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Build your AI marketing department with this Claude skill: https://clickhubspot.com/uyon Ep. 448 Can you really fire your entire marketing team and replace them with AI? Kieran dives into the reality behind agentic marketing systems by putting an AI-powered marketing “team” to the test for a fast-growth AI company. Learn more on how AI audits and rewrites website copy, tackles product positioning, competes in search and LLMs, and whether these emerging systems can actually outperform the average marketer or just generate average results. Mentions Loop: Outlearn. Outmarket. Outgrow https://www.hubspot.com/loop-marketing-book Claude https://claude.ai/login ChatGPT https://chatgpt.com/ Ramp https://ramp.com/ One Mind https://onemind.org/ Get our guide to build your own Custom GPT: https://clickhubspot.com/customgpt Resource [Free] Steal our favorite AI Prompts featured on the show! Grab them here: https://clickhubspot.com/aip We're on Social Media! Follow us for everyday marketing wisdom straight to your feed YouTube: https://www.youtube.com/@matgpod Twitter: https://twitter.com/matgpod TikTok: https://www.tiktok.com/@marketingatg Thank you for tuning into Marketing Against The Grain! Don't forget to hit subscribe and follow us on Apple Podcasts (so you never miss an episode)! https://podcasts.apple.com/us/podcast/marketing-against-the-grain/id1616700934 We really appreciate your support. Host Links: Kipp Bodnar, https://twitter.com/kippbodnar Kieran Flanagan, https://twitter.com/searchbrat ‘Marketing Against The Grain' is a HubSpot Original Podcast // Brought to you by Hubspot Media // Produced by Darren Clarke.
Key takeaways: The "demo versus product" gap: An AI demo is judged on its best day, but an institutional-grade product is judged on its worst. Building reliable financial tools requires rigorous, auditable grounding frameworks to avoid hallucinations and ensure every output can be traced back to a verified source. Don't bet against the model: Developers should avoid wasting resources on complex workarounds for temporary constraints on models that are evolving rapidly. Instead, they should focus on elements that models cannot natively learn: details specific to the firm, such as proprietary data or how data sets are connected to each other. Tackling legacy constraints: Successful innovation lies in redesigning workflows from first principles rather than simply automating legacy bottlenecks to do the same tasks faster. In this episode of Goldman Sachs Exchanges, Chris Churchman, head of Marquee, Goldman Sachs' digital platform for institutional and corporate clients, talks about building effective artificial intelligence (AI) products for institutional investors. Churchman, who is also co-chair of the Global Banking & Markets AI Working Group, describes an ongoing shift from a world where users must learn software to one where software learns the user. He tells hosts Allison Nathan of Goldman Sachs Research and George Lee, co-head of the Goldman Sachs Global Institute, about the challenges of grounding generative AI in hard facts, and emphasizes the need to design systems that enhance human reasoning rather than outsourcing critical thinking to machines. The opinions and views expressed herein are as of the date of publication, subject to change without notice, and may not necessarily reflect the institutional views of Goldman Sachs or its affiliates. The material provided is intended for informational purposes only, and does not constitute investment, legal, or tax advice, a recommendation from any Goldman Sachs entity to take any particular action or be used as a basis for any other investment decision, or an offer or solicitation to purchase or sell any securities or financial products. Any forward-looking statements, case studies, computations or examples set forth herein are for illustrative purposes only. Past performance is not indicative of future results. Neither Goldman Sachs nor any of its affiliates make any representations or warranties, express or implied, as to the accuracy or completeness of the statements or information contained herein and disclaim any liability whatsoever for reliance on such information for any purpose. Each name of a third-party organization mentioned is the property of the company to which it relates, is used here strictly for informational and identification purposes only and is not used to imply any sponsorship, affiliation, endorsement, ownership or license rights between any such company and Goldman Sachs. This material should not be copied, distributed, published, or reproduced in whole or in part or disclosed by any recipient to any other person without the express written consent of Goldman Sachs. Disclosures applicable to information relating to Goldman Sachs Global Banking & Markets, if any, mentioned herein, are available: https://www.goldmansachs.com/disclaimer/salesandtrading Disclosures applicable to research with respect to issuers, if any, mentioned herein are available through your Goldman Sachs representative or at http://www.gs.com/research/hedge.html. A transcript is provided for convenience and may differ from the original video or audio content. Goldman Sachs is not responsible for any errors in the transcript. Date of Recording August 11, 2026 © 2026 Goldman Sachs. All rights reserved. Learn more about your ad choices. Visit megaphone.fm/adchoices
Kendra didn't really have an agenda for this episode. She just wanted to talk about what she's been working on, what's changing in her business, and the things she's been thinking about lately.She gets into her new weekly/biweekly webinar strategy, why she's moved away from relying on an automated webinar, and what she's learning as she tests a brand-new webinar with cold traffic. She also shares why she finally decided to hire a business coach again after nearly two years without one, and what she's hoping to get out of the investment.Then things get a little more existential. Kendra talks about AI, why she doesn't think human connection is going anywhere, and the slightly unhinged “AI apocalypse plan” she and her partner are cooking up in case AI eventually eats the internet. It's a very Kendra episode: part business strategy, part behind-the-scenes, and part what the hell are we all going to do when AI takes over?In this episode Kendra goes behind the scenes on:✔️ What a bi-weekly webinar actually is, and why almost everyone gets the frequency thing wrong✔️ How my tech VA resets the entire funnel in 15 minutes while I'm live, so the ads never turn off✔️ Why I hired a coach after two years without one, and what it cost me to go without✔️ The very unsexy thing my partner and I are investing in as an AI apocalypse planRESOURCES: Get FG Funnels: https://kendraperry.net/fgfunnelsLeave the podcast a 5-star review: https://ratethispodcast.com/wealthy
In this episode, I sit down with Lindsay Quinn, founder of Heartwise Collective, to explore how orthodontists can move beyond basic ChatGPT prompts and begin using AI as a true operational partner. Lindsay has spent 20 years in orthodontics and the last decade helping practices improve their systems and efficiency. In her own business, she used AI to double growth for two consecutive years without adding team members—and now she's teaching orthodontic practices how to create that same leverage.We discuss how AI can support every department of your practice, from marketing and financial analysis to treatment coordinator training, lead nurturing, and policy development. Lindsay also explains the difference between simply asking Claude or ChatGPT a question and building an AI system that understands your practice, brand, patients, and goals. You'll walk away with practical ways to reduce stress, improve predictability, strengthen accountability, and spend less time rebuilding the same systems from scratch.
Join the Millionaire University AI Mastermind at MillionaireUniversity.com/AI #1024 What if AI could save you hours every week — not by replacing your job, but by taking over the tasks you dread most? In part 1 of this 2-part episode, host Brogan Williams sits down with software developer-turned-entrepreneur David Mitchell to explore practical ways business owners can use AI and automation today. David shares how he transitioned from tech to running an irrigation company, why he's now helping local service businesses implement AI, and how tools like Claude Code and ChatGPT are streamlining everything from coding to back-office operations. They also discuss landing your first AI client, building confidence by automating your own business first, and why AI is becoming an essential advantage for entrepreneurs! What we discuss with David: + Using AI in local service businesses + From software developer to entrepreneur + Landing your first AI client + Claude Code vs. ChatGPT workflows + AI-powered business automation + Eliminating repetitive admin tasks + Building AI solutions for your own business + Protecting sensitive business data with AI + Creating scalable AI service offerings + Using AI to reclaim your time Thank you, David! Check out Part 2 of this episode. Check out Dialed in Trades at DialedinTrades.com. Follow David on Instagram, Twitter, and YouTube. Watch the video podcast of this episode! Get your FREE 5 Minute Business Plan at MillionaireUniversity.com/Plan To get exclusive offers mentioned in this episode and to support the show, visit MillionaireUniversity.com/Sponsors Learn more about your ad choices. Visit megaphone.fm/adchoices
Join the Millionaire University AI Mastermind at MillionaireUniversity.com/AI #1025 What if the fastest way to get more out of AI isn't building complex automations — but simply asking better questions? In part 2 of this 2-part episode, host Brogan Williams continues his conversation with entrepreneur David Mitchell to explore practical, everyday ways business owners can put AI to work. David shares why AI should be treated as a thought partner instead of a magic solution, how to identify the highest-impact tasks to automate first, and why research, meeting summaries, and email management are some of AI's most underrated use cases. They also discuss building a personal AI "second brain," choosing between tools like ChatGPT, Claude, Gemini, and Grok, and simple strategies to help beginners start using AI with confidence today! What we discuss with David: + AI is a tool, not magic + Find your biggest pain point first + Deterministic vs. agentic AI + Build an AI "second brain" + Choosing ChatGPT, Claude, Gemini, or Grok + Use AI for research and summaries + Turn meetings into actionable notes + Train AI to match your style + Start with simple everyday tasks + Let multiple AI models challenge each other Thank you, David! Check out Part 1 of this episode. Check out Dialed in Trades at DialedinTrades.com. Follow David on Instagram, Twitter, and YouTube. Watch the video podcast of this episode! Get your FREE 5 Minute Business Plan at MillionaireUniversity.com/Plan To get exclusive offers mentioned in this episode and to support the show, visit MillionaireUniversity.com/Sponsors Learn more about your ad choices. Visit megaphone.fm/adchoices
In this episode, I crashed Pattern's office to sit down with Jacob Miller (VP of Platform Intelligence) and Jeremy Mumford (Lead AI Engineer) from Pattern to discuss their newly co-authored book, "Architected Intelligence." We dive deep into the reality of building scalable AI systems, explaining why companies cannot simply put an LLM in front of everything. We also explore the importance of curating data to avoid the "semantic swamp," the reality of adapting organizational structures to external marketplace algorithms, and the collaborative process of writing a tech book using AI as an "anti-sycophantic" sparring partner. We also discuss the booming tech and startup scene in Utah, the future of autonomous cloud agents powered by budget-friendly AI models, and more.Buy Architected Intelligence: https://amzn.to/4haOqArThe Joe Reis Show is invitation-only. Unsolicited guest pitches and PR outreach are not considered.
Link Up w/The Morning Sickness Digitally All Over:Instagram: @hms_98_official, @bosskupd, @bretvesely, @dickToledoX/Twitter: @HMSon98, @DickToledo, @bretveselyFacebook: @HMSKUPDYouTube: @hmspodcast9320, @98kupdRequest/Call in/Wakeup Song line:(IN AZ) 602.585.9800More HMS: holmbergpodcast.com, 98kupd.comEmail: dtoledo@98kupd.com, bvesely@98kupd.com, bbogen@98kupd.comSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
Link Up w/The Morning Sickness Digitally All Over:Instagram: @hms_98_official, @bosskupd, @bretvesely, @dickToledoX/Twitter: @HMSon98, @DickToledo, @bretveselyFacebook: @HMSKUPDYouTube: @hmspodcast9320, @98kupdRequest/Call in/Wakeup Song line:(IN AZ) 602.585.9800More HMS: holmbergpodcast.com, 98kupd.comEmail: dtoledo@98kupd.com, bvesely@98kupd.com, bbogen@98kupd.comSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
A CMO Confidential Interview with Dr. Ed Dobbles, Founder of Dobbles.AI and former VP of Analytics and Insights at Diageo, H&R Block, and SUPERVALU. Ed discusses the evolution of analytics from the Almanac to BI to Generative Analytics and explains his thinking on why great tools often don't get used. Key topics include:- Why "Analytics is hard, but people are harder"- How generative analytics will allow leaders to truly talk to their data- The importance of AI governance- Why "All models are wrong but some are useful"Tune in to hear stories about H&R Block, Malort Liquor, and the racquetball court at Best Buy. ⏱️ Chapters1:44 - Defining Analytics and Business Intelligence3:26 - The Evolution of Data Adoption9:31 - Analytics and Human Factors15:06 - AI Systems and Synthetic Panels24:35 - Building Future Analytics Teams32:10 - Closing Advice and StoriesSubscribe for weekly episodes featuring world-class marketing leaders, board members, and C-Suite executives.#CMOConfidential, #MarketingLeadership, #BrandStrategy, #CorporateActivism, #MarketingStrategy, #CMO, #AIinMarketing, #ExecutiveLeadership, #BrandReputation, #ConsumerTrust, #DigitalMarketing, #MarketingInsights, #ThoughtLeadership, #BusinessStrategy, #CustomerCentricSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
Lamont made his weekly check-in on their NewsMaker line and this time around got a call from Arnold Schwarzenegger. Listen to The Lamont Show Monday through Friday, 6-10am, on 107.7 The Bone. For more of 107.7 The Bone go to: 1077thebone.com Connect with 107.7 The Bone on Facebook, Instagram, X, YouTube and TikTok. Connect with 107.7 The Bone on Apple, Spotify or Amazon Music.See omnystudio.com/listener for privacy information.
Lamont made his weekly check-in on their NewsMaker line and this time around got a call from Arnold Schwarzenegger. Listen to The Lamont Show Monday through Friday, 6-10am, on 107.7 The Bone. For more of 107.7 The Bone go to: 1077thebone.com Connect with 107.7 The Bone on Facebook, Instagram, X, YouTube and TikTok. Connect with 107.7 The Bone on Apple, Spotify or Amazon Music.See omnystudio.com/listener for privacy information.
Creative Strategies' Austin Lyons talks with TITV Host Akash Pasricha about AMD's new Helios AI rack scale system and how it stacks up against Nvidia. We also talk with Neil Chilson, Head of AI Policy at the Abundance Institute, and Ryan Fedasiuk, Fellow at the American Enterprise Institute, about the US AI policy debate reignited by China's Kimi K3 model. The Information's Cory Weinberg discusses human data labeling startup Mercor's concentrated revenue growth, and we get into why Anthropic is lagging in voice and chat AI with Author of Applied AI Laura Bratton.Articles discussed on this episode: https://www.theinformation.com/articles/mercors-fast-growth-relies-biggest-ai-companies-documents-showhttps://www.theinformation.com/newsletters/applied-ai/anthropic-best-powering-customer-service-new-data-showhttps://www.theinformation.com/newsletters/ai-agenda/new-kimi-k3-model-means-u-s-china-ai-raceSubscribe: YouTube: https://www.youtube.com/@theinformation The Information: https://www.theinformation.com/subscribe_hSign up for the AI Agenda newsletter: https://www.theinformation.com/features/ai-agendaTITV airs weekdays on YouTube, X and LinkedIn at 10AM PT / 1PM ET. Or check us out wherever you get your podcasts.Follow us:X: https://x.com/theinformationIG: https://www.instagram.com/theinformation/TikTok: https://www.tiktok.com/@titv.theinformationLinkedIn: https://www.linkedin.com/company/theinformation/Chapters:00:00 - Introduction00:01 - AMD Launches New Helios AI System00:12 - Kimi K3 ReIgnites US AI Policy Debate00:28 - Mercor's Fast Growth Relies on Biggest AI Companies00:37 - Anthropic Lags in Voice and Chat AI
Dr. Peter Boulden, Founder of Bulletproof Dental Practice & Cory Pinegar, CEO & Founder of Reach discuss: The 61 AI touchpoints in dentistry A systems crisis in dentistry Human connection in the AI age If you are interested in learning more about Reach and their virtual assistant solutions that integrate with AI workflows visit: https://getreach.co/ To learn more about Bulletproof Practice visit: https://www.bulletproofdentalpractice.com/ To register for Bulletproof Summit on August 7th & 8th in Scottsdale, AZ visit: https://www.bulletproofsummit.com/ Subscribe to our channel for more episodes and stay updated on the latest DSO news, insights, and events! If you like our podcast, please give us a ⭐⭐⭐⭐⭐ review on iTunes https://apple.co/2Nejsfa and a Thumbs Up on YouTube.
The Dáil has heard that the work of a Clare artist was treated by an AI system as a "resource to be harvested". Sinn Féin has this week tabled a motion aimed at protecting the copyright of Irish artists in the era of artificial intelligence. The bill has received vocal support from the likes of the International Federation of Actors, Danny O'Donoghue of The Script, and former arts minister Catherine Martin. Speaking in the Dáil, Shannon Sinn Féin TD Donna McGettigan says the use of the Clare artist's work in this way "reflected the priorities of an algorithm".
Why do AI agents and applications look impressive in demos but struggle when companies try to deploy them in production? In this episode of Tech Talks Daily, I speak with Nikunj Bajaj, co-founder and CEO of TrueFoundry, about why enterprise AI has become a systems problem, what companies need to move AI from proof of concept to production, and how better infrastructure can improve reliability, governance, security, observability, and cost control. Before founding TrueFoundry, Nikunj worked at Meta on conversational AI systems serving more than a billion users and contributed to the company's internal machine learning platforms. He explains how developers at Meta could concentrate on solving business problems while infrastructure handled logging, monitoring, deployment, and governance by default. In many enterprises, the same journey from an AI idea to a production application can still take weeks or months. Nikunj argues that increasingly capable AI models are not necessarily the biggest barrier to enterprise adoption. The harder challenge is building reliable systems around them. Companies need to know what happens when a model becomes unavailable, how an agent is behaving, which data it can access, how much it is costing, when a human should intervene, and whether there is a kill switch when something goes wrong. We discuss why AI proofs of concept often fail when exposed to real users. Controlled demonstrations rarely reproduce production conditions such as unexpected prompts, malicious actors, heavy workloads, model outages, latency, and dependencies between multiple components. Even when individual parts of a system perform reliably, combining them can create failure rates that businesses cannot accept for mission-critical workflows. The conversation also examines the infrastructure required as companies introduce multiple AI models and agents. Nikunj explains the roles of model gateways, MCP gateways, and agent gateways, and how bringing these components together through an AI gateway can give enterprises a control plane for observing and governing AI traffic. Cost is another major challenge. Nikunj explains why sending every request to the most powerful model can waste significant amounts of money when smaller or cheaper models could produce comparable results for simpler tasks. Intelligent model routing can help companies balance quality, latency, availability, and price. He shares how organizations using this approach have reduced model costs by as much as 75 to 80 percent in some production environments. We also discuss what reliable multi-agent systems require in practice. Companies need clearly defined boundaries for what agents can do, escalation routes to other agents or people, safeguards against infinite agent loops, and complete audit trails of interactions and decisions. For CIOs, CTOs, AI engineering teams, platform leaders, and companies trying to move generative AI and agentic AI into production, this conversation provides a practical guide to the infrastructure decisions that determine whether AI applications remain impressive prototypes or become reliable business systems. The next stage of enterprise AI will not be defined by models alone. Companies that can connect, observe, govern, secure, and control their AI applications while managing costs will be better positioned to turn experimentation into dependable production systems.
-OpenAI's first device will apparently be rechargeable and can easily be carried from one room to another. -Twenty-six former Meta employees are suing the company for allegedly using biased AI tools that "disproportionately selected" people who took medical leave as candidates to be laid off. -Hachette Book Group, Cengage Learning, Elsevier and writer Scott Turow are seeking a class action lawsuit against Google on claims that the tech company broke copyright law by using their works to train its Gemini AI. Learn more about your ad choices. Visit podcastchoices.com/adchoices
Curious what it actually looks like to build with AI instead of just talking about it? Start here: https://www.youtube.com/watch?v=uMPx7b3_LOA 856 members. Under 3 percent churn most months. One hire changed how this gym runs everything. Everyone assumes AI adoption means fewer people on payroll. Dave Rafuse spent more, not less, because the tool only pays off when someone builds it into the business first. Blended Athletics grew 23 percent, then 25 percent, then 28 percent over the last three years, and Dave says the systems that got them to 150 members never would have gotten them to 856. In this episode you'll learn: — Why Dave hired an AI architect instead of cutting payroll — The interview question Dave asks every single candidate about AI — How health scores catch members before they silently churn — Why visit frequency, not price, predicts who cancels — How AI rebuilt Blended's event calendar around real attendance data — Why 40 percent of their members were being ignored by every event they ran — The weekly 45 minute meeting that keeps their team sharing AI wins — Why using AI like a search engine wastes what it can actually do — How a morning brief pulling from 12 sources sets Dave's whole day in 10 minutes — The systems that took Blended from 150 members to 856 — Why community, not results, is now the top reason members stay If your team is still guessing who's about to cancel, this episode shows you exactly how to stop. Timestamps: 0:00 Dave Rafuse returns, GSD record holder recap 1:45 Going all in on AI early 4:42 Hiring for AI instead of doing it all himself 6:19 Why AI architect is the fastest growing job in the industry 8:21 The interview question that filters for AI mindset 11:13 AI cleans and uploads an ad list in 7 minutes 12:54 Building a 4 day visit itinerary in 10 minutes 15:54 Meet Victor, the AI running Mike's day 19:44 Dave's morning brief, broken down 24:30 Train With Us and the shift to community 28:02 Health scores and catching silent churn 30:57 Rebuilding events around real attendance data 34:48 Going from 150 members to 856 41:16 The biggest mistake gym owners make with AI 44:09 The weekly meeting that keeps their team sharp 49:10 Victor managing payroll, sales, and vendor deals 55:48 How to connect with Dave Connect with Dave Rafuse: Email: dave@blendedathletics.com ———————————————————————— Dave Rafuse turned Blended Athletics into a business most gym owners only think is possible on paper. The full plan the best gyms are using to get there is one click away. Watch the 100K Plan: https://www.youtube.com/watch?v=uMPx7b3_LOA Turns out the secretary never left. She got a lot better at her job.
Discusses ethical issues associated with the use of AI in teaching. Our guest today is Tiffany Bourelle, who is a professor at The University of New Mexico, an instructional strategist, and an AI ethics scholar with more than a decade of experience designing high-impact educational programs. Additional resources: The EU Artificial Intelligence Act: https://artificialintelligenceact.eu/ Multiliteracies for a Digital Age: https://www.siupress.com/9780809325511/multiliteracies-for-a-digital-age/ Empire of AI: https://www.penguinrandomhouse.com/books/743569/empire-of-ai-by-karen-hao/ Anatomy of an AI System: https://anatomyof.ai/ AI Ethics: https://mitpress.mit.edu/9780262538190/ai-ethics/ Stuart Selber on AI: https://sites.psu.edu/selber/chatgpt/ Teaching with AI: https://www.press.jhu.edu/books/title/54122/teaching-ai Tiffany Bourelle Publications: https://www.tiffanybourelle.com/about CITI Program's Tech Ethics solution: https://about.citiprogram.org/solutions/tech-ethics/
In this episode of The Ross Simmonds Show, Ross sits down with Nick Lafferty, Founding Marketing Engineer at Profound, to unpack the fast-moving world of AI visibility, AEO, GEO, and AI search. They explore how brands can earn citations across ChatGPT, Claude, Perplexity, Grok, and Google AI, why visibility is no longer just an SEO problem, and how marketers can build systems that help their teams move faster. Key Takeaways and Insights: 1. Building Marketing Taste Before Automating with AI - Nick explains why AI does not have taste on its own and why marketers need judgment, experience, and creative instincts before automating workflows. - Great marketing taste comes from studying campaigns, consuming strong creative work, testing in public, and learning from feedback. - Creating content consistently, whether through LinkedIn posts, newsletters, blogs, or videos, helps marketers sharpen their voice and understand what resonates. 2. The Rise of the Marketing Engineer - A marketing engineer is part builder, part artist: someone who understands marketing strategy and can build AI-powered systems to solve business problems. - Nick shares how he automated manual unsubscribe syncing across multiple email tools at Profound, saving time for the marketing operations team. - The strongest marketing engineers are AI-native, deeply curious, and focused on redesigning workflows with AI at the center instead of simply automating outdated processes. 3. AI Visibility, AEO, GEO, and the New Search Landscape - Nick challenges the idea that AI visibility is only a content or website problem, noting that most AI citations come from third-party sources. - Profound research shows only about 5–10% of citations come from a brand's own domain, while the majority come from places like Reddit, YouTube, review sites, press releases, documentation, and partner ecosystems. - Enterprise brands need cross-functional alignment across SEO, PR, social, product marketing, affiliates, and content to compete in AI search. 4. Making the Case for AI Visibility Internally - Nick recommends marketers look for declining organic traffic, rising impressions with fewer clicks, inaccurate AI answers, and poor competitive comparisons as signs of an AI visibility problem. - The Profound team uses the concept “make the invisible visible” to surface hidden risks and opportunities. - Marketers should bring screenshots, prompt examples, traffic trends, and suggested solutions to leadership to win buy-in. 5. Measuring AI Visibility and Proving ROI - Nick advocates for using a required “How did you hear about us?” field to capture self-reported attribution from sources like ChatGPT, Claude, Gemini, and Perplexity. - Profound tracks AI bot traffic, server logs, citation trends, competitive benchmarks, and visibility changes over time. - The conversation highlights why measurement needs to evolve as buyers increasingly discover brands through AI-generated answers. 6. Personas, Memory, and Personalized AI Search Results - Profound's personas feature helps brands understand how different buyer types may see different AI answers. - Teams can analyze visibility across personas such as SEO managers, CMOs, affiliate managers, PR leaders, and demand generation teams. - Personas help marketers approximate how memory and personalization may shape AI search results for different audiences. 7. Reddit, Listicles, and Off-Site Citation Strategy - Nick explains why Reddit requires a contribution-first mindset and compares it to joining a dinner party where listening matters before speaking. - Listicles may still work in some industries, especially affiliate-heavy categories, but many marketers are over-investing in them as a short-term tactic. - The bigger opportunity is building adaptable systems that can respond to changing citation patterns across AI search platforms. Resources & Tools:
A U.S. official, speaking anonymously to The Associated Press, revealed that Anthropic's Mythos model, in collaboration with U.S. intelligence agencies, identified these weaknesses within hours. While the model quickly pinpointed vulnerabilities, the official clarified that this did not mean it could exploit them within the same timeframe. HBO and Warner Bros. Home Entertainment plan to release on 4K Blu-ray The Sopranos: The Complete Series. The release is scheduled to arrive on the market on December 8. The incident occurred on June 18 as hundreds of soccer fans gathered at Seoul International Park in the Koreatown neighborhood to watch the Mexico versus South Korea match. The victim, Luis Romero, 56, of Duarte, was attending a nearby watch party with his son when an armed suspect suddenly arrived and fired off several rounds. Crowds of panicked people were seen scrambling to safety after hearing the gunfire. Please Like, Comment and Follow 'Philip Teresi on KMJ' on all platforms: --- Philip Teresi on KMJ is available on the KMJNOW app, Apple Podcasts, Spotify, YouTube or wherever else you listen to podcasts. -- Philip Teresi on KMJ Weekdays 2-6 PM Pacific on News/Talk 580 AM & 105.9 FM KMJ | Website | Facebook | Instagram | X | Podcast | Amazon | - Everything KMJ KMJNOW App | Podcasts | Facebook | X | Instagram See omnystudio.com/listener for privacy information.
A U.S. official, speaking anonymously to The Associated Press, revealed that Anthropic's Mythos model, in collaboration with U.S. intelligence agencies, identified these weaknesses within hours. While the model quickly pinpointed vulnerabilities, the official clarified that this did not mean it could exploit them within the same timeframe. HBO and Warner Bros. Home Entertainment plan to release on 4K Blu-ray The Sopranos: The Complete Series. The release is scheduled to arrive on the market on December 8. The incident occurred on June 18 as hundreds of soccer fans gathered at Seoul International Park in the Koreatown neighborhood to watch the Mexico versus South Korea match. The victim, Luis Romero, 56, of Duarte, was attending a nearby watch party with his son when an armed suspect suddenly arrived and fired off several rounds. Crowds of panicked people were seen scrambling to safety after hearing the gunfire. Please Like, Comment and Follow 'Philip Teresi on KMJ' on all platforms: --- Philip Teresi on KMJ is available on the KMJNOW app, Apple Podcasts, Spotify, YouTube or wherever else you listen to podcasts. -- Philip Teresi on KMJ Weekdays 2-6 PM Pacific on News/Talk 580 AM & 105.9 FM KMJ | Website | Facebook | Instagram | X | Podcast | Amazon | - Everything KMJ KMJNOW App | Podcasts | Facebook | X | Instagram See omnystudio.com/listener for privacy information.
What if your practice could run smoother, convert more patients, and scale without burning out your team?This episode dives into the playbook of Kristen Davis, a strategic operator who's worn nearly every hat in a dental office, from ground-level execution to high-level growth planning.Kristen shares the real story behind launching and scaling a de novo dental practice during the chaos of COVID-19, turning disruption into a blueprint for resilience and expansion. She introduces SOPHIE, a dynamic AI-supported platform that transforms dental operations by bridging the gap between software and staff, ensuring consistency, accountability, and real-time visibility. Kristen walks us through practical tactics that boost retention and reduce stress, from patient-first scripting and high-conversion follow-up cycles to purposeful morning huddles. Plus, she reveals hiring secrets, onboarding frameworks, and the essential tech tools practices overlook, all rooted in her firsthand trials and wins.What You'll Learn in This Episode:How a dental startup thrived during a pandemic by systemizing operationsThe exact follow-up schedule proven to improve unscheduled treatment conversionsPatient-phone call frameworks that nail the “why choose us” question fastChairside scripts and cues that increase case acceptance (without pressure)The daily and weekly team habits that cut chaos and elevate accountabilityWhy separating treatment and financial coordination roles drives smoother workflowsStructured onboarding that creates confident, culture-matched new hiresHow to use technology like SOPHIE and Patient Prism to maximize team performanceProven strategies for holding vendors accountable and protecting your dataWays to infuse your practice's mission and values into everything your team doesHit play and discover actionable strategies you can use to build a practice that grows, adapts, and never skips a beat, no matter what challenges come your way.Sponsors:Oryx: All-In-One Cloud-Based Dental Software Created by Dentists for Dentists. Patient engagement, clinical, and practice management software that helps your dental practice grow without compromise. Click or copy and paste the link here for a special offer! https://thedentalmarketer.lpages.co/oryx/Click here for a special offer!Net32: Founded by a dentist, for dentists. Net32 is the leading online marketplace for dental supplies, helping dental and medical professionals save on high-quality products for over 25 years. Start saving today at: https://www.net32.com/dentalmarketerClick here for a special offer!Business Name: SOPHIECheck out Kristen's Media:SOFIE: https://www.hisophie.ai/Instagram: https://www.instagram.com/kldavsherm/LinkedIn: https://www.linkedin.com/in/kristen-davis-sherman-331831a8/Mentions & Links:Tools:Patient PrismBIT USASunbitCareCreditCherry FinancingHost: Michael AriasJoin my newsletter: https://thedentalmarketer.lpages.co/newsletter/Join this podcast's Facebook Group: The Dental Marketer SocietyLove the Podcast? Follow on Your Favorite App! https://lnkfi.re/TDMPod
Barry O'Sullivan, Professor of Computer Science at University College Cork, reacts to a warning from security experts that AI models that could take down governments are months away.
In this episode of The Ross Simmonds Show, Ross sits down with Travis Tallent of DayNova to unpack how organizations can use AI tools like Claude, Claude Code, Claude Chat, and Claude Co-Work to save time, improve workflows, and amplify business growth. Travis shares practical AI agent examples for marketing, sales, operations, finance, and account management, while emphasizing a strategic approach: automate the right work, keep humans in the loop, and reinvest saved time into higher-value output. Key Takeaways and Insights: 1. Using Claude to Build Smarter AI Workflows - Travis explains why Claude is his most-used AI tool and how he uses it for deep research, competitive analysis, proposals, and decision support. - Claude Code helps build and deploy proposal workflows, while Claude Chat acts as a strategic sparring partner. - Claude Co-Work can support daily briefs, research, project prioritization, and competitive monitoring. - The key is building strong skills with brand context, tone, design rules, and clear instructions so outputs feel useful and aligned. 2. The DayNova Framework for AI Transformation - Travis introduces the DayNova framework: Narrow, Orchestrate, Validate, and Amplify. - “Narrow” means identifying which tasks are actually worth automating instead of wasting time on low-impact workflows. - “Orchestrate” focuses on shared knowledge bases, governance, brand assets, and culture skills so teams use AI consistently. - “Validate” keeps humans in the driver's seat, while “Amplify” reinvests productivity gains into growth, innovation, and domain expertise. 3. Helping Teams Adopt AI Without Fear - Travis explains why AI adoption is not just a software rollout; it is a change management challenge. - Leaders need to acknowledge uncertainty, build psychological safety, and help teams turn anxiety into agency. - AI should be positioned as a tool to change how work gets done, not as something that replaces people's identity or value. - Successful adoption requires trust, team-specific training, and clear communication about how saved time will be reinvested. 4. AI Agents for Every Business Function - Marketing teams can build conversational agents connected to performance data, rankings, sales trends, and campaign insights. - Operations teams can create internal knowledge bases for policies, brand guidelines, culture, travel rules, and process documentation. - Account management teams can automate meeting notes, project management updates, and client communication scoring - Finance teams can use AI for PO reconciliation, forecasting, payroll workflows, contractor payments, and month-end close support. 5. AI for Sales, Revenue, and Relationship Building - Sales teams can use AI to summarize RFPs, analyze prospects, prepare for calls, and build automated sales coaching systems. - AI-powered prospect research helps teams enter conversations with stronger context and more relevant talking points. - Travis and Ross discuss how AI can strengthen both business and personal relationships through better follow-up and context tracking. - The highest-value human work shifts toward innovation, strategy, relationship-building, and big ideas that previously lacked enough time. Resources & Tools:
Myles McNamara is Tarkenton's lead technical architect and full-stack developer, specializing in building secure, scalable software solutions. He oversees infrastructure, code, and system design, serving as the team's in-house expert. Previously, he worked with Fortune 500 government contractors and ran his own software and hosting companies. In this episode… Integrating responsible AI tools and systems into business operations depends less on the model itself and more on the privacy and security controls a company embeds around it. "We need AI" is often where the conversation starts, but turning that need into a safe and controlled environment requires a clear understanding of where data lives, who can access it, and what the AI system is allowed to do. Those considerations shape whether AI can support the business without creating unnecessary risks. How can organizations design and implement AI in a way that is secure and grounded in real business needs? Before companies implement a new AI system, they need to set guardrails around how it will operate in practice. Governance needs to be built into the system from the beginning, not left in a policy or bolted on later. Establishing clear data boundaries, access controls, and system-level permissions defines what the AI tool can access and which actions it can perform. Logging and audit trails give companies visibility into how the system is functioning, so if something goes wrong, they can understand what happened and why. AI will continue to evolve, and companies also need to ensure that their privacy and security controls keep pace through regular monitoring and continued improvements. In this episode of She Said Privacy/He Said Security, Jodi and Justin Daniels talk with Myles McNamara, Principal Software Engineer at Tarkenton, about designing and implementing AI tools and systems responsibly. Myles shares what it takes to build AI agents and systems in a secure, controlled way, including how companies should think about whether AI is needed and how much autonomy it should have. He emphasizes the importance of integrating governance into system design and offers advice for safeguarding data. Myles also shares how engineering teams can balance business expectations with privacy and security concerns and discusses why AI governance might get overlooked in practice.
Welcome to a special blockbuster compilation edition of The Edge of Show, broadcasting live from the ground Consensus Miami capturing the biggest shifts in tech! First we sit down with Adam Hollander from OpenSea, who discusses how the world's largest NFT marketplace is widening its scope. Beyond proving on-chain ownership through digital collectibles Next, to battle the dangerous risks of unchecked autonomous code, George Xian Zeng breaks down on NEAR's lastest launched, Ironclaw, a secure agent harness that lets AI handle sensitive information safely inside private execution environments.Max Rabinovich, CSO at Chiliz, outlines their return to the massive U.S. sports market following crucial regulatory guidance from the SEC and CFTC. And finally Ramon Macieros let us know that GAIB is letting everyday retail investors finance massive AI GPU data centers and buy real on-chain equity in SpaceX and OpenAI starting at just $100.Let's hear how the biggest players in Web3 and AI are building systems that actually make money, click play on this jam-packed episode.Support us through our Sponsors! ☕ Want to make content like ours? Sign up with Castmagic to make your creative process easy: https://bit.ly/CastmagicReferral Work smarter, grow faster. Automate your SEO, get AI insights, and manage all your clients in one place with Helm. Start today 50% off your first month at helmseo.com
As countries race to adopt artificial intelligence, the challenge is building capability they actually control, without falling behind or over‑relying on outside providers. Alan Webber, Program Vice President - National Security, Defense and Intelligence at IDC, tells us what it takes to get that right.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
Summary:Dr. Stephanie Wigner sits down with her husband, Kyle, to unpack how AI is transforming the way they operate multiple clinics. They share practical examples of using AI beyond content creation, from auditing team performance and streamlining communication to building smarter systems and creating more leadership capacity. This conversation highlights why AI is not about replacing people, but elevating them into higher-value roles. The real opportunity is not learning another tool. It is becoming the kind of leader who leverages technology to create more margin, clarity, and growth.Get the Free Claude Cowork Guide for Practitioners:https://go.thewealthypractitioner.com/ai-cowork-for-practitioners?utm_source=MTWpodcast&utm_medium=podcast&utm_campaign=cowork_LMChapters:00:03:12 CEO capacity gap00:06:58 Audit log unlock00:10:01 Team leverage shift00:12:47 AI as a systems builder00:16:05 Financial intelligence00:18:38 Internal AI assistants00:19:27 Why you're not behindKey Takeaway:The leaders who win with AI are not replacing people, they are creating more leverage for themselves and their teams.
On this detailed training learn how to use this proven AI system to get warm leads and even appointments set for you! Sign Up For AI Flipper Today!https://myaiflipper.com/joinWith over 500,000 subscribers, this is the #1 channel on YouTube for all things wholesaling and flipping. SUBSCRIBE NOW! https://www.youtube.com/@FlippingMastery Podcast fan? Listen to your favorite Flipping Mastery TV videos on your favorite podcast platform! http://FlippingMasteryPodcast.com Jerry Norton went from digging holes for minimum wage in his mid 20's to becoming a millionaire by the age of 30. Today he's the nation's leading expert on flipping houses and has taught thousands of people how to live their dream lifestyle through real estate. **NOTE: To Download any of Jerry's FREE training, tools, or resources… Click on the link provided and enter your email. The download is automatically emailed to you. If you don't see it, check your junk/spam folder, in case your email provider put it there. If you still don't see it, contact our support at: support@flippingmastery.com or 888) 958-3028.Get Access to Unlimited Free Property Searches and Downloads: https://flippingmastery.com/propwireWholesaling & House Flipping Software: https://flippingmastery.com/flipsterpodMake $10,000 Finding Deals: https://flippingmastery.com/10kpodGet 100% funding for your deals: https://flippingmastery.com/fspodMentoring Program: https://flippingmastery.com/ftpodFREE 8 Week Training Program: https://flippingmastery.com/8wpodGet Paid $8700 To Find Vacant Lots For Jerry: https://flippingmastery.com/lfpodFREE 30 Day Quickstart Kit https://flippingmastery.com/qkpodFREE Virtual Wholesaling Kit: https://flippingmastery.com/vfpodFREE On-Market Deal Finder Tool: https://flippingmastery.com/dcpodFREE Wholesaler Contracts: https://flippingmastery.com/wcpodFREE Comp Tool: https://flippingmastery.com/compodFREE Funding Kit: https://flippingmastery.com/fkpodFREE Agent Offer Sheet & Scripts: https://flippingmastery.com/aspodFREE Cash Buyer Scripts: https://flippingmastery.com/cbspodFREE Best Selling Wholesaling Ebook: https://flippingmastery.com/ebookpodFREE Best Selling Fix and Flip Ebook: https://flippingmastery.com/ebpodFREE Rehab Checklist: https://flippingmastery.com/rehabpod LET'S CONNECT! FACEBOOK http://www.Facebook.com/flippingmastery INSTAGRAM http://www.instagram.com/flippingmastery
Data poisoning—where adversaries tamper with training data to corrupt model behavior—poses significant risks as AI adoption expands across critical sectors. Organizations without mechanisms in place to detect or prevent data poisoning are open to an avenue of attack that, once exploited, is difficult to remediate. Machine unlearning and model retraining are not always viable or effective solutions. In today's operational climate, where threat actors look to influence models and degrade the trust of users through incorrect behaviors, preventing data poisoning is more important than ever. In this episode of the SEI Podcast Series, Julie Lawler and James Cunningham—AI security researchers at Carnegie Mellon University's Software Engineering Institute—discuss the growing threat of data poisoning in AI systems and highlight emerging mitigation strategies, including chain-of-custody controls.
In this mind-blowing episode of Brave New Bookshelf, hosts Steph Pajonas and Danica Favorite welcome back prolific sci-fi author and technical innovator Malorie Cooper from The Writing Wives to explore the cutting edge of advanced AI workflows. Malorie shares her journey of building custom multi-agent AI systems, detailing how she co-authored a full-length novel and "sharded" a massive, 40-day continuous Claude conversation into specialized AI agents that coordinate tasks and communicate on a digital "mind board." From automating her schedule and coding custom software to using structured data as "sensory organs" for her AI assistants and training them to embrace uncertainty, Malorie's data-driven insights offer a fascinating blueprint for the future of publishing and collaborative creation. Visit our website https://bravenewbookshelf.com to view the full episode notes, links and apps mentioned in the episode, and the full transcript.
This episode originally aired previously and is being re-shared due to its continued relevance. Enjoy this conversation with Jeff Hawkins on intelligence, neuroscience, and the future of AI. With growing concerns over whether or not AI will take away jobs and eventually become superior to human intelligence, maybe it's time to take a closer look at the human brain and discover how AI will always have its limitations. Hosts and finance professors Jonathan Berk and Jules van Binsbergen sit down with Jeff Hawkins, a neuroscientist and computer scientist, whose book A Thousand Brains challenges the way we think about intelligence and how the brain works. Jonathan, Jules, and Jeff discuss the fundamentals of how the human brain operates and how it differs from the way current AI models work. They also dive into the cutting-edge innovations happening in the world of AI and whether future versions of the technology could one day emulate the human brain more closely. Find All Else Equal on the web: https://lauder.wharton.upenn.edu/allelse/ All Else Equal: Making Better Decisions Podcast is a production of the UPenn Wharton Lauder Institute through University FM. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
In this episode of The Trading Coach Podcast, Akil Stokes answers your biggest trading questions covering strategy development, AI in trading, Forex vs Futures, and knowing when to stick with — or abandon — a trading system.If you're struggling with consistency, confidence, or strategy evaluation, this episode is for you.
In this talk, Mariano, Lead Data Scientist and ML Engineer at OLX, shares his journey building high-impact AI media solutions. We explore the transition from traditional e-commerce models to Generative AI and Agentic tools, focusing on how to take AI products from a notebook to full-scale production.You'll learn about:How to master the full product cycle from requirement gathering to deployment.Using video-to-ad technology to automate car listings and seller experiences.Essential modern tools like FastAPI, Arize, and why UV is a game-changer.When to use LLMs versus specialized vision models like CLIP and YOLO.Why production pipelines are moving from Jupyter notebooks to CLI tools.How agentic coding and AI assistants are 10x-ing development speed.TIMECODES:0:00 Community Introduction and Slack Engagement4:16 Career Journey: From Argentina to Barcelona7:16 Product-Driven AI vs. Traditional Reporting9:41 AI Media Solutions for E-Commerce Sellers10:55 Video-to-Ad: The Future of Marketplaces13:45 Automated Content Creation for Sellers17:10 Defining End-to-End Ownership in Data Science21:12 The Longevity of the CRISP-DM Framework25:33 Impact of Agentic Coding and GitHub Copilot31:42 Why LLMs Aren't Always the Best Solution37:39 Translating Business Needs to ML Requirements41:18 Managing Explicit and Implicit Feedback Loops48:26 Architecture Deep Dive: Image Description Logic55:28 The Declining Role of Notebooks in Production1:02:53 The Modern Tech Stack: Fast API, UV, and ArizeConnect with Mariano: Linkedin - https://www.linkedin.com/in/msemelman/Connect with DataTalks.Club:- Join the community - https://datatalks.club/slack.html- Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/r?cid=ZjhxaWRqbnEwamhzY3A4ODA5azFlZ2hzNjBAZ3JvdXAuY2FsZW5kYXIuZ29vZ2xlLmNvbQ- Check other upcoming events - https://lu.ma/dtc-events- GitHub: https://github.com/DataTalksClub- LinkedIn - https://www.linkedin.com/company/datatalks-club/ - Twitter - https://twitter.com/DataTalksClub - Website - https://datatalks.club/
Joe Maionchi (Co-founder & COO) and Rod Christensen (Co-founder & Chief Architect) of RocketRide join the MLOps Community to walk through AIDE — the AI Integrated Development Environment. RocketRide is an open-source AI pipeline platform that lets developers build, debug, and run production-grade agentic AI workflows directly from their IDE, with support for 13+ LLM providers, 8+ vector databases, and full multi-agent orchestration.AI Is Fast. AI Projects Are Slow. Let's Fix That. // MLOps Podcast #378 with JRocketRide's Joe Maionchi (Co-founder & COO) and Rod Christensen (Co-founder & Chief Architect)A huge shout-out to RocketRide for this collaboration!
BuzzHPC Roundtable episode: Architecting Modern AI Systems: Platforms, Agents, and Integration Join the Community: https://go.mlops.community/YTJoinInGet the newsletter: https://go.mlops.community/YTNewsletterMLOps GPU Guide: https://go.mlops.community/gpuguideBig shout-out to BuzzHPC for the collaboration!// AbstractAs AI systems evolve into more autonomous, agent-driven architectures, the way we design platforms, tools, and infrastructure is rapidly changing. In this session with BuzzHPC, we explore the shifting boundary between platforms and tools, what developers expect platform providers to handle versus what they want to control and build themselves. We unpack what modern agentic stacks look like today, how teams are structuring them in production, and where these architectures are heading as systems become more complex and distributed. A key focus will also be on agent interoperability, how different agents communicate, coordinate, and operate within shared environments.Finally, we share insights and lessons from a recent AI hackathon delivered in partnership with Bell, Buzz, Mila, and KHP, highlighting how these concepts are being tested and applied by builders in real-world scenarios.// BioAllen RoushAllen has held senior technical and AI leadership roles at companies like Oracle and Intel. He's very active in the AI research space and open source communities. He's passionate about improving the creativity and coherence of AI systems.Frédéric BénardFrédéric is Senior Director of AI Applications Development at Mila (Quebec AI Institute), where he leads a team focused on building the engineering foundations for applied AI systems. His work centers on translating cutting-edge research into scalable applications, including AI-driven platforms and agent-based systems used across research and industry collaborations.Shuo WangShuo leads the Responsible AI Office for Bell Canada, where all AI use cases are reviewed and assessed for potential harm and bias. Previously, he led a team of data scientists to expand a large-scale ML program to improve customer support effectiveness.// Related LinksWebsite: https://www.buzzhpc.ai/~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin our Slack community [https://go.mlops.community/slack]Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register]MLOps Swag/Merch: [https://shop.mlops.community/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with Allen on LinkedIn: /allen-roush-27721011b/Connect with Frédéric on LinkedIn: /benard/Connect with Shuo on LinkedIn: /shuow/
Today I want to walk through how to set up an AI system specifically for real estate agents using three tools. Claude, Make, and Tally. By the end of this you'll know how to qualify buyer leads before you waste time on a call, draft personalized follow-ups for cold prospects, and generate property descriptions from a handful of bullet points.Get help here >> https://wilwaldon.com Join our business automation community >> https://www.skool.com/ai-and-automation-3750
Why are some coaches getting thousands of views but zero clients while others land buyers with a simple post? In this episode, Jason breaks down the real reason most content fails to convert in today's AI-driven world. He reveals a three-phase system built around belief shifting, identity-based positioning, and strategic content amplification that helps coaches attract pre-sold clients instead of passive followers. From fixing weak messaging to leveraging AI without sounding robotic, this conversation dives into how modern creators can stand out, build trust, and turn content into consistent revenue. "Attention is not the currency that we're currently in right now. We're in getting the right attention." What You Need To Know: Views do not equal sales. Content that only teaches information may attract attention, but belief-shifting content is what converts followers into paying clients. Positioning matters more than tactics. Coaches who sell an aspirational identity and belief system stand out more than those relying on generic promises or broad niche messaging. Pre-sold buyers are created before the sales call. Effective marketing shifts beliefs around the problem, possibility, solution, timing, and trust in the coach before a prospect ever reaches out. AI should amplify your voice, not replace it. Using AI to repurpose transcripts, organize ideas, and scale content works best when it is trained on your unique perspective and communication style. One strong piece of content can fuel an entire marketing system. A single workshop or long-form video can be repurposed into reels, emails, captions, and posts that consistently reinforce your message across multiple platforms. Connect with Jason Meland: Email: jason@goliveonlinemastermind.com Website: https://www.growmyvisibility.com/ Instagram: @coachjasonmeland Facebook: Jason Meland - In Demand Coach LinkedIn: Jason Meland
Today I want to walk through how to put together a simple AI system for a small business using three tools. Claude, Make, and a form builder like Typeform or Tally. By the end of this you'll know how to set things up so new customer inquiries get answered automatically, leads who go quiet get followed up with, and a two-minute voice memo turns into a week of social media posts.Before any of that makes sense I should probably explain what these tools actually are.Claude is an AI assistant. Same general category as ChatGPT, made by a different company called Anthropic. You can use it free at claude dot ai. People who use AI for real work tend to prefer it because it writes in a more natural voice and handles bigger documents better.Make is an automation platform. The way to think about it is that it connects apps to each other so they can pass information back and forth without you copying and pasting. You build little flows where one thing triggers another. If you've heard of Zapier, it's the same idea. Make is usually cheaper and gives you more room to do interesting stuff.Typeform and Tally are form builders. Drag and drop, no coding, you put a form together in maybe ten minutes and paste a link to it on your website.Reach out >>> https://wilwaldon.com
The rise of Private AI Systems has created a rush of developers trying to bolt AI onto everything they touch. But the developers who are actually creating long-term value are approaching AI differently. They are not starting with hype. They are starting with friction. In this interview, Matt Levenhagen shares a practical perspective on AI adoption that cuts through most of the noise surrounding modern tooling. Instead of trying to launch the next AI startup immediately, he focused on solving operational problems inside his own business first. That shift in mindset changes everything. About Matt Levenhagen Matt is the founder and CEO of Unified Web Design, a web development agency focused on custom solutions, WordPress development, e-commerce, memberships, and business systems. His background as both a builder and agency owner gave him a unique perspective on where AI creates real leverage instead of superficial automation. Follow Matt on LinkedIn. Private AI Systems Start with Operational Friction Most developers approach AI backward. They start with the technology and search for a use case later. Matt described taking the opposite path. He recognized that AI was becoming foundational technology and knew he needed hands-on experience with it. But instead of building a flashy product immediately, he asked a more important question: What problems already exist inside the business? That led him toward creating internal systems capable of understanding business context, workflows, client history, and operational memory. This matters because AI becomes exponentially more valuable when connected to existing processes. A chatbot with no context is a novelty. A system that understands your operations becomes infrastructure. The strongest AI products often begin as internal tools before becoming commercial products. Why Developers Need Persistent Business Memory One of the most important ideas Matt discussed was memory. Traditional SaaS AI tools often operate inside isolated conversations. They respond to prompts but lack continuity and deep operational understanding. Matt wanted something different: a system capable of remembering his business. That distinction is critical. Most businesses lose enormous amounts of value through fragmented information: Past client solutions Process documentation Internal discussions Technical decisions Workflow patterns Sales conversations Without persistent memory, every project starts partially from scratch. Matt envisioned a system that could recognize patterns and surface relevant historical information automatically. Instead of manually searching documentation or task systems, the AI could identify relationships between past work and current problems. This transforms AI from a content generator into an operational assistant. Private AI Systems Reduce Dependency on Generic SaaS AI A major challenge businesses face today is the rapid AI feature expansion inside existing software platforms. Every tool suddenly has "AI." Slack ClickUp HubSpot Email platforms CRM systems But Matt pointed out an important limitation: most embedded AI features solve narrow tasks. They summarize. They search. They auto-generate drafts. Useful? Yes. Transformational? Usually not. The reason is simple. These systems only understand fragments of your business. A privately controlled AI layer can aggregate context across multiple systems instead of remaining trapped inside individual platforms. That allows developers to build workflows tailored to how the business actually operates. This is where builders gain an advantage over passive software consumers. Adding AI to a workflow does not automatically improve the workflow. Poor systems become faster poor systems. The Real Advantage of Building Internal AI First One of the smartest strategic decisions Matt described was delaying external commercialization. That sounds counterintuitive in startup culture, where speed dominates every conversation. But internal development creates several advantages: 1. Lower Risk Mistakes affect internal operations instead of customers. 2. Faster Iteration Developers can experiment without worrying about public perception. 3. Better Understanding Builders learn where AI genuinely helps versus where it creates friction. 4. Operational Integration The system evolves naturally around existing workflows. This mirrors how many successful SaaS products originated historically. Internal tooling frequently becomes productized later because the creator already understands the operational problem deeply. Developers often skip this stage entirely and immediately chase scale. That usually leads to shallow products solving imaginary problems. Private AI Systems Force Better Architectural Thinking One of the deeper technical themes in the conversation involved memory architecture and contextual retrieval. Matt discussed implementing approaches like RAG (Retrieval-Augmented Generation) to avoid loading massive amounts of irrelevant context into every interaction. This highlights a major evolution happening in software development right now. AI development is becoming less about prompting and more about architecture. The real engineering challenge is: What information matters? When should it be retrieved? How should context be structured? What belongs in memory? What should remain isolated? Developers who understand contextual architecture will build significantly more valuable systems than developers focused purely on model experimentation. The future competitive advantage in AI may come less from the model itself and more from how businesses structure and retrieve institutional knowledge. Why the "Builder Mindset" Matters More Than the AI Stack One of the strongest themes throughout the episodes was mindset. Matt consistently approached AI as a builder, not as a trend follower. That mindset changes how decisions get made: Start with business friction Solve operational problems Build incrementally Learn through implementation Protect flexibility Focus on systems over hype This approach is far more sustainable than chasing every new AI release. The tools will continue changing rapidly. The builder mindset remains valuable regardless of which model dominates next year. Identify one repetitive workflow in your business this week and document how information moves through it before introducing AI. Conclusion Private AI Systems represent a shift away from generic automation and toward operational intelligence. Matt Levenhagen's approach demonstrates an important principle for developers and founders alike: the most valuable AI solutions are often built by deeply understanding your own workflows first. Instead of asking: "How do I add AI?" The better question becomes: "Where does my business repeatedly lose time, context, or knowledge?" That question leads to systems that create leverage instead of noise. Stay Connected: Join the Developreneur Community
#911 If you thought Part 1 was packed with value, Part 2 takes it even further! In this conclusion to our 2-part series, host Brien Gearin continues his conversation with Corey Ganim — host of the "Build with AI" podcast and owner of Return My Time — diving into the final three pillars of his AI Operating System: Finance, Operations, and Intelligence. Corey introduces the Weekly P&L One-Pager, a skill that gives business owners a real-time pulse on their finances instead of waiting 45 days for last month's numbers. He then walks through how to fully automate client onboarding — turning a 30-to-45-minute manual process into a seamless, error-free experience that runs itself. Finally, Corey shares a powerful Intelligence skill that generates a personalized one-page client brief before every call, helping you show up fully informed and deliver a world-class experience every time. He also breaks down his three levers of ROI — effectiveness, efficiency, and quality — so you can evaluate any AI tool or implementation with clarity. If you're ready to stop being reactive in your business and start letting AI do the heavy lifting, this episode is your blueprint! What we discuss with Corey: + The Weekly P&L One-Pager skill + Stop waiting 45 days for financials + Course-correct mid-month, not after + Automating client onboarding end-to-end + Saving 30-45 minutes per new client + AI-generated pre-call client briefs + The three levers of ROI + Setting permissions and guardrails for AI + Treat Claude like a new employee + Connecting AI to your financial tools safely Thank you, Corey! Check out Part 1 of this episode. Check out Return My Time at ReturnMyTime.com. Listen to The Build With AI Podcast. Work with Corey. Watch the video podcast of this episode! To get access to our FREE Business Training course go to MillionaireUniversity.com/training. To get exclusive offers mentioned in this episode and to support the show, visit millionaireuniversity.com/sponsors. Learn more about your ad choices. Visit megaphone.fm/adchoices
#910 If your business is growing but you are the bottleneck, this episode will change the way you work forever! In Part 1 of this 2-part episode, host Brien Gearin sits down with Corey Ganim — host of the "Build with AI" podcast and owner of Return My Time — to break down his AI Operating System, a practical framework for installing AI into every part of your business so you can scale without hiring and without learning to code. Corey walks through the three-tool foundation (Claude, Claude Cowork, and Skills) and dives deep into the first two of five business pillars: Sales and Marketing. You'll learn why speed to lead is the single highest-ROI opportunity for most small businesses — backed by an MIT study showing you're 21x more likely to close a deal if you respond in under five minutes — and how to build an AI-powered system that sends personalized responses to new leads around the clock. Corey also shares a simple but powerful marketing skill that turns a 30-second voice memo into a polished LinkedIn post, saving business owners hours every week! What we discuss with Corey: + AI Operating System: scale without hiring or coding + 3 tools: Claude (brain), Cowork (hands), Skills (playbooks) + Skills = AI-executable SOPs + Speed to lead is your biggest revenue opportunity + Average B2B response time: 42 hours + MIT study: 21x more likely to close in under 5 minutes + AI sends personalized lead responses around the clock + Voice memo → polished LinkedIn post on autopilot + 5 skills = ~250 hours saved per year + AI handles sales & marketing so you stop being the bottleneck Thank you, Corey! Check out Return My Time at ReturnMyTime.com. Listen to The Build With AI Podcast. Work with Corey. To get access to our FREE Business Training course go to MillionaireUniversity.com/training. To get exclusive offers mentioned in this episode and to support the show, visit millionaireuniversity.com/sponsors. Learn more about your ad choices. Visit megaphone.fm/adchoices
This episode features Dr. Rania Saleh sharing her journey from dentist and practice owner to founder of Oryx Dental, a cloud-based dental practice management software. She and Dr. Grace Yum discuss how AI, automation, and smarter systems are transforming dentistry, along with practical insights on choosing software that supports long-term practice growth and efficiency. Episode Highlights: How Dr. Rania Saleh turned real practice challenges into a dental software company Why choosing scalable, AI-powered software matters for growing practices Common mistakes dentists make when selecting practice management systems How AI and automation can improve workflows, patient experience, and profitability The future of dentistry and why adaptability is key for practice owners Ready to thrive as a dentist and a mom? Join a supportive community of like-minded professionals at Mommy Dentists in Business. Whether you're looking to grow your practice, find balance, or connect with others who understand your journey, MDIB is here to help. Visit mommydibs.com to learn more and become a part of this empowering network today!
Raja-Elie Abdulnour is the Chief Clinical Innovation Officer at NEJM Group and an associate physician in the Pulmonary and Critical Care Medicine Division at Brigham and Women's Hospital. Stephen Morrissey, the interviewer, is the Executive Managing Editor of the Journal. A. Sikora, L.A. Celi, and R.-E.E. Abdulnour. Can AI Say “I Don't Know”? N Engl J Med 2026;394:1873-1875.
Welcome to the Wholesale Hotline Podcast Weekend Edition (Flipping Mastery Edition), where Jerry teaches how to master the art of house flipping, wholesaling, and new construction development.Show notes -- in this episode we'll cover:Straightforward, step-by-step training on making six and seven figures from real estate deals.Insider tactics for finding motivated sellers, analyzing deals, and raising private money.Learn how to flip houses virtually from anywhere—even with zero experience.Whether you're a beginner or scaling up, Jerry gives you the blueprint to build real wealth through real estate. Please give us a rating and let us know how we are doing!➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖ ☎️ Welcome to Wholesale Hotline & Flipping Mastery Breakout! ☎️Jerry Norton went from digging holes for minimum wage in his mid 20's to becoming a millionaire by the age of 30. Today he's the nation's leading expert on flipping houses and has taught thousands of people how to live their dream lifestyle through real estate. **NOTE: To Download any of Jerry's FREE training, tools, or resources…Click on the link provided and enter your email. The download is automatically emailed to you. If you don't see it, check your junk/spam folder, in case your email provider put it there. If you still don't see it, contact our support at: support@flippingmastery.com or 888) 958-3028. ➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖
We are officially entering the "Multi-AI Era." Much like the multi-cloud times, organizations are no longer just using a single AI tool like Microsoft Copilot, they are building custom, agentic workflows using diverse third-party models and MCP servers . In this episode, Ashish sits down with Shawn Hays from Varonis to discuss why the security market has over-pivoted on AISPM (AI Security Posture Management) . Shawn spoke about how having visibility and an inventory of your AI models is a great start, but it fails to secure the enterprise if you lack the guardrails to actually stop an agent from going off the rails and exfiltrating data . Shawn breaks down the components of a robust AI security platform (like Varonis Atlas) and explains why data security is inseparable from AI security. He spoke about why AI agents will blindly "read whatever is on the teleprompter," meaning your AI is only as secure as the data access and identity controls surrounding it . Tune in to learn how to apply Zero Trust across the entire AI chain from the prompter to the cloud infrastructure Guest Socials - Shawn's Linkedin Podcast Twitter - @CloudSecPod If you want to watch videos of this LIVE STREAMED episode and past episodes - Check out our other Cloud Security Social Channels:-Cloud Security Podcast- Youtube- Cloud Security Newsletter If you are interested in AI Security, you can check out our sister podcast - AI Security PodcastQuestions asked:(00:00) Introduction(02:50) Shawn's Background: Microsoft, CMMC, and Varonis (03:50) The Biggest AI Security Challenges (Copilot to Agentic AI) (05:50) Third-Party AI Risk (Jira and Salesforce Agents) (08:40) The Connector Ecosystem Danger (Copilot + Salesforce) (11:50) 8 Distinct Areas of an AI Security Platform (Varonis Atlas) (14:00) Entering the "Multi-AI Era" (Analogies to Multi-Cloud) (16:00) The AI Bill of Materials (Athena AI & Grammarly) (20:50) Why Data Security and AI Security are Intertwined (22:00) Applying Zero Trust to the Entire AI Chain (24:50) The Role of Identity and ITDR in AI Systems (27:00) HIPAA, OCR, and Regulating AI Data Access (31:30) Creating a Governance Plan for Microsoft Copilot (33:50) Securing Pro-Code AI Systems (AWS Bedrock & MCP Servers) (38:30) Why the Security Market is Over-Pivoting on AISPM (44:10) The "Ron Burgundy" Analogy for AI Agents (45:50) Fun Questions: Crocodile & Caramel Tasting (47:20) The Ed Sheeran & Yelawolf Mixtape Connection (48:50) Hobbies & Pride: DJing Weddings and Playing Ice Hockey in Alabama (51:50) Favorite Food: Alabama White Sauce BBQ & Milo's BurgersResources spoken about during the episode:Varonis Atlas
Hundreds of prominent AI scientists and other notable figures signed a statement in 2023 saying that mitigating the risk of extinction from AI should be a global priority. At 80,000 Hours, we've considered risks from AI to be the world's most pressing problem since 2016. But what led us to this conclusion? Could AI really cause human extinction? We're not certain, but we think the risk is worth taking very seriously. In particular, as companies create increasingly powerful AI systems, there's a concerning chance that:These AI systems may develop dangerous long-term goals we don't want.To pursue these goals, they may seek power and undermine the safeguards meant to contain them.They may even aim to disempower humanity and potentially cause our extinction.This article is written by Cody Fenwick and Zershaaneh Qureshi, and narrated by Zershaaneh Qureshi. It discusses why future AI systems could disempower humanity, what current AI research reveals about behaviours like power-seeking and deception, and how you can help mitigate the dangers.You can see the original article — packed with graphs, images, footnotes, and further resources — on the 80,000 Hours website: https://80000hours.org/problem-profiles/risks-from-power-seeking-ai/ Chapters:Risks from power-seeking AI systems (00:01:00)Introduction (00:01:17)Summary (00:03:09)Why are the risks from power-seeking AI a pressing world problem? (00:04:04)Section 1: Humans will likely build advanced AI systems with long-term goals (00:05:43)Section 2: AIs with long-term goals may be inclined to seek power (00:11:32)Section 3: These power-seeking AI systems could successfully disempower humanity (00:26:26)Section 4. People might create power-seeking AI systems without enough safeguards, despite the risks (00:38:34)Section 5: Work on this problem is neglected and tractable (00:47:37)Section 6: What are the arguments against working on this problem? (00:59:20)Section 7: How you can help (01:25:07)Thank you for listening (01:28:56)Audio editing: Dominic ArmstrongProduction: Zershaaneh Qureshi, Elizabeth Cox, and Katy Moore
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