Lead With AI

• In the City of Neon & Code, Your New AI Stylist Is an Algorithm

  Thirty percent of all clothes go straight from the factory to the landfill without ever being worn. Zoher Karu, Head of AI at Taelor, built an AI-powered styling platform that tackles this sustainability crisis while solving what he calls "the matching problem" for men's fashion. In this episode of Lead with AI, Dr. Tamara Nall speaks with Zoher about how Taelor learns your preferences, body type, and calendar to deliver outfits that build confidence and reduce waste. Zoher shares how the platform processes data like a brain driving down the street, evaluating weather, upcoming events, fit preferences, and style compatibility simultaneously. One customer landed a job because the right outfit gave him confidence in the interview. Taelor combines machine learning with human oversight, renting clothes to users who can keep favorites and return the rest, creating feedback loops that tell manufacturers what men actually want to wear. For anyone curious about how AI transforms everyday decisions while making the world more sustainable, Zoher explains what happens when algorithms understand style better than most humans.Want to experience AI-powered personal styling? Visit taelor.ai to sign up and access Taelor's machine learning platform that matches your style, fits your calendar, and builds confidence through better fashion choices. Follow or Subscribe to Lead with AI Podcast on your favorite platforms:Website: LeadwithAIPodcast.com | Apple Podcasts: Lead-with-AI | Spotify: Lead with AI | Podbean: Lead-with-AI-Podcast | YouTube: @LeadWithAiPodcast | Facebook: Lead With AI | Instagram: @leadwithaipodcast | TikTok: @leadwithaipodcast | Twitter (X): @LeadWithAiFollow Dr. Tamara Nall:LinkedIn: @TamaraNall | Website: TamaraNall.com | Email: [email protected] Zoher Karu: LinkedIn: @ZZKaru | Facebook: Zoher.Karu | Email: [email protected] AI: Website: Taelor.Style

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• Former Docker VP Reveals the AI Security Gap Costing Teams 80 Hours

  Most companies deploying AI models right now cannot prove what's actually running in production. Jesse Williams, Co-founder and COO of Jozu and former VP at Docker, built infrastructure that cuts model audit compilation from three weeks to seconds while solving the security gap keeping enterprise teams awake at night. In this episode of Lead with AI, Dr. Tamara Nall speaks with Jesse about the moment defense contractors discovered their ML pipeline had no single source of truth, how a malicious prompt change slipped into AWS developer tools unnoticed, and why KitOps packages everything into cryptographically signed artifacts. Jesse shares how one team wasted 80 developer hours creating audit logs that Jozu now generates automatically, why infrastructure-level ethics matter more than model guardrails when a Chevy chatbot sold a car for one dollar, and his prediction that we'll soon see the first billion-dollar company run by 10 people as AI levels the playing field globally.Want to experience secure AI deployment? Visit jozu.com and kitops.org to access the open source framework and enterprise platform making ML governance automatic.#AIGovernance #EnterpriseAI #AIInfrastructure #DevOpsAI #LeadWithAI #FutureOfAI #AIMissionControl #ModelOps #ResponsibleAI #TechInnovation #OpenSourceAI Follow or Subscribe to Lead with AI Podcast on your favorite platforms:Website: LeadwithAIPodcast.com | Apple Podcasts: Lead-with-AI | Spotify: Lead with AI | Podbean: Lead-with-AI-Podcast | YouTube: @LeadWithAiPodcast | Facebook: Lead With AI | Instagram: @leadwithaipodcast | TikTok: @leadwithaipodcast | Twitter (X): @LeadWithAiFollow Dr. Tamara Nall:LinkedIn: @TamaraNall | Website: TamaraNall.com | Email: [email protected] Jesse Williams: LinkedIn: @JesseWilliams1Follow Jozu: Website: Jozu.com

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• Google Director Reveals How Two Billion People Now Search Using Conversational AI

  Two billion monthly users now interact with Google through conversational AI instead of traditional keyword searches. Soufi Esmaeilzadeh, Director of Product Management for Google Search, leads the team that transformed how humanity discovers information through AI Overviews and AI mode. In this episode of Lead with AI, Dr. Tamara Nall speaks with Soufi about the query fan out technique that breaks complex questions into subtopics and researches them simultaneously, mimicking how humans naturally reason through problems. Soufi shares how college students navigate career decisions through back-and-forth dialogue with AI mode, how parents plan family vacations by describing nuanced requirements in natural language, and how Search Live allows people to debug appliances simply by pointing their camera and asking questions. She reveals three innovation frontiers reshaping information discovery: agentic capabilities where AI books reservations on your behalf, multi-modal interfaces that understand video and audio inputs, and personalization that remembers your preferences without requiring repetition. For anyone curious about how search evolved beyond blue links and keywords into conversational assistance, Soufi explains what happens when two billion people shift from searching to having conversations.Want to experience the future of search? Visit google.com/ai to access Google's latest AI-powered search capabilities, including AI mode, Search Live, and visual AI features. Follow or Subscribe to Lead with AI Podcast on your favorite platforms:Website: LeadwithAIPodcast.com | Apple Podcasts: Lead-with-AI | Spotify: Lead with AI | Podbean: Lead-with-AI-Podcast | YouTube: @LeadWithAiPodcast | Facebook: Lead With AI | Instagram: @leadwithaipodcast | TikTok: @leadwithaipodcast | Twitter (X): @LeadWithAiFollow Dr. Tamara Nall:LinkedIn: @TamaraNall | Website: TamaraNall.com | Email: [email protected] Soufi Esmaeilzadeh: LinkedIn: @Soufi-EGoogle Live Search: Website: google.com/ai

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• How This AI Memory App Is Helping Us Preserve the Stories & Memories of Our Loved Ones

  What started as morning text prompts to her mother became an AI platform preserving family memories before it's too late. In this episode of Lead with AI, host Dr. Tamara Nall interviews Kimberly Carson, former IBM Watson researcher and founder of Ancestral Echoes, and explains how sensory questions like "What did Sunday morning smell like in your childhood?" unlock stories that heal rather than just create nostalgia. A beta tester who lost her mother unexpectedly found voice memos that felt like letters her mom left behind without knowing. Carson reveals how AI organizes these memories into multi-modal capsules that preserve voice, tone, and cultural context, creating living archives for future generations. This isn't about recreating voices or faking memories. It's about making space for stories that matter while the people who lived them are still here to share.Follow or Subscribe to Lead with AI Podcast on your favorite platforms:Website: LeadwithAIPodcast.com | Apple Podcasts: Lead-with-AI | Spotify: Lead with AI | Podbean: Lead-with-AI-Podcast | Email: [email protected] Dr. Tamara Nall:LinkedIn: @TamaraNall | Website: TamaraNall.com | Email: [email protected] Kimberly Carson:LinkedIn: @KimberlyaCarson | Ancestral Echoes: Ancestral-Echoes-Signup.Lovable.App | Instagram: @Kims_AI_Imaginarium | Linktr.ee: Kims_AI_Imaginarium | YouTube: @Kims_AI_Imaginarium

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• Meet the AI Framework That Turns LLMs Into Fully Transparent Machines

  Most AI development tools hide what's happening under the hood. Scott Vance built the opposite. Convo Lang is a plain text framework that exposes every part of the AI interaction process, making context engineering precise and visible. In this episode of Lead with AI, host Dr. Tamara Nall speaks with Scott, a creator and developer from Cincinnati who spent nearly 20 years building software tools. Scott explains how Convo Lang started as a small library to eliminate repetition in his AI projects and evolved into a comprehensive framework for developing AI-native applications. He describes how every interaction with an LLM gets stored in local files you can review, helping developers understand how AI reached specific decisions. Scott shares how he used his new tool Convo Make to complete a week's worth of work in just a few hours, generating an entire application frontend and backend including security rules in one shot. He reveals his vision for language models that can interpret code written specifically for AI rather than forcing models to generate the same code humans have been writing for decades. For developers frustrated by tools that treat AI interactions like black boxes, Scott demonstrates what becomes possible when you expose the full context and make every message visible in plain text format you can read and organize.Follow or Subscribe to Lead with AI Podcast on your favorite platforms:Website: LeadwithAIPodcast.com | Apple Podcasts: Lead-with-AI | Spotify: Lead with AI | Podbean: Lead-with-AI-Podcast | Email: [email protected] Dr. Tamara Nall:LinkedIn: @TamaraNall | Website: TamaraNall.com | Email: [email protected] Scott Vance:LinkedIn: @scott-vance | Convo Lang AI: Learn.Convo-Lang.ai | Email: [email protected]

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