware innovation slows, AI devours chip supply OpenAI teams with Jony Ive on strange new AI-first device Smart glasses privacy backlash and DuckDuckGo's tongue-in-cheek sunglasses Meta fined $942 million by New Mexico court for youth harms Apple sues OpenAI over alleged stolen secrets, countersuits ensue UK revives "Snooper's Charter" for backdoors, Apple fights in secret court License plate readers spark local backlash and privacy activism U.S. water systems face cyber sabotage as critical infrastructure weakens Bending Spoons buys Airtable, fueling SaaS layoffs and AI data grabs Nicholas DeLeon uses AI tools to get fit NASA hacks keep aging Voyager probes alive for another year Host: Leo Laporte Guests: Iain Thomson and Nicholas De Leon Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: bitwarden.com/twit NetSuite.AI/TWIT ZipRecruiter.com/twit adaptivesecurity.com superhuman.com

Autonomous AIs are hacking, collaborating, and outpacing human defenders, raising urgent questions about what happens when the machines start breaking into each other (and potentially us). Plus, a Tucson coder is using AI to reinvent local journalism, exposing how automation could fill the gaps left by shrinking newsrooms. Tucson Daily Brief uses AI to revive local news coverage Data centers boom in Arizona, with harsh environmental impact Amazon's Texas data center to run on polluting natural gas Nuclear and solar debates for sustainable data center power Black Hat and DEF CON: Security pros, hackers, and mohawks OpenAI's runaway AI hack at Black Hat stuns security community AI agents collaborate, evade controls, and break into real-world systems Industry struggles to regulate AI, and defense lags behind automated attackers White House, Congress, and AI execs clash over regulation proposals AI "kill switch" and model bans: pipe dreams in a global race Google's DeepMind shakeup, Demis Hassabis moves upstairs Jeff Dean and key talent exit Google for self-improving AI startup Google, Meta, Apple: AI brain drain and market repercussions Phones stagnate as hardware innovation slows, AI devours chip supply OpenAI teams with Jony Ive on strange new AI-first device Smart glasses privacy backlash and DuckDuckGo's tongue-in-cheek sunglasses Meta fined $942 million by New Mexico court for youth harms Apple sues OpenAI over alleged stolen secrets, countersuits ensue UK revives "Snooper's Charter" for backdoors, Apple fights in secret court License plate readers spark local backlash and privacy activism U.S. water systems face cyber sabotage as critical infrastructure weakens Bending Spoons buys Airtable, fueling SaaS layoffs and AI data grabs Nicholas DeLeon uses AI tools to get fit NASA hacks keep aging Voyager probes alive for another year Host: Leo Laporte Guests: Iain Thomson and Nicholas De Leon Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: bitwarden.com/twit NetSuite.AI/TWIT ZipRecruiter.com/twit adaptivesecurity.com superhuman.com

Autonomous AIs are hacking, collaborating, and outpacing human defenders, raising urgent questions about what happens when the machines start breaking into each other (and potentially us). Plus, a Tucson coder is using AI to reinvent local journalism, exposing how automation could fill the gaps left by shrinking newsrooms. Tucson Daily Brief uses AI to revive local news coverage Data centers boom in Arizona, with harsh environmental impact Amazon's Texas data center to run on polluting natural gas Nuclear and solar debates for sustainable data center power Black Hat and DEF CON: Security pros, hackers, and mohawks OpenAI's runaway AI hack at Black Hat stuns security community AI agents collaborate, evade controls, and break into real-world systems Industry struggles to regulate AI, and defense lags behind automated attackers White House, Congress, and AI execs clash over regulation proposals AI "kill switch" and model bans: pipe dreams in a global race Google's DeepMind shakeup, Demis Hassabis moves upstairs Jeff Dean and key talent exit Google for self-improving AI startup Google, Meta, Apple: AI brain drain and market repercussions Phones stagnate as hardware innovation slows, AI devours chip supply OpenAI teams with Jony Ive on strange new AI-first device Smart glasses privacy backlash and DuckDuckGo's tongue-in-cheek sunglasses Meta fined $942 million by New Mexico court for youth harms Apple sues OpenAI over alleged stolen secrets, countersuits ensue UK revives "Snooper's Charter" for backdoors, Apple fights in secret court License plate readers spark local backlash and privacy activism U.S. water systems face cyber sabotage as critical infrastructure weakens Bending Spoons buys Airtable, fueling SaaS layoffs and AI data grabs Nicholas DeLeon uses AI tools to get fit NASA hacks keep aging Voyager probes alive for another year Host: Leo Laporte Guests: Iain Thomson and Nicholas De Leon Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: bitwarden.com/twit NetSuite.AI/TWIT ZipRecruiter.com/twit adaptivesecurity.com superhuman.com

Autonomous AIs are hacking, collaborating, and outpacing human defenders, raising urgent questions about what happens when the machines start breaking into each other (and potentially us). Plus, a Tucson coder is using AI to reinvent local journalism, exposing how automation could fill the gaps left by shrinking newsrooms. Tucson Daily Brief uses AI to revive local news coverage Data centers boom in Arizona, with harsh environmental impact Amazon's Texas data center to run on polluting natural gas Nuclear and solar debates for sustainable data center power Black Hat and DEF CON: Security pros, hackers, and mohawks OpenAI's runaway AI hack at Black Hat stuns security community AI agents collaborate, evade controls, and break into real-world systems Industry struggles to regulate AI, and defense lags behind automated attackers White House, Congress, and AI execs clash over regulation proposals AI "kill switch" and model bans: pipe dreams in a global race Google's DeepMind shakeup, Demis Hassabis moves upstairs Jeff Dean and key talent exit Google for self-improving AI startup Google, Meta, Apple: AI brain drain and market repercussions Phones stagnate as hardware innovation slows, AI devours chip supply OpenAI teams with Jony Ive on strange new AI-first device Smart glasses privacy backlash and DuckDuckGo's tongue-in-cheek sunglasses Meta fined $942 million by New Mexico court for youth harms Apple sues OpenAI over alleged stolen secrets, countersuits ensue UK revives "Snooper's Charter" for backdoors, Apple fights in secret court License plate readers spark local backlash and privacy activism U.S. water systems face cyber sabotage as critical infrastructure weakens Bending Spoons buys Airtable, fueling SaaS layoffs and AI data grabs Nicholas DeLeon uses AI tools to get fit NASA hacks keep aging Voyager probes alive for another year Host: Leo Laporte Guests: Iain Thomson and Nicholas De Leon Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: bitwarden.com/twit NetSuite.AI/TWIT ZipRecruiter.com/twit adaptivesecurity.com superhuman.com

Autonomous AIs are hacking, collaborating, and outpacing human defenders, raising urgent questions about what happens when the machines start breaking into each other (and potentially us). Plus, a Tucson coder is using AI to reinvent local journalism, exposing how automation could fill the gaps left by shrinking newsrooms. Tucson Daily Brief uses AI to revive local news coverage Data centers boom in Arizona, with harsh environmental impact Amazon's Texas data center to run on polluting natural gas Nuclear and solar debates for sustainable data center power Black Hat and DEF CON: Security pros, hackers, and mohawks OpenAI's runaway AI hack at Black Hat stuns security community AI agents collaborate, evade controls, and break into real-world systems Industry struggles to regulate AI, and defense lags behind automated attackers White House, Congress, and AI execs clash over regulation proposals AI "kill switch" and model bans: pipe dreams in a global race Google's DeepMind shakeup, Demis Hassabis moves upstairs Jeff Dean and key talent exit Google for self-improving AI startup Google, Meta, Apple: AI brain drain and market repercussions Phones stagnate as hardware innovation slows, AI devours chip supply OpenAI teams with Jony Ive on strange new AI-first device Smart glasses privacy backlash and DuckDuckGo's tongue-in-cheek sunglasses Meta fined $942 million by New Mexico court for youth harms Apple sues OpenAI over alleged stolen secrets, countersuits ensue UK revives "Snooper's Charter" for backdoors, Apple fights in secret court License plate readers spark local backlash and privacy activism U.S. water systems face cyber sabotage as critical infrastructure weakens Bending Spoons buys Airtable, fueling SaaS layoffs and AI data grabs Nicholas DeLeon uses AI tools to get fit NASA hacks keep aging Voyager probes alive for another year Host: Leo Laporte Guests: Iain Thomson and Nicholas De Leon Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: bitwarden.com/twit NetSuite.AI/TWIT ZipRecruiter.com/twit adaptivesecurity.com superhuman.com

(0:00) Bestie intros! Brad Gerstner fills in for Chamath (2:16) Major shakeups at Google: AI brain drain or better strategy? (20:39) SpaceX's big quarter: Terafab, AI Capex, $1T revenue projection? (45:44) All-In Summit Speaker Announcements! (48:01) Airtable sells for a 90% discount: SaaSpocalypse? (1:05:56) Chinese AI labs are buying US training data to catch up Apply for Summit 2026: https://allin.com/events Follow Brad: https://x.com/altcap Follow the besties: https://x.com/chamath https://x.com/Jason https://x.com/DavidSacks https://x.com/friedberg Follow on X: https://x.com/theallinpod Follow on Instagram: https://www.instagram.com/theallinpod Follow on TikTok: https://www.tiktok.com/@theallinpod Follow on LinkedIn: https://www.linkedin.com/company/allinpod Intro Music Credit: https://rb.gy/tppkzl https://x.com/yung_spielburg Intro Video Credit: https://x.com/TheZachEffect Referenced in the show: https://x.com/the_ai_investor/status/2084687703707361429 https://x.com/Tesla/status/2085365278276284803

David Frankel is one of the great seed investors of our time. As the Co-Founder of Founder Collective he has backed the likes of Uber, Coupang, Suno, PillPack, Airtable, Whoop, Shield AI and many more. In a world of expanding fund sizes, David and Founder Collective are one of the only successful franchises to truly stick to small, boutique funds.  AGENDA: 00:00 The Bubbles Are Getting Bigger—and There Will Be a Lot of Roadkill 05:21 The Worst-Performing Funds Will Be the $50M–$100M Seed Funds 25:06 "We're Greedy for Returns, Not Management Fees" 30:10 "Pro Rata Is the Original Sin" 32:59 "A $1BN Valuation Is the New Series A" 46:39 "I Have Never Seen Secondary Markets This Liquid" 58:03 Microsoft Has Done a Crappy Job of AI—and Another Dot-Com Crash Is Inevitable 01:08:25 OpenAI and Anthropic Will Be Disrupted—and China Could Do It 01:16:12 "Anyone Who Claims They Knew Is Full of Shit" 01:19:56 Our Children Won't Need to Drive—and Chemotherapy Will Look Prehistoric  

This week, we discuss the Situational Awareness meltdown, Airtable getting sold, and review the Java documentary. Plus, what you should actually buy at IKEA. Watch the YouTube Live Recording of Episode 584 Runner-up Titles Duffle bag of leftovers 5Are you dead in this scenario? Bury me with my IKEA bags Don't automate the world, nobody really wants that AttentionIsAllYouNeed.blog Take some money off the table No more great ideas Rundown IKEA FRAKTA Leopold Aschenbrenner's $45B Fund Implodes AI investor Leopold Aschenbrenner forced to unwind all public stock positions after steep losses, sources say His Wedding Guests Were Arriving—Just as His $45 Billion Fund Was Falling Apart Bending Spoons Buys Airtable for $1.28B Bending Spoons to buy Airtable for $1.28B sell on story, or sell on revenue The Java Story | The Official Documentary Relevant to your Interests Who's Writing Open Source Code? Satyress Robotics GitHub - mgwalkerjr95/texas-grocery-mcp: MCP server for HEB grocery shopping BMW Spider-Man in-car advertising An announcement from Superlogical An interactive visualization that follows a single HTTP request through its entire ~200ms life Supercharge your Claude, Cursor, and Codex. | Unstructured Linux Foundation Launches the Tokenomics Foundation valock July 2026 Recap tl;dv (Too Lazy; Didn't Validate): 181,874 Meetings Left Wide Open npm Worm Poisons keyv, cacheable and 400+ Other Packages Across Twelve Organisations Using AI for Product Management - The Tanzu Platform product management experience Is the future of data centers portable? Runware builds a pod to find out Google's AI reshuffle: Chief scientist Jeff Dean exits and Demis Hassabis steps down as DeepMind CEO Investigating three real-world incidents in our cybersecurity evaluations Boris Cherny: We Cut 80% of Claude Code's Prompt Microsoft's stock rockets more than 15% for largest single-day jump in history Amazon revenue soars as AI investments pay off Meta's stock drops on disappointing guidance, dwindling free cash flow Clouded Judgement 7.31.26 - AWS CapEx ROI Sponsors Signadot: making sure AI-written code actually works. Conferences WeAreDevelopers NA, Sept 23-25, 2026, Discount Code: DEVPOD50 25 Free Tickets AI Connect, Aug 22nd, 2026 - Riga, Latvia, Coté speaking. DevOpsDays Graz, Sept 4-5, 2026 Cloud Foundry Summit, Sept. 21st to 22nd, Heidelberg, Coté speaking. DevOpsDays Rockies, Sept. 22 – 23, 2026, Discount Code: 26DODSWEDEFTALK 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 Cloud Native Denmark, Nov 19th, 2026, Copenhagen, Coté keynoting. 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: Brooks GTS 25 Matt: NearbyWiki Reading Maps Coté: Descript Underlord

Sam records from the beach while dealing with a broken bilge pump. Dave calls in after herding cattle. Fortunately, tech continues without them, which Sam takes as further proof that AGI is already running the industry. The crew unpacks Google's leadership shakeup and Jeff Dean's departure after 27 years, debates whether Airtable's sale to Bending Spoons is the blueprint for surviving the AI transition, and Sam argues that today's AI labs look increasingly like yesterday's overvalued SaaS companies. Along the way they explain why Sam's AI built his kid an iPhone game, why OpenAI's luxury creator retreat backfired, why Apple may have accidentally created its own lawsuit, and whether AI can ever overcome the growing public backlash against it. Chapters:0:00 Episode Trailer1:07 Episode Start2:08 Sam's Boston Whaler Beach Studio3:13 Dave Herds Cattle in Montana5:31 Google's AI Shakeup, Jeff Dean Leaves, Demis Steps Back8:57 Why Great Researchers Don't Always Make Great CEOs10:48 Recursive Self-Improvement and the AI Talent Wars19:41 Airtable Sells to Bending Spoons25:33 Not Every SaaS Company Is Dead27:50 The Constellation Software Playbook30:05 The Next Big Write Downs Are AI Labs31:59 Apple vs. OpenAI, Courtesy of iCloud35:20 OpenAI's Creator Summit Backlash40:53 Why People Still Hate AI43:39 AI Slop and the Content Problem45:11 SpaceX's Lockup and Number Big48:00 Nikita Bier Leaves X50:22 Jess's Posting Dilemma53:40 Next Week on More or LessWe're also on ↓X: https://twitter.com/moreorlesspodInstagram: https://instagram.com/moreorlessSpotify: https://podcasters.spotify.com/pod/show/moreorlesspodConnect with us here:1) Sam Lessin: https://x.com/lessin2) Dave Morin: https://x.com/davemorin3) Jessica Lessin: https://x.com/Jessicalessin4) Brit Morin: https://x.com/brit

Send us Fan MailGet vidIQ Boost for an exclusive price! https://vidiq.com/podcastWant a 1 on 1 coach? https://vidiq.ink/theboost1on1Join our Discord! https://www.vidiq.com/discordWatch the video: https://youtu.be/_kUOrWhNynwWe break down how People Vs Food stays fresh after a decade by pairing a clear creative North Star with systems that make videos scalable and easy to click. Nicole shares what it really takes to reduce key man risk, test new formats, and package ideas so the audience understands the promise instantly. • Nicole's career path from traditional film and TV into digital food content and YouTube • Using food as a storytelling vehicle for culture, education, and shared history • Defining the channel's North Star before choosing formats, topics, or games • Managing key man risk with hosts as anchors and an ensemble cast model • How casting works at scale with polls, topic buckets, and scheduling constraints • Bulk shooting 10–14 episodes in two days across multiple studios • Why ideation and packaging beat “cool ideas” without a clear title, hook, and thumbnail • Testing new formats over multiple uploads and judging success by the intended goal • Where AI helps and where it fails, especially for research and fact accuracy • Workflow automation with Airtable to reduce manual work and protect creative focus I want y'all to leave me a comment. Which which video from uh people versus food is your favorite? 

I recorded this one live on the last day of week two of my birthday sabbatical, and it published about ten minutes after I stopped talking. Because I spent the last seven days — on roughly four hours of sleep a night — building a custom client portal that replaced Airtable, Fillout, Notion, Google Docs, and Google Sheets in my business.What started as "let me move my AI assistants out of ChatGPT" turned into a full app where my clients log in, map their client journey, draft their emails, submit support tickets, send me voice notes, and do their weekly check-ins. I had a fully deployed version in 12 hours after telling myself since February that I needed time to plan it.I also knocked South Dakota off my list (47 states down, 3 to go), and I get into the irony of doing the exact thing I tell y'all not to do with your own systems.Demo and debrief coming to the blog soon. Get on the list so you don't miss it: coliejames.com/subscribeWork with me: Systems in Session | The Experience Edit

In questa puntata partiamo da Google, dove Demis Hassabis lascia la guida operativa di DeepMind mentre continua la guerra per i talenti dell'AI. Poi guardiamo i primi numeri di SpaceX da società quotata e ci chiediamo che azienda sia diventata davvero: spazio, connettività o infrastruttura per l'intelligenza artificiale? Torniamo anche su OpenAI, dagli agenti che riescono a coordinarsi fuori da una sandbox allo scontro con Apple sul possibile nuovo device. Infine la big story: Bending Spoons compra Airtable e si ritrova sempre più al centro della conversazione della Silicon Valley.

Don, Aaron and Jack unpack a big week in venture, AI and building companies. Venture Downunder with Innovation Bay: pirate parties, poker, the Kill All The Puppies triage session (bridge, dilute, sell or fold), and why founder pitches at events should be three minutes, not ten. Canva blames frontier AI costs for a rare revenue downgrade: growth guidance cut from 30% to 20%, Canva AI 2.0 halted, in-house models to replace OpenAI and Veo 3, and why Tribe cancelled its Canva seats for Claude Design. Sovereign AI: Prof Anton Van Den Hengel's case for Australian capability. The only capability that survives is research, your advantage is momentum not checkpoints, and Anthropic engineers reckon they have nine to twelve months of coding left. HotDoc founder Ben Hurst steps away after 14 years: the maturity to recognise when your company needs a CEO and not a founder, and why the two energies are different jobs. Incumbents milking it: Don's Ansarada rant (pricing that scales with your data room, a 2007 interface, switching costs locked in by your deal risk framework), and Airtable reportedly selling for about $1 billion, 88% below peak, with founders wiped out by the preference stack. How 26-year-old Grace Brown built Andromeda into a $100 million robotics company, and the story of Abby the robot getting a couple dancing to their wedding song again after 20 years. Anti-portfolio goals: Vu Tran on why making a top VC's anti-portfolio is a benchmark, not a rejection. Ken Griffin on Citadel buying Sowood's $30 billion portfolio overnight: things come to those who wait, but only what's left by those who hustle. Sharts: data centre investment overtaking hotels and retail, Peter V'landys and NRL scoring, Federal Circuit Court general protections claims up 100% in three years, and EVs plus hybrids about to cross petrol and diesel in Australian vehicle sales. hello@tribeglobal.vc

Special Guest: Nikesh Arora, CEO @ Palo Alto Networks.  AGENDA: 04:50 Airtable Sold to Bending Spoons for $1.285B  17:00 Leo Aschenbrenner's Situational Awareness Blows Up as Citadel Buys His $16BN Book 22:30 Anthropic's AI Models Breach Three Companies as Cyber Threat Accelerates 33:35 Moonshot AI Raises $3.5B at $35B as Chinese Models Crush AI Prices 38:05 Valar Atomics Triples to $6B as Sequoia Bets on Nuclear Power for AI 42:50 OpenAI and Anthropic Could Trigger a Massive Public-Market Dislocation 52:55 Big Tech and Palantir Earnings Ignite the Next Phase of the AI Gold Rush 1:04:30 Procore Buys DroneDeploy for $900M in a High-Stakes 12x Revenue Bet 1:10:55 Scale AI Hits $1.5B ARR After the Meta Deal Left It for Dead  

OpenAI and Anthropic have confirmed their AI models were involved in separate third-party cybersecurity testing incidents resulting in a real website being breached and social engineering attacks against sites outside the intended testing boundaries. Plus Bending Spoons to buy Airtable for $1.2 billion. We ask everyone what they think of Bending Spoons track record so far in managing the companies they've acquired so far. And we close the week with a quiz about desserts! Or was that deserts? Find out on today's show! Starring Sarah Lane, Tom Merritt, Robb Dunewood, Roger Chang, Joe. To read the show notes click here! Support the show on Patreon by becoming a supporter!

Apple gears up for its September iPhone event, Google Earth's AI imagery enabled fabricated scenes of bombings, Claude's models broke containment and even tried to trick real people, and why Bending Spoons ruins everything it touches.Member Promo Code: IWANTCHAPTERS (Click above and the $2.50 promo will be auto applied!)Top Five Tech | Stephen's PodcastCreative Effort | Jason's PodcastWatch on YouTube!Show Notes via EmailEmail Us: podcast@primarytech.fm@stephenrobles on Threads@jasonaten on ThreadsSponsors:Framer - Start creating for free at framer.com/primary and get 30% off an annual Pro plan!CleanMyMac - Get Tidy Today! Try 7 days free and use my code PRIMARYTECH for 20% off at clnmy.com/PRIMARYTECHLinks from the showKan Do - Stephen's New Task App! (01:00)Apple News Ad - Mastodon post from John GruberMasterCraft brings CarPlay and Android Auto to its pontoon boats (05:28)Apple Starts Preparing for September iPhone Event - MacRumorsQ3 results: 3D pricing, EGOT timing, and underestimating demand – Six ColorsOne Reason Apple's Computers Are Mostly Made In China: A Tiny Screw | Texas StandardThe US government just banned Roombas (13:42)X post from Brendan CarrFriend re-launches its AI pendant with a speaker that talks to you, for twice the price | The VergeX post from Avi SchiffmannApple is getting this wrong | OpenAIX post from Sam AltmanYour Fitbit data can now connect directly to Apple Health | The VergeGoogle just announced a major shakeup of its top AI leadership | The VergeSee how Google Earth let people make fake scenes of bombings, riots and destruction (43:12)Anthropic says Claude accidentally hacked real companies too | The VergeRogue AI agents created fake online identities in another hacking attempt | The VergeIncident Report: unsanctioned agent behaviour during cyber testing | AISI WorkBending Spoons to buy Airtable for $1.28B | TechCrunchAfter $18B IPO, Bending Spoons founder says success comes from minimizing luck | TechCrunchEvernote cuts back on free plans, pushing users to upgrade | TechRadarWeTransfer owner snaps up apps, then sacks workers and raises prices - Follow the MoneyEurope's AI labeling and transparency rules are now in effect | The VergeReddit comment from r/nerdfighters (00:00) - Intro (03:19) - Apple News Ads Are Bad (05:27) - CarPlay in Boats (07:54) - September iPhone Event (11:03) - Instagram's Terrible Browser (13:41) - FCC Bans Robot Vacuums (21:28) - Friend AI Pendent 2 (25:30) - OpenAI's Bizarre Response (37:25) - Sponsor: Framer (39:19) - Sponsor: CleanMyMac (40:55) - Google AI Shake Up (43:10) - Google Maps AI Slop (48:08) - Claude Broke Containment (51:36) - Why Bending Spoons is Bad (01:07:24) - Mac Window Habits ★ Support this podcast ★

In this well timed episode, we break down the massive news that Airtable is being acquired by the Italian company Bending Spoons. We dive into the details of the valuation, the shock to the community, and what this means for the future of the platform. We explore Bending Spoons' track record with previous acquisitions like Evernote and StreamYard, discussing their reputation for restructuring pricing and product tiers. We also leverage the Hyperagent Analysis of Airtable Acquisition to examine how the company might operate the platform based on their previous acquisitions. Finally, we weigh the risks of losing institutional knowledge against the potential for fresh investment and long-term stability under a publicly traded company.

This Week In Startups is made possible by: Vanta https://www.vanta.com/twist Agree https://agree.com Odoo https://Odoo.com/twist Today's show: *Airtable just sold for $2.25 billion, an 81% drop from its peak of $11.7 billion. On this week's TWiST VC Roundtable, Aditya Agarwal (South Park Commons), Niko Bonatsos (Verdict Capital), and Rick Heitzmann (FirstMark Capital) break down why the venture world sees this as a good outcome, not a financial disaster. By declining the deal, would Airtable's team have just been delaying the inevitable? Is the fact that they reached $400M+ ARR on its own a reason to celebrate? Find out why our investor panel prefers unwinding a stuck situation rather than chasing a growth rate that's no longer sustainable. PLUS Robinhood's booming prediction market business, the secondary market flap over Anduril shares, why so many VCs shy away from "vice" categories, and a glimpse at how insiders are talking about the Apple-OpenAI lawsuit. Guests Aditya Agarwal on X: https://x.com/adityaag South Park Commons: https://www.southparkcommons.com/apply Niko Bonatsos on X: https://x.com/bonatsos Verdict Capital: https://verdictcap.com/ Rick Heitzmann on X: https://x.com/rick FirstMark Capital: https://firstmark.com/ Relevant Links Airtable: https://www.airtable.com/ Bending Spoons announces Airtable acquisition: https://investors.bendingspoons.com/newsroom/bending-spoons-agrees-to-acquire-airtable Constellation Software: The Anti-Conglomerate: https://www.eaglepointcap.com/blog/constellation-software-the-anti-conglomerate Introducing Robinhood Ventures Fund II: https://robinhood.com/us/en/newsroom/introducing-rvii/ Quartz: Robinhood posted record quarterly revenue: https://qz.com/robinhood-record-revenue-prediction-markets-earnings-073026 Riot Games: https://www.riotgames.com/en AngelList's USVC Fund: https://usvc.com/ Baseten: https://www.baseten.co/ OpenEvidence: https://www.openevidence.com/ Hermes Agent: https://hermes-agent.org/ Granola: https://www.granola.ai/ Timestamps: 0:00 VC intros & Bending Spoons buys Airtable 9:19 Why growth is the only metric that matters 9:45 Vanta - Get $1000 off your SOC 2 at https://www.vanta.com/twist 20:52 Agree.com - Stop chasing invoices and automate your entire contract-to-cash stack. Go to https://agree.com and tell them Jason sent you to get 50% off for life! 26:25 When should VCs sell in secondary markets? 30:55 Odoo - The all-in-one business platform. Get started for free at https://Odoo.com/twist 35:38 Robinhood's prediction markets are exploding 43:13 The USVC-Anduril secondary controversy 46:18 How VC firms use open source models 58:43 Telling the real founders from the grifters 1:02:38 Why Apple is suing OpenAI Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.com Check out the TWIST500: https://www.twist500.com Subscribe to This Week in Startups on Apple: https://rb.gy/v19fcp   Follow Lon: X: https://x.com/lons   Follow Alex: X: https://x.com/alex LinkedIn: ⁠https://www.linkedin.com/in/alexwilhelm   Follow Jason: X: https://twitter.com/Jason LinkedIn: https://www.linkedin.com/in/jasoncalacanis   Check out all our partner offers: https://partners.launch.co/   Great TWIST interviews: Will Guidara, Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarland   Check out Jason's suite of newsletters: https://substack.com/@calacanis   Follow TWiST: Twitter: https://twitter.com/TWiStartups YouTube: https://www.youtube.com/thisweekin Instagram: https://www.instagram.com/thisweekinstartups TikTok: https://www.tiktok.com/@thisweekinstartups Substack: https://twistartups.substack.com

Es gibt bis zu 200 €, wenn ihr Friends & Family zu Scalable Capital bringt! Das Ganze geht nur bis zum 31. August. Mehr Infos in der App oder auf scalable.capital/oaws. Und hier sind die Teilnahmebedingungen.Ölkonzerne verdoppeln Gewinne, Trump will was davon. Iran-Deal drückt Ölpreis. Bending Spoons kauft Airtable. USA pushen Coherent, Lumentum und Applied Optoelectronics. Caterpillar macht Rekord. Zalando & Spotify verlieren. Snap, Zebra & Wayfair gewinnen.Palantir (WKN: A2QA4J) wächst 80% und hat 47% operative Marge. Aber die Aktie steht beim 100-fachen Gewinn. Karp und Thiel verkaufen für hunderte Millionen. Kann das Wachstum die Bewertung rechtfertigen?Diesen Podcast vom 05.08.2026, 3:00 Uhr stellt dir die Podstars GmbH (Noah Leidinger) zur Verfügung. Learn more about your ad choices. Visit megaphone.fm/adchoices

Cybersecurity startup Horizon3 raised $250 million at a $2 billion valuation as companies want continuous, AI-powered security validation instead of annual penetration testing. Also, at its peak in 2021, Airtable was valued at over $11 billion, but earlier this year, its shares were said to be trading on the secondary markets at a valuation of $4 billion. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Plus - Bending Spoons to buy Airtable for $1.28B; Influencers draw backlash for attending OpenAI's first luxury trip Learn more about your ad choices. Visit podcastchoices.com/adchoices

OpenAI took Apple's trade-secrets lawsuit to the court of public opinion, receipts and all. Bending Spoons bought Airtable, Anthropic inked a $10B Norway compute deal, the US eyed polysilicon tariffs, and Microsoft told engineers tokenmaxxing was over. Links OpenAI drags Apple's lawsuit into the court of public opinion (The Verge) Bending Spoons agrees to acquire Airtable in an all-cash deal valuing the US software company at $1.285B, set to close by 2026's end, its first post-IPO deal (Reuters) Bending Spoons buys Airtable at an implied equity value of ~$2.25B, five years after a $735M round valued the no-code company at $11.7B; Airtable's ARR is now ~$480M (Silicon Republic) Sources: Anthropic agreed to a $10B deal for computing capacity in Norway from Nvidia-backed AI cloud startup Volta Infra, which says the deal is for six years (Bloomberg) Sources: the US is preparing to set a price floor and impose tariffs on polysilicon, a material critical to chips, later this month, in a bid to counter China (Reuters) Sources: Beijing is growing concerned about the cyber capabilities of Mythos and other US-developed frontier AI models and their potential as offensive weapons (Bloomberg) White House to host AI companies Tuesday to review new model-testing framework (CNBC) Internal email: Microsoft introduces token budget limits for employees' AI use, saying "tokenmaxxing is not what we are optimizing for" (404 Media) Subscribe to the ad-free feed.

Aaref Hilaly, Partner at Bain Capital Ventures, and Chase Packard, Founding Partner at Marathon, talk with guest TITV Host Stephanie Palazzolo about Airtable's $1.3B acquisition. We also talk with The Information's Anita Ramaswamy about why a SpaceX-Tesla merger makes sense, Laura Bratton about enterprises building internal AI coding agents to complement Claude Code, and we get into AI interpretability with Goodfire CEO Eric Ho.Articles discussed on this episode: https://www.theinformation.com/newsletters/applied-ai/firms-like-coinbase-building-coding-agents-complement-anthropics-claude-codehttps://www.theinformation.com/articles/spacex-tesla-merger-benefit-shareholders-companiesSubscribe: YouTube: https://www.youtube.com/@theinformation The Information: https://www.theinformation.com/subscribe_hSign up for the AI Agenda newsletter: https://www.theinformation.com/features/ai-agendaTITV airs weekdays on YouTube, X and LinkedIn at 10AM PT / 1PM ET. Or check us out wherever you get your podcasts.Follow us:X: https://x.com/theinformationIG: https://www.instagram.com/theinformation/TikTok: https://www.tiktok.com/@titv.theinformationLinkedIn: https://www.linkedin.com/company/theinformation/Chapters:00:00 - Introduction00:01 - Airtable Acquired by Bending Spoons for $1.3B00:11 - Why a SpaceX-Tesla Merger Could Benefit Shareholders00:21 - Enterprise AI Coding: Coinbase & Shopify Diversify Beyond Claude Code00:29 - Goodfire Launches 'Silico' AI Interpretability Platform

Amazon zahlt OpenAI die vollen 50 Milliarden aus, obwohl keine der vereinbarten Bedingungen eingetreten ist. Google hat für Anthropic eine 200-Milliarden-Konstruktion aus Broadcom, Apollo, Blackstone, Morgan Stanley und ehemaligen Krypto-Minern gebaut. Pip erklärt dabei von Grund auf, wie Off-Balance-Sheet-Finanzierung funktioniert und warum niemand diese Chips in der eigenen Bilanz haben will. Daraus entwickelt er eine These: AI 2.0 kommt erst noch. Aus China kommen die passenden Belege, mit Alibabas neuem Modell und einem DeepSeek, das je Aufgabe ein Hundertstel der westlichen Konkurrenz kostet. Dazu Palantirs Zahlen und ein Rechenexempel über die Margen zwischen Chip und Kunde. Zum Schluss schauen wir in die SpaceX Earnings. Unterstütze unseren Podcast und entdecke die Angebote unserer Werbepartner auf ⁠⁠⁠⁠⁠⁠⁠doppelgaenger.io/werbung⁠⁠⁠⁠⁠⁠⁠. Vielen Dank!  Philipp Glöckler und Philipp Klöckner sprechen heute über: (00:00:00) SpaceX vor den Zahlen (00:13:06) Amazon investiert in OpenAI (00:17:25) Eine Milliarde Nutzer (00:19:51) Off-Balance-Sheet erklärt (00:23:23) Googles 200-Milliarden-Maschine (00:41:32) AI 2.0 (00:43:57) Alibaba Qwen3.8-Max (00:44:53) DeepSeek V4-Flash (00:46:41) Chinas Militär destilliert (00:48:49) Amazon bei drei Billionen (00:49:30) Palantir (01:00:33) Snap (01:01:07) xAI gegen Minnesota (01:03:05) Telegram im App Store (01:04:07) Google zieht Satellitenbilder zurück (01:05:25) Liechtenstein gehackt (01:08:47) Airtable an Bending Spoons (01:09:26) SpaceX-Earnings Shownotes Amazon schließt 50-Mrd.-Investment in OpenAI ab - ft.com OpenAI überschreitet eine Milliarde Nutzer - wsj.com Googles 200-Mrd.-Finanzierungsmaschine für Anthropic - ft.com Off-Balance-Sheet-Finanzierung erklärt - corporatefinanceinstitute.com Alibaba veröffentlicht Qwen3.8-Max - bloomberg.com DeepSeeks V4-Flash ist das günstigste bekannte Modell - reuters.com Chinesische Militärforscher trainieren mit US-Modellen - reuters.com Amazon überschreitet drei Billionen Dollar Marktwert - bloomberg.com Palantir-Quartalszahlen, Umsatz plus 93 Prozent - cnbc.com Palantir-Aktie steigt nach turbogeladenem Wachstum - marketwatch.com Snap stellt AR-Brille für 2.195 Dollar in Aussicht - bloomberg.com Snap-Aktie springt über 10 Prozent - cnbc.com Richter lässt Minnesotas Nudify-Verbot in Kraft - nbcnews.com Telegram nach kurzem Rauswurf zurück im App Store - reuters.com Google zieht KI-Satellitenbilder zurück - npr.org Hacker stehlen 31.000 Datensätze aus Liechtensteins Geldwäscheregister - zeit.de

Diana Elder and Nicole Dyer explore the value of writing an ancestor's military story by correlating multiple sources. Diana uses her father Bob Shults's World War II Navy records as a case study. She demonstrates how to use AI to cross-reference personal oral histories with official documents like muster rolls and discharge papers. Listeners learn how to build a comprehensive timeline that bridges the gap between limited personal recollections and formal military service records. The discussion highlights the use of the FamilySearch Simple Search tool to locate unindexed muster rolls that reveal specific locations and dates of service. Diana shows how she organizes this research in Airtable to track her father's path through training in Tennessee, Oklahoma, and Florida, and his eventual deployment on the USS Antietam in the Western Pacific. By integrating this specific documentation with historical context about training bases and ship operations, researchers can effectively flesh out an ancestor's service experience and uncover new avenues for future investigation. This summary was generated by Google Gemini. Links A Navy Life: The World War II Service of Bobby Gene Shults - https://familylocket.com/a-navy-life-the-world-war-ii-service-of-bobby-gene-shults/ "Formal Naval Air Station Memphis," NAVFAC  - https://www.bracpmo.navy.mil/BRAC-Bases/Southeast/Former-Naval-Air-Station-Memphis/ Technical Training, Naval Aviation News, November 15, 1944; imaged, Oklahoma Naval Air History - https://www.oklahomanavalairhistory.com/techarticle01.php Lelan Kent, "Yellow Water N.A.G.S. & Weapons Storage," Abandoned Southeast - https://abandonedsoutheast.com/2023/10/11/yellow-water-n-a-g-s-weapons-storage/ Andrew Bucholtz, "San Diego in WWII, Part IV: Home Base of the Pacific," posted 11 October 2023, SDHist - https://sdhist.com/home-base-pacific-san-diego-wwii-iv/ CV 36/CVA 36 / CVS 36 – USS Antietam, Seaforces-online - https://www.seaforces.org/usnships/cv/CV-36-USS-Antietam.htm Sponsor – Newspapers.com For listeners of this podcast, Newspapers.com is offering new subscribers 20% off a Publisher Extra subscription so you can start exploring today. Just use the code "FamilyLocket" at checkout.   Research Like a Pro Resources Airtable Universe - Nicole's Airtable Templates - https://www.airtable.com/universe/creator/usrsBSDhwHyLNnP4O/nicole-dyer Airtable Research Logs Quick Reference - by Nicole Dyer - https://familylocket.com/product-tag/airtable/ Research Like a Pro: A Genealogist's Guide book by Diana Elder with Nicole Dyer on Amazon.com - https://amzn.to/2x0ku3d Research Like a Pro with AI Workbook – Second Edition (eBook) - https://familylocket.com/product/research-like-a-pro-with-ai-workbook-second-edition-ebook/ 14-Day Research Like a Pro Challenge Workbook - digital - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-digital-only/ and spiral bound - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-spiral-bound/ Research Like a Pro Webinar Series - monthly case study webinars including documentary evidence and many with DNA evidence - https://familylocket.com/product-category/webinars/ Research Like a Pro eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-e-course/ RLP Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-study-group/ Research Like a Pro Institute Courses - https://familylocket.com/product-category/institute-course/ Research Like a Pro with DNA Resources Research Like a Pro with DNA: A Genealogist's Guide to Finding and Confirming Ancestors with DNA Evidence book by Diana Elder, Nicole Dyer, and Robin Wirthlin - https://amzn.to/3gn0hKx Research Like a Pro with DNA eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-with-dna-ecourse/ RLP with DNA Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-with-dna-study-group/ Thank you Thanks for listening! We hope that you will share your thoughts about our podcast and help us out by doing the following: Write a review on iTunes or Apple Podcasts. If you leave a review, we will read it on the podcast and answer any questions that you bring up in your review. Thank you! Leave a comment in the comment or question in the comment section below. Share the episode on Twitter, Facebook, or Pinterest. Subscribe on iTunes or your favorite podcast app. Sign up for our newsletter to receive notifications of new episodes - https://familylocket.com/sign-up/ Check out this list of genealogy podcasts from Feedspot: Best Genealogy Podcasts - https://blog.feedspot.com/genealogy_podcasts/

Can you run a thriving, hyper-local accounting practice while living in Mexico for four months of the year? Most accounting firm owners and managing partners assume that running a local firm requires being chained to a brick-and-mortar office—especially during busy seasons. In this episode of Growing Your Firm, host David Cristello sits down with Nancy McClelland, CPA (widely known as The Dancing Accountant). Nancy shares how she built a highly profitable, 100% remote, hyper-local firm in Chicago that allows her to spend every tax season working from Mexico. If you are a bookkeeping firm owner, a CPA starting a firm, or an operations manager trying to fix a broken tax season, this episode provides a masterclass in firm boundaries, client selection, and bookkeeper-to-tax-pro collaboration. In this episode, we unpack: The Hyper-Local Strategy: How Nancy built a 25-year-old firm serving only small businesses within a few specific Chicago neighborhoods. The "No Bookkeeping, No Tax" Rule: Why Nancy refuses to prepare tax returns for clients unless her team handles their monthly bookkeeping and advisory. Fixing the Bookkeeper-to-Tax Pro Handoff: Eliminating duplication of effort, preventing missed reconciliations, and creating a standardized "tax-ready" handoff checklist. Voting Clients Off the Island: How Nancy's team uses quarterly "paid happy hours" to identify and offboard clients who disrespect team members or drag down morale. Shunning "Growth for Growth's Sake": Why turning down new clients and focusing on deep advisory for a capped client base creates a more profitable, stress-free practice. Key Metrics & Workflow Takeaways: 100% Remote Flexibility: How Nancy transitioned her entire team to remote work over a decade ago using simple tools like Zoom, AirTable, and QBO. The Tax-Ready Bookkeeping Standard: Shifting year-end cleanups into recurring, junior-staff-driven monthly processes.   Featured Guest: Nancy McClelland  

There are roughly 100x more people who use code than who can write code. As code that “just works” becomes easier to generate, this group may be the biggest prize of all — if you can get the agentic interface right.A key trend we have been tracking over at AINews is the absolute explosion in Codex usage this year, with MAU now up >10x from Jan 2026. Less than two weeks after their July 9th launch, OpenAI said ChatGPT Work and Codex had reached 10M users combined (as we cover in the pod, Codex now powers ChatGPT Work, so all ChatGPT Work users are now users of the Codex harness, even if they aren't traditional engineers) — showing the early innings of what happens when you graduate from coding agents to knowledge work agents:We've been calling out how coding agents are “breaking containment” to do everything else this year to power every other part of knowledge work - and it started with the org chart, with a major reorg last month that amounted to two of Codex's most prominent leaders, Greg and Tibo, taking responsibility over product and ChatGPT specifically, completing a “Superapp” consolidation cycle first discussed in March.With these updates Codex is no longer just a coding tool. In June, OpenAI said knowledge workers already accounting for roughly 20% of Codex's user base and growing more than 3x as quickly as developers. A product dedicated for knowledge workers was being pulled out of the Codex team.However, knowledge work has a different set of problems and environments than coding. For decades, knowledge work has been scattered across different primitives like documents for writing, spreadsheets for analysis, slide decks for communication, and specialized applications for everything else. ChatGPT Work now enables users to work across every primitive with agents. Instead of opening an application and manually operating its features, the user can describe an outcome and collaborates with an agent that can assemble the tools, context, and artifact needed to reach it.From building no-code products at Airtable to leading Productivity Engineering at OpenAI, Akshay Nathan has spent much of his career trying to make the power of software accessible to people who do not write code. In this episode, Akshay joins swyx and Vibhu to unpack the launch of ChatGPT Work, why Codex unexpectedly took off among non-developers inside OpenAI, and the company's broader plan to bring useful agents from software engineers to knowledge workers and eventually everyone.We go deep on the shared agent harness behind Codex and ChatGPT Work, why OpenAI brought the experiences together without making them identical, and how persistent computers, artifacts, Sites, plugins, memory, and sub-agents are changing what people can delegate to AI. Akshay explains why some teams are replacing decks and spreadsheets with interactive websites, how agents can gather context across code, Slack, documents, and local files, and what OpenAI learned from personal-agent products like OpenClaw.Side note: also don't miss Abhihek's sandbox track keynote at AIE, which now powers a lot of the sandboxing for ChatGPT Work… and yes was also broken by an unreleased OpenAI model in the recent HuggingFace incident.Akshay also reflects on how AI is transforming product development itself: why more people will become generalists with a specialty, why ideas and taste become the bottlenecks when almost anyone can build, why LLMs still struggle to generate genuinely grounded new ideas, and why teams must distinguish increased motion from actual progress.We discuss:* Why Codex unexpectedly took off among non-developers inside OpenAI* Why employees felt like using Codex gave them a new superpower* The product insight that led OpenAI to build ChatGPT Work* Why Codex and ChatGPT Work share the same underlying agent harness* How their UX, Git visibility, artifacts, and sandboxing defaults differ* Why OpenAI merged its agent experiences instead of building separate products* How AI is blurring the boundaries between engineering, design, strategy, and operations* Why OpenAI wants the default model configuration to work for most users* When power users should use deeper reasoning, Ultra, or multi-agent modes* Artifacts, agentic spreadsheets, and creating high-fidelity work products* Why interactive Sites may replace decks and spreadsheets* The challenge of designing a simple interface for an agent that can build almost anything* Why users should retry tasks that models could not handle three or six months ago* How AI can gather context for performance reviews without replacing human judgment* The OpenAI automation that turns internal Slack and document activity into memes* What reaching ten million ChatGPT Work and Codex users means for the product* How OpenClaw inspired persistent environments, scheduled tasks, and personal agents* Using ChatGPT for financial planning, budgeting, workouts, meals, and household management* The design tradeoffs behind sub-agents and how much of their work users should see* ChatGPT memory, Chronicle, and long-term context* Why AI may make more people generalists with deep specialties* Why ideas and taste become more important when almost anyone can build* Why LLMs still struggle with the instruction “bring me new ideas”* Measuring productivity through quality at-bats instead of commits, tokens, or pull requests* The critical difference between AI-generated motion and meaningful progressAkshay Nathan* LinkedIn: https://www.linkedin.com/in/akshaynathan/* X: https://x.com/akshaynathan_Timestamps00:00:00 Introduction and Bringing the Power of Code to Everyone00:01:33 Joining OpenAI and Preserving a Startup Culture00:02:40 What OpenAI Learned from Enterprise AI Adoption00:05:28 Why OpenAI Built ChatGPT Work00:07:17 Codex vs. ChatGPT Work and the Shared Agent Harness00:12:07 Why OpenAI Merged Its Agent Experiences00:16:24 Models, Reasoning Levels, and Choosing the Right Default00:20:26 Artifacts, Agentic Spreadsheets, and Model–Product Collaboration00:24:22 Why Sites Could Replace Decks and Spreadsheets00:30:08 Designing an Agent That Can Build Almost Anything00:34:28 From Developer Agents to Knowledge Work—and Everyone00:36:07 Power-User Advice and AI-Assisted Performance Reviews00:40:41 OpenAI's Internal AI Memes and the Ten-Million-User Launch00:44:39 OpenClaw, Personal Agents, and ChatGPT as an Operating System00:50:24 Sub-Agents, Ultra Mode, and How Much Control Users Need00:54:39 ChatGPT Memory, Personalization, and Chronicle01:00:19 How AI Is Reshaping Product Development and Tech Roles01:03:15 Ideas, Taste, and Why LLMs Struggle to Generate New Ideas01:04:42 Measuring Productivity, Quality At-Bats, and Motion vs. ProgressTranscriptIntroduction: Akshay Nathan, ChatGPT Work, and the No-Code ArcSwyx [00:00:00]: We're here in the studio with Akshay from OpenAI. Welcome.Akshay Nathan [00:00:07]: Thank you.Swyx [00:00:08]: And with our trusty co-host, Vibhu. So you recently launched ChatGPT Work. You lead Core Product Engineering. It's been a long journey, into all this. I find it very interesting that you started with no code or low code, with Walrus and Airtable. And to some extent, ChatGPT Work is like the super app of super apps of, well, here is the ultimate no code. You just write a prompt.Akshay Nathan [00:00:32]: Yeah. It's funny how things come, full circle. I think for a long time in my career, I started my career working consumer fintech, but then after that, like, there's this hypothesis that, the things that we were able to do with code, like, as engineers, like, if we could bring that to many more people in a more, accessible way, then that would be truly magical. We were working on a startup. It's funny, like, before LLMs, before vision LLMs, on how to do automated testing with AI. It was just kinda jank, back then, but doing what we can, and then worked at Airtable for a while on the same thesis that, like, if we can bring a database or the primitives behind a database to people, that'd be really useful to them. But once LLMs came onto the scene, it became clear that, this was the missing piece, like, the missing technology required to, like, bring the magic of code to everyone without them having to know what's going on underneath the hood. And so, like, I think this launch and a lot of the stuff that we've been up to is, like, the manifestation of that.From Walrus and Airtable to OpenAIVibhu [00:01:33]: How was stuff when you joined? So you joined OpenAI 2023. Now we've got, so much more stuff, so ChatGPT, Codex app, ChatGPT Work. Have things changed?Joining OpenAI and What Hasn't ChangedAkshay Nathan [00:01:44]: I think the more interesting thing is how things haven't changed. Like, one, I joined I remember when I joined, it was, like, five hundred people. One thing I was worried about was, like, I was looking for something, more early stage and, like, was it gonna feel startup enough? And I joined, and I was like, “This feels even more startup-y than I could ever imagine.” And, like, that really hasn't changed even till now. I think the, like, level of, like, bottoms-up ambition and, like, the ability of anyone to, like, do anything or have an idea and ship it is really cool. But on the, like, mission side, I think what was really compelling to me is this mission of, bringing frontier intelligence to everyone. Like, building AGI and then bringing it to everyone. And, I think acknowledging back then that, like, that vision is gonna, not be a linear progression. Like, we're probably gonna, like, try different products and have different things that succeed and don't. But the vision has stayed the same, and the mission has stayed the same, and we're starting to see the pieces, fall together, and that's really cool.Enterprise Lessons: No One-Size-Fits-All AISwyx [00:02:40]: You worked on Enterprise. What A lot of people never touch ChatGPT Enterprise. What is something that you learned from there that you're bringing into your work now?Akshay Nathan [00:02:52]: I think how there's no one-size-fits-all solution in Enterprise. I remember in the early days of ChatGPT Enterprise, like, when we talked to customers and, like, everyone. That was, like, when I think it was a year after ChatGPT was released, and everyone was so excited to bring, AI into their enterprise. And, there were all these teams being stood up. It was, like, the AI deployment team with, like, these enormous budgets. And if you asked anyone, like, what were they excited about? Like, what were they excited about solving? Like, at first, you'd get, like, kinda like the baseline answers of, like, “Yeah, we have all this context and data and all this stuff.” But then if you ask them, like, “What was, like, a discrete use case that, like, they want AI to enable in their workplace?” You get such a different, like, variance, like, explosion of, different types of answers. And it's interesting, like, you using, like, these models and these products, you have this box, and you can say anything to it, which is the magic. But it'on the flip side, it also means that, like, you don't know what to do with it. And in Enterprise, I think a big part of that is, like, meeting the users where they are, like, what use case were they trying to solve, and then teaching them how they can use AI to, like, gain leverage there.Swyx [00:03:56]: Do you meaningfully differentiate that from forward-deployed engineering?Akshay Nathan [00:04:01]: I think there is the go-to-market side of it and then there is the product side of it. I think you need someone on the product side. And I think, like, however good we get at FDE motion, like, I think at the end of the day, if we have a user who's, like, looking at their computer or looking at their phone, like, it's our job in the product to, like, be enabling them and showing them where to go. So we're really excited about that.Vibhu [00:04:24]: Do you think there's been changes, over the past three years of adoption? So there have been, step function changes. You have reasoning models and whatnot. Is there still the same problems of Enterprise has black box, don't know what to do with it, or have things changed?Adoption, Agents, and the Next 10x MarketAkshay Nathan [00:04:39]: We're seeing now that, like, there's this huge uptake, right? Everyone is extremely excited about it. It feels like, many people are, millions, hundreds of millions of people are using ChatGPT. They understand, like, how generally to work with AI. But then, like, every time, like, a new capability gets unlocked, so now, like, we're seeing with agents, like, there is probably a contingent of, like, early adopters still who, truly get it, who are like, “ we you can do anything. You just have to make sure the right context is there, it's connected to the right tools, and that you are supervising it, but, like, anything is possible.” But then there's, like, this, like, 10x or 100x bigger market where, like, they don't yet get that, or they don't yet see that. And so I think that's the next stage here. So to answer your question, like, I think the adoption is there and growing fast, but I think the opportunity is, like, far bigger than that. That's where we wanna play, especially with ChatGPT Work.ChatGPT Work, Codex, and the Super App MergeSwyx [00:05:27]: Yeah. well, let's, let's skip ahead to ChatGPT Work. only, like, a month ago or so, announced. what was the decision process that led into it? there was this, overall merging of the super app. Is that what we're officially calling it? you deprecated the browser as well. Just, summarize your last, like, couple months of working on this thing.Akshay Nathan [00:05:50]: Yeah. It feels like forever now, but it's only been a few months. I think maybe the one, impetus that, like- Is most salient is when we release Codex, or even internally had Codex, like, it was really surprising to us, I think we recently put out some stats on this, that there was this, like, real inflection of, like, adoption among non-developers at OpenAI. And, I, through this product development process, like, would go to, like, these UXR sessions to talk to people internally. And the thing that stuck out to me is, like, one, like, you go talk to, like, strategic finance or marketing or whatever, and they're all using Codex for, their use cases. That part's cool, but the thing that really stuck out to me is how proud people were that they were using Codex. Like, how, likeSwyx [00:06:34]: It's like, “I'm not supposed to be using it, but I am.”Akshay Nathan [00:06:36]: It was that. It was, like, that they were, early to this, like, new thing, but it was also this thing of, like, they felt like they had a superpower, right? And, what we recognized then is that, like, the power of Codex, the power of agents, like, we already had this massive distribution base of people who have, come to know and love ChatGPT. Like, how do we show that to them? Like, how do we bring it to them? Which is, like, a hard product problem, and it's, like, a tricky thing, right? There's many ways you can go about it. And so that's what we called the Merge and the Super App over time, and ultimately launched it in ChatGPT Work, is how do we do that? But it came from that initial realization that, like, the power was not only for developers, like, much earlier than probably even we thought. Like, it could be extended to everyone.Swyx [00:07:17]: How do you see the products differently? So, like, who is it for, right? So Codex started out even CLI, then app. Now there's a merge of ChatGPT Codex and ChatGPT Work, so is it the opening for the average user, for enterprise, for work? How do you position it?Akshay Nathan [00:07:36]: I think we want to get it to position it for if you're doing work-related things, for lack of a better word, right?Who ChatGPT Work Is ForAkshay Nathan [00:07:42]: I think productivity is what, like, the pillar that I support. Like, that's the name of the team. And the reason for that, the reason we call it productivity and not, like, enterprise or, like, work or something like that, is because there's also personal productivity, right? And, like, I think ChatGPT Work is I've seen people do things in their personal lives that you wouldn't classify as, like, work technically, but, like, these agents are, super capable for. Like, one recent example that someone posted about, on our Slack is, like, someone had, like, a missed package, like they didn't receive it, and then they got, like, the picture of it, from Amazon or whoever the courier was, and they, like, asked ChatGPT Work to, like, find out where that package is. And, like, the agent, is extremely tenacious and, like, took the image and, like, looked at a bunch of, like, listings around their neighborhood and figured out exactly the apartment complex in which the package was, like, gave them some information. And so, like, I think there's all these things that, like, you, work-related or productivity-related things, I think that's what we want the product to be. You asked about Codex. I think we think Codex is, a durable brand, but we have a principle that, like, the user we don't want a user to get stuck in a tab or an experience where they don't get the power of the product. And so, like, everything that you can do, in the Codex portion of the product on desktop, you can do in ChatGPT Work and vice versa. But we made some opinionated product decisions on, like, how much of the Git state, if you're in a Git repo, do we wanna expose to the end user? Or how much do we wanna make the experience of seeing the agents thinking, like, diff forward so that you get exposed to the diffs out of the box. And then, like, on the safety side, like, how do we wanna think about, like, sandboxing and making sure that we have the right defaults in one state versus the other? So, there's, like, some opinions that go behind that, but we do want We don't want the user to need to choose which experience they're in.Swyx [00:09:26]: That is a good goal for AGI, right? Like, people don't want, like, to hide to choose what version of AGI they want. They just want the AGI to decide for them. can I get an answer or, like It's not super clear to me. Is the Codex harness and the ChatGPT Work harness the same? Is it just UI affordances, or are there prompt level or even deeper differences?Shared Harness, Different UX: Codex vs. WorkAkshay Nathan [00:09:49]: So the harness is the same. The harness is shared. on In both of the products, we made improvements to the harness to make it good for knowledge work, especially as it relates to plug-ins or computer use or artifacts. You get that power regardless of which experience you're in. On the UX side, there's opinionated takes that we have when you're in Codex mode, what the UX should be how the UX should behave, and some stuff around the sandbox like I mentioned, but the underlying harness and capabilities should be the same.Swyx [00:10:16]: I'm just kinda curious. Maybe we can, -- Is there a query that we can run that would look different in the two modes?Akshay Nathan [00:10:23]: Yeah. I tried to create, like ask it to create, like, a retirement calculator spreadsheet or something, in both modes. And then in Codex mode, you might have to be in a repo for this, but you'll see, like, the diffs of, like, the sheet that it's creating and stuff like that, and the file edits. But in Work you won't be able to see that.Swyx [00:10:42]: I think that's, that's super clear. And then also the other thing I wanted to dive into was your, the productivity team. what else is there? first of all, what are the top-level teams other than productivity? Isn't productivity everything?Productivity Teams and Core ChatAkshay Nathan [00:10:55]: SoSwyx [00:10:55]: Science?Akshay Nathan [00:10:55]: We have a team focused on ChatGPT. Like, the core chat experience, for consumer, which is like, not, I think all productivity. Like, there'People are using ChatGPT every day for search to, figure out how to write messages to loved ones, to think about, how to, like, learn a new topic, et cetera. And so there's so much more inside to create images. And there's so much more in chat that, the hundreds of millions of users are using that warrants, like, a very dedicated effort. And there's teams focused on enterprise and infrastructure and API and stuff like that, so.Swyx [00:11:33]: I will bring it up.Retirement Calculator Demo and Git-First UXSwyx [00:11:34]: Yeah. So I have them both running. This is ChatGPT Work. There's a Codex version here. I picked “Five Little Ducks” song, so this will take a while.Akshay Nathan [00:11:43]: Huh.Swyx [00:11:43]: I think we'll just keep it in the background and, as they finish, we'll look into some of the differences.Akshay Nathan [00:11:48]: Yeah. But immediately, I think if you flip back to the Codex version you'll see that,Swyx [00:11:53]: That it assumesAkshay Nathan [00:11:54]: Like theSwyx [00:11:54]: It assumes Git. Yeah. Yeah.Akshay Nathan [00:11:56]: The, like, dynamic island assumes that you're in a Git repo. And you might miss some stuff because some of it is, like, in the actual chain of thought with those changes and how we display that, but yeah.Swyx [00:12:07]: Is there an unintuitive like, is there a thing that you wanted to ship and then you got feedback, and you were like, “No, let's not do it?” Like, what's the thinking behind that?Why Merge the ExperiencesAkshay Nathan [00:12:14]: In, ChatGPT Work?Akshay Nathan [00:12:17]: I think one direction we could have gone with this is, like, keeping the experiences, like, completely separate. So it's like, whySwyx [00:12:22]: Different apps.Akshay Nathan [00:12:23]: Exactly, like different apps or even in the same app, like different, completely different experiences. Like, why merge it all? Like, what is. Codex, people love. Like, why bring these products together? And I think the intuition here is that, like, all of our jobs are, like, changing dramatically with AI. Like, for, like, every few months, like, I feel like I wake up, and I'm, like, doing a completely different thing than I was doing a few months ago. And my hypothesis here is that, or I should say our hypothesis is that, like, part of what we're, we're building, this technology is giving people leverage. Like, the things, maybe it's the more mundane parts of your job or parts that, like, if you were able to automate, you'd be able to share more ideas faster or whatever, like, you're able to do now. And because of that, like, that might blur the lines between someone who's, like, only writing code or creating strategy docs or, planning events or, helping with marketing or doing podcasts or whatever, right? And so, like, these things are gonna get blurred over time. And so, like, trying to draw a hard boundary based on, like, the who you are is gonna be, is gonna be tough. And, like, we should enable users to choose, but we shouldn't box them in. And so a lot of the work that went in here, like, keeping the primitives the same, like for example, plugins are, like, unified across, this product and ChatGPT and the cloud, was because of that. It's this thesis that, like, eventually things are gonna come together and we don't wanna be Like, we wanna be prescriptive about when to be in either experience, but we don't want to box anyone in.Swyx [00:13:45]: I wonder if there's users who are very tuned to the old ChatGPT harness that is effectively now replaced by the Codex harness. I can't imagine what that was, but maybe they're more the more conversational side. Can you compare and contrast the two harnesses? ‘Cause only you've seen it.Akshay Nathan [00:14:02]: Yeah. I think ChatGPT, the existing harness, like, still exists today. Like, it exists in this app,Harness Engineering: ChatGPT vs. CodexSwyx [00:14:08]: The classic, right?Akshay Nathan [00:14:09]: TheVibhu [00:14:09]: You just start a new chat, and you don't go under Work, right?Akshay Nathan [00:14:13]: Yeah. If you startVibhu [00:14:13]: SoAkshay Nathan [00:14:14]: A new chat and go to chat, then you're, you're talking to ChatGPT with the instant model.Vibhu [00:14:16]: Oh, we can technically do another. But on instant.Swyx [00:14:21]: Yeah. So this one's not gonna code or it's gonna be in line. It's on a in line in a sandbox.Akshay Nathan [00:14:26]: It'llVibhu [00:14:27]: Oh, that's coolAkshay Nathan [00:14:27]: We try to push you to go to Work if you're creating a spreadsheet. Yeah, but this isSwyx [00:14:30]: And this is a router decision? Sorry. Is it a router decision?Akshay Nathan [00:14:34]: This is the decision that, the model is making, and then, like it sees that you're able to. or you're trying to do something that would be better served in Work mode. But I think your question was like, what are the advantages of, like, the chat, like ChatGPT chat harness?Swyx [00:14:48]: It's more broadly, like, I wanna, do an oral history of harness engineering. Right? the ChatGPT harness lasted us from, let's call it the ‘01 era, until now, and now it's being replaced by the Codex harness effectively. And they're, they're overlapping somewhat, but I'm curious what changed if there is.Akshay Nathan [00:15:10]: My perspective on this is, like, there's, there's, there's there's like a constant process of, like, divergence, convergence, divergence, convergence. And in chat, like, many of the use cases I was talking about before, like, search or learning, I think we're, we're really optimizing for latency and optimizing for personality and, like, different things that, over time, like the product The reason people love ChatGPT is because we've been optimizing for those things and working on them for so long. Codex, what we learned was that, like, if you give the agent access to this infinitely flexible environment as a computer, it can do really powerful things. And so when we think about, like, okay, well, for knowledge work, like, what is which mode should we choose? It was like it felt more natural to us to bring that to this, like, computer environment and, maybe abstract some of the details of this computer away from users who might not be used to that, but, like, give them that same power. But ultimately, I think that we want the power in all places, right? We wanna meet people where they are. So I'm sure there'll be work down the road in order to get things to be, equivalently capable in all scenarios. But it's just a question of, like, what we've been focusing on the product on historically and what we're focusing on now.Models, Defaults, and the Reasoning SliderVibhu [00:16:24]: I think alongside that, outside of just harness and when to use Codex, ChatGPT, or Work, there's also the new models you've released, right? any guidance there? So people love to min-max what to use, like only use Terra on high reasoning versus, for this, you wanna use Sol here, ignore all theseAkshay Nathan [00:16:44]: There's 32 options.Vibhu [00:16:46]: But, that being said, for people that are expanding, so, productivity trying stuff for work that don't have the breakdown of what all this is what's, what's the advice, right?Akshay Nathan [00:16:59]: Well, I think before the advice, like the first thing is, like, none of this would be possible without these models. Like, the, I think you asked earlier, like, what was, like, the inspiration for work and, like, early on, like I mentioned, like, what we were seeing with Codex, but that was also because the models were getting infinitely more capable. That's happening again. I think it's like another step function jump now. And to answer the question on advice, like we want this default to be the best possible. Like, we wanna be opinionated about the default, and so we've we've chosen a default that we think is gonna be the best for everyone. And, we have for power users options under the hood. We could One could argue that there might be too many right now, and we're, working on simplifying it. But you can extend, the reasoning level, and you can change between the different model classes if you need to, but the default should be the best for most use cases. So my advice to most people would be to stick to that. And then, if you reach a situation in which you think that you could, you wanna try, a different configuration, if you're not seeing either the efficiency on the cost side or the quality on the intelligence side, then you can change the defaults and see if you can get something better. But we think that the default should be good enough.Swyx [00:18:09]: I have, I'm just gonna run something by you since you have way more experience than me. I've recently been doing Sol Lite but with goal, with the idea that the goal augments the reasoning effort, but with more terminations and turns.Swyx [00:18:24]: Is that a good way to think about it as opposed to Sol Ultra or Sol, Extra High?Akshay Nathan [00:18:29]: Yeah. It's hard to say becauseSwyx [00:18:31]: Yeah. It's like an interaction effect.Akshay Nathan [00:18:33]: exactly. It's like there's a preference on, for you as an individual, like how do you like to collaborate with the models? Like how many of those like terminations, as you call them, do you want where, you can steer or make sure that it's doing the right thing?Akshay Nathan [00:18:46]: I think generally people should try whatever works for them. I think that like using Ultra or the like multi-agent setups are best for like when you have like tasks that are either incredibly complicated, like open explorations or very paralyzable. I think even for tasks using goal, I think is best for tasks that you'll be able to make consistent progress in a way that's verifiable over time. But I think for most tasks, they don't fall into either of those buckets. And so like at least when they're starting, and so that's why I think the best first step is like trying it with the default configuration and then seeing like where you wanna go from there.Swyx [00:19:29]: Right. You guys worked on a slider, which is super helpful for reducing the amount of panic.Vibhu [00:19:36]: It's nice on mobile at least. There's a nice slider there.Swyx [00:19:38]: It's nicer.Vibhu [00:19:39]: I haven't tried it.Swyx [00:19:40]: So you have the advanced view there, but if you click advanced view. Yeah.Vibhu [00:19:44]: Ooh, it's just a nice slider. Yeah.Swyx [00:19:46]: Very pretty, very colorful.Akshay Nathan [00:19:48]: Yeah. The idea was here was like reduce it to like one dimension even though there's multiple dimensions, right? Try to project it onto a single dimension for the user. Like, something from that represents like, speed and efficiency on one side and then like quality and thoroughness on the other side.Artifacts, Spreadsheets, and the Work LaunchSwyx [00:20:04]: I am just puzzled that it uses Sol so much, like the lowerVibhu [00:20:07]: NoSwyx [00:20:07]: Grounds I would've usedVibhu [00:20:08]: I think the slider, if I'm not mistaken, isSwyx [00:20:09]: Terra.Vibhu [00:20:10]: Oh, it is.Swyx [00:20:11]: Yeah. See? So they preset Terra to only be the light one. But like I think a lot of people would more people should use Terra. One, because Sol keeps running out of capacity.Vibhu [00:20:22]: I'm the reason. Here's ten minutes of ourSwyx [00:20:24]: There you goVibhu [00:20:25]: Retirement calculator.Swyx [00:20:26]: Oh, that's the Excel thing working for you.Vibhu [00:20:28]: This is,Swyx [00:20:28]: Oh my God. Look at thatVibhu [00:20:28]: This is work, and then Codex is still cooking, so we'll get back into it. I think it'll be interesting to see the thought process, the reasoning, and also, this is eight minutes on work. Codex is still cooking.Swyx [00:20:41]: Yeah. And by the way, so I've, do Gabriel Chua? He's part of the OpenAI Singapore team. He showed me this, and I was like pretty shocked that this looks like Excel. It edits Excel files. You never paid an Excel license, right? Like, but somehow this is like workable and it's agentic Excel.Akshay Nathan [00:21:01]: Yeah. one of the big like pushes that we made for this launch was like artifacts, right?Akshay Nathan [00:21:05]: Like both on the model side, like I think if you compare this with GPT-5.5 and GPT-5.4 before that, you'll see that there's been pretty dramatic improvements in the quality of these artifacts and then also on the product side.Vibhu [00:21:16]: The UX side is also crazy, like hosted sites and whatnot. No longer needing to host your own little webpage, like itSwyx [00:21:23]: Oh, I have a story about that. I can do, a separate thing. I'll need to take the visuals here, but we-we'll, we'll cut to that later. Was there co-training, because you were moving making this big move and you launched GPT-5.6 on the same day as ChatGPT Work? Was there influence between the model training teams and the harness teams, or did they did the launch dates just happen to line up the same day?Akshay Nathan [00:21:46]: I think the we collaborate heavily with the research teams, and I think that's like one of the most magical parts of the job, like the most fun parts of the job. But yeah, just using artifacts as an example. Like, a lot of what you're seeing, like underneath the hood, there's a lot of work that went into making sure that like, we had the right infra to be able to train the models to get better at this. And then on the product side, like had the right experience for users to be able to collaborate with the model on an artifact like this. In fact, like this whole viewer, like the intuition here is that like, it's not necessarily that you wouldn't need an Excel license. This is stage one, right? Like, this is probably not what you meant when you're like making a retirement calculator.Vibhu [00:22:24]: Yeah, you can iterate very easily. Yeah.Akshay Nathan [00:22:24]: You wanna iterate and like when you're seeing it, and if this thing is high fidelity to like what you would see in or what your coworkers would see if you were to send this to Sean, like that I think makes it so easier and makes you trust the product in terms of iteration.Vibhu [00:22:39]: When you say coworkers would see, do you see a multiplayer, multi-team collaboration with artifacts? Any things you guys think about that?Multiplayer Artifacts and CollaborationSwyx [00:22:46]: You can already share it, right?Akshay Nathan [00:22:48]: Yeah. It's inter It's something that, we're actively thinking about. one thing that, we've noticed internally without talking too much about the roadmap is that like there's many times when someone will ping me about something, and I will ask ChatGPT Work the question, and then I'll ping them back the answer.Akshay Nathan [00:23:04]: And then I'll be thinking likeVibhu [00:23:04]: Like the simplest would be, the three of us are just all on one hosted.Akshay Nathan [00:23:07]: Exactly. And I'll think about like was I required in this loop or and then maybe it was, rephrase like what they were asking or pulled from certain context or whatever. But like, when I gave them back the answer, that process was also lossy, right? Like I gave them just like my interpretation of what ChatGPT Work cooked up. But like underneath the hood, there's so much context like in the rollout and stuff that could be interesting.Vibhu [00:23:28]: Yeah, it'sSwyx [00:23:28]: So like the answer was preemptively respond to every inbound request?Akshay Nathan [00:23:33]: No, it was just like literally like this is what I do sometimes as my job.Swyx [00:23:36]: I know you copy-paste and then you're just a message forwarding serviceAkshay Nathan [00:23:39]: Yeah. Yeah, exactlySwyx [00:23:39]: From AI to AI.Vibhu [00:23:40]: But I think it's interesting, right? It helps people understand the capability of what you can ask and delegate that oftentimes people don't realize until they try or someone shows you, and then you're like, “Oh, okay. Okay, I see.”Swyx [00:23:52]: I think it's als there's also like a, light security issue, where like you're the permissions layer. Like yes, I could query everything that you query, and I could get an automated response, but maybe I'm not supposed to see it. And that there's no way I would know because I'm not supposed to know what I don't know.Akshay Nathan [00:24:07]: Especially as like, with ChatGPT Work, we're, we're asking you to connect your plug-ins and, it's pulling from your local files and stuff like that. Like the amount of context that the agent has access to is like- Deeply personal and like that's something I think we need to preserve, so that'll be definitely a challenge.Swyx [00:24:22]: There's Excel, there's PowerPoint, there's Docs, the, grand trio of work. What other formats of work do you think about? like you worked on Airtable. Is there a future where there's like OpenAI Airtable? Like what does that look like if you ever ended up doing it?Akshay Nathan [00:24:41]: It's a really good question. I think,Formats of Work: Sites as Knowledge ArtifactsAkshay Nathan [00:24:43]: one that you didn't bring up was Sites, and I think that wasSwyx [00:24:46]: SitesAkshay Nathan [00:24:46]: A core part of this launch. There's one side of Sites that I think people commonly talk about, especially on Twitter and stuff or X, of like, this like prototyping tool. And like we saw that happen with this launch even. The model slider that you guys were referencing earlier, like that was developed almost fully in a Site. Like, the collaboration between design and engineering and product on that was like on a site where we play with, the affordance and figure out how it feels and all of that. But the other aspect that I think is a little bit less talked about is like Sites as like an artifact for knowledge work. I was talking to someone the other day who's on like our corporate finance team, and like we were mentioning how like now when they have these reports that they're, they're working on as a team month to month, historically those things were in slide decks and in spreadsheets, and now they're just in Sites. And like Sites is the mechanism that they collaborate across the team. And the reason is ‘cause it's like, it's like somewhat higher bandwidth. Like, at these tools like PowerPoint and Excel are like infinitely flexible, but at some point you reach the boundary of like either as a human you may not know how to use some feature or something, or the product itself doesn't support it. But with a site you can do anything. You ask for anything and you can get that. once people see that magic, I think it's been really valuable.Swyx [00:26:02]: Yeah, let me show you my case study. this involves all the hot topics including ChatGPT Work, but also GPT-5.6 token billionaires and token maxing and Sites and auto research. I'm a fan of this game called Strata. It's, it's like a little board game that youSites, Auto Research, and Research DashboardsSwyx [00:26:17]: That you play with, physical blocks, that come on top of it like that. So over the weekend I took like thirty photos and just threw into ChatGPT. one point seven billion tokens later, out comes this site with a fully playable thingAkshay Nathan [00:26:32]: WowSwyx [00:26:32]: With 3D, block placement and everything. Because it requires physical blocks and I needed friends to train on it so they can get better, so I can play against them. But also, I could also, do things like train an AI on it and that's, thatAkshay Nathan [00:26:45]: That's your auto researchSwyx [00:26:46]: That gets into auto research. So, you want to train your own AIs, and then make sure they self-play against, each other. I need to set both AIs. So this is AI versus AI, and they're, they're gonna self-play. the AIs start out bad and then you want to define a loss function and get good. I wasn't gonna supervise all this. I was at, I was down in San Mateo, attending a conference. What I ended up doing was, auto researching and on this and creating benchmarks and that there was just way too many parameters for me to read. So I started asking it for a site, and it's created this lab, panel. Where is there a, is there a shortcut for a site that is created?Akshay Nathan [00:27:28]: You should be able to go in the sidebar to Sites, top of the sidebar. The left sidebar.Swyx [00:27:33]: This one? Oh, left?Akshay Nathan [00:27:35]: Yeah. Just scroll all the way to the top.Swyx [00:27:36]: Oh. Oh, it says Sites. Oh, there you go. Yeah.Akshay Nathan [00:27:39]: Ooh.Swyx [00:27:40]: So it create, it creates the sites. I don't, I don't think this is, it is exactly what I wanted, but let me show you what it popped up, right? Like I think as a research artifact, it is very important to communicate, exactly, what is being done. Outputs this thing which I eventually started publishing. So I moved it off of Sites because I wanted more, database and infrastructure than Sites afforded me. But this is like a research output that you can start to mess with and like try to think about like what hyperparameters are you tuning for training AIs. And like I was trying to make like scaling laws and everything and doing all sorts of like game optimization stuff. And the fact that you can just throw this up as a research artifact, like I no longer need to read ChatGPT output. I read Site output. But then there's also a huge sprawl. Like look at how long this thing is. There's so many numbers. It is pretty overwhelming, so then I have to start pruning it from there. But, it's an interesting transition from Markdown effectively that you're putting out to, you're putting out a whole functional site.Akshay Nathan [00:28:41]: I think Markdown just isn't that optimal for people to read, right? Might as well just write HTML website and I don't know. I think you can do a lot with customizing this, right? You have your skills that explain what you want. Like I noticed they're quite verbose. I don't need a lot of this information.Swyx [00:28:57]: It's very verbose.Akshay Nathan [00:28:58]: So and then the nice thing of having a site side by side is, you just iterate on what you want and what you don't, right?Swyx [00:29:05]: Yeah. I don't know if, any that triggers any stories for you of how it's run internally. Am I doing this right?Akshay Nathan [00:29:11]: Yeah. I think that this is like a workflow that we're seeing like all different types of teams use, where like the canonical artifact that was previously a deck or something is now becoming a site. And like with a site you, because it's just HTML, you can like. It's infinitely flexible. And so, if you want to give more prominence to a certain thing that like in a slide deck would, feel like it was buried, like you can do that. You can have it be like the hero image, right? And so I think that like, people are starting to see that. There's more work to be done to make these things like much more easier, easy to collaborate on. You mentioned that they're very, they're long and verbose, could be broken up. I'm sure that there's still something to do there.Swyx [00:29:53]: They're super long. Yeah.Akshay Nathan [00:29:54]: Yeah. But I think we're starting to see that like there is this aspect of this is a really interesting, format, for people to use, that's like much more flexible than what they ever had before.Swyx [00:30:07]: I think your job also comes becomes meta. You're not designing the products. You're designing a product to make products, and I'm curious how you manage that.Designing a Product That Makes ProductsAkshay Nathan [00:30:18]: I think one thing that we've been Like when we look at the UX, like that we've been thinking a lot about is how can we balance like simplicity with capability? Like if we're designing a product, like you said, that like is made to make up build other things, right? You can build so many different things. But we can't put that all in front of you because you'll get overwhelmed.Vibhu [00:30:41]: Yes.Akshay Nathan [00:30:41]: And so we had similar problem or similar challenges even Chat-with ChatGPT, but especially now, like when there's so much that can be done, I think the balance that we're constantly trying to strike is like, how can we give the user enough of a UI surface where, they can be expressive, they can tell the agent what they need, they can verify that it's using the right tools, it's pulling from the right sources, et cetera, but then it gets out of the way. And then how can we build the right system such that we can show them instead of telling them what can be done? Because so much of this is gonna be like, how do they discover the next use case and the next one after that if they really want to be super powered by the AI.Games, Private Evals, and Show-Don'TellVibhu [00:31:19]: Yeah. It's interesting. I feel like everyone also just has a different way to do it, right? I made a similar version of this same game. I didn't take any pictures of board or rule game. I threw in at goal eighteen minutes, fifty-three seconds later, a lot of tokens later, I've got a similar version. not with all the auto research and whatnot, butAkshay Nathan [00:31:39]: You gotta do all the latest trends.Vibhu [00:31:40]: And yeah, I did it with, did it with Codex, not Work, but it's interesting, right?Akshay Nathan [00:31:45]: Yeah. And this is GPT Image generating the pro avatars. Very good for game design. LikeVibhu [00:31:51]: AndAkshay Nathan [00:31:52]: A lot of game designers were like really into GPT Image for assets.Vibhu [00:31:54]: I will say like the broader takeaway probably is the reason that we do this is more so just to test the tools, right? Like, this was also a test for GPT-5.6 came out. I had done the game on GPT-5.5, right? The ability for me to no longer need it to. I had to feed it the rules. It's, it's a pretty niche game. It couldn't find how to do this on its own.Akshay Nathan [00:32:15]: Oh, yeah.Vibhu [00:32:15]: GPT-5.6Akshay Nathan [00:32:16]: It is out-of-distribution, which is why I was also very keen on testing the GPT-5.6 capability.Vibhu [00:32:21]: But, this is just as work comes out, as new things come out, these are just our side ways to test things, right?Akshay Nathan [00:32:27]: Yeah. It's some private eval. That is not this private.Vibhu [00:32:31]: But also valuable because now you can send this to your friends and I learned about this game through seeing this.Akshay Nathan [00:32:36]: It's a hard game. He's very good.Vibhu [00:32:39]: It's good to when no one is competing with you. But yes, it's a classic RL problem of like self-play, bootstrapping your game AI. yeah, you see how easily work becomes personal and personal becomes work because the thing I do for personal, it directly informs people I work with because I showed it to them. They were like, “Oh, you can do that with GPT?” Which like I imagine is the growth strategy.Akshay Nathan [00:33:02]: Yeah. The show not tell is a big piece that, I think we've we're not still not fully cracked of like, showing people all the things that they can do with the product versus like trying to teach that to them through like, articles or onboarding or whatever.Akshay Nathan [00:33:18]: So meeting them in the moment.Vibhu [00:33:19]: It's a career risk for me, because I used to be in developer relations, right? Where your job is to show, and then you're like, “What do you mean? You don't, you don't need.” your job is to tell. And then. But the product people are like, “Well, we don't need you if our product is intuitive enough.” SoAkshay Nathan [00:33:37]: Yeah. that's the magic of the models. So you can tailor the telling or the showing to like specifically what the user needs, like what they care about, what they've done in the past, exactly where they are on the adoption journey. So I think that's like gonna be a super big opportunity.Vibhu [00:33:50]: Seems easier and easier now to tailor custom showing, right? People have different use cases. As much as you said you don't wanna segment different people into different buckets, right? It's also not that hard to for people that are in different categories. But the question, is you said your team is more broadly on. What was the term you used? Productivity?From Developers to Knowledge Work to EveryoneAkshay Nathan [00:34:12]: Productivity.Vibhu [00:34:12]: Productivity. So howAkshay Nathan [00:34:12]: Which is now work.Vibhu [00:34:14]: Is it work? Is there another distribution that we're not hitting? Is there a group of people that will have something different than ChatGPT, Codex or Work? Is there more that the mass isn't targeting?Akshay Nathan [00:34:28]: I see it as like a sequencing, like. The vision is like bring useful agents to everyone. We started with like developers. Like developers historically are like early adopters that are willing to put up with more friction, set things up, et cetera. Like that's where, Codex started. I think the next opportunity is like what we call general knowledge work, all the other functions around developers. I think when you go from developers to this segment, like there's inherent challenges with like, this show not tell thing that we're talking about, making the product more understandable, bringing in new capabilities that matter more for this cohort than matter for developers, things like artifacts, things like computer use, et cetera. And then I think like the same learnings, like similarly how we took the learnings from developers and brought it to, general knowledge work, the next stage will be like taking the learnings from general knowledge work and bringing it to everyone no matter what they're doing in their lives. And we're already seeing that a little bit. Like this game example that you have is, something that's like on the border of like fun and personal life to, your professional life. I use ChatGPT Work full-time at home for everything, like for whatever I'm doing. I used it the other day to come up with a meal plan and like, save that on the like computer environment that it has and something that I can continue going back to. Like is everyone doing that yet? Probably not because the thing says work on it, but eventually, we wanna get people there.Vibhu [00:35:51]: ChatGPT life.Akshay Nathan [00:35:52]: Yeah, exactly. ChatGPT cooking. But I think there's a lot of, there's a lot of opportunity there, but I see it as like, we're, we're built we built a foundation in software engineering, and we're gonna take the same learnings that we take from software engineering to knowledge work to everyone.Vibhu [00:36:07]: Do you have any power user advice? I feel like, there's a group of people that will live it, use it for everything, stay on it twenty four-seven. And then there's a bit of a gap between that crew and people that, okay, I use it for work. I use it occasionally. Sometimes I type questions. any advice, any learnings, anything you recommend or just, takeaways that you've found that help bridge that gap?Power User Advice: Push the Frontier of ImaginationAkshay Nathan [00:36:30]: I think a couple things that I've seen is like, one, that it really helps to broaden your imagination of what's possible, and this has been a learning even for me. Like, the technology has progressed so fast that, something that, like, even three months ago, like, no way the models can do this. Like, now it's like, wow, it's like it can. Like,Swyx [00:36:52]: Give an exampleAkshay Nathan [00:36:52]: We're going through right now our, like, review cycle internally, and, people always talked about this as, like, a thing that the models are good at and like, there's a cliché of like: Okay, like, no one wants to be writing reviews and, like, we just use AI to do it. But in all seriousnessSwyx [00:37:09]: And it can evaluate it as well.Akshay Nathan [00:37:10]: Yeah, exactly. In all seriousness, before it was, like, just, like, slop and, like, I think it was helpful, but, not super productive. Now I've found that, like, the model can do a much better job than me, especially in this environment of, like, pulling context on, like, what people are up to, how they've like the things that they've done to make a difference, highlighting like, wins that they've had that, like, I might may not even have seen. It has access to, like, everything, right? Like the code, like, things that they've caught, reviews, Slack, everything. And so it's, like, incredibly powerful in that domain and, like, just like six months ago, the last time we did this cycle, like, I didn't even I tried using it, but it was not at all helpful. And this time it's been, like, incredibly helpful and, like, so I think continuing to push the frontier of imagination of what's possible, even if you tried something before, I think is maybe the my biggest piece of advice. The other, thing is, like, the more you put in, especially in this environment where, like, the model has access to everything on your computer or in ChatGPT Work, like you can create, artifacts over time and save them in your library and, like, the model will continue having access to those. Like, the more information you give it about whatever domain you're in, whether it's your life or your work, the more valuable it becomes, and it'll become valuable in, like, ways that might surprise you. Like, it might pull from context in a way that, may be proactive and that you might not even have thought about. But it needs to have access to those, to that those tools or that context first.Reviews, Agentic Search, and Context GatheringSwyx [00:38:27]: One thing I just wanna talk about the review stuff because I'm still that's a very sensitive thing and you're, you're a founder, you've managed people, you've hired people. As manager myself, I'm very reticent to put out any LLM-generated things especially when it comes to people, ‘cause it feels like you don't care.Swyx [00:38:46]: Presumably at OpenAI, people are more open to being eval rated by GPT. But are there any unofficial rules around this? Like, what's the etiquette?Akshay Nathan [00:38:57]: Oh, I think the etiquette is that, like, I would never write something via, like, well, solely via AI and, like, present it as, like, a review for someone. What I was talking about is more, like, gathering context. That's the place where it's incredibly helpful.Swyx [00:39:08]: So it's just search.Akshay Nathan [00:39:09]: Yeah, exactly.Swyx [00:39:09]: It's agentic search. Yeah.Akshay Nathan [00:39:10]: It's like agentic search, but, that you can tailor and steer much more capably than you could before, ‘cause, like, the thing is it's all there's a flywheel happening, right? Because of Codex, people are able to do, and because of ChatGPT, people are able to do so much more now than ever before. And if you're able to do so much more, it's easy to miss things as well. And so, like, I think we need to use these same tools to keep up with all the impact that people are having and understand, where we can be helpful.Swyx [00:39:39]: I think the thing, like, I run a small company, so easy to search, but at the scale of OpenAI with the amount of messages that you guys put in Slack, do you think that it misses things?Remembering What Humans MissAkshay Nathan [00:39:50]: Probably, but I think that I also miss things.Swyx [00:39:52]: Like, it doesn't matter, right?Vibhu [00:39:53]: I think sometimes it'sSwyx [00:39:53]: Like it's, as it needs to be human-levelAkshay Nathan [00:39:54]: It's all relative, right? Yeah.Vibhu [00:39:56]: Sometimes it's nice when it finds things you wouldn't, right? Like right now, my Codex system prompts, they're set up in such a way that every project I have has a secret- separate, notes MD, and it just writes learnings to there. And then the global one can pull from all these. So sometimes it'll be like: Oh, there's this project you did like four months ago. Here's a note that we had, and it randomly pulls it back into context that I would never do, I haven't thought about.Vibhu [00:40:20]: And I'm like, okay, this is quite superhuman, right? Like, stuff that would. And, it'll save like hours on chunking of stuff or find something that's already been done. I'm like, as much as it might miss stuff, I would too, but it's very useful when it finds stuff. And I have like a very, non-super engineered solution to this. It's just marked down files that get pulled whenever they want.Akshay Nathan [00:40:41]: Yeah. I have a funny anecdote about this. Like, recently gearing up to this launch, the team has been, really cooking on it for a couple months, and over that time, like there's so much conversation and chatter going on in Slack and Docs and elsewhere. And, one of the members of the team set up this, scheduled tasks, like automation to like look at everything that's going on and, like, come up with the best memes and then post it in one of our shared channels. And like, there are two cool things about this. Like, the first is, like, I think the models are, over time, like starting to become like funny.Swyx [00:41:13]: Funny. Nice.Akshay Nathan [00:41:13]: Whereas like, a year ago, like that was not at all the case. The second is, it was what you were saying, like they find things that in surprising ways that you may not have thought of and like create connections that you may not have thought of. And that really helps with like the meme generation because then you can see something that, genuinely surprises you and, is funny in that way. So yeah, that's like not like the most productive, use of this the technology, but it does it does uncover this, like this capability that's emerging, which is just like to find information that you otherwise would not know of.Launch Momentum and the 10 Million User MilestoneSwyx [00:41:43]: Talking about the launch, I think, I have pretty much said this is the most successful launch in a long time. I think even more successful personally than 5.0, and they're announcing ten million users. Does it feel different? You've been through a lot of launches.Akshay Nathan [00:41:58]: I think it feels like a culmination. Well, I think two things. One, it feels like a culmination, like I was mentioning earlier, like this like vision mission that we've been on for a long time. Like I said, we saw the magic of Codex internally, and then we're like extremely excited to bring this to many more people and to see it working, to like see us reach, the distribution goal, numbers that you mentioned, like I think that's like huge and super exciting. The flip side of that is like, there's so much more to do too. Like, that's also really exciting. Like, ChatGPT as a whole, like the this product that, everyone almost equates to AI and like loves, has hundreds of millions of users. And so like ten million is really cool, but like we need to get this to everyone. Like, we need everyone to feel this magic. And so that's the next step from here. But yeah, I think extremely pumped about how it's going so far and the opportunities.Swyx [00:42:46]: Awesome. I did want to also Because I've, I've, I've been tracking the number closely, it transitioned at some point from just Codex users to Codex plus ChatGPT Work, because they're same harness. The whole point is that you don't, you can't, count them separately. Do you have roughly a billion, ChatGPT users? Why did it just jump to one billion right away? Like, isn't that the default on ChatGPT or no?Codex, ChatGPT Work, and the Developer BrandAkshay Nathan [00:43:11]: We don't default you into ChatGPT Work if you're on ChatGPTSwyx [00:43:14]: If you're free. YeahAkshay Nathan [00:43:15]: It's also only available to paid users right now. And I think there's like a process of, educating users of what is the value of this product, having them try it, learning from their feedback, and making it better over time. But the goal is to, get as many of the people who love ChatGPT today to like feel the power of ChatGPT Work. But I think it'll be a journey.Swyx [00:43:36]: Yeah. And Codex will still be alive as a brand for the foreseeable future. And we'll just toggle between them as needed for UI stuff.Akshay Nathan [00:43:44]: Yeah, I think it's even stronger point than that. Like, I think we fully intend to like, treat developer. Like, developers have been, a core market for us for so long, and like there's, there's so much more that we can do to make Codex great specifically for, software development, and we'll continue to do that. This doesn't take away from that at all. If anything, it should increase the utility of something like Codex, because now you can move seamlessly between writing a diff to creating an artifact or, doing a search over your factor.Swyx [00:44:11]: I do wonder how much this terminology leaks to the non-technical user. Like, do they have to learn to say artifact if I want artifact? Or.Akshay Nathan [00:44:20]: It's funny, like we call it artifacts internally ‘cause that's what the teams call it.Swyx [00:44:23]: It's nice. Yeah.Akshay Nathan [00:44:23]: But like externally, like no one says that, no one calls it an artifact. But I think that people like often, like describe things, whatever they're used to, right? So if, ChatGPT Work is good at creating slides, they'll say ChatGPT Work is good at creating slides, and that's what we want.OpenClaw, Personal OS, and Persistent ComputersSwyx [00:44:38]: One big Another, it's July of twenty-six. One big thing that also happens in, for OpenAI was OpenClaw, and that's I think a lot of people's first time really maxing a agent for personal stuff, but also crossing over to work in essence same way. As far as I understand, OpenClaw is still independent, but did you go through your own OpenClaw moments? Were there any lessons you took from OpenClaw to Codex or back? Whatever.Akshay Nathan [00:45:06]: I think there's a lot of inspiration. I did go through my own OpenClaw moment. I,Swyx [00:45:10]: Yeah, tell the storyAkshay Nathan [00:45:10]: Me and my wife like set up an OpenClaw to like try to manage everything in our house. Not that there's like a ton, but it was like quite useful. We gave it a calendar. It started, creating events for us and stuff. At some point, the laptop that we were running on, it died and never got a chance to pick it back up. But there was a lot of inspiration there, like, in ChatGPT Work, in web and mobile, like you get access to this like persistent computer environment where, you can store files, and those files stay around between sessions. And the idea is to be able to enable use cases like this. one of the members of our team uses ChatGPT Work for what they used OpenClaw from before, and then feel like it has like completely transitioned, which is like, workout planning and like meal tracking. which again, it's like a work-related thing, right? It's like not work necessarily, but it's like in personal productivity space. But it has all the same primitives. So it has scheduled tasks. It has the ability to store files on a file system. It has the ability to like reference those things over time. And so you start to see the same types of use cases emerge, which has been really cool.Swyx [00:46:14]: Is there a point that ChatGPT Work completely replaces OpenClaw? they're independent, so.Akshay Nathan [00:46:20]: Yeah, I'm, I'm not close to it, so I can't speak to the OpenClaw roadmap, but I don't think so. I think that there's gonna be, there's always a need for like this like incredible, like open source technology that team has built. And I think that we can draw inspiration, in the product and, ChatGPT, I think many more people have like heard about and used ChatGPT than have used OpenClaw. And if we can take the magic from OpenClaw and bring it to them, I think that'll be a success. I think that like one thing on the ChatGPT Work side that we feel strongly about is that like the core experience is that you come to this product and you have a conversation, start a session, whatever you wanna call it, with this agent. And the magic of the product is that you can do anything in that moment. And we would like to create a product where you don't have to click a button or to go to a different place, whatever, and you can get whatever functionality exists in, your finances app or where or any other product like in this one place. And so that's the goal. It's like it we want an extensible system with plugins where you can connect to the tools that you need in order to be able to accomplish like a financial task, where you can, if you're doing like science work, like we have an ability to like extend the system in such that you can like write the tech and it performs well. There'll always be like products that we support that are best in class at those things, but we want as much of the magic as possible in that core experience.Swyx [00:47:45]: Yeah. Do you think that you can do everything you used to do with Wealthfront in ChatGPT Finance?Finance, Data Access, and Centralized ContextAkshay Nathan [00:47:50]: I tried it. like ChatGPT doesn't yet custody, cash and assets for me. So that part, no, not yet. But I, there was like a whole component of like retirement planning and, like financial planning and budgeting and stuff that, we were looking into when I was there. And like with the finances plugin, like that's all possible with ChatGPT today. So, I feel

In this episode, Kamille demonstrates the power and limitations of using Claude and the Model Context Protocol (MCP) to build an Airtable base from scratch. She walks through a live experiment where she prompts Claude to create a complex meal planner, including tables for recipes, ingredients, and a shopping list, as well as the necessary automations and interfaces. The team also dives into recent Airtable updates, including the new Slack integration and the ability to manage automations via MCP. They discuss the current limitations of AI-driven base building—such as the inability to edit existing interfaces or handle script steps—and compare the experiences of using Claude versus Airtable's Omni.

Get up to speed on the latest Airtable news and learn how to expand your no-code toolkit with Softr. We start with a breakdown of recent Airtable automation updates that make handling arrays much easier, saving you from unnecessary schema complexity. Then, we jump into a practical build. Watch as we use Softr to create a teacher portal powered by Airtable. We cover everything from user login and onboarding to implementing global data restrictions so users only see the records they are authorized to access.

Ever felt the pain of updating hundreds of records one by one? In this episode, Kamille Parks shows you how to build a custom "Bulk Updater" tool directly within Airtable to save hours of manual work. We walk through a real-world scenario—managing event meal requests—to demonstrate how to handle new, revised, and removed entries. Whether you are a scripting pro or prefer using Airtable's native automation features, you'll walk away with actionable strategies to level up your interface designs. Plus, we share some "under the hood" insights on navigating the complexities of Airtable's Interface Designer and the nuances of Record Review pages. Resources Bulk Upload Wizard - https://www.airtable.com/universe/expan0oT3Npoh6LtY/bulk-update-wizard The base Kamille shows full of advanced functionality to explore bulk updates and conditional visibility with full automations in both scripting and non-scripting workflows.

Did you like the episode? Send me a text and let me know!!No Money, No Problem: The Step-by-Step Framework for Finding a Technical Co-Founder Using ValidationEpisode Summary: You have the idea. You have the drive. You have absolutely zero cash for salaries. So how do you find the brilliant technical partner who can actually build the thing — and convince them to join you? In this episode of Business Conversations with Pi and Piette 2.0, PI and Piette tackle one of the most dangerous and high-stakes challenges in entrepreneurship, driven by a real listener question from tuepodcast.net/askpi.Drawing from Harvard Business School research, Y Combinator strategy, Mike Moyer's Slicing Pie model, Dan Martell's co-founder playbook, and startup employment law, this episode delivers the exact blueprint for building a technical team when cash isn't an option — and reveals why that constraint might actually be your greatest advantage.What You'll Learn:Why 65% of startups die because founders hate each other — not because they ran out of moneyWhy you probably don't need a developer yet — and the no-code trap most founders fall intoHow to build leverage before you pitch anyone using no-code validation toolsWhere to find technical co-founders beyond your immediate networkThe 90-day rule that forces a decision and prevents analysis paralysisHow to vet a developer when you don't know a single line of codeDan Martell's "10-hour weekend test" and what friction response revealsWhy a 50/50 equity split on day one is called the "quick handshake penalty" — and how it kills valuationsHow Mike Moyer's Slicing Pie dynamic equity model works with multipliersThe employment law trap that can destroy your company before it startsWhat a four-year vesting schedule and one-year cliff actually mean — and why they protect everyoneTimestamps:[00:00:00] – Introduction & The Listener Question[00:01:00] – The Harvard Study: 65% of Startups Die Because Founders Hate Each Other[00:02:30] – Why Co-Founded Startups See 163% More Valuation Growth[00:03:30] – Do You Actually Need a Developer Right Now?[00:04:00] – No-Code First: Webflow, Airtable, Bubble — Validate Before You Build[00:04:30] – Dan Martell's Filter: Why Top Developers Ignore Idea Guys[00:05:30] – How to Show Up With Leverage, Not a Pitch[00:06:00] – Where to Find Technical Co-Founders: Start Closer Than You Think[00:06:30] – Michael Seibel's Strategy: Make a Real Offer, Not a Favor[00:07:00] – Friends vs. Strangers: The Surprising Data on Who Makes Better Co-Founders[00:08:30] – Co-Founder Matching Platforms: YC Cofounder Match & Start2Pitch Explained[00:09:30] – The 90-Day Rule: Set a Hard Deadline or Fall Into Analysis Paralysis[00:10:30] – How to Pitch Vision When You Have No Cash[00:11:30] – How to Vet a Developer When You Can't Code[00:12:30] – Dan Martell's 10-Hour Weekend Test & the Friction Response Framework[00:13:30] – The Equity Conversation: Why 50/50 Is a Trap[00:14:30] – Noam Wasserman's Quick Handshake Penalty & Investor Red Flags[00:15:30] – Mike Moyer's Slicing Pie: Dynamic Equity With 1X and 2X Multipliers[00:17:30] – The Employment Law Trap: Can You Legally Pay People Only in Equity?[00:19:00] – Contractors vs. Employees: The Classification That Could Destroy Your Company[00:19:30] – Vesting Schedules & the One-Year Cliff Explained[00:21:00] – The Full Playbook Summary[00:22:00] – The Mind-Bending Final Question: Do You Even Need VC Money?[00:23:00] – Submit Your Question & Wrap-UpPlatforms & Resources Mentioned:

#990 What if the AI tool you swore by six months ago isn't the one you should be using today? In part 2 of this two-part episode, Kinsey Soderberg returns to dig into the practical, ever-shifting reality of building a business with AI. She talks candidly about switching from ChatGPT to Claude (and back, and back again), why she recommends going deep with one or two tools instead of chasing every shiny new app, and how to actually know when an AI-generated output is ready to use versus needs more polish. Kinsey also breaks down her go-to framework for automating a task — start manual, refine it, turn it into a skill, then automate — plus how she's using Airtable and Claude together to track her growing pile of subscriptions and tools. We close out with reflections on niching down, bringing real-world expertise to AI workflows, and advice for young entrepreneurs figuring out their own path in the age of AI! What we discuss with Kinsey: + ChatGPT to Claude switch (and back, and back again) + Bringing expertise + AI = the real magic + When to trust AI output vs. polish it more + Avoiding shiny object syndrome with tools + Going deep with one or two tools, not all of them + Manual first, then skill, then automate + Niching down as an AI freelancer/consultant + Using Airtable + Claude to track subscriptions + Claude Code and "plan mode" thinking + Advice for young entrepreneurs in the AI era Thank you, Kinsey! Check out Part 1 of this episode. Check out Authentic AI at ⁠AuthenticAI.co⁠. Get a free ⁠AI System Snapshot⁠. Join ⁠Her AI Club⁠. Watch the ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠video podcast⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ of this episode! To get access to our FREE Business Training course go to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠MillionaireUniversity.com/training⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ To get exclusive offers mentioned in this episode and to support the show, visit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠millionaireuniversity.com/sponsors⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Learn more about your ad choices. Visit megaphone.fm/adchoices

#989 Ever wish you could clone your brain into ChatGPT or Claude and have it actually sound like you? In part 1 of this two-part episode, we sit down with Kinsey Soderberg, founder of Authentic AI, who helps entrepreneurs (especially women) use AI tools without losing their voice, quality, or thought leadership. Kinsey breaks down her five core strategies for "training" an AI assistant on your brand — vision and values, ideal customer, voice and personality, offer ecosystem, and messaging/stories — and explains why she hosts all of it in an Airtable "brand brain" connected directly to Claude. We also dig into content systems (idea banks, content calendars, and auto-posting), the difference between automation tools like Make, n8n, and Zapier, and how Claude Skills can supercharge your workflows without needing to know how to code. Whether you're just starting to experiment with AI or ready to build out full automation systems, this episode is packed with practical, real-world ways to make AI work for your business — without sacrificing what makes it yours! What we discuss with Kinsey: + Training AI on your brand's 5 core strategies + Vision, values, and mission first + Defining your ideal customer for AI + Going deeper than "friendly" brand voice + Mapping your offer ecosystem + Sharing stories AI can't invent + Airtable as a "brand brain" database + Claude Skills vs. markdown files + Building a content hub and auto-calendar + Make vs. n8n vs. Zapier automation Thank you, Kinsey! Check out Part 2 of this episode. Check out Authentic AI at AuthenticAI.co. Get a free AI System Snapshot. Join Her AI Club. Watch the ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠video podcast⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ of this episode! To get access to our FREE Business Training course go to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠MillionaireUniversity.com/training⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ To get exclusive offers mentioned in this episode and to support the show, visit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠millionaireuniversity.com/sponsors⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Learn more about your ad choices. Visit megaphone.fm/adchoices

What does it actually look like to run a growing online business behind the scenes? In the final episode of this Behind the Scenes mini-series, Tori and her OBM Meredith pull back the curtain on the systems, communication, and leadership practices that keep Big Money Strategies running smoothly. From why they rarely have meetings, to how they use Slack and Airtable to manage projects, client journeys, launches, and team communication, this episode is a practical look at what sustainable business operations really look like. They also unpack how they approach hiring, launching new offers, managing contractors, continuous improvement, and why building a business isn't about holding everything in your head—it's about creating systems your team can trust. If you've ever wondered what happens behind the scenes of a business that continues to scale without constant chaos, this episode gives you an honest look inside.

We are back! Season 25 kicks off with a deep dive into the latest Airtable updates that every builder needs to know. From a brand new automation trigger for comments to the technical advantages of inserting data as JSON strings, we cover the tools that will speed up your workflow. We also look at how Airtable's AI is moving into Slack and what that means for your team's productivity, including a breakdown of its current limitations. Join us as we unbox these features and share our honest thoughts on the latest interface changes and the shift from User Groups to Builder Crews.

Are you holding your business back because you are terrified of the word "no"? Most business owners actively avoid pitching themselves for guest spots, speaking gigs, or collaboration opportunities because they view a rejection as a deep personal failure. This fear creates a massive visibility bottleneck, leaving your brand stagnant while your competitors take center stage. In this episode of Podcasting Unlocked, Alesia discusses her current quest for 100 rejections and explains how having a strong pitching strategy will yield more yeses than you may think. This week, episode 291 of Podcasting Unlocked is about pitching for rejection and how failing will scare your visibility!In this episode of Podcasting Unlocked, I'm sharing the importance of having a strong strategy for pitching your podcast or business and actionable steps you can take right now to start your own 100 rejection challenge. I also chat about the following: Gamify Failure for Intentional Progress: Discover how setting a personal goal to collect 100 rejections completely detaches your mind from the anxiety of the outcome. By using a physical tracking system to celebrate a "no," you build the confidence needed to pitch massive, top-tier opportunities.The "Yes" Inevitability: Learn why chasing a high volume of rejections naturally guarantees a high volume of client wins and media features. When you increase your input, you inadvertently collect life-changing approvals that scale your platform visibility.Build a Systematic Pitching Strategy: Move away from sloppy, unorganized outreach. Learn how to map a clean workflow using a data-tracking system like ClickUp, Airtable, or a Google Sheet to manage host names, show criteria, and current pitch statuses.Respect Host Infrastructure and Boundaries: Stop spamming podcast inboxes. Discover why submitting pitches via a host's designated website form or asking for their preferred pitching protocol creates a stellar first impression and instantly prevents your email from getting blocked.Deploy Automated Follow-Up Systems: Understand that a lack of response is not a formal rejection. Learn how to build a 10-to-14-day automated reminder check-in that assumes the host is simply handling a busy production schedule, keeping your pitch top-of-mind without causing administrative fatigue.This month, I challenge you to step completely out of your comfort zone and collect just 5 rejections. Send that bold email, pitch that dream podcast, or ask for that high-level collaboration. You might be surprised by how many "yeses" are hiding behind the fear of a "no". Be sure to tune in to all the episodes to receive tons of practical tips on turning your podcast listeners into leads and to hear even more about the points outlined above. Thank you for listening! If you enjoyed this episode, take a screenshot of the episode to post in your stories and tag me! And don't forget to follow, rate and review the podcast and tell me your key takeaways!Learn more about Podcasting Unlocked at https://galatimedia.com/podcasting-unlocked/ CONNECT WITH ALESIA GALATI:InstagramLinkedInWork with Galati Media! Work with Alesia 1:1LINKS MENTIONED:Feminist Podcasters CollectivePodMatchWhat are Common Podcast Pitching Mistakes People Make?How to Create an Effective Podcast Pitch with Michelle GlogovacProud member of the Feminist Podcasters Collective.

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

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

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