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Gemini 3 is a few days old and the massive leap in performance and model reasoning has big implications for builders: as models begin to self-heal, builders are literally tearing out the functionality they built just months ago... ripping out the defensive coding and reshipping their agent harnesses entirely. Ravin Kumar (Google DeepMind) joins Hugo to breaks down exactly why the rapid evolution of models like Gemini 3 is changing how we build software. They detail the shift from simple tool calling to building reliable "Agent Harnesses", explore the architectural tradeoffs between deterministic workflows and high-agency systems, the nuance of preventing context rot in massive windows, and why proper evaluation infrastructure is the only way to manage the chaos of autonomous loops. They talk through: - The implications of models that can "self-heal" and fix their own code - The two cultures of agents: LLM workflows with a few tools versus when you should unleash high-agency, autonomous systems. - Inside NotebookLM: moving from prototypes to viral production features like Audio Overviews - Why Needle in a Haystack benchmarks often fail to predict real-world performance - How to build agent harnesses that turn model capabilities into product velocity - The shift from measuring latency to managing time-to-compute for reasoning tasks LINKS From Context Engineering to AI Agent Harnesses: The New Software Discipline, a podcast Hugo did with Lance Martin, LangChain (https://high-signal.delphina.ai/episode/context-engineering-to-ai-agent-harnesses-the-new-software-discipline) Context Rot: How Increasing Input Tokens Impacts LLM Performance (https://research.trychroma.com/context-rot) Effective context engineering for AI agents by Anthropic (https://www.anthropic.com/engineering/effective-context-engineering-for-ai-agents) Upcoming Events on Luma (https://lu.ma/calendar/cal-8ImWFDQ3IEIxNWk) Watch the podcast video on YouTube (https://youtu.be/CloimQsQuJM) Join the final cohort of our Building AI Applications course starting Jan 12, 2026 (https://maven.com/hugo-stefan/building-ai-apps-ds-and-swe-from-first-principles?promoCode=vgrav): https://maven.com/hugo-stefan/building-ai-apps-ds-and-swe-from-first-principles?promoCode=vgrav
AI Unraveled: Latest AI News & Trends, Master GPT, Gemini, Generative AI, LLMs, Prompting, GPT Store
Welcome to AI Unraveled (November 21, 2025): Your daily strategic briefing on the business impact of AI.Today's Highlights: Foxconn brings OpenAI's hardware ambitions to US soil; internal leaks reveal OpenAI's deep anxiety over Google's Gemini 3; Google begins monetizing AI search with ads; and the new Nano Banana Pro model redefines on-device efficiency.Strategic Pillars & Topics:
Prolonged conversations with ChatGPT and other LLM chatbots have created rapid developments of severe delusions, paranoia, and even death by suicide in some cases. In this episode, Dr. David Puder sits down with Columbia researchers Dr. Amandeep Jutla and Dr. Ragy Girgis to unpack five shocking real-world cases, explain why large language models are dangerously sycophantic, trained to agree, mirror, and amplify any idea instead of challenging it. By listening to this episode, you can earn 1.25 Psychiatry CME Credits. Link to blog Link to YouTube video
Is Canada's A.I. champion eating the news?Canada is betting big on Cohere, but a lawsuit alleges that the company's flagship LLM is bypassing paywalls and hallucinating content. What happens to the news industry if A.I. continues to run amok? Host: Jesse BrownCredits: James Nicholson (Producer), Jules Bugiel (Associate Producer and Fact Checking) Caleb Thompson (Audio Editor and Technical Producer), max collins (Director of Audio), Jesse Brown (Editor)Guest: Douglas SoltysAdditional music by Audio NetworkFurther Reading on Our Website Sponsors: Sprague Cannery: You can find Sprague goods across the nation in major Canadian retailers like Costco, Loblaws, Walmart, Giant Tiger and many smaller independent stores.Douglas: Douglas is giving our listeners a FREE Sleep Bundle with each mattress purchase. Get the sheets, pillows, mattress and pillow protectors FREE with your Douglas purchase today. Visit douglas.ca/canadaland to claim this offer.Squarespace: Check out Squarespace.com/canadaland for a free trial, and when you're ready to launch use code canadaland to save 10% off your first purchase of a website or domain.If you value this podcast, Support us! You'll get premium access to all our shows ad free, including early releases and bonus content. You'll also get our exclusive newsletter, discounts on merch at our store, tickets to our live and virtual events, and more than anything, you'll be a part of the solution to Canada's journalism crisis, you'll be keeping our work free and accessible to everybody. Hosted on Acast. See acast.com/privacy for more information.
We chat with Alex Duffy who as Head of AI Training at Every Consulting run an amazing project where different AI models competed against each other in Diplomacy. Plus we discuss the upcoming Australian Open tournament. Intro The guys introduce the show and Gavin flags he'll be moving further away from Ken, so the show will become more online than face-to-face (0 mins 15 secs) Interview with Alex Duffy They introduce the interview with Alex from Every Consulting and GoodStartLabs about different AI models playing against each other in Diplomacy (4 mins) The interview kicks off with Alex discussing the research project he ran at Every Consulting where various AI Large Language Models (LLMs) competed against each other in Diplomacy (6 mins 45 secs) Gavin asks Alex how he got into Diplomacy originally (9 mins 50 secs) They discuss the thinking behind the project. During his answer he mentions the Twitch stream of the AI models playing against each other - you can view this on their AI Diplomacy Twitch channel (11 mins 15 secs) They look at how data should be structured and presented to the LLMs (15 mins 45 secs) Alex talks about the different style of play adopted by each LLM - you can read their summary on the Every Consulting AI page (18 mins 45 secs) Gavin asks about how different models approached strategy nnd iterative training of the models so they learn from how they perform in games (24 mins) Gavin reflects on how he sometimes plays in cycles of play (32 mins) They discuss why the game Diplomacy keeps being used researched in the AI space (34 mins) Alex introduces his lates project: The Battle of Bots. You can find out more and register your interest on their Battle of the Bots web page (40 mins 30 secs) They reflect on the newer generations of players bringing their enhanced technology experience to the game (45 mins) Alex asks Gavin and Ken what they've learned from playing Diplomacy to apply to real life (48 mins 30 secs) Gavin asks Alex whether he plans to get more into playing Diplomacy face to face (53 mins 45 secs) Alex discusses other games he's interested in getting into more (57 mins) Just a reminder, you can find out more and register your interest on their Battle of the Bots web page (1 hr 0 mins) Ken suggests some games he feels would be appropriate to research. Alex provides his email address to hear listener's suggestions on other games ot look into (1 hr 2 mins) They begin wrapping up the interiew (1 hr 5 mins 30 secs) The guys reflect on the chat (1 hr 7 mins) Diplomacy Chat Gavin is off to compete in the Australian Open, being hosted the weekend of 21 to 23 November. Plus they talk about the Bismark Cup (1 hr 23 mins) After some tangental talk, they return full circle to the Australian Open. Gavin mentions doing some recordings when not playing, however, with his house move he can't find the recorder which is packed somewhere (1 hr 33 mins) They discuss getting and staying in the right zone, and reflect on Mitchell and Webb's the Inebriati sketch (1 hr 37 mins 30 secs) Gavin incorrectly cites Mitchell and Webb again, but it is actually Stephen Fry and Hugh Lawrie's Treaty of Westphalia sketch (1 hr 39 mins 30 secs) The guys start wrapping up the show (1 hr 40 mins) Venue: At home Drinks for the interview: Gavin: Proximo tempranillo from Rioja, Spain Ken: Poet's Country Crisp lager from Yenda, NSW Just a reminder you can support the show by giving it 5 stars on iTunes or Stitcher. And don't forget if you want to help pay off the audio equipment... or buy the guys a drink, you can also donate at Patreon, plus you get extra podcast episodes! Lastly, don't forget to subscribe so you get the latest Diplomacy Games episodes straight to your phone. Thanks as always to Dr Dan aka "The General" for his rockin' intro tune.
Tom Kocmi, Researcher at Cohere, and Alon Lavie, Distinguished Career Professor at Carnegie Mellon University, join Florian and Slator language AI Research Analyst, Maria Stasimioti, on SlatorPod to talk about the state-of-the-art in AI translation and what the latest WMT25 results reveal about progress and remaining challenges.Tom outlines how the WMT conference has become a crucial annual benchmark for assessing AI translation quality and ensuring systems are tested on fresh, demanding datasets. He notes that systems now face literary text, social-media language, ASR-noisy speech transcripts, and data selected through a difficulty-sampling algorithm. He stresses that these harder inputs expose far more system weaknesses than in previous years.He adds that human translators also struggle as they face fatigue, time pressure, and constraints such as not being allowed to post-edit. He emphasizes that human parity claims are unreliable and highlights the need for improved human evaluation design.Alon underscores that harder test data also challenges evaluators. He explains that segment-level scoring is now more difficult, and even human evaluators miss different subsets of errors. He highlights that automated metrics built on earlier-era training data underperformed, particularly COMET, because they absorbed their own biases.He reports that the strongest performers in the evaluation task were reasoning-capable large language models (LLMs), either lightly prompted or submitted with elaborate evaluation-specific prompting. He notes that while these LLM-as-judge setups outperformed traditional neural metrics overall, their segment-level performance varied.Tom points out that the translation task also revealed notable progress from smaller academic models around 9B parameters, some ranking near trillion-parameter frontier models. He sees this as a sign that competitive research is still widely accessible.The duo concludes that they must carefully choose evaluation methods, avoid assessing models with the same metric used during training, and adopt LLM-based judging for more reliable assessments.
Is MCP just another server you need to threat model, patch, and monitor? How do you keep users from over-privileged access, block LLM injection, and stop blind spots? We unpack the VentureBeat article https://venturebeat.com/security/mcp-stacks-have-a-92-exploit-probability-how-10-plugins-became-enterprise with real-world tips. We are always happy to answer any questions, hear suggestions for new episodes, or hear from you, our listeners. DevSecOps Talks podcast LinkedIn page DevSecOps Talks podcast website DevSecOps Talks podcast YouTube channel
В гостях выпуска Алексей Толстиков - кандидат физико-математических наук, руководитель Школы анализа данных Яндекса, эксперт в олимпиадах по программированию. Разговаривать мы, разумеется, будем про ШАД. Зачем когда-то (аж 18 лет назад) появилась Школа Анализа Данных? Как руководить большим направлением в компании, когда хочется писать образовательные программы и код? Зачем ШАДу взаимодействие с ВУЗами? Куда уходят выпускники ШАД? Как работает комьюнити выпускников? Сломаны ли процессы в современном образовании из-за бурного развития LLM? Стоит ли учиться в ШАД только ради "ачивки"? А чему вообще можно научиться в Школе Анализа Данных? Кто такие исследователи-разработчики? Не снижается ли радикально роль живого преподавателя с учётом того, что теперь легко можно взаимодействовать с ChatGPT-like моделями в интерактивном режиме? Можно ли реально "расти" без "боли"? Как поступить в ШАД, если математика была давно? Из каких этапов состоит поступление? Как готовиться к экзаменам? Обо всём этом в выпуске!Ссылки выпуска:ШАД (https://shad.yandex.ru)Все в ШАД - телеграм-канал с полезными материалами для подготовки к поступлению (https://t.me/vse_v_shad)Буду благодарен за обратную связь!Подписывайтесь на телеграм-канал "Стать специалистом по машинному обучению" (https://t.me/toBeAnMLspecialist)Обо мне (https://t.me/toBeAnMLspecialist/935)Мой телеграм для связи (https://t.me/kmsint)Ещё со мной можно связаться по электронной почте: kms101@yandex.ruЯ сделал бесплатный курс по созданию телеграм-ботов на Python и aiogram на Степике (https://stepik.org/120924). Присоединяйтесь, если хотите научиться разрабатывать телеграм-ботов и вообще вести проекты на Python!Также в соавторстве с крутыми разработчиками я пишу курс по продвинутой разработке телеграм-ботов с элементами микросервисной архитектуры (https://stepik.org/a/153850?utm_source=mlpodcast&utm_campaign=ep_76).Выразить благодарность можно добрым словом и/или донатом (https://www.tinkoff.ru/rm/kryzhanovskiy.mikhail11/NkwE718878/)
Send us a text- On-Demand Programme Link - https://mailchi.mp/bb2a7b851246/kairos-centreWhat is 'Manly'?: A conversation with Damian Andrews of SHAIR.Care Podcast (Australia) in 2023.What is Man-ness? There is still a caveman instinct inside of us as men. Has the image got distorted as men try to metamorphize ourselves to fit what society tells us a man should be. Trying to fit what we are really not, is hard work. At some point there may be an increased desire to self-soothe and escape into cyberworld for a while – using sex, porn and/or other compulsive behaviours. Consider this poem: Children Learn What They LiveAuthor: Dorothy Law NolteIf a child lives with criticism, he [she] learns to condemn.If a child lives with hostility, he [she] learns to fight.If a child lives with ridicule, he [she] learns to be shy.If a child lives with shame, he [she] learns to feel guilty.If a child lives with tolerance, he [she] learns to be patient.If a child lives with encouragement, he [she] learns confidence.If a child lives with praise, he [she] learns to appreciate.If a child lives with fairness, he [she] learns justice.If a child lives with security, he [she] learns to have faith.If a child lives with approval, he [she] learns to like himself [herself].If a child lives with acceptance and friendship, he [she] learns to find love in the world.Templates and scripts from batons and intergenerational patterns passed on, are already shaping the developing brain in such an early formative time, which will set up patterns that continue to play out in adulthood. Therefore, significance must be given to this period in the man's life.(Let's build upon this in the subsequent episodes of this interesting podcast chat).Get some help from The Kairos Centre. See what you cannot see. Begin to change that which you begin to better understand.Help someone: https://igg.me/at/ThekairosCentreHelp is here for you: bit.ly/pornaddictionhelpGary McFarlane (BA, LLM, Dip, Certs), Accredited EMDR Practitioner.Key words: sex addiction, addicted, partner, porn addiction, recovery, sex drive, therapy, sex therapy, podcast, relationships, relationship counseling, relationship advice, addiction, couples, couples therapy, sex therapy, emdr, love addiction, behavior, psychology, codependency, sex life, neuroscience, sex ed, sober, sobriety, sexual dysfunction, relationship issues, sex coach, sexual, trauma, ptsd, sex science, The sex porn love Addiction Podcast, The Singles Partners Marrieds and Long Time Marrieds Podcast, Gary McFarlane, porn addiction, what neuroscience says, neuroscience, young adults, sex, sex addict, porn, recovery, porn addiction issue, porn addiction in teens, sex addiction in teens, sex hormones, hormones,Support the show
In der heutigen Folge sprechen Thorsten und der neue Nodesignal Host Zetti mit Flashman und Ronin über den aktuellen Stand am Bitcoin Node Markt. Diese Folge ist ein Update zu der im Januar erschienenen Plebnode 3.0 Folge. Wir sprechen über unterschiedliche Node Implementierung und zeigen Alternativen auf. Im zweiten Teil der Folge führt uns Ronin in die Welt der selbst gehosteten KI Modelle ein. Er erklärt die Basics und zeigt auf, was mit welcher Hardware möglich ist und was nicht. Dabei kommt auch das Thema Stromverbrauch und Anschaffungskosten nicht zu kurz. Ein Deepdive über den aktuellen Stand der Technik.Von und mit: - Thorsten - Ronin(Shield of Satoshi) - Flashman - ZettizettlerProduziert und geschnitten: ThorstenHier könnt ihr uns eine Spende über Lightning da lassen: ⚡️nodesignal@getalby.comNeben dem Podcast findet ihr uns auch auf YouTubeFür Feedback und weitergehenden Diskussionen kommt gerne in die Telegramgruppe von Nodesignal und bewertet uns bei Spotify und Apple Podcasts, das hilft uns sehr. Folgt uns auch gerne bei Nostr:npub1n0devk3h2l3rx6vmt24a3lz4hsxp7j8rn3x44jkx6daj7j8jzc0q2u02cy und Twitter.Blockzeit: 923335Nodesignal-Talk – E247 – Pädagogisches Orangepilling mit ZettiNodesignal-Talk – E214 – PlebNode 3.0, mit Ronin und FlashmanRaspiBlitz ProjektStartOS Projektumbrel ProjektOllama ProjektLM Studio SuiteNostr Post von Thorsten zu der Einrichtung von OpenWebUI mit PPQMarks von Maple bei Citadel DispatchMatt Ahlborg von PPQ bei Citadel DispatchRonins Liste aus der FolgeTimestamps:(00:00:00) Intro(00:00:22) Einführung von Zetti und Vorschau(00:05:31) Begrüßung Gäste(00:07:44) Rückblick auf PlebNode 3.0 und aktuelle Entwicklungen(00:13:36) Erfahrungen mit verschiedenen Node-Setups(00:22:27) Probleme mit Start9 und Software-Updates(00:29:55) Umbrel vs. Start9: Ein Vergleich der Node-Lösungen(00:33:38) Backup-Strategien und Herausforderungen bei Nodes(00:40:27) Die Notwendigkeit einer 24/7 Node und alternative Ansätze(00:48:04) Einführung in KI und lokale Hosting-Optionen(00:55:30) Die Entstehung von Open Source KI-Modellen(00:59:01) Olamas und LM Studio: Desktop-Lösungen für KI(01:02:00) Parameter und Quantisierung in KI-Modellen(01:04:45) Hardware-Anforderungen für KI-Modelle(01:11:27) Praktische Anwendungen und Kosten von KI-Setups(01:17:07) Zukunftsausblick: KI für den Alltag(01:21:06) Marktentwicklung und Preisprognosen für KI-Technologie(01:31:11) Hardware-Empfehlungen für KI-Anwendungen(01:35:11) Kosteneffizienz und Nutzung von KI-Diensten(01:39:16) Zukunft der KI und private LLMs(01:44:08) Frage von Calso, wann sind private LLM's möglich?(01:50:47) Verabschiedung und Outro
“AI Radar od Thoughtworksa” - Szymon ironicznie nazywa Technology Radar Vol. 33, który zamienił się w zbierankę AI-owej drobnicy. “Tu jak wcześniej były jakieś większe tematy, to tu jest dużo mikro narzędzi” - fragmentacja ekosystemu AI w pełnej krasie. MCP podbija rynek (każdy vendor dodaje support), A2A umarł (“vendorzy będą się bronić rękami i nogami”), AI-accelerated shadow IT wraca jako antypattern, service mesh bez sidecarów pojawił się dwa lata za późno (“to powinno być w Adopcie już dawno temu”). CloudNativePG? “Naprawdę bardzo dobrze zrobione.” N8N? “Po co ja to robiłem? To mogłyby być trzy linijki kodu.” A Text-to-SQL? Łukasz stawia sprawę jasno: “Kluczem niestety jest to, że schematy baz danych relacyjnych noszą wiedzę plemienną” - i problemem nie jest GenAI, tylko klasyczne: kupa na wejściu, kupa na wyjściu. Plus DeepEval z “LLM as a judge” do testowania AI w CI/CD - wreszcie sposób na pilnowanie, czy model nie zwariował po cichu. Twój stack też wygląda jak zbieranka drobnicy? Przynajmniej teraz wiesz, że nie jesteś sam.
What if the biggest cyber risk inside your company wasn't malware — but identity? In this episode, I sit down with Santhosh Jayaprakash, founder & CEO of UnoSecur, to unpack one of the fastest-moving transformations in cybersecurity: the rise of identity as the new perimeter. Attackers don't break in anymore — they log in. And with AI agents, LLM workflows, and machine-to-machine communication exploding, identity risk is growing faster than security teams can react. UnoSecur is building an identity security platform that monitors identity behavior after login, detecting stolen credentials, risky machine identities, and AI agent misuse in real time. Think of it as the layer that finally answers the question: Who is actually doing what inside your systems — and should they be doing it? Our sponsor:
CrowdStrike research into AI coding assistants reveals a new, subtle vulnerability surface: When DeepSeek-R1 receives prompts the Chinese Communist Party (CCP) likely considers politically sensitive, the likelihood of it producing code with severe security flaws increases by up to 50%. Stefan Stein, manager of the CrowdStrike Counter Adversary Operations Data Science team, joined Adam and Cristian for a live recording at Fal.Con 2025 to discuss how this project got started, the methodology behind the team's research, and the significance of their findings. The research began with a simple question: What are the security risks of using DeepSeek-R1 as a coding assistant? AI coding assistants are commonly used and often have access to sensitive information. Any systemic issue can have a major and far-reaching impact. It concluded with the discovery that the presence of certain trigger words — such as mentions of Falun Gong, Uyghurs, or Tibet — in DeepSeek-R1 prompts can have severe effects on the quality and security of the code it produces. Unlike most large language model (LLM) security research focused on jailbreaks or prompt injections, this work exposes subtle biases that can lead to real-world vulnerabilities in production systems. Tune in for a fascinating deep dive into how Stefan and his team explored the biases in DeepSeek-R1, the implications of this research, and what this means for organizations adopting AI.
Send us a textWhat if most of the economy can be automated without anything we'd call real general intelligence? That provocative idea launches a candid tour with Ben Goertzel through the difference between LLM “breadth” and the kind of generalization that marks true AGI. We unpack why today's models are powerful yet limited, how they'll reshape work in the near term, and what ingredients are missing for systems that reason, invent, and move beyond the data that formed them.We dig into a practical path forward: blending deep neural networks with logic engines, evolutionary learning, and a massive knowledge graph so each part amplifies the others. Ben shares how the Hyperon framework and the ASI chain bring AI on-chain, not just coordinated by it. That means a new AGI language, MeTTa, serving as a smart contract language, enabling formal verification, rich composability, and an integrated reputation layer. Together, these tools aim to embed trust into the stack while opening the door to decentralized AI networks that resist capture by any single company or state.Culture, narrative, and emotion matter just as much as code. A robot-led band nearly got booed off stage until the performance was reframed as exploration, not replacement—proof that context shapes how people accept new tools. We follow that thread into creativity, where AI can mix stems, spark ideas, and widen access for musicians, even as some roles compress. The larger question becomes not whether AI can do the job, but what humans will choose to do for meaning, connection, and joy. Along the way, we weigh openness versus control through a proactionary lens and point you to resources to explore decentralized, trustworthy AI.If this conversation challenged your assumptions or sparked new ones, follow the show, share it with a friend, and leave a quick review to help others find it. Your thoughts shape where we go next—what part of decentralized AGI are you most curious about?This episode was recorded at Web Summit in Lisbon on November 13, 2025. Read the blog article and show notes here: https://webdrie.net/creating-benevolent-decentralized-agi-at-singularitynet/..........................................................................
Is AI empathy a life-or-death issue? Almost a million people ask ChatGPT for mental health advice DAILY ... so yes, it kind of is.Rosebud co-founder Sean Dadashi joins TechFirst to reveal new research on whether today's largest AI models can recognize signs of self-harm ... and which ones fail. We dig into the Adam Raine case, talk about how Dadashi evaluated 22 leading LLMs, and explore the future of mental-health-aware AI.We also talk about why Dadashi was interested in this in the first place, and his own journey with mental health.00:00 — Intro: Is AI empathy a life-or-death matter?00:41 — Meet Sean Dadashi, co-founder of Rosebud01:03 — Why study AI empathy and crisis detection?01:32 — The Adam Raine case and what it revealed02:01 — Why crisis-prevention benchmarks for AI don't exist02:48 — How Rosebud designed the study across 22 LLMs03:17 — No public self-harm response benchmarks: why that's a problem03:46 — Building test scenarios based on past research and real cases04:33 — Examples of prompts used in the study04:54 — Direct vs indirect self-harm cues and why AIs miss them05:26 — The bridge example: AI's failure to detect subtext06:14 — Did any models perform well?06:33 — All 22 models failed at least once06:47 — Lower-performing models: GPT-40, Grok07:02 — Higher-performing models: GPT-5, Gemini07:31 — Breaking news: Gemini 3 preview gets the first perfect score08:12 — Did the benchmark influence model training?08:30 — The need for more complex, multi-turn testing08:47 — Partnering with foundation model companies on safety09:21 — Why this is such a hard problem to solve10:34 — The scale: over a million people talk to ChatGPT weekly about self-harm11:10 — What AI should do: detect subtext, encourage help, avoid sycophancy11:42 — Sycophancy in LLMs and why it's dangerous12:17 — The potential good: AI can help people who can't access therapy13:06 — Could Rosebud spin this work into a full-time safety project?13:48 — Why the benchmark will be open-source14:27 — The need for a third-party “Better Business Bureau” for LLM safety14:53 — Sean's personal story of suicidal ideation at 1615:55 — How tech can harm — and help — young, vulnerable people16:32 — The importance of giving people time, space, and hope17:39 — Final reflections: listening to the voice of hope18:14 — Closing
In this episode of The Metrics Brothers, Ray “Growth” Rike and Dave “CAC” Kellogg break down one of the emerging metrics in the Agentic AI era: Containment Rate - the percentage of tasks an AI agent completes (resolves) end-to-end without human intervention.They explore multiple aspects of the Containment Rate Metric including:How containment rate differs from classic chatbot metric - deflection rateWhy defining “resolved” and/or "completed" is essential to calculating containment rateHow the metric connects directly to ROIWhy ROI needs to include both the benefit (cost-savings) and the investment (expense) for the AI AgentRay and Dave also trace the history of containment from IVR to Chatbots to LLM-powered agents, debate common misconceptions, and outline benchmarks across customer support, IT, HR, and back-office agentic AI workflows.If you're building, buying, or benchmarking AI agents - or trying to turn AI investments into measurable ROI — this episode delivers the context, clarity, and humor only The Metrics Brothers can provide.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
In this episode, Aydin sits down with Ryan McCready, who went from hating AI to becoming one of the most creative AI-powered content builders on the internet. After getting laid off in mid-2025, Ryan realized that every job interview demanded AI fluency. So he went all-in, teaching himself Zapier, Lovable, Supabase, and advanced prompting to engineer a “Content Factory” that turns a webinar into blog posts, clips, and social content in minutes.He shares the mindset shift from “AI is plagiarism” to “AI is an input-output engine,” why content engineering is the future, what makes AI workflows actually work, and how breaking big tasks into many small steps is the secret to non-sloppy AI content.You'll see how he built a 30-step Zapier workflow that analyzes a webinar transcript, extracts frameworks and insights, turns them into pitches, builds outlines, writes social posts, and even generates clip candidates for Descript. If you create content or run marketing—this one is a masterclass.Timestamps0:23.00 – Why he believed AI was a “plagiarism machine”2:04.00 – Getting laid off and realizing every employer wanted AI skills4:37.00 – The workflow that kickstarted his learning (LinkedIn voice extraction + employee advocacy shares)5:40.00 – Learning Lovable and Supabase by building real projects6:51.00 – Why “everyone is a builder now” because of AI tools7:52.00 – Introducing “Content Engineering” and why most marketers can't do it9:03.00 – Example: turning a webinar into 10+ pieces of content10:58.00 – Why webinars usually die after they're aired—and why that's a waste11:43.00 – The “Webinar Content Flywheel” teaser16:30.00 – Why Ryan moved back from n8n to Zapier17:55.00 – Zapier vs. n8n: simplicity, stability, and architecture19:03.00 – “Start small”: a two-step Zap example20:09.00 – Interface demo: uploading a transcript and hitting “Go”21:22.00 – Why Zapier Interfaces make deployment easy22:40.00 – Step-by-step breakdown of the workflow24:06.00 – Example: webinar analysis output (themes, chapters, frameworks)27:02.00 – Creating three blog pitches from the transcript30:43.00 – Sending the pitches to Slack for review31:03.00 – Clip extraction workflow + Descript integration32:14.00 – How he uses Descript's “Underlord” to auto-cut clips33:20.00 – Why this beats automated clip tools like Riverside for B2B35:02.00 – Social content workflow (framework angle, data angle, hot take, wildcard)37:12.00 – Why prompting manually is wasteful—build once, automate forever40:11.00 – “Big → small → big” framework: the secret to non-sloppy AI content41:21.00 – Google's “AI content penalty” myth, according to Ryan42:47.00 – Why your input quality determines whether your AI output is good43:44.00 – What excites him most in the next 12 monthsTools & Technologies MentionedZapier: Automation platform used to chain 30+ steps together: analysis, pitch creation, clip extraction, social content, Notion updates, etc.AI by Zapier: Zapier's built-in LLM module used for analysis, extraction, outline generation, and writing.n8n: Open-source workflow automation platform. Ryan tested it, but ultimately moved back to Zapier for stability and structure.Lovable: AI-enabled “vibe coding” tool that turns prompts into functional web apps.Supabase: A database + backend platform used for storing structured content data from builds.Descript (Underlord): Video editing tool with an AI agent that cuts clips based on transcript timecodes generated by the workflow.Notion: Used as the source of truth for storing transcripts, outlines, clip docs, and the full content tracker.Claude / ChatGPT: Used for second-pass expansion—turning outlines or social angles into fully polished blog posts and posts.Fellow.ai: AI meeting assistant—summarizes meetings, tracks decisions, and generates insights and performance summaries.Subscribe at thisnewway.com to get the step-by-step playbooks, tools, and workflows.
Benjamin Netter navigue dans un univers où une simple erreur de clic peut coûter des millions.Un monde où l'humain est souvent la première faille, et où la menace est devenue si sophistiquée que même un Bac + 8 peut tomber dans le piège.Tout ça, il l'a vécu chez October, la plateforme de prêts aux entreprises qu'il avait cofondée.Un simple email de phishing a suffi pour compromettre leurs systèmes.Et là, c'est le déclic : si sa boîte peut se faire piéger, alors des milliers d'entreprises sont en danger.Il teste d'abord sa propre équipe, 15 % se font prendre, même la CFO.Benjamin comprend que la cybersécurité ne peut plus être un sujet réservé aux experts.Elle doit devenir un réflexe collectif.Il quitte tout, lance RIOT, et décide de protéger le maillon le plus vulnérable, l'employé.Aujourd'hui, RIOT accompagne 1 500 entreprises, protège 1,5 million d'employés, et double son revenu chaque année.L'objectif, atteindre 20 millions d'ARR d'ici la fin de l'année.RIOT envoie des fausses attaques pour tester les équipes, analyse les comportements et déploie un compagnon cyber intelligent qui sensibilise chaque employé de manière personnalisée.Une pédagogie moderne, directe, qui ressemble davantage à un coach individuel qu'à un audit poussiéreux sur PowerPoint.Après 2 millions levés auprès de Y Combinator, puis 45 millions au total auprès d'autres fonds, Benjamin garde la même philosophie : construire une boîte faite pour durer, pas pour impressionner.Dans cet épisode, découvrez les coulisses d'un marché qui explose, pourquoi les LLM ont rendu les cybercriminels encore plus dangereux, et comment RIOT se prépare à devenir une référence mondiale.Bonne écoute !===========================
De Chief AI Scientist Yann LeCun van Meta stapt na twaalf jaar op en begint met zijn eigen AI-startup. Dat bevestigt Bloomberg, nadat het gerucht al even in de lucht hing. LeCun uitte openlijk kritiek op de visie van Meta en de grote focus op LLM's. De fundamentele meningsverschillen tussen LeCun en Meta-baas Mark Zuckerberg zorgde regelmatig voor interne conflicten. Rosanne Peters vertelt erover in deze Tech Update. Zelf gelooft LeCun meer in een toekomst waar de focus ligt op Advanced Machine Intelligence. Deze technologie zou voorspellingen kunnen doen over de fysieke wereld en op een andere manier worden getraind dan LLM's. Volgens LeCun wordt dit de nieuwe grote AI-revolutie van de toekomst. Verder in deze Tech Update: Bij veilinghuis Christie's in Parijs is een zeldzame Enigma M4-coderingsmachine geveild Amazon Prime Video komt met een uitbreiding van de functie 'X Ray Recaps' die samenvattende video's maakt van series See omnystudio.com/listener for privacy information.
In this episode, Peter Maddison and Dave Sharrock welcome Justin Trombold, President and Founder of Antison Advisors, to discuss the parallels between agile transformation and generative AI adoption in organizations.Justin shares insights from his work helping companies navigate generative AI readiness, revealing that the biggest challenges aren't technical; they're organizational. From end-user proficiency to cross-functional collaboration, the conversation explores why companies struggle to move beyond "toy apps" to create real business value with AI.Key topics covered:• Why organizations need an AI strategy before investing in tools• The critical importance of end-user proficiency with LLMs• How cross-functional collaboration enables AI success• Why annual planning cycles may be holding your AI initiatives back• The parallels between agile adoption and AI transformation• Moving from efficiency gains to true value creationWhether you're leading AI initiatives, managing agile transformations, or wondering why your organization's AI investments aren't paying off, this conversation offers practical frameworks for thinking about organizational readiness in the age of generative AI.THREE KEY TAKEAWAYS:1. End-user proficiency is everything. 2. Define the sandbox before choosing the toys.3. Innovation in planning matters as much as innovation in products. Contact us: feedback@definitelymaybeagile.com#GenerativeAI #AgileTransformation #OrganizationalChange #AIReadiness #DigitalTransformation #LLM #CrossFunctionalTeams #Innovation
Hey everyone, Alex here
Teaser ... Alex's influential "Google PM Bible" ... What is a tech aggregator? ... AI is much more than chatbots ... The dangers of centralized AI ... What you want vs what you want to want ... How an LLM's memory locks you in ... AGI vs ASI ... Alex's solution to the lock-in problem ... Alex's ode to “resonance” ...
How can Azure Site Reliability Engineering Agents help your Azure infrastructure? While at Techorama in Utrecht, Richard chatted with Deepthi Chelupati about the LLM service that helps you build and maintain more reliable applications and infrastructure in Azure. Deepthi talks about monitoring deployment problems, handling errors in production, and application telemetry in operation as areas where Azure SRE Agents can help catch issues earlier and let you respond faster. The conversation dives into the array of capabilities and where you can provide information to administrators so they can decide how to proceed—perhaps pushing information to development or starting a recovery process of some kind. How you use Azure SRE Agents is up to you!LinksAzure SRE AgentPagerDutyAzure MonitorAzure DevOpsRecorded October 28, 2025
In this Kitchen Side episode of The Long Game Podcast, the Omniscient team dives into a wide-ranging discussion on trust, research quality, and marketing visibility in an AI-driven world. They start with epistemology—what makes research “good” or “bad”—and reflect on how flawed correlations can mislead marketers. The team then unpacks their recent Winter study on how B2B buyers use LLMs like ChatGPT in the purchase journey, revealing that while LLMs are common early in research, peer feedback and brand transparency are essential in final decisions. They also explore the evolution of SEO into GEO/AEO, discuss organizational roles and feedback loops, and propose new cross-functional models for digital visibility in a world of probabilistic, AI-generated content.Key TakeawaysNot All Research Is Trustworthy: Internal/external validity and sample bias can distort marketing data—marketers need stronger research literacy.Correlation ≠ Causation: Data trends, especially in AI visibility, often include spurious relationships—interpret with caution.LLMs Are Entry Points, Not Final Decision Tools: While many B2B buyers start with AI search, they turn to peers and review sites before converting.Transparency Beats Perfection: Buyers trust brands that clearly state who they serve, what they do, and where they fall short.GEO Relies on Accuracy: Incorrect or outdated online information can mislead LLMs—fixing this improves visibility and conversions.Sentiment and Product Reality Matter: Negative perception from bad UX or old reviews isn't a marketing problem—it's a product and comms one.AEO Needs Cross-Functional Ownership: Teams like PR, content, SEO, and product marketing must collaborate to influence LLM visibility.A New Role May Be Needed: “Digital visibility lead” or a cross-team committee could help unify efforts across brand, SEO, and off-page strategy.Show LinksConnect with David Khim on LinkedIn and TwitterConnect with Alex Birkett on LinkedIn and TwitterConnect with Allie Decker on LinkedIn and TwitterConnect with Omniscient Digital on LinkedIn or TwitterWhat is Kitchen Side?One big benefit of running an agency or working at one is you get to see the “kitchen side” of many different businesses; their revenue, their operations, their automations, and their culture.You understand how things look from the inside and how that differs from the outside.You understand how the sausage is made. As an agency ourselves, we're working both on growing our clients' businesses as well as our own. This podcast is one project, but we also blog, make videos, do sales, and have quite a robust portfolio of automations and hacks to run our business.We want to take you behind the curtain, to the kitchen side of our business, to witness our brainstorms, discussions, and internal dialogues behind the public works that we ship.Past guests on The Long Game podcast include: Morgan Brown (Shopify), Ryan Law (Animalz), Dan Shure (Evolving SEO), Kaleigh Moore (freelancer), Eric Siu (Clickflow), Peep Laja (CXL), Chelsea Castle (Chili Piper), Tracey Wallace (Klaviyo), Tim Soulo (Ahrefs), Ryan McReady (Reforge), and many more.Some interviews you might enjoy and learn from:Actionable Tips and Secrets to SEO Strategy with Dan Shure (Evolving SEO)Building Competitive Marketing Content with Sam Chapman (Aprimo)How to Build the Right Data Workflow with Blake Burch (Shipyard)Data-Driven Thought Leadership with Alicia Johnston (Sprout Social)Purpose-Driven Leadership & Building a Content Team with Ty Magnin (UiPath)Also, check out our Kitchen Side series where we take you behind the scenes to see how the sausage is made at our agency:Blue Ocean vs Red Ocean SEOShould You Hire Writers or Subject Matter Experts?How Do Growth and Content Overlap?Connect with Omniscient Digital on social:Twitter: @beomniscientLinkedin: Be OmniscientListen to more episodes of The Long Game podcast here: https://beomniscient.com/podcast/
A new study just came out that explores the similarity between LLM and human responses across countries, seeking to test whether LLMs are less similar to humans in cultures that are more distant from the United States. The general answer they found was yes, they are less similar. However, as I thought about it, it provoked more questions than answers. I share more here, which I hope sparks some questions for you as well. Thanks for listening. As always, Much Love ❤️ and please take care.
Jason Howell and Jeff Jarvis explore Google's Gemini 3 multimodal AI with visual and interactive features, Microsoft's AI Copilot launch across Windows, and Jeff Bezos's new well-funded AI startup Project Prometheus focused on engineering and manufacturing. Note: Time codes subject to change depending on dynamic ad insertion by the distributor. CHAPTERS: 00:00 - Podcast begins 01:55 - Do LLM's understand? AI Pioneer Yann Le Cun spars with DeepMind's Adam Brown 20:45 - A new era of intelligence with Gemini 3 34:25 - Microsoft is packing more AI into Windows, ready or not - here's what's new 37:59 - Inside Microsoft Agent 365: How AI Workers Will Be Secured, Identified, and Governed 42:24 - At a major AI conference, one startup got voted most likely to flop 44:48 - Hugging Face CEO says we're in an ‘LLM bubble,' not an AI bubble 46:07 - Google boss warns 'no company is going to be immune' if AI bubble bursts 49:02 - Google unveils agentic tools to help advertisers - So does Amazon 49:23 - And Meta introduces a foundation model for advertisers 53:17 - DeepMind releases WeatherNext2 56:05 - OpenAI introduces group chats with ChatGPT 58:28 - Microsoft's new Anthropic partnership brings Claude AI models to Azure 59:26 - Amazon and Microsoft Back Effort That Would Restrict Nvidia's Exports to China 1:00:42 - Jeff Bezos Creates A.I. Start-Up Where He Will Be Co-Chief Executive Learn more about your ad choices. Visit megaphone.fm/adchoices
Dennis Wei, Senior Research Scientist at IBM specializing in human-centered trustworthy AI, speaks with Pitt's HexAI podcast host, Jordan Gass-Pooré, about his work focusing on trustworthy machine learning, including interpretability of machine learning models, algorithmic fairness, robustness, causal inference and graphical models.Concentrating on explainable AI, they speak in depth about the explainability of Large Language Models (LLMs), the field of in-context explainability and IBM's new In-Context Explainability 360 (ICX360) toolkit. They explore research project ideas for students and touch on the personalization of explainability outputs for different users and on leveraging explainability to help guide and optimize LLM reasoning. They also discuss IBM's interest in collaborating with university labs around explainable AI in healthcare and on related work at IBM looking at the steerability of LLMs and combining explainability and steerability to evaluate model modifications.This episode provides a deep dive into explainable AI, exploring how the field's cutting-edge research is contributing to more trustworthy applications of AI in healthcare. The discussion also highlights emerging research directions ideal for stimulating new academic projects and university-industry collaborations.Guest profile: https://research.ibm.com/people/dennis-weiICX360 Toolkit: https://github.com/IBM/ICX360
Are you tired of competition and struggling to find collaborators in biotech? In this episode, returning host Patrick Reed, RTTP, talks with Christiaan Engstrom, MBA, Founder and CEO of BLPN, a member-led club connecting life science dealmakers with one goal: helping each other succeed. Christiaan shares how BLPN has built a thriving community where collaboration, mentorship, and trust come first — creating opportunities that go far beyond business cards and conference booths. In this episode, you'll discover: How a simple mantra — “Find someone to help, repeat” — is reshaping biotech networking. Why connection, not competition, is the key to sustainable industry growth. How leaders can strengthen regional biotech ecosystems and bring coastal innovation energy inland. Tune in to learn how genuine collaboration can transform biotech partnerships – and why the most powerful deals start with helping someone else. Links: Connect with Christiaan Engstrom, MBA, and check out BLPN. Connect with Patrick Reed, RTTP, and learn about Auburn University IPX. Learn about Tulane Medicine Business Development and the School of Medicine. Connect with James Zanewicz, JD, LLM, RTTP, and Tamika Jackson. Check out JPM, BioAlabama, and The Beautiful Way Foundation. Connect with Ian McLachlan, BIO from the BAYOU producer. Check out BIO on the BAYOU. Learn more about BIO from the BAYOU - the podcast. Bio from the Bayou is a podcast that explores biotech innovation, business development, and healthcare outcomes in New Orleans & The Gulf South, connecting biotech companies, investors, and key opinion leaders to advance medicine, technology, and startup opportunities in the region.
"La performance, c'est pas juste un benchmark dans un coin, c'est un vrai sujet d'équipe qui doit se traiter tout au long du cycle de développement." Le D.E.V. de la semaine est Adrien Cacciaguerra, cofondateur de CodSpeed. Ensemble, on plonge dans la performance logicielle, un sujet souvent relégué au second plan par les devs mais qui devient vite central quand le code rame en prod. Adrien partage les raisons qui l'ont poussé à créer CodSpeed pour aider les équipes à éviter les régressions et fiabiliser leurs déploiements. On explore l'intégration des tests de performance dans la CI/CD, les galères des environnements partagés et l'évolution des pratiques avec l'arrivée de l'IA et des LLM. Un échange nourri d'anecdotes, de conseils terrain et d'une vision lucide sur l'avenir de la perf et des outils.Chapitrages00:00:53 : Introduction à la performance00:01:13 : La genèse de CodSpeed00:05:34 : Optimisation des performances en CI00:07:52 : Environnement de test et métriques00:11:17 : Défis et solutions pour les bases de données00:14:36 : Mesurer la performance : enjeux et méthodes00:18:26 : L'impact des LLM sur la performance00:20:00 : Micro-optimisation vs. performance globale00:22:16 : Évaluer les tendances de performance00:25:04 : Outils de profiling et apprentissage pour les devs00:30:29 : Intégration de CodSpeed dans les langages00:32:27 : Variabilité des tests en environnement CI00:39:07 : Défis des systèmes distribués00:41:26 : L'avenir des performances avec les LLM00:48:41 : Conclusion et recommandations Liens évoqués pendant l'émission Chaine YT: Code Aesthetic **Restez compliant !** Cet épisode est soutenu par Vanta, la plateforme de Trust Management qui aide les entreprises à automatiser leur sécurité et leur conformité. Avec Vanta, se mettre en conformité avec des standards comme SOC 2, ISO 27001 ou HIPAA devient plus rapide, plus simple, et surtout durable. Plus de 10 000 entreprises dans le monde utilisent déjà Vanta pour transformer leurs obligations de sécurité en véritable moteur de croissance.
A mesterséges intelligenciával felturbózott humanoid robotok még csak raktárakban szerencsétlenkednek, de egyre többet tudnak, és az amerikai techcégeknek Kínával is lépést kell tartaniuk. Közben az AI-ipar továbbra is veszteséges, de 2026 fordulópont lehet. Hogy miért? Ezt beszéltük át az AI Híradó új adásában.See omnystudio.com/listener for privacy information.
On this week's episode, Joe Fairless interviews Jeffrey Brogger. Jeffrey shares practical ways to revive “dead” contacts using AI voice agents that hold natural two-way conversations and surface real buying signals. He explains where these tools outperform blast emails and basic SMS, why latency and compliance matter, and how he builds lower-cost, highly customizable stacks with VAPI, Twilio and modern LLM voices. The discussion closes with an omnichannel playbook that uses ads, email, website activity and AI automations to turn quiet databases into qualified call-backs. Jeffrey Brogger Current role: AI Strategist, Growth Architect, Founder of JJB Industries Based in: Huntington Beach, California Say hi to them at: https://jjbind.com/ Alternative Fund IV is closing soon and SMK is giving Best Ever listeners exclusive access to their Founders' Shares, typically offered only to early investors. Visit smkcap.com/bec to learn more and download the full fund summary. Join us at Best Ever Conference 2026! Find more info at: https://www.besteverconference.com/ Join the Best Ever Community The Best Ever Community is live and growing - and we want serious commercial real estate investors like you inside. It's free to join, but you must apply and meet the criteria. Connect with top operators, LPs, GPs, and more, get real insights, and be part of a curated network built to help you grow. Apply now at www.bestevercommunity.com Podcast production done by Outlier Audio Learn more about your ad choices. Visit megaphone.fm/adchoices
Gemini 3 is officially here. ✨ ✨ ✨For about 8 months, Gemini 2.5 Pro has mostly maintained its standing as the top LLM in the world yet Google just unleashed its successor in Gemini 3.0. So, what's new in Gemini 3? And whether you're a developer or casual user, what does Google's new model unlock? Join us as we chat with Google's Logan Kilpatrick's for all the answers. Gemini 3: What's new and what it unlocks for your business with -- An Everyday AI Chat with Google DeepMind's Logan Kilpatrick and Jordan WilsonNewsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Thoughts on this? Join the convo and connect with other AI leaders on LinkedIn.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:Gemini 3 Release Overview & FeaturesState-of-the-Art AI Benchmarks ExceededGemini 3 in Google Ecosystem ProductsGemini 3 Vibe Coding Capabilities DemoNon-Developer Use Cases for Gemini 3Multimodal Understanding and VisualizationsAgentic AI Tools: Gemini Agent & Anti GravityBusiness Growth with Gemini 3 AI IntegrationTimestamps:00:00 Gemini 3: State-of-the-Art AI05:59 "Gemini 3: Build Ambitiously"08:16 "AI Studio: Bringing Ideas Alive"12:44 Gemini App Agents & Anti-Gravity14:57 "Enhancing AI as a Thought Partner"17:01 AI Studio: Build Apps FasterKeywords:Gemini 3, Gemini 3 Pro, Google AI, AI Studio, Vibe Coding, multimodal model, agentic coding, tool calling, anti gravity, generative interfaces, Gemini app, APIs, AI capabilities, interactive experience, visual dashboard, bespoke visualization, state-of-the-art model, developer platform, agentic developer tools, benchmark results, code editor, IDE integration, product experiences, infrastructure teams, triage inbox, personal assistant, proactive agents, 2.5 Pro, model capability, product feedback, code generation, gallery applets, build mode, ambition in AI, software engineering, feature enhancement, thought partner, AI-powered building, on demand experience, interactive visualizations, coding advancements, user engagement, real-time rollout.Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Head to AI.studio/build to create your first app. Head to AI.studio/build to create your first app.
Meta está reorganizando su estrategia de IA mientras dos visiones chocan entre ellas: Zuckerberg apuesta por los LLM actuales, pero LeCun prepara su salida para explorar otro tipo de arquitecturas. Dos visiones incompatibles sobre el futuro de la IA.Profundiza:TítuloLoop Infinito, podcast de Xataka, de lunes a viernes a las 7.00 h (hora española peninsular). Presentado por Javier Lacort. Editado por Alberto de la Torre.Contacto:
In this special episode recorded live at Amazon UnBox in Nashville, I sit down with Charlotte Maines, Head of Device Advertising for Fire TV at Amazon. We dive into the massive reach of Fire TV—over 300 million devices sold globally—and what that means for brands aiming to connect with high-value, logged-in Amazon customers.Charlotte shares how Amazon is evolving the ad experience from simple tune-in campaigns to interactive, full-funnel marketing opportunities. We unpack the growing role of Alexa Plus, Amazon's new LLM-powered assistant, and how it's revolutionizing personalized, voice-driven engagement across devices. From shoppable connected TV to dynamic creative powered by GenAI, this episode is packed with insights for any brand looking to harness the next wave of CTV innovation.Timeline Summary:[0:38] - Why Fire TV's 300M device footprint is a game-changer for advertisers[2:40] - The “six-minute window”: How brands can show up during viewer decision time[4:22] - Evolution of Fire TV advertising—from HBO tune-ins to full-funnel brand engagement[6:12] - Inside Alexa Plus: How LLMs are powering Amazon's new conversational AI[8:10] - Shopping with your voice: Fire TV and Alexa's seamless commerce experiences[10:00] - The future rotator: Amazon's prime CTV ad real estate explained[12:45] - Full-funnel advertising: How Amazon connects the dots across devices and media[15:15] - GenAI in action: How brands are creating audio ads in seconds using Amazon tools[18:12] - What brands—big and small—are learning from Amazon's self-service creative tools[20:33] - Why devices are key to Amazon's dominance in full-funnel marketingLinks & Resources:Learn more about Alexa Plus: Amazon AlexaExplore Sabio's platform: sabioctv.com
We reframe SEO for an AI-first world and show how agentic workflows turn messy sales processes into predictable follow-through. Matthew Bertram and Stephen Werley discuss how to map the stack, from transcripts and enrichment to Slack-driven next actions that recover hidden revenue.• rebrand to Best SEO Podcast and new AI-derived book• why LLMs matter for analysis, decks, and feedback• custom GPTs tuned with domain knowledge• building automations in n8n, Make, ClickUp, and HighLevel• human in the loop as the quality guardrail• data enrichment with RB2B and Clay for true personalization• marketing, RevOps, and agent orchestration converge• LLM visibility certification and next stepsGuest Contact Information: Website: stevenwerley.comLinkedIn: linkedin.com/in/stevenwerleyInstagram: instagram.com/stevewerleyFacebook: facebook.com/steven.werleyMore from EWR and Matthew:Leave us a review wherever you listen: Spotify, Apple Podcasts, or Amazon PodcastFree SEO Consultation: www.ewrdigital.com/discovery-callWith over 5 million downloads, The Best SEO Podcast has been the go-to show for digital marketers, business owners, and entrepreneurs wanting real-world strategies to grow online. Now, host Matthew Bertram — creator of LLM Visibility™ and the LLM Visibility Stack™, and Lead Strategist at EWR Digital — takes the conversation beyond traditional SEO into the AI era of discoverability. Each week, Matthew dives into the tactics, frameworks, and insights that matter most in a world where search engines, large language models, and answer engines are reshaping how people find, trust, and choose businesses. From SEO and AI-driven marketing to executive-level growth strategy, you'll hear expert interviews, deep-dive discussions, and actionable strategies to help you stay ahead of the curve. Find more episodes here: youtube.com/@BestSEOPodcastbestseopodcast.combestseopodcast.buzzsprout.comFollow us on:Facebook: @bestseopodcastInstagram: @thebestseopodcastTiktok: @bestseopodcastLinkedIn: @bestseopodcastConnect With Matthew Bertram: Website: www.matthewbertram.comInstagram: @matt_bertram_liveLinkedIn: @mattbertramlivePowered by: ewrdigital.comSupport the show
Richard Gearhart and Elizabeth Gearhart, co-hosts of Passage to Profit Show interview media strategist Jess Todtfeld from Media Ambassadors, Micki Vandeloo from Lakeview Consulting and Kenny Kelley from Silent Beacon. If you're not showing up online in 2025, you're disappearing! Media strategist & Guinness World Record holder Jess Todtfeld breaks down why leaders are leaving massive opportunities on the table—and how a few simple shifts can skyrocket your visibility. From turning everyday conversations into offers, to becoming your own media outlet, to getting found by AI, Jess shares power-packed insights that every entrepreneur needs right now. Read more at: https://www.jesstodtfeld.com/ Unlock hidden funding for your manufacturing business! Grant expert Micki Vandeloo from Lakeview Consulting reveals how companies are securing millions to grow, innovate, and hire—without giving up equity. If you think grants are only for nonprofits, think again! Read more at: https://www.lakeviewconsulting.net/ What if one button could save your life? Silent Beacon founder Kenny Kelley turned his own near-fatal accident into a breakthrough safety technology now protecting people everywhere. From instant 911 calls to discreet alerts and real-time GPS, Kenny reveals how one-touch emergency response is changing the game for individuals, families, and businesses. Read more at: https://silentbeacon.com/ Whether you're a seasoned entrepreneur, a startup, an inventor, an innovator, a small business or just starting your entrepreneurial journey, tune into Passage to Profit Show for compelling discussions, real-life examples, and expert advice on entrepreneurship, intellectual property, trademarks and more. Visit https://passagetoprofitshow.com/ for the latest updates and episodes. Chapters (00:00:00) - Offering Money to Start a Business(00:00:33) - Passage to Profit(00:02:03) - Getting Noticed as a Business Person(00:03:15) - The Challenges of Getting Noticed by the Manufacturing Community(00:03:56) - What About Getting Noticed, Funded or Taken Seriously?(00:07:22) - Make More Proposals(00:08:58) - How to Get Out There in the Media(00:15:42) - Jess Toddfeld on Guinness World Record for Publicity(00:20:25) - Jess Thodfeld on How to Get Out There in Media(00:23:42) - How to Become a Media Ambassador: Just Do It(00:26:53) - Commercial(00:27:54) - The Cruise Hotline(00:29:12) - How Business is Using AI in their Business(00:30:39) - How AI is Affecting Grant Writing(00:31:53) - How Is AI Affecting Your Business?(00:33:11) - How Businesses Are Using AI in their(00:40:17) - How to Use the LLM for Older People(00:41:54) - Passage to Profit: Car Insurance Hotline(00:44:34) - Artificial Intelligence and the Copyright(00:48:17) - Hidden Funding for Manufacturing(00:50:29) - What is a Production Grant?(00:54:16) - What kind of grants would be available for entrepreneurs?(00:56:26) - How to Get Grant Money?(00:57:21) - How to Apply for a Grant(00:59:51) - Silo Beacon: A Silent Beacon(01:02:44) - How to Always Be Ready for Nurses(01:04:14) - Silent Beacon: The Need for Personal Safety(01:09:09) - Silent Beacon: The Beacon to Find You(01:10:12) - What is your top market right now? Top demographic(01:11:35) - Passage to Profit(01:13:19) - Jess Toddfeld and Kenny Kelly(01:17:45) - Legal Issues(01:19:23) - Passage to Profit
In this episode of Technology Reseller News, Doug Green interviews Lyle Pratt, Founder & CEO of Vida.io, following the company's announcement of a $4 million Series A funding round—a major milestone marking rapid growth, platform maturity, and expanding traction across MSPs, SaaS vendors, and business software providers. Pratt explains that Vida.io is an AI Agent Operating System for business, designed to help companies deploy, manage, monitor, and scale AI agents that perform real work across voice, SMS, email, and web chat. While many products offer a chatbot or voice agent, Vida.io delivers the full operational backbone required for real-world use: observability, SOC 2/HIPAA compliance, billing-as-a-service, UI components, and detailed interaction scoring. Since the last podcast, Vida.io has grown dramatically, surpassing 100 million AI agent interactions and onboarding a rapidly expanding network of partners. Initially focused on MSPs, the platform is now widely adopted by SaaS companies that embed AI agent capabilities directly into their vertical applications—roofing, moving, and other SMB-focused sectors—bringing instant scale to Vida.io's distribution. A key breakthrough discussed in the interview is Vida.io's ability to deliver low-latency, high-intelligence voice agents that reliably meet real-world customer experience expectations. “If latency is off even slightly, users get frustrated. We had to solve that,” Pratt notes. The result: AI agents that in many cases outperform humans, including one customer reporting 40% more meetings booked compared to human-based calling teams. Vida.io's partner program remains the company's primary growth engine. MSPs are now using AI agents to capture revenue from call flows they previously handed off to outsourced call centers—often redirecting hundreds of thousands of monthly minutes back into their own billing. The platform also supports direct SIP registration, enabling AI agents to function as standard PBX extensions across NetSapiens, Broadsoft, Metaswitch, and other systems widely deployed by MSPs. Pratt emphasizes that the AI revolution is fundamentally redefining UCaaS and business communications: “When the price of intelligence approaches zero, the entire enterprise software ecosystem transforms.” Even if LLM progress froze today, he argues, the impact on communications and business automation would still be historic. As the industry approaches 2026, Pratt sees a major new revenue frontier for MSPs—one that doesn't require deep AI expertise but does require timely action. Vida.io provides the tools to make AI agent deployment fast, repeatable, and profitable. To learn more or join the partner program, visit https://vida.io/. Software Mind Telco Days 2025: On-demand online conference Engaging Customers, Harnessing Data
How AiDigiCards Help Kids Learn AI Safely ft. Amber Ivey | My EdTech Life 343 In Episode 343 of My EdTech Life, I sit down with Amber Ivey to explore AiDigiCards, a new screen-free way to introduce kids to AI literacy, curiosity, and critical thinking. Amber breaks down the journey from her AI-for-adults work, to her children's book AI Meets AI, to her new hands-on learning system for kids ages 4–8.We talk about parent concerns, privacy, LLM overreliance, ethical design, and why AI learning should start at the kitchen table, not on a tablet. If you're an educator, parent, or anyone thinking about the future of AI readiness for kids, this conversation is packed with insight and practical takeaways.Timestamps00:00 – Introduction 02:00 – Why Amber focuses on AI for kids 05:30 – From books to workshops 09:15 – Introducing AiDigiCards 10:30 – Why screen-free AI learning matters 12:00 – Parent concerns about AI 14:00 – Protecting curiosity and creativity 17:00 – The four C's of AI literacy 21:00 – Kids spotting real vs fake 26:00 – “Are kids too young for AI?” 27:00 – Teach kids AI… or AI teaches them 29:00 – The problem with unsafe AI tools 35:00 – Amber's personal journey 37:30 – What keeps her up (in a good way) 40:00 – AiDigiCards Kickstarter 46:00 – Thank you to our sponsors!
Connect with Will at: https://bsky.app/profile/wiverson.com https://www.linkedin.com/in/wiverson Mentioned during the series: Will's Youtube channel: https://changenode.com/ https://www.youtube.com/@ChangeNode Mentioned in this episode: killed by google: https://killedbygoogle.com build your own LLM: https://www.freecodecamp.org/news/code-an-llm-from-scratch-theory-to-rlhf/ The post 312 AI as a Capital Market first appeared on Agile Noir.
What if the way your team talks is the blueprint for every product you ship? We sit down with Erica Hall—co‑founder of Mule Design and author of Just Enough Research and Conversational Design—to connect the dots between internal communication, ethical practice, and the systems that end up in people's hands. From AI hype to accessibility debt, Erica challenges the default settings that turn “innovation” into convenience theater and shows how small, human choices reshape outcomes.We unpack Conway's Law and why so many “conversational” tools are really shields that prevent actual conversation. Erica explains why accessibility must be the foundation of value delivery, not an add‑on, and how multimodal design—voice, text, GUI—honors real life context switching. We talk about the political economy behind today's platforms: funding fads, LLM bandwagons, and the quiet scaling of bias through automated decision making. Along the way, we explore the power dynamics of in‑house design teams, why external partners once provided crucial leverage, and how fear erodes the point of view needed to build responsible products.Most importantly, we get practical. Erica shares tactics to rebuild trust at work through private, human conversations that aren't mediated or recorded; ways to move beyond AI theater by naming goals before choosing tools; and advice for new graduates navigating a volatile market without losing themselves. If you're wrestling with inclusion, ethics, or the pressure to “ship a chatbot,” this conversation offers clear language, real examples, and a path to designing with dignity.Listen, share with a colleague who needs a sanity check, and leave a review so more builders can find this conversation. Subscribe for future episodes focused on ethical design, accessibility, and the real work of making technology serve people.Support the showFollow axschat on social media.Bluesky:Antonio https://bsky.app/profile/akwyz.com Debra https://bsky.app/profile/debraruh.bsky.social Neil https://bsky.app/profile/neilmilliken.bsky.social axschat https://bsky.app/profile/axschat.bsky.social LinkedInhttps://www.linkedin.com/in/antoniovieirasantos/ https://www.linkedin.com/company/axschat/ https://www.linkedin.com/in/neilmilliken/Vimeohttps://vimeo.com/akwyzhttps://twitter.com/axschathttps://twitter.com/AkwyZhttps://twitter.com/neilmillikenhttps://twitter.com/debraruh
✅ Silicon Valley entrepreneurship takes on a whole new meaning in this conversation with Lin Wu, whose extraordinary journey from a broom shop to a Fortune 500 technology executive embodies the true immigrant entrepreneur story, the evolution of Silicon Valley history, and the modern pressures of AI and the future of work. In this episode, we explore the insights, lessons, and pivotal moments that shaped one of the earliest engineers in Silicon Valley—and what his story means for anyone navigating today's rapidly shifting tech landscape.If you're researching how Silicon Valley really works, how careers in tech evolve, or whether innovation still lives in the Valley, this episode brings clarity. Listeners searching for how to break into tech, how AI is changing software jobs, or how immigrants succeed in entrepreneurship will hear real-world stories from someone who lived through the transistor revolution, the birth of mainframes, and the rise of venture-backed startups. Lin Wu provides candid insight into how the industry has changed—and what remains timeless.For founders, engineers, and professionals evaluating where to build their career, Lin breaks down the competitive realities of today's tech ecosystem, from tech career advice to the impact of rise of AI in tech, chip war and semiconductor industry dynamics, and the truth about cost of living in Silicon Valley. His decades of experience at IBM, Fujitsu partnerships, and startup building reveal how today's challenges mirror—and differ from—the early days of modern computing.This video helps answer key questions people frequently search:Is Silicon Valley still worth moving to?How will AI reshape software careers?Can immigrants still achieve the American Dream?How should students choose majors for the future economy?Where is the AI race between the U.S. and China actually heading?Lin Wu's wisdom offers not just answers—but perspective. You'll walk away with actionable insights on innovation, mindset, adaptability, and how to thrive as technology undergoes the biggest transition since the birth of the PC.⭐ Timestamps (15:36 total)00:00 – Introduction to Lin Wu01:00 – Immigrant beginnings and early struggles02:00 – Paying for school and first jobs in America03:00 – Entering the Ivy League and meeting IBM04:00 – Mainframe computing and the birth of Silicon Valley05:00 – Venture capital and the first startup experience06:00 – The Japanese partnership and technology transfer07:00 – Growing a company into the Fortune 50008:00 – Then vs. Now: Evolution of Silicon Valley09:00 – AI, chips, Nvidia, and the U.S.–China tech race10:00 – Remote work, Austin & Miami migrations11:00 – The American Dream then and now12:00 – How the iPhone changed tech forever13:00 – Who is winning the LLM race?14:00 – Career advice for the next generation15:00 – How to find Lin Wu's book⭐ Hashtags#SiliconValley #Entrepreneurship #LinWu #ImmigrantSuccess #AIRevolution #TechCareers #StartupLife #AmericanDream #SiliconValleyHistory #FutureOfWork #AIandTech #SemiconductorIndustry #Nvidia #TSMC #VentureCapitalTo check out the YouTube (video podcast), visit: https://www.youtube.com/@drchrisloomdphdDisclaimer: Not advice. Educational purposes only. Not an endorsement for or against. Results not vetted. Views of the guests do not represent those of the host or show. Click here to join PodMatch (the "AirBNB" of Podcasting): https://www.joinpodmatch.com/drchrisloomdphdSubscribe to our email list: https://financial-freedom-podcast-with-dr-loo.kit.com/Thank you to all of our sponsors and advertisers that help support the show!Financial Freedom for Physicians, Copyright 2025
Application volumes are continuing to rise, but finding quality hires remains a challenge. The usual suspects that tend to get the blame are candidates using AI, economic uncertainty, and a continuing decline in job board effectiveness. However, research suggests a more fundamental issue that many organizations overlook. The words in job descriptions matter more than most teams realize. Non-inclusive language is actually a key factor that stops many qualified candidates from applying. At the same time, regulations around pay transparency and anti-discrimination are proliferating across the US and EU, creating complex compliance requirements for job ads that vary by market. Many employers are also outsourcing their job ad creation to generic LLMs that have more potential to amplify bias than they do to eliminate it. So, how should employers utilize technology to ensure inclusivity, compliance, and a high-quality response from their advertising My guest this week is Pil Byriel, CEO and co-founder of Lyser. In our conversation, Pil shares research on how language shapes candidate behavior, why LLM reinforces bias, and the growing complexity of job ad compliance around the world In the interview, we discuss: The impact of language on applications from qualified candidates The human-led research behind inclusive communication Why generic AI LLMs amplify stereotypes and bias Compliance challenges across global markets What actually drives job ad performance Why structure, clarity, and transparency matter Building data-driven recruitment communication Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.
How do you bring AI into a newsroom as big and globally distributed as the BBC, an editorial network that stretches across 42 languages and more than 5,000 journalists?This week on Newsroom Robots, host Nikita Roy talks to Olle Zachrison, Head of News AI at BBC News, where he leads the BBC's efforts to advance AI use and strengthen its journalism and audience experiences. Previously, the Head of AI at Swedish Radio, Olle has spent the past few years implementing practical newsroom AI workflows while upholding public-service values.In our conversation, Olle breaks down BBC's four-part AI strategy, covering large-scale translation and transcription, content reformatting, investigative tools, and early experiments with synthetic audio and conversational news. He shares what's working inside one of the world's largest news organizations, what routinely stalls AI projects, and why the most challenging part of AI transformation isn't the technology but the collaboration required across editorial, product, and engineering. Olle also reflects on what it means to innovate as a public broadcaster in an AI-driven ecosystem, and why archives, credibility, and direct audience relationships will determine which journalism remains indispensable in the years ahead.In this episode, we cover:03:39 – The BBC's four-part AI strategy: Boosting productivity, reformatting content, augmenting journalism, and innovating user experience as the core themes05:10 – Using AI for large-scale transcription, tagging, live pages, alt text, newsletter production, and translation to save time and make content more searchable.08:17 – Reformatting content across platforms and formats20:59 – Innovating user experiences with synthetic audio and conversational formats31:59 – How the BBC uses strategic themes, clear metrics, and fast pilots to decide what's worth building and scaling46:59 – Inside the BBC's fine-tuned LLM and Style Assist52:01 – What it means to be a public broadcaster in an AI-driven ecosystem01:02:58 – Olle's personal AI stackSign up for the Newsroom Robots newsletter for episode summaries and insights from host Nikita Roy. Hosted on Acast. See acast.com/privacy for more information.
Today on the show, we have Kevin White, Head of Marketing at Scrunch AI, a platform helping brands stay discoverable in the era of AI-powered search. Kevin brings experience from leading go-to-market and marketing teams at Segment, Retool, and Common Room, as well as advising fast-growing startups like Ashby, Deepnote, and Gretel.ai. In this episode, we explore how the rise of answer engines like ChatGPT and Perplexity is reshaping how people find information online—and what it means for marketers. We discuss how Scrunch helps brands optimize their sites for large language models (LLMs), why bots are becoming the new audience, and how AI-driven search is redefining visibility and discovery. We also delve into lessons from Segment and Retool on balancing self-serve and enterprise growth, how activation-first onboarding drives retention, and why doing “white-glove at scale” can triple user success. We wrap up by unpacking Kevin's biggest learnings on churn and growth—from Reforge's “don't fill a leaky bucket” principle to why something as simple as naming conventions can make or break a company's ability to scale.Churn FM is sponsored by Vitally, the all-in-one Customer Success Platform.
When trying to grow your property management business, have you ever thought to yourself, "Man, it would be great if I just had more leads?" In this episode of the #DoorGrowShow, property management growth experts Jason and Sarah Hull discuss the Leads Myth and how "just having more leads" will not actually help you grow your business. You'll Learn [02:06] The Myth of Needing More Leads [11:39] Leaks in Your Sales Pipeline [22:41] The Future of SEO with AI Quotables "Why do we call it the leads myth? Well, the myth is this lie that we believe that you just need more leads. And the assumption in that is that all leads are the same." "The more clarity you have, the less wrong stuff you're going to be doing." "Not all clients are equal, right? Which means not all leads you get are equal. You need to qualify them." Resources DoorGrow and Scale Mastermind DoorGrow Academy DoorGrow on YouTube DoorGrowClub DoorGrowLive Transcript Jason Hull (00:00) Most of the industry is trapped in a cycle of suck. This is why most property managers suck in most markets. Maybe even you that's listening. We are Jason and Sarah Hull, the owners of DoorGrow, the world's leading and most comprehensive coaching and consulting firm for long-term residential property management entrepreneurs. For over a decade and a half, we have brought innovative strategies and optimization to the property management industry. We help people grow their property management businesses quickly. And our mission is to transform property management business owners and their businesses. We want to transform the industry, eliminate the BS, build awareness, change perception, expand the market, and help the best property management entrepreneurs win. Now let's get into the show. All right. So today we're going to be chatting a little bit about the leads myth that a lot of people believe. So if you have ever thought to yourself, I just need more leads. If I just had more leads, everything else would be great in my business. What do you have to say about that? Well, I think that is not the case. Okay. It's definitely not the case. And I also think almost kind of be careful what you ask for a little bit. getting a whole bunch of leads was never really the best. strategy anyway, unless you have people who are just picking up the phone and calling you and saying hey, I Would love for you to just manage my property. I don't have any questions. Here's my money. I just had a contract Those are leads I want but cold leads that are Not ready to go that need to be warmed up that have a bajillion questions That might not even understand why they want to work with you Specifically, yeah, I'm just not interested in those leads. And the other thing I think we need to discuss on this episode specifically is the changes that we're seeing because of AI. So AI is really great and also it's changing things very rapidly and leads and SEO that's very effective by this too. Okay. So. Let's get into this. So a lot of people believe they just need more leads. And the danger in that is if you really just think you need more leads, you're going to go out to the marketplace and talk to marketers and they're going to go, cool, I'll give you leads. And they will sell you leads basically. So why do we call it the leads myth? Well, the myth is this lie that we believe that you just need more leads. And the assumption in that is that all leads are the same. And they're not, they're not even remotely the same. So there's a couple of different frameworks that we usually talk about to kind of destroy the leads myth. One is the four Ds to revenue. Another is the cycle of suck we talk about and how people get stuck in growth. We talk sometimes about the pipeline leaks that you have in your pipeline. And we talk about the myth of SEO or internet marketing. And then we often talk about any others warm versus cold leads and then David versus Goliath. Okay. So we can tackle these all really quickly and go through each of these and maybe some other things will pop up as we go. Cool. Let's talk about all of that and then we'll talk about why AI has changed all of, really all of those things. Okay. That'll be in conjunction with SEO. All right, so let's go through these. And so for those following along, if you stack all these concepts, each one compounds your speed of growth. They're all related. And so these are frameworks that I love to share with clients to help them understand so that they don't make the mistake of doing the wrong stuff. The more clarity you have, the less wrong stuff you're going to be doing. The less you're going to be experimenting, the less you're going to be wasting time. And if you really wanna collapse time, the easiest hack is reach out to us and we can help you with all of this. We've been doing this for over a decade and a half. We have had hundreds of guinea pigs to figure this all out and we have over 100. case studies and testimonials more than anyone else in the industry. All right. Let's get into this. let's talk about the four D's to revenue. So these are four numbers when multiplied equal the gross revenue in your business. And I sometimes call them the four doors to revenue. And I showed four doors with a little multiplication X next to each of them equals your money. Right? So not all leads are equal. So the, these D's are, if you want to write them down, they each start with a D. It is Deals, doors, duration, and dollars. Okay? So the first is like how many deals is this client going to bring you? Not all clients are equal, right? Which means not all leads you get are equal. You need to qualify them. And how many doors are they bringing to the table? Or how many doors per deal are they bringing? And then the third D is duration. How long are they going to stick around or be involved in property management? is are they an accidental investor that's going to stick around for maybe a year, or are they in the buy and hold game and they'll be around for 10? And then the last D is revenue or is dollars. And so are they a cheapo? Are they a premium buyer? Where do they kind of fit? Or are they somewhere in the middle, like the normals as I call them? So we've got these four Ds. So let's play a quick example. Let's take the accidental investor. They couldn't sell their property. They wanna get it rented out. How does this play out in the 4Ds? done one deal. They didn't mean to do a deal, but they did. And it's usually just one door. Maybe sometimes they have two, but very often we just see one door and they're not looking to... to do more deals because as soon as the market spikes and the market is hot, they're going to bail. They're going to sell, which means the duration is questionable. Let's say it's like one year, like if they can just get it rented. but it might be a few months because if the market spikes three months from now, they're probably going to dump that property pretty quick. And then. than the dollars, they're not your premium buyers. They're not looking to do a lot of improvements. They're not looking to spend a lot of money. They're the people who, they have this property, they aren't quite sure what to do with it. They figure, let's just see if I can get it rented. They want it well taken care of, but they're not generally looking to spend a lot of money or invest a lot of money in either the property or maintenance or repairs or improvements or a property manager. So they're just trying to... Do what they need to do. It's like the bare minimum in order to get a tenant. All right, so one, one, one, right? Like one deal, one door, one year duration, for example, if this is worst case scenario and you sign a one year agreement with them and they're a cheapo, right? Now let's take a really great scenario. What would be maybe an opposite scenario or a really great opportunity? Like my, I will say my second largest client. He had 42 doors I think was the right answer but I was looking to buy more. So when I took him on he had 42 by the time I sold the business he had 60 something. So he was always doing multiple deals. Yeah. The doors that he had came out of multiple deals. So since he did multiple deals he also had multiple doors. was consistently looking to grow. He didn't want to just stop, you know, at a certain point he was always looking. He also was a buy and hold investor. He wasn't trying to buy these things and then wait, you know, until the market spiked and then try to sell them and make a profit. He wasn't up for the long term. And he was not a cheapo. He wasn't trying to cut corners. He wasn't trying to cut costs. You he wanted to work with. a property manager, wanted to take care of the properties and make sure that they were being maintained properly. Yeah. Okay. So that's a great example that previous client that you had. So let's just say like on each of these fees, we use tens instead of ones, right? Like let's say they do 10 deals over the life of being with you. They've got 10 doors. Maybe sometimes it's 10 doors per deal if they're doing small multis or something like this, right? And then you've got a 10 year buy and hold duration. In this hypothetical example that I just threw out, it would be 10 times 10 times 10. This would be over a thousand times greater lifetime value than that accidental investor in our previous hypothetical. Does that make sense? So are these even remotely equal? No, not even remotely equal. Should you then spend the same amount of time trying to cultivate both of those type of leads? Probably not. Would you spend the same amount of time following up or giving them attention? Probably not. And the great investor clients probably are easier to deal with, less emotional, have a much higher margin and operational cost is lower, right? And so there's a lot of benefits. so this is, we're just talking about the revenue piece, but when we look at the cost side of things as well, everybody knows having a really bad owner that's really needy and difficult and emotional about the property. can be a big headache and a big challenge and you may be losing money on some of those doors. So, four D's to revenue, that's one concept. One quick thing I wanna add to that is where do you think these owners hang out? So, if you've got an accidental landlord and they are looking for a property manager, where might that lead come from? Versus where might the lead of a client that has 42 doors come from? There's a lot higher probability that an online lead is going to be an accidental landlord. It's not impossible to get an online lead that has 42 doors. It's just probably not your norm because the ones that have 42 doors, they aren't really dabbling. They aren't going, oh, geez, I wonder if I should get a property manager to maybe help me with these. They are just a little bit more savvy. A lot of times those aren't going to be the leads that you're getting if you're buying leads. Although those are the leads that you want, it's not going to be the norm that you get. All right, so we're 10 minutes into this. We're going to crank through some of the rest of these. So cycle of suck. Cycle of suck, real simple. If you take on any client, it leads to you having some bad clients. So if you take on bad clients, that leads to you having bad properties, which leads to having bad. Residents or tenants which leads to having a bad reputation or reviews which leads to you attracting more bad clients. So not all leads are good. You don't want to take on every client and you definitely don't want to attract or get more bad leads. And so this is a framework that if you understand you can reverse it and focus on a cycle of success where you're picky about the owners you take on, you're picky about the properties you take on, you're picky about the tenants which everybody tries to do anyway. but those first two steps are supremely important. And then you're going to have a methodology for getting more positive reviews. These are things we help our clients with. And so then you create a cycle of success. Most of the industry is trapped in a cycle of suck. This is why most property managers suck in most markets. Maybe even you that's listening. We want you to get out of the cycle of suck. All right, let's talk about the pipeline leaks. Okay. So usually if I were drawing, I would draw a spigot or a faucet or whatever you attach a hose to, and then I would draw a hose, and then I would draw a little plant or tree that you're trying to grow at the end of the yard that this hose is trying to get water to. Most of you listening think, I just need more leads. This is where the lead Smith becomes really obvious, trying to turn on that faucet even more. I just need more water flowing through the hose. That would make sense, that would be true unless there's a problem with the hose, right? Like the hose has some leaks. And if the hose has some major holes in it, there's not going to be a lot coming out the other end. Sometimes very little at all. And so it's not about how many leads you're getting, sometimes it's just how good is your pipeline? How tight is your product? And so we need to make sure that we get those leaks shored up. And we'll just mention what they are real quick, but. One of the earliest ones that affects you is just awareness. It's going to be your perception and reputation online. It's going to be your website. It's going to be your branding. So they can tell that you are in this industry and that it's clear that that's your focus and it's not real estate or something else. And what else? Your culture and purpose. This is the actual product that you sell. So that is another one. And there are two more. Pricing. Pricing, which everybody's trying to price the same way, 10 % or worse, pure percentage, or they're doing flat fee. We have a different innovative pricing model. If you're curious about that, set up a call with our team. We can tell you about it. That allows you to close more deals more easily at a higher price point. And the last is the pitch, right? Selling. And so if you can dial in each of these leaks, what we've noticed over the years is we can double a company's close rate without changing the amount of leads or lead sources that they're getting currently if we can get those things dialed in. And that's significant. Maybe you don't need more leads. Maybe you just need less leakage in your pipeline. Cool. All right, the next one, you had mentioned warm versus cold leads. Do you wanna explain the difference? Yeah, we can talk about warm versus cold. So when I had my property management business, Yeah. what is a cold lead? So cold lead is someone who really has almost zero, very little familiarity with who you are in your company and your brand and what you do. They don't. they should work with you. That's the big thing is why they should work with you. So they don't know you, trust you or like you. That's a cold lead. And a warm lead. Warm lead would be something like a referral or some sort of recommendation. hey, Sarah is the best, I work with her and you should too. Now they're coming in already feeling like, somebody that I know that I trust recommended this person, so therefore I should also trust this person. So those obviously have a much different close rate. And there are things that you can do to increase your close rate or to warm up deals, of course. But if you're spending all of your time trying to close a bunch of cold leads, which generally is going to be what happens when you're purchasing leads, you really don't get to buy warm leads. Right. They're all cold. I mean, that would be great if you could, but when you're buying leads, you're usually buying a lead that is very cold. They don't know you at all. And oftentimes that same lead is being sold to multiple different companies. There's a lot of blood in the water there. So warm leads versus cold leads, the close rate on warm leads will be really high, like 90 % or higher. Cold leads, like the opposite, 10 % or worse. And so I would rather a client get five warm leads and maybe close four of them than 10 cold leads and maybe get one. The hidden pain point or secret with warm versus cold lead generation. or cold lead strategies is time. Cold leads take a massive amount of time because you have to nurture them and warm them up and build the trust and create the relationship. And even after all of that, and all of sudden done, the conversion rate's really low. So all of you know how high the close rate is if you get a really great word of mouth referral. We love those, right? That's a warm lead. So we have strategies and methods that we focus on with clients to increase the warm leads. while avoiding and doing cold lead advertising and avoiding worrying about cold leads. Once you start getting some growth engines installed for your business that give you warm leads, you're not going to want the cold leads. They feel like garbage in comparison, and you're not going to have time for them. And you're not going to wanna waste time on those because those are often the worst owners. All right. What I would say is as far as getting leads in, if you give me three warm leads, I will take three warm leads over even 100 cold leads. Sure. don't, I don't, I'm not really interested because even if I close, let's say two out of the three warm leads, that's great. What's the close rate on 100 cold leads? If it's about 10%, you might close 10. And some of you might be going, Sarah, 10 is better than two. Yeah, you're right. But how much work did it take for me to close the two versus how much work? did it take for me to close the 10? I would rather close two very easy warmed up leads because I can do that again and again and again. So in the same amount of time, I can close way more warm leads than I can cold leads. So I would rather take three warm leads than a hundred cold leads any day of the week. We have a sponsor for this episode. Many of you tell me that maintenance is probably the least enjoyable part of being a property manager and definitely the most time consuming. But what if you could cut that workload by up to 85 %? That's exactly what Vendero has achieved. They've leveraged cutting edge AI technology to handle nearly all your maintenance tasks from initiating work orders and troubleshooting to coordinating with vendors and reporting. This AI doesn't just automate, it becomes your ideal employee, learning your preferences and executing tasks flawlessly, never needing a day off and never quitting. This frees you up to focus on the critical tasks that really move the needle for your business, whether that's refining operations, expanding your portfolio, or even just taking a well deserved break. Over half of the room last year at DoorGroad Live, our conference signed up with Vendero right there. And then a year later, they're not just satisfied, they're raving about how Vendero has transformed their business, don't let maintenance drag you down. Step up your property management game with Vendoroo. Visit Vendoroo.ai slash door grow today and make this the last maintenance hire you'll ever need. All right. I thought it was a good time because it was a good time. Waste of time and I don't like to waste time and maintenance coordination can be a huge waste of time. Yes. All right. Let's talk about David versus Goliath. So I'll give you an example. We've got a client. that has, so this is dumb David versus smart David, right? The story of David and Goliath, if you're not familiar with the Bible. David goes to fight Goliath. These two warring nations send out their best person and David decides he is not going to wear the armor, the sword, the shield, all the heavy stuff. He's just bringing out his slingshot. He's got his sling, he's got some rock and he goes out to fight Goliath and he's like, I don't need all that stuff. What most property managers do is David basically brought a superior technology. He brought a gun to a sword fight and he was good at this. He trusted himself. He had skill. He had a better tech to beat this giant. He flung the rock right into the guy's head. I had knocked him unconscious or killed him, I don't know. And then he chopped the guy's head off with his own sword. Right. And so that's the story of David and Goliath. So let's talk about the dumb version of David. Like if David wasn't smart. And he said, I'm going to do all the same stuff. I'm going to use the sword of SEO and the shield of pay per click and the helmet of content marketing and the breastplate of social media marketing. And I'm going to do all the same stuff, digital marketing that all the other big companies are doing that are spending two to $3,000 a month or greater. I'm going to go compete with them as a small startup or a small pro. two to 400 unit property management business and try and compete with these big companies that have thousands of doors. One of our clients, as an example, came to us has 6,000 doors. They were spending $30,000 a month doing these strategies to try to grow and it wasn't even working for them. So why would you go and do what the big guys are doing and lose the battle with them and it's not even working for them, right? So that's the idea of David and Goliath. Don't go do what the big guys are doing, find a better way to compete, especially if you're smaller than them. You don't wanna try to outspend them, because that's not going to be possible. right, myth of SEO. All right, and we'll talk a little bit about the future and AI, all right, to wrap things up. So, all of you can go check this out for yourself. This is not me making stuff up. You can go on trends.google.com. You can go look up property management. date it, the time period, to the current time back to 2004, to the present. And you can filter by the US if you want to. What you'll see is that property management search volume, the amount of people searching for property management on Google has not increased since they started tracking data back in 2004. What has increased? The Goliaths, right? The companies spending a lot of money on digital marketing trying to do all this stuff. And so it's created a lot more competition. So this is where we get into another framework that we share, which is the blue ocean versus the red ocean. There's this small little area of the ocean that's red bloody water where all the sharks are fighting over the worst fish, which are these terrible property management business owners that are at the end of the sales cycle. Basically the crappy scraps that fell off the word of mouth table that the warm lead stuff has captured. They're what's left over. And so there's these ugly gross fish and the sharks are all fighting over the worst stuff. And there's this huge ocean full of fish in the U.S. 60 % are self-managing. There's tons of business out there. And so the myth of SEO is basically this, that in order to win the game, you need to have the top spot on Google. Not true. You don't even have to show up on Google in order to go out and be able to create business. Because there aren't really people searching for property management. It's very small. So you don't need to be found on Google. You need to go find owners because the best clients are offline and they're not looking for you and they don't like doing property management and they need you, but they're not looking for property management actively right now. And you can figure out how to go make that happen and we can teach you, right? So let's talk about the future of AI. What are we noticing? Well, I don't think it's any surprise. messed up a lot of Yeah, it's changing everything. AI is going to change everything. And if you haven't noticed it yet, just hold on because you will. It's crazy if you haven't even seen it yet. But it's it's going to flip everything you know upside down, including SEO. Yeah, including SEO. So everyone that is like, no, I don't care. I'm still going to do SEO. That's the only way to go. Like we made a video about this. specifically for this reason, but even the ones who are still clinging to SEO and you just can't let it go and you don't know that there's another way and maybe you don't believe it and you're like, no, I'm no, this is the only thing I'm going to do and I'm going to do this and that's the only way I can grow the business. That is all right and SEO is going to force you to look at that. Okay, yeah, so what we're seeing is search volume on Google is going down. There's less people using Google. More people are now going to LLMs like ChatGPT, Clod, Perplexity, Google's Gemini. So people are using tools now, sometimes within software, and they're using these tools to ask questions, to figure things out, figure out who they should use or who they should choose or what they need. And so Is it still relevant to have good reviews? Yes. Is it still relevant to maybe have some SEO stuff going? Probably, but it's certainly on the down slope and it's certainly decreasing. The game is changing. Even if you search on Google now, the AI at the top will respond to your search request anyway. And a lot of people are just reading that and not really looking at the results below. And so this is the new future. It's changing very quickly. and some are calling it AEO, some are calling it LLM, SEO, there's all these different phrases that are coming out. If you want to do a quick experiment, open up one of these LLMs like ChatGBT. Don't be in your own. It's a large language model. It's basically all these different AI chat tools. So go into ChatGBT. Everybody should be familiar with that by now if you're not. and go to ChatGPT open that up, but make sure you're not logged in or you use a different account and just, or say don't use any of my previous data or open a private window and say don't use any of my previous information or data and say who's the best property manager or what property manager should I choose in X market, right? And see if it comes up. See if your business comes up and see what shows up. And so this is... how people are kind of doing some of their research, but all the stuff we just talked about still applies. Don't think your whole goal needs to be LLM SEO, where you need to start getting these chat tools to tell people. Why? Because most people are not looking for a property manager. They're not looking. They are not trying to find you. That's the mistake most people make. The majority of people that are self-managing, the potential business, are not looking for a property manager. It's really rare that somebody has a property manager that they're looking actively for a new one unless they've really done a bad job or stolen money or done something really obvious. The people that need your services are not looking for you. You need to be looking for them. And so this is where you can skip all of the cold lead marketing. You don't need to spend money on SEO or AI SEO or Google Ads or pay-per-click or any of these marketing agencies, you don't need to spend any money and you can actually grow faster if you use our strategies and it costs you nothing to do the strategies that we give you. It costs time and action, but it actually takes less time because warm leads and focusing on more effective strategies give you a much greater result in less time. So less time, less money, more results. And that's why we call it the Leadsmith. A lot of people think I just need leads. Cool. there's better ways. Not all leads are equal and we can help you out. Cool. Anything else we should add in wrapping up? I don't think so. I think we covered everything. Okay. I think we got it. So cool. Well, if you are wanting to figure out how do I grow this business? How do I finally get out of the rut that I've been in? How do I scale this? Maybe adding more doors is creating you grief and pain and you want freedom from your business. These are the things we help clients with. We'll help you figure out how to grow dramatically faster and we'll help you figure out how to make your business scalable while getting you out of the day to day and getting you to exit the business in various ways so that you get more freedom. So if you felt stuck or stagnant, you want to take it to the next level, reach out to us at doorgrow.com. Also join our free Facebook community just for property management business owners at doorgrowclub.com if you would like to get the best ideas in property management, join our newsletter at where? doorgrow.com/subscribe And if you found this even a little bit helpful, don't forget to subscribe and leave us a review. We'd really appreciate it. And until next time, remember the slowest path to growth is to do it alone. So let's grow together. Bye everyone.
Mike Hanson, CTO at Clockwise, joins the show to break down how our relationship with computers is changing as language based systems reshape expectations. We explore why natural storytelling feels so intuitive with today's AI tools, how context is becoming the new currency of great software, and why narrow AI is often more powerful than the industry hype suggests.This conversation gives tech leaders a grounded look at what is real, what is noise, and what is coming fast.Key Takeaways• Natural storytelling is becoming the default way people communicate with AI, and products must adjust to that shift.• Context is the driving force behind great interaction design and LLM powered systems now surface and use context at a scale traditional UIs never could.• Most real world gains come from narrow AI that solves focused everyday problems, not from broad AGI promises.• Multi agent systems and multiplayer coordination are emerging as the next frontier for enterprise AI.• The biggest risk is not model weakness but user uncertainty about when an answer is trustworthy.Timestamped Highlights01:21 What Clockwise is building with its scheduling brain and how natural language creates new value04:13 Why humans default to storytelling and how LLMs finally make that instinct useful08:00 The rising expectation that software should understand context the way people do12:13 The shift away from feed centric design and toward multi person coordination in AI systems17:31 Why narrow AI delivers real value while wide AI often creates anxiety23:52 A real world example of how AI can remove busy work by orchestrating tasks across tools26:24 Why we do not need AGI to meaningfully improve everyday productivityA standout thoughtPeople have always tried to talk to computers in a natural way. The difference now is that the systems finally understand us well enough to meet us where we already are.Pro Tips• Look for AI that reduces busy work across tools rather than chasing broad capability.• Prioritize context rich interactions in your product planning. It will define user expectations for years to come.• Treat multi person workflows as the next major opportunity. Most teams still rely on manual coordination.Call to actionIf this episode helped you think differently about where AI is actually useful, follow the show and share it with someone who is building product in this space. And join me on LinkedIn for weekly insights on tech, people, and impact.
LLMs are already “deciding” your brand for buyers. Are you shaping that story or letting the machine write it? If your marketing still sounds like everybody else's, congratulations: you've trained the models to ignore you.This week we rip into the hottest B2B reality: AI Engine Optimization (AEO) meets human-only brand. Ari Yablok, head of brand at Island, shows how to beat sameness by sending clear “this is new” signals, building experiential brands that people feel (not just read), and using unreasonable hospitality to make products and events feel theirs, not “yours.”We also cover:AEO is the new SEO: how to show up inside LLM answers and make people prefer you before they ever ask a bot.Signals over slogans: designing booths, visuals, and copy that telegraph “category shift” without a single bullet point.Unreasonable hospitality in B2B: turning product nuance and in-person moments into retention (and reputation) machines.The “feeling of knowing”: why brand confidence shortens deals—even when buyers can't explain why.Human as the counter-trend: embracing curated flaws and analog touchpoints to stand out as AI perfects the average.
Smart Agency Masterclass with Jason Swenk: Podcast for Digital Marketing Agencies
Would you like access to our advanced agency training for FREE? https://www.agencymastery360.com/training How are you preparing your clients to start thinking about AI as part of their SEO strategy? Are you educating them on what they can expect now that the landscape is changing with AI optimization? As an agency, you should be starting these conversations because you can be sure your clients are already thinking about AI, even if they still don't understand its applications for how clients will get to their content. Artificial intelligence isn't just changing how people find information, it's rewriting the rules of search altogether. Today's featured guest is already running AI audits for his clients; he thinks all agency owners should be doing this. He'll unpack what AI optimization really means for agencies, marketers, and business owners who've lived and breathed SEO for decades. Vishal Mahida is the Director of Digital Marketing at E2M Solutions, where he helps over 100 agencies scale their SEO and digital marketing operations. With a 40+ person team specializing in SEO, PPC, and operations support, Vishal works directly with agencies on systems that drive measurable growth and keep them ahead of major shifts in the industry. In this episode, we'll discuss: SEO vs. AI Optimization No, SEO is not dead, so your website still matters. Preparing your agency and clients for AI search. Subscribe Apple | Spotify | iHeart Radio The Difference Between SEO and AI Optimization There's a lot of buzz around how AI has come to change and maybe even replace SEO. Vishal clarifies that AI optimization isn't replacing SEO, it's expanding it. Traditional SEO focused primarily on optimizing for Google rankings, keywords, and backlinks. The goal was to get traffic from search results. But as Vishal explains, the modern search landscape has fragmented. Users are now searching on multiple platforms including ChatGPT, Perplexity, and Claude, not just Google. This shift means brands must move beyond "ranking on Google" and focus on being visible wherever their audience searches for information. Whether someone asks ChatGPT for "the best roofers in Austin" or Google's AI mode for "running shoes under $5,000," AI systems are gathering and summarizing information across multiple sources in real time, including social platforms like Reddit, Quora, and LinkedIn. Think about it as building a multimedia visibility strategy and ensuring your brand, expertise, and answers exist across platforms that large language models (LLMs) pull from. "You're not optimizing for one search engine anymore," he says. "You're optimizing for how the internet talks about you." Why Your Website Still Matters in the AI Era Will websites become irrelevant if AI answers everything for users? According to Vishal, websites won't disappear, they'll evolve. Think of them as your source of truth rather than your traffic generator. When AI summarizes answers for users, it still references real content and authoritative sources. So, your website remains essential for credibility, events, and conversion, even if fewer users arrive there through traditional search. For instance, if someone asks ChatGPT about agency growth events in Austin, and you've mentioned your event across social media, your website, and podcasts, AI will likely include it in the results. "That's how people find you now," Vishal agrees. "Not just through search but through signals from every platform." Of course, you should still think about the content you're putting out on your website. Are you answering the questions that people are asking? Or you just optimizing for the keywords. Optimizing for the keywords won't work. People will ask LLMs questions and if you're already answering them on your content there are more chances that AI results will find you and list your website. Redefining Reporting and KPIs for Agencies One of the biggest challenges agencies face is explaining to clients why organic traffic might be dropping even as visibility increases. Why? Traditional SEO metrics no longer tell the whole story. So how to report back? Basically, you'll need to educate clients and start measuring mentions, citations, and referrals coming from AI platforms. Vishal suggests tracking LLM bot hits in server logs and monitoring whether AI crawlers are visiting key pages. These indicators reveal your brand's visibility in AI-generated results. While raw traffic might decline, the quality of leads and conversions often improves. "You might get fewer leads," he says, "but they'll be more qualified, because AI searchers are deeper in their intent." Leads from AI chats tend to be more serious buyers who have already researched their problems. The shift, then, isn't a loss but rather an opportunity to educate clients on new performance indicators that reflect where users actually search today. Preparing Your Agency and Clients for AI Search When it comes to optimizing for AI, Vishal recommends a hybrid approach: combine solid technical SEO fundamentals with a new layer of AI-readiness. This includes making sure your site is clean, crawlable, and structured properly, while also ensuring your brand has visibility across other platforms. At E2M, Vishal's team runs AI search audits to check how often their clients' brands appear in LLM answers. They even query ChatGPT and Perplexity directly to see what those systems say about them and their competitors. From there, they reverse-engineer visibility by identifying which platforms, podcasts, or publications help brands get cited more often by AI. Mentions on Reddit, Quora, and podcasts count, even if they're not linked, because they help build trust signals that LLMs detect. Agencies, Vishal says, can sell these as AI search audits, AI content audits, or full AI optimization packages — new recurring revenue streams that build on their SEO expertise. The Human Edge in an AI-Driven World Agencies can't afford to be "order takers" who wait for clients to bring up AI. If your clients are asking about AI before you bring it up, you're already behind. Instead, agencies should position themselves as trusted advisors who help clients navigate the shift confidently. So go to your clients and start those conversations, or you WILL be replaced by AI. At the end of the day, people still want connection, which is why both Jason and Vishal agree that AI will never replace the human element and the strategy, empathy, and creativity that come from real human connection. People will always want someone that can help guide them through the new marketing trends. As Vishal puts it, "Business owners don't have time to learn all this. They want someone they trust to handle it." AI might make average easier, but connection, data, and network will always be your edge. Do You Want to Transform Your Agency from a Liability to an Asset? Looking to dig deeper into your agency's potential? Check out our Agency Blueprint. Designed for agency owners like you, our Agency Blueprint helps you uncover growth opportunities, tackle obstacles, and craft a customized blueprint for your agency's success.
Register for Founder University Japan's Kickoff! https://luma.com/cm0x90mkToday's show:Find out why AI is perfectly suited to legal tasks… despite being too fast for “billable hours”On today's TWiST, Alex takes a deep dive into LLM Law with Harvey AI co-founder/president Gabe Pereyra. It turns out, much like software development, doing legal work relies on learning specialized language and sifting through a dense and expansive corpus of information… making it an IDEAL use case for LLMs.Buuuuut AI works so fast… the current structure of legal payments (billable hours) no longer applies. Find out how Harvey is working around these challenges — and what they plan to do if OpenAI decides to get into the legal game — in this fascinating interview.THEN, Alex chats with another AI visionary — OpenRouter co-founder and CEO Alex Atallah — who allows developers to plug and play all the major models into their applications. Find out why specialized LLMs trained for “resourcefulness” are coming into fashion… why benchmarks and evals have become so crucial to the industry… AND whether we'll end up spending as much on AI inference as the human workers it's replacing… in this essential discussion.PLUS Jason stops by for some more Founder Q's!Timestamps:(0:00) Welcome back to TWiST!(1:32) Alex kicks off the show with Harvey AI co-founder and President Gabe Pereyra to talk about applying AI to the legal profession(4:52) How major international law firms (and their enterprise clients) fueled Harvey's mega-growth(6:54) Why LLMs are perfectly suited for legal work(9:24) Enterpret - Enterpret turns feedback noise into Customer Intelligence, so your team knows exactly what to fix and build next. Head to Enterpret.com/twist to book a demo and see it in action.x and build next. Head to Enterpret.com/twist to book a demo and see it in action.(17:22) Looking ahead: expanding beyond the law.(20:42) Uber AI Solutions - Your trusted partner to get AI to work in the real world. Book a demo with them TODAY at Uber.com/twist(21:44) The problem: AI can't charge “billable hours”… it's too fast!(23:44) Will the major AI players like Google and OpenAI build their own version of this?(29:53) Lemon.io - Get 15% off your first 4 weeks of developer time at https://Lemon.io/twist(30:41) Alex welcomes OpenRouter co-founder and CEO Alex Atallah, whose rankings he loves and uses all the time(33:10) Why Alex says we're seeing more specialized LLMs trained for more “resourcefulness”(36:05) How increased competition and diversification makes things tougher for developers(41:09) Alex suggests that new models are exciting for users, like product launches used to be(42:29) OK, let's get into it… How does OpenRouter make money?(45:38) Understanding what kinds of training data the AI companies want the MOST(47:47) The important currency of evals and benchmarks(49:13) Why OpenRouter is ramping up its LLM recommendation engine(53:44) Will AI inference spend end up costing as much as the humans it's replacing?(56:49) Time for a Founder Q! What should founders do about quick vibe-coded competitors?Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.comCheck out the TWIST500: https://www.twist500.comSubscribe to This Week in Startups on Apple: https://rb.gy/v19fcpFollow Lon:X: https://x.com/lonsFollow Alex:X: https://x.com/alexLinkedIn: https://www.linkedin.com/in/alexwilhelmThank you to our partners:(9:24) Enterpret - Enterpret turns feedback noise into Customer Intelligence, so your team knows exactly what to fix and build next. Head to Enterpret.com/twist to book a demo and see it in action.x and build next. Head to Enterpret.com/twist to book a demo and see it in action.(20:42) Uber AI Solutions - Your trusted partner to get AI to work in the real world. Book a demo with them TODAY at Uber.com/twist(29:53) Lemon.io - Get 15% off your first 4 weeks of developer time at https://Lemon.io/twist
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