Podcasts about llm

ETH Zurich's deep-dive into the world's top password managers exposes how feature overload and legacy design obscure real security flaws, forcing a rethink of what "zero knowledge" actually means for your vault. Learn why recent fixes matter—and why open source may be your safest bet. CA's warn us to urgently prepare for the inevitable. Three U.S. states attempt to ban 3D printed firearms. Denied ransom, ShinyHunters leaks 967,000 personal details. "Billions" of U.S. social security numbers leaked. Is Apple planning to add cameras to three new gadgets. No more security fixes for Firefox on Windows 7 & 8. Russia blocks the official Linux kernel site they need. Will the U.S."freedom.gov" site post EU blocked content. LLM's will offer secure passwords. Do Not Use Them. As predicted, the "ClickFix" attack strategy takes over. A listener believes his computer is compromised. How could three popular password managers get things wrong. Show Notes - https://www.grc.com/sn/SN-1066-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to Security Now at https://twit.tv/shows/security-now. You can submit a question to Security Now at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: guardsquare.com bitwarden.com/twit zscaler.com/security hoxhunt.com/securitynow material.security

ETH Zurich's deep-dive into the world's top password managers exposes how feature overload and legacy design obscure real security flaws, forcing a rethink of what "zero knowledge" actually means for your vault. Learn why recent fixes matter—and why open source may be your safest bet. CA's warn us to urgently prepare for the inevitable. Three U.S. states attempt to ban 3D printed firearms. Denied ransom, ShinyHunters leaks 967,000 personal details. "Billions" of U.S. social security numbers leaked. Is Apple planning to add cameras to three new gadgets. No more security fixes for Firefox on Windows 7 & 8. Russia blocks the official Linux kernel site they need. Will the U.S."freedom.gov" site post EU blocked content. LLM's will offer secure passwords. Do Not Use Them. As predicted, the "ClickFix" attack strategy takes over. A listener believes his computer is compromised. How could three popular password managers get things wrong. Show Notes - https://www.grc.com/sn/SN-1066-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to Security Now at https://twit.tv/shows/security-now. You can submit a question to Security Now at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: guardsquare.com bitwarden.com/twit zscaler.com/security hoxhunt.com/securitynow material.security

ETH Zurich's deep-dive into the world's top password managers exposes how feature overload and legacy design obscure real security flaws, forcing a rethink of what "zero knowledge" actually means for your vault. Learn why recent fixes matter—and why open source may be your safest bet. CA's warn us to urgently prepare for the inevitable. Three U.S. states attempt to ban 3D printed firearms. Denied ransom, ShinyHunters leaks 967,000 personal details. "Billions" of U.S. social security numbers leaked. Is Apple planning to add cameras to three new gadgets. No more security fixes for Firefox on Windows 7 & 8. Russia blocks the official Linux kernel site they need. Will the U.S."freedom.gov" site post EU blocked content. LLM's will offer secure passwords. Do Not Use Them. As predicted, the "ClickFix" attack strategy takes over. A listener believes his computer is compromised. How could three popular password managers get things wrong. Show Notes - https://www.grc.com/sn/SN-1066-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to Security Now at https://twit.tv/shows/security-now. You can submit a question to Security Now at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: guardsquare.com bitwarden.com/twit zscaler.com/security hoxhunt.com/securitynow material.security

ETH Zurich's deep-dive into the world's top password managers exposes how feature overload and legacy design obscure real security flaws, forcing a rethink of what "zero knowledge" actually means for your vault. Learn why recent fixes matter—and why open source may be your safest bet. CA's warn us to urgently prepare for the inevitable. Three U.S. states attempt to ban 3D printed firearms. Denied ransom, ShinyHunters leaks 967,000 personal details. "Billions" of U.S. social security numbers leaked. Is Apple planning to add cameras to three new gadgets. No more security fixes for Firefox on Windows 7 & 8. Russia blocks the official Linux kernel site they need. Will the U.S."freedom.gov" site post EU blocked content. LLM's will offer secure passwords. Do Not Use Them. As predicted, the "ClickFix" attack strategy takes over. A listener believes his computer is compromised. How could three popular password managers get things wrong. Show Notes - https://www.grc.com/sn/SN-1066-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to Security Now at https://twit.tv/shows/security-now. You can submit a question to Security Now at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: guardsquare.com bitwarden.com/twit zscaler.com/security hoxhunt.com/securitynow material.security

ETH Zurich's deep-dive into the world's top password managers exposes how feature overload and legacy design obscure real security flaws, forcing a rethink of what "zero knowledge" actually means for your vault. Learn why recent fixes matter—and why open source may be your safest bet. CA's warn us to urgently prepare for the inevitable. Three U.S. states attempt to ban 3D printed firearms. Denied ransom, ShinyHunters leaks 967,000 personal details. "Billions" of U.S. social security numbers leaked. Is Apple planning to add cameras to three new gadgets. No more security fixes for Firefox on Windows 7 & 8. Russia blocks the official Linux kernel site they need. Will the U.S."freedom.gov" site post EU blocked content. LLM's will offer secure passwords. Do Not Use Them. As predicted, the "ClickFix" attack strategy takes over. A listener believes his computer is compromised. How could three popular password managers get things wrong. Show Notes - https://www.grc.com/sn/SN-1066-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to Security Now at https://twit.tv/shows/security-now. You can submit a question to Security Now at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: guardsquare.com bitwarden.com/twit zscaler.com/security hoxhunt.com/securitynow material.security

ETH Zurich's deep-dive into the world's top password managers exposes how feature overload and legacy design obscure real security flaws, forcing a rethink of what "zero knowledge" actually means for your vault. Learn why recent fixes matter—and why open source may be your safest bet. CA's warn us to urgently prepare for the inevitable. Three U.S. states attempt to ban 3D printed firearms. Denied ransom, ShinyHunters leaks 967,000 personal details. "Billions" of U.S. social security numbers leaked. Is Apple planning to add cameras to three new gadgets. No more security fixes for Firefox on Windows 7 & 8. Russia blocks the official Linux kernel site they need. Will the U.S."freedom.gov" site post EU blocked content. LLM's will offer secure passwords. Do Not Use Them. As predicted, the "ClickFix" attack strategy takes over. A listener believes his computer is compromised. How could three popular password managers get things wrong. Show Notes - https://www.grc.com/sn/SN-1066-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to Security Now at https://twit.tv/shows/security-now. You can submit a question to Security Now at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: guardsquare.com bitwarden.com/twit zscaler.com/security hoxhunt.com/securitynow material.security

ETH Zurich's deep-dive into the world's top password managers exposes how feature overload and legacy design obscure real security flaws, forcing a rethink of what "zero knowledge" actually means for your vault. Learn why recent fixes matter—and why open source may be your safest bet. CA's warn us to urgently prepare for the inevitable. Three U.S. states attempt to ban 3D printed firearms. Denied ransom, ShinyHunters leaks 967,000 personal details. "Billions" of U.S. social security numbers leaked. Is Apple planning to add cameras to three new gadgets. No more security fixes for Firefox on Windows 7 & 8. Russia blocks the official Linux kernel site they need. Will the U.S."freedom.gov" site post EU blocked content. LLM's will offer secure passwords. Do Not Use Them. As predicted, the "ClickFix" attack strategy takes over. A listener believes his computer is compromised. How could three popular password managers get things wrong. Show Notes - https://www.grc.com/sn/SN-1066-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to Security Now at https://twit.tv/shows/security-now. You can submit a question to Security Now at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: guardsquare.com bitwarden.com/twit zscaler.com/security hoxhunt.com/securitynow material.security

My guest today is Dan Sundheim. Dan is the founder and CIO of D1 Capital Partners. He thinks about markets and businesses constantly, and has built a career entirely around that obsession. He manages over $30B across both public and private markets, with investments in SpaceX, OpenAI and Anthropic, and a public portfolio of names you may never have heard of. Dan shares the story of the short case he wrote on Orthodontic Centers of America and posted on Value Investors Club, which crashed the stock, and helped him land his first job. He shares why he backed Anthropic at a moment when many people told him it was the Lyft to OpenAI's Uber, what reading Dario Amodei's essays reminded him of Jeff Bezos, and how he thinks about LLM business models through the lens of Netflix and Spotify. We spend time on the extraordinarily stressful moment in early 2021 when GameStop hit the firm, and what Dan believes is the single biggest tail risk facing the global economy right now. For the full show notes, transcript, and links to mentioned content, check out the episode page ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠.  ----- Become a Colossus member to get our quarterly print magazine and private audio experience, including exclusive profiles and early access to select episodes. Subscribe at ⁠colossus.com/subscribe⁠. ----- ⁠Ramp's⁠ mission is to help companies manage their spend in a way that reduces expenses and frees up time for teams to work on more valuable projects. Go to⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠ramp.com/invest⁠⁠ to sign up for free and get a $250 welcome bonus. ----- Trusted by thousands of businesses, ⁠Vanta⁠ continuously monitors your security posture and streamlines audits so you can win enterprise deals and build customer trust without the traditional overhead. Visit ⁠vanta.com/invest⁠.  ----- ⁠WorkOS⁠ is a developer platform that enables SaaS companies to quickly add enterprise features to their applications. Visit⁠⁠ ⁠WorkOS.com⁠⁠⁠ to transform your application into an enterprise-ready solution in minutes, not months. ----- ⁠Rogo⁠ is the AI platform for finance. They're building agents for Wall Street that are trained to understand how bankers and investors actually do work: from diligence and modeling, to turning analysis into deliverables. To learn more, visit rogo.ai/invest. ----- ⁠Ridgeline⁠ has built a complete, real-time, modern operating system for investment managers. It handles trading, portfolio management, compliance, customer reporting, and much more through an all-in-one real-time cloud platform. Visit⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ridgelineapps.com⁠. ----- Editing and post-production work for this episode was provided by The Podcast Consultant (⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://thepodcastconsultant.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠). Timestamps: (00:00:00) Welcome to Invest Like the Best (00:02:43) Intro: Dan Sundheim (00:03:58) The State of Public & Private Investing (00:07:32) Investing in OpenAI and Anthropic (00:10:22) LLMs Business Model (00:14:13) How LLMs are like Netflix and Spotify (00:17:08) Focus v. Scope (00:22:43) The Bear Case for Hyperscalers (00:26:36) The Software Sell-Off (00:31:08) If Scaling Laws Stopped (00:32:18) Advice to a 12-Year-Old Investor (00:33:54) GameStop: D1's Darkest Hour (00:37:14) The Pivotal Dinner with LPs (00:40:56) Staying Calm and Confident (00:42:08) Economic Optimism vs. Societal Uncertainty (00:44:26) Investing on SpaceX and Rivian (00:48:09) Why Dan Loves Shorting (00:48:51) Sources of Inefficiency in Today's Markets (00:51:45) The Importance of Loyalty (00:53:11) Dan's Group Chat for Founders (00:55:39) What Motivates Dan (00:57:28) Posting on Value Investors Club (01:01:46) What Dan Learned at Viking (01:04:22) The Beauty of Art (01:06:49) Under-appreciated Parts of the Global Economy (01:08:00) The US-China-Taiwan Collision Course (01:12:10) Good Leaders vs. Good Businesses (01:13:15) The Kindest Thing

Diffusion models changed how we generate images and video—now they're coming for text.In this episode, we sit down with Stefano Ermon, Stanford computer science professor and founder of Inception Labs, to unpack how diffusion works for language, why it can generate in parallel (instead of token-by-token), and what that means for latency, cost, and real-time AI products.We talk through:The simplest mental model for diffusion: generate a full draft, then refine it by “fixing mistakes”Why today's autoregressive LLM inference is often memory-bound—and why diffusion can shift it toward a more GPU-friendly compute profileWhere Mercury wins today (IDEs, voice/real-time agents, customer support, EdTech—anywhere humans can't wait)What changes (and what doesn't) for long context and architecture choicesThe real-world way to evaluate models in production: offline evals + the gold-standard A/B testStefano also shares what's next on Mercury's roadmap—especially around stronger planning and reasoning for agentic use cases.Try Mercury + learn more: inceptionlabs.aiFor more practical, grounded conversations on AI systems that actually work, subscribe to The Neuron newsletter at https://theneuron.ai.

Se Stanislavem Fortem o nástupu AI agentů, limitech a rizicích umělé inteligenci, ochraně a opravování softwarových katedrál a budování kyberbezpečnostního startupu Aisle v Praze. Moderuje Štěpán Sedláček.Pravděpodobně prožíváme technologickou revoluci, jejíž rychlost, rozsah a potenciálních dopady na lidský život a práci nemají obdoby, ať už skončí jakkoli. Nástup velkých jazykových modelů a generativní AI je čím dál patrnější napříč různými sférami lidské činnosti od programování po umění. Otázky, které dříve řešila poměrné malá skupina lidí spojených s výzkumem a vývojem umělé inteligence nebo science fiction, jsou dnes často ve středu zájmu celospolečenské debaty, byť by si možná zasloužily ještě více pozornosti a to i ze strany států. Otázku po tom, jestli někdy bude k dispozici umělá inteligence, která předčí člověka, dnes spíše přebíjí otázka, jestli nás od ní dělí rok, několik let nebo víc času. Stanislav Fort je matematik, fyzik a expert na umělou inteligenci a velké jazykové modely (LLM), který dříve působil v předních světových společnostech v oboru Google DeepMind nebo Anthropic. Jak vidí letošní rok na poli AI?„Myslím, že letos si většina lidí uvědomí, že AI funguje a je schopná dělat užitečnou intelektuální práci. V roce 2025 se staly mainstreamem přemýšlecí (tzv. reasoning) modely zejména v souvislosti s nástupem modelu R1 od společnosti DeepSeek. Během té doby se modely extrémně zlepšily a začaly být schopné řešit dlouhé a obtížné intelektuální úkoly napříč obory u nichž je třeba koordinovat přemýšlení přes dlouhé časové horizonty. A ty se měsíc po měsíci prodlužovaly rapidním tempem. Dnes si už většina lidí v programování i softwarovém inženýrství a odvětvích, která silně závisejí na využití počítačů, uvědomuje, že jsme na hraně toho, kdy tyto věci dokáží pracovat na podobných věcech jako elitní lidé a nepotřebují příliš supervize. Rok 2026 bude rokem, kdy AI agenti a přemýšlecí modely, které je pohánějí, začnou fungovat v reálných ekonomicky důležitých činnostech,“ říká expert Stanislav Fort, který společně s Ondřejem Vlčkem a Jayou Baloo založil firmu Aisle, kde působí jako hlavní vědec.Podařilo se jim vytvořit autonomní AI nástroj, který umí rychle nacházet a opravovat bezpečnostní chyby ve složitých softwarových systémech jako je protokol OpenSSL, který šifruje většinu komunikace na webu. Jaké mají po roce fungování na poli kybernetické bezpečnosti cíle? Jaký zásadní problém se jim podařilo vyřešit? Co říká na nástup AI agentů dění kolem sítě Moltbook? Vidí nějaké fundamentální limity ve vývoji umělé inteligence? Co si myslí o AI bublině na trzích? Jak by se měla Evropa postavit k aktuálním závodům ve vývoji AI? A jaká úskalí má zakládání kyberbezpečnostního startupu v Praze? Nejen na to se ptá v podcastu Zeitgeist Štěpán Sedláček.

Your biggest threat this year isn't malware. It's your own AI assistant.OpenClaw connects an LLM directly to your terminal, browser, email, and chat. It runs with your permissions. It executes tasks without hesitation.Days after launch, researchers found a One-Click RCE.Cisco called it a security nightmare.Gartner called it an unacceptable risk.OpenClaw (formerly known as Clawdbot and Moltbot) represents a new phase of agentic AI: autonomous assistants operating inside your environment with almost no guardrails.The headlines around OpenClaw have been clear: it's a serious threat. But how should we handle agentic AIs like OpenClaw moving forward?In this Threat Talks episode, Field CTO Rob Maas and SOC analyst Yuri Wit break down what OpenClaw actually does, where AI agent security breaks, and whether or not you should deploy OpenClaw.OpenClaw is powerful. It's useful.It's also proof that many of us are not ready for AI agents with this level of autonomy. Before you let an AI agent into your systems, understand what happens when it runs unchecked.TimestampsKey Topics Covered·         How OpenClaw works and why agentic AI changes the security model·         The One-Click RCE and what it reveals about AI agent security·         Malicious skills, default allow design, and autonomous privilege abuse·         Realistic mitigation strategies including sandboxing and controlled environmentsResources·         Threat Talks: https://threat-talks.com/ ·         ON2IT (Zero Trust as a Service): https://on2it.net/ ·         AMS-IX: https://www.ams-ix.net/ams Subscribe to Threat Talks and turn on notifications for deep dives into the world's most active cyber threats and hands-on exploitation techniques.Click here to view the episode transcript.  

Planet Nix and SCaLE are just days away, and we're getting a head start with two guests, the tech, and the trends shaping open source. Our trip starts here!Sponsored By:Jupiter Party Annual Membership: Put your support on automatic with our annual plan, and get one month of membership for free! Managed Nebula: Meet Managed Nebula from Defined Networking. A decentralized VPN built on the open-source Nebula platform that we love. Support LINUX UnpluggedLinks:

We push past rankings and traffic to map the real skills SEOs need to influence AI answers. Duane Forrester explains the machine layer, vector embeddings, semantic density, and why structured data is a must if you want reliable retrieval.• AI reshapes marketing and elevates SEO's role across the business• Good SEO foundations as the prerequisite for AI performance• Writing for chunks with high semantic density• Structured data and entity clarity to validate facts• Vector embeddings as the new alignment target• KPIs beyond rankings: retrieval confidence and zero‑click presence• Why LLMs.txt lacks adoption and what matters instead• Practical tracking of AI answers and trend analysis• The gap between search engines and LLM information retrieval• Learning paths to keep pace with faster platform updatesGuest Contact Information: Website: duaneforrester.comLinkedIn: linkedin.com/in/dforresterTwitter/X: x.com/DuaneForresterMore from EWR and Matthew:Leave us a review wherever you listen: Spotify, Apple Podcasts, or Amazon PodcastFree SEO Consultation: 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 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

AI is changing how shoppers discover products, and Amazon sellers need to pay attention now. In this episode, Scott breaks down the rise of AI-driven product discovery through tools like Amazon Rufus and ChatGPT, and explains why visibility in AI answers is becoming a new layer of competition for sellers. He unpacks Amazon's Cosmo framework, including the key product-understanding questions AI systems use to evaluate listings, and introduces SmartScout's new tools built for this shift: the Amazon AI Scorecard and the AI Visibility Monitor. Scott explains how the scorecard audits your listing content across bullets, A+ content, and images to measure how well your product answers AI-relevant questions. He also shows how the visibility monitor tracks how often your products appear in ChatGPT recommendations over time, even when AI responses are inconsistent. Scott also shares how sellers can improve AI visibility through better listing content, stronger online presence, and a more intentional long-term strategy for LLM discovery. If you want to know whether your brand is winning the AI visibility race in your category, this episode lays out the framework. Episode Notes: 02:00 - Amazon Rufus adoption and what it could mean for product discovery 03:10 - ChatGPT shopping behavior and why AI shopping queries still matter 04:06 - Why AI shopping accuracy is not perfect yet, but still important 04:34 - Amazon Cosmo and the product questions AI systems use to understand listings 07:00 - The shift from keyword-only thinking to AI-ready product content 07:32 - SmartScout's Amazon AI Scorecard and how it evaluates listing quality 08:10 - How the scorecard creates a feedback loop for continuous improvement 10:23 - SmartScout's AI Visibility Monitor and tracking LLM recommendation share 12:40 - Why ChatGPT results are non-deterministic and how visibility percentage helps 14:53 - Creatine example: measuring AI visibility by niche and query type 16:23 - How to improve AI visibility through listing content and off-Amazon signals 17:44 - Why this matters for sellers, brands, and teams in 2026   Related Post Top 10 Amazon FBA Reimbursement Services to Recover Your Funds   Scott's Links: LinkedIn: linkedin.com/in/scott-needham-a8b39813 X: @itsScottNeedham Instagram: @smartestseller YouTube: www.youtube.com/@smartestamazonseller2371 Newsletter: https://www.smartscout.com/newsletter-sign-up • • Blog: https://www.smartscout.com/blog

Segment 1 - Interview with Tim Morris Bringing intelligence to assets You've been through 6 CMDB projects in the last decade. None of them came close to the original goals, the CMDB was already out-of-date long before the project had any hopes of completing. Is building an asset inventory just too ambitious a project for most organizations, or is there a better way? Tim Morris shares a different approach with us today. It might require some convincing and some courage, but it seems much more likely to succeed than any of your past CMDB efforts… Segment Resources Trusted automation: Building autonomous IT with confidence This segment is sponsored by Tanium. Visit https://securityweekly.com/tanium to learn more about them! Segment 2 - Topic: the new White House cybersecurity strategy In this segment, we explore some early details about the White House's new, but yet unreleased cybersecurity strategy. It appears that drafts have been shared (or leaked) to the press, so there's plenty to discuss here! Segment 3 - News Finally, in the enterprise security news, Massive amounts of funding and acquisitions as we get close to RSA Open source registries need help Microsoft Copilot reads email marked as DO NOT READ Don't use an LLM to generate passwords is prompt injection a vulnerability defining risks AI changes the build versus buy equation the scammer's perspective All that and more, on this episode of Enterprise Security Weekly. Visit https://www.securityweekly.com/esw for all the latest episodes! Show Notes: https://securityweekly.com/esw-447

Segment 1 - Interview with Tim Morris Bringing intelligence to assets You've been through 6 CMDB projects in the last decade. None of them came close to the original goals, the CMDB was already out-of-date long before the project had any hopes of completing. Is building an asset inventory just too ambitious a project for most organizations, or is there a better way? Tim Morris shares a different approach with us today. It might require some convincing and some courage, but it seems much more likely to succeed than any of your past CMDB efforts… Segment Resources Trusted automation: Building autonomous IT with confidence This segment is sponsored by Tanium. Visit https://securityweekly.com/tanium to learn more about them! Segment 2 - Topic: the new White House cybersecurity strategy In this segment, we explore some early details about the White House's new, but yet unreleased cybersecurity strategy. It appears that drafts have been shared (or leaked) to the press, so there's plenty to discuss here! Segment 3 - News Finally, in the enterprise security news, Massive amounts of funding and acquisitions as we get close to RSA Open source registries need help Microsoft Copilot reads email marked as DO NOT READ Don't use an LLM to generate passwords is prompt injection a vulnerability defining risks AI changes the build versus buy equation the scammer's perspective All that and more, on this episode of Enterprise Security Weekly. Visit https://www.securityweekly.com/esw for all the latest episodes! Show Notes: https://securityweekly.com/esw-447

What if your mobile app strategy was holding back your entire company's growth? In this episode, Amanda and Adam of Branch welcome back Matt Hudson, founder of BILDIT, to discuss why mobile-first thinking isn't just about technology—it's an organizational imperative. From breaking down the real ROI of app investment and the myth of channel cannibalization, to preparing your ecommerce business for AI discovery optimization, Matt shares hard-won lessons on aligning teams, personalizing customer experiences, and staying ahead of LLM-driven search trends. Whether you're scaling retail, launching a mobile strategy, or wrestling with how to compete in an AI-first world, this conversation cuts through the noise to deliver actionable insights that will reshape how you think about customer engagement across all channels. Links and Resources: Matt Hudson on LinkedIn BILDIT website Branch - Mobile Attribution Platform and App Analytics Solutions For Enterprises Today's topics include: How to determine if your ecommerce business actually needs a mobile app Why organizational alignment across teams matters more than technology The critical difference between SEO and AI discovery optimization How to immediately implement AI-ready data on your site today Why React Native and cross-functional web-and-mobile teams accelerate app growth How AI personalization works at scale using embeddings and vectors Quotes from Matt Hudson: “The entire org of your company, no matter how big or small, has got to be vested in the growth of the mobile app.” “You know who doesn't care about cannibalization? The customer. The customer. They want the easiest experience to convert.” “If the mobile app doesn't improve your ROAS, your return on ad spend, nobody's going to do anything with it."

Segment 1 - Interview with Tim Morris Bringing intelligence to assets You've been through 6 CMDB projects in the last decade. None of them came close to the original goals, the CMDB was already out-of-date long before the project had any hopes of completing. Is building an asset inventory just too ambitious a project for most organizations, or is there a better way? Tim Morris shares a different approach with us today. It might require some convincing and some courage, but it seems much more likely to succeed than any of your past CMDB efforts… Segment Resources Trusted automation: Building autonomous IT with confidence This segment is sponsored by Tanium. Visit https://securityweekly.com/tanium to learn more about them! Segment 2 - Topic: the new White House cybersecurity strategy In this segment, we explore some early details about the White House's new, but yet unreleased cybersecurity strategy. It appears that drafts have been shared (or leaked) to the press, so there's plenty to discuss here! Segment 3 - News Finally, in the enterprise security news, Massive amounts of funding and acquisitions as we get close to RSA Open source registries need help Microsoft Copilot reads email marked as DO NOT READ Don't use an LLM to generate passwords is prompt injection a vulnerability defining risks AI changes the build versus buy equation the scammer's perspective All that and more, on this episode of Enterprise Security Weekly. Show Notes: https://securityweekly.com/esw-447

Photo by Masahiro Naruse on Unsplash Published 23 February 2026 e544 with Andy, Michael and Michael – Stories and discussion on rumoured AI devices, addictive predictives, listening through bananas (or mud), and what happens when VR platforms die? Plus the usual assortment or other things. This week’s episode kicks off with a check in on which tech giants are working on what devices, now? Apple stepping back from headsets but working on glasses and pendants, and OpenAI making some kind of smart Pod for your dumb Home? Then, there’s discussion of the challenges of privacy when LLMs get access to private email and chats. Oh, and if you’re not sure if your AI is an LLM or a sentience, then Anthropic can’t answer that. We hope you’re listening to the show in perfect digital quality, but we’re also interested to know if you’ve tried piping it to your ears through any kind of fruit – let us know. Meta’s fully backing away from VR for Horizon Worlds, and in case Blizzard ever stops making the client software for World of Warcraft, Michael tried an open source version. Finally, don’t let hackers get hold of your brainwaves! (it could happen) These show notes were lovingly hand crafted by a real human, and not by a bot.  All rights reserved.  That's our story and we're sticking to it. Selected Links AI Apple AI Glasses OpenAI and Jony Ive device Thank god Microsoft is shoving Copilot AI crap into everything. One gets the sense this isn't going to be an isolated occurrence. From Bleeping Computer: "Microsoft says a Microsoft 365 Copilot bug has been causing the AI assistant to summarize confidential emails since late January, bypassing data loss prevention (DLP) policies that organizations rely on to protect sensitive information." https://www.bleepingcomputer.com/news/microsoft/microsoft-says-bug-causes-copilot-to-summarize-confidential-emails/ — BrianKrebs (@briankrebs@infosec.exchange) 2026-02-18T18:24:34.707Z HEADLINE: "Prediction Markets Are Sucking Huge Numbers of Young People Into Gambling" ALT HEADLINE: "All Our Incentives Lead to Bad Outcomes, and Prediction Markets Are Just One Example" https://futurism.com/future-society/prediction-markets-gambling — Mike Elgan (@MikeElgan@mastodon.social) 2026-02-16T17:06:59.555Z Episode 80 on prediction markets Claude isn’t sure what it is I gave Claude access to my pen plotter Audio Audiophiles can’t tell mud from bananas? AR/VR Meta ditching VR for Horizon Worlds Open Source WoW client Makers Reverse engineering a sleep mask Bonus link Trek-o-rama

Large Language Models entwickeln sich zu vollwertigen digitalen Mitarbeitern. Sie unterstützen bei Texterstellung, Website-Analyse, technischer Dokumentation, globaler Übersetzung und Recruiting-Prozessen. Durch strukturierte Delegation in fünf Stufen entstehen kontinuierlich lernende Assistenten. Die entscheidende Frage ist nicht was KI kostet, sondern welchen Mehrwert sie generiert. ----------------------------------------------------------- Lesen Sie den kompletten Beitrag: 583 LLM als digitaler Kollege im Team ----------------------------------------------------------- Hinweise zum Anmeldeverfahren, Versanddienstleister, statistischer Auswertung und Widerruf finden Sie in der Datenschutzerklärung.

Chaty, faça uma descrição para um episódio de podcast, sem parecer uma LLM (sem musica com direitos autorais)

Is bigger always better? While Large Language Models (LLMs) like GPT-5 and Gemini 2.5 dominate the headlines, a silent revolution is happening on our devices. In this episode, we explore the rise of Small Language Models (SLMs) and why they are becoming the "Specialists" of the AI world.We dive into the security risks of centralized cloud infrastructure, the demand for offline AI in corporate environments, and how gadgets like Apple AirPods and Meta Glasses are bringing real-time intelligence to our palms—without the privacy baggage. If you're a security architect or an AI enthusiast, this session is a roadmap for understanding why "no internet" might just be the best security feature for the next generation of intelligence.

OpenClaw is a self-hosted AI agent daemon that executes autonomous tasks through messaging apps like WhatsApp and Telegram using persistent memory. It integrates with Claude Code to enable software development and administrative automation directly from mobile devices. Links Notes and resources at ocdevel.com/mlg/mla-29 Try a walking desk - stay healthy & sharp while you learn & code Generate a podcast - use my voice to listen to any AI generated content you want OpenClaw is a self-hosted AI agent daemon (Node.js, port 18789) that executes autonomous tasks via messaging apps like WhatsApp or Telegram. Developed by Peter Steinberger in November 2025, the project reached 196,000 GitHub stars in three months. Architecture and Persistent Memory Operational Loop: Gateway receives message, loads SOUL.md (personality), USER.md (user context), and MEMORY.md (persistent history), calls LLM for tool execution, streams response, and logs data. Memory System: Compounds context over months. Users should prompt the agent to remember specific preferences to update MEMORY.md. Heartbeats: Proactive cron-style triggers for automated actions, such as 6:30 AM briefings or inbox triage. Skills: 5,705+ community plugins via ClawHub. The agent can author its own skills by reading API documentation and writing TypeScript scripts. Claude Code Integration Mobile to Deploy Workflow: The claude-code-skill bridge provides OpenClaw access to Bash, Read, Edit, and Git tools via Telegram. Agent Teams: claude-team manages multiple workers in isolated git worktrees to perform parallel refactors or issue resolution. Interoperability: Use mcporter to share MCP servers between Claude Code and OpenClaw. Industry Comparisons vs n8n: Use n8n for deterministic, zero-variance pipelines. Use OpenClaw for reasoning and ambiguous natural language tasks. vs Claude Cowork: Cowork is a sandboxed, desktop-only proprietary app. OpenClaw is an open-source, mobile-first, 24/7 daemon with full system access. Professional Applications Therapy: Voice to SOAP note transcription. PHI requires local Ollama models due to a lack of encryption at rest in OpenClaw. Marketing: claw-ads for multi-platform ad management, Mixpost for scheduling, and SearXNG for search. Finance: Receipt OCR and Google Drive filing. Requires human review to mitigate non-deterministic LLM errors. Real Estate: Proactive transaction deadline monitoring and memory-driven buyer matching. Security and Operations Hardening: Bind to localhost, set auth tokens, and use Tailscale for remote access. Default settings are unsafe, exposing over 135,000 instances. Injection Defense: Add instructions to SOUL.md to treat external emails and web pages as hostile. Costs: Software is MIT-licensed. API costs are paid per-token or bundled via a Claude subscription key. Onboarding: Run the BOOTSTRAP.md flow immediately after installation to define agent personality before requesting tasks.

Send a textWelcome everyone as we travel to the city of brotherly love and Rocky, Philadelphia. Today on the show, we have former Philadelphia warrant squad member Tristin Kilgallon.  Tristin grew up in Philadelphia and started his career in law enforcement with the city's Warrant Unit, tracking fugitives and working the tough streets of Philly. Tristin later moved to Ohio to attend law school, earning a JD and LLM. Tristin went on to teach pre-law and criminal justice for more than a decade before joining LexisNexis, where he now works in the legal tech industry, helping law firms adopt AI-driven tools. He's also the co-author of Philly Warrant Unit, a true-crime memoir about his time working fugitive apprehension in Philadelphia.Please enjoy this fun interview about a unique and small crime-fighting unit that had a large impact on crime, which no longer exists. In today's episode, we discuss:·      Growing up in the rough part of Philly. ·      Where and how Tristin got interested in law enforcement.·      What led him to the Philly Warrant Unit, and why he didn't pursue a career with the Philly Police.·      Did his investigations ever conflict with the local PD, state, or feds?·      How they picked which warrants to execute. ·      Knock vs. No-Knock Warrants.·      The difference between a search/arrest warrant.·      The prostitute calling the police on herself.·      Meeting Sylvester Stallone.·      Why he went into a teaching career.All of this and more on today's episode of the Cops and Writers podcast.Check out the Philly Warrant Unit Facebook page. Visit the Cops & Writers Website!Check out my newest book! Police Stories: The Rookie Years - True Crime, Chaos & Life as a Big City Cop!Support the show

Olive Song from MiniMax shares how her team trains the M series frontier open-weight models using reinforcement learning, tight product feedback loops, and systematic environment perturbations. This crossover episode weaves together her AI Engineer Conference talk and an in-depth interview from the Inference podcast. Listeners will learn about interleaved thinking for long-horizon agentic tasks, fighting reward hacking, and why they moved RL training to FP32 precision. Olive also offers a candid look at debugging real-world LLM failures and how MiniMax uses AI agents to track the fast-moving AI landscape. Use the Granola Recipe Nathan relies on to identify blind spots across conversations, AI research, and decisions: https://bit.ly/granolablindspot LINKS: Conference Talk (AI Engineer, Dec 2025) – https://www.youtube.com/watch?v=lY1iFbDPRlwInterview (Turing Post, Jan 2026) – https://www.youtube.com/watch?v=GkUMqWeHn40 Sponsors: Claude: Claude is the AI collaborator that understands your entire workflow, from drafting and research to coding and complex problem-solving. Start tackling bigger problems with Claude and unlock Claude Pro's full capabilities at https://claude.ai/tcr Tasklet: Tasklet is an AI agent that automates your work 24/7; just describe what you want in plain English and it gets the job done. Try it for free and use code COGREV for 50% off your first month at https://tasklet.ai CHAPTERS: (00:00) About the Episode (04:15) Minimax M2 presentation (Part 1) (17:59) Sponsors: Claude | Tasklet (21:22) Minimax M2 presentation (Part 2) (21:26) Research life and culture (26:27) Alignment, safety and feedback (32:01) Long-horizon coding agents (35:57) Open models and evaluation (43:29) M2.2 and researcher goals (48:16) Continual learning and AGI (52:58) Closing musical summary (55:49) Outro PRODUCED BY: https://aipodcast.ing SOCIAL LINKS: Website: https://www.cognitiverevolution.ai Twitter (Podcast): https://x.com/cogrev_podcast Twitter (Nathan): https://x.com/labenz LinkedIn: https://linkedin.com/in/nathanlabenz/ Youtube: https://youtube.com/@CognitiveRevolutionPodcast Apple: https://podcasts.apple.com/de/podcast/the-cognitive-revolution-ai-builders-researchers-and/id1669813431 Spotify: https://open.spotify.com/show/6yHyok3M3BjqzR0VB5MSyk

S6:E17 Everyone wants the shortcut. No one wants to hear there isn't one. Queue Up Episode This week on Small Business Stories, Dr. LL sits down with technical advisor and business coach Matthew Mamet to unpack what AI is actually changing and what it is not. If people don't trust you, they won't buy from you. If they can't distinguish your expertise from a bot, they won't remember you. Matthew brings perspective from the dot-com era through today's LLM shift, explaining why growth hacks fail and why authority now matters more than ever.

An airhacks.fm conversation with Kabir Khan (@kabirkhan) about: Discussion about the A2A (Agent-to-Agent) protocol initiated by Google and donated to the Linux Foundation, the A2A Java SDK reference implementation using quarkus, the Java SDK development accepted by Google, comparison of python and Java expressiveness and coding practices, the concept of an agent as a stateful process versus a tool as a stateless function call, the agent card as a JSON document advertising capabilities including supported protocols and descriptions and input/output modes and examples, the three wire protocols supported: JSON RPC and HTTP+JSON (REST) and grpc, the proto file becoming the single source of truth for the upcoming 1.0 spec, the facade/adapter pattern for the unified client across protocols, the agent executor interface with request context and event queue parameters, the distinction between simple message interactions and long-running multi-turn tasks, tasks as Java Records containing conversation history with messages and artifacts, message parts including text parts and data parts and file parts, task lifecycle with task IDs and context IDs for stateful conversations, the event queue as internal plumbing for propagating task updates, the separation between spec package (wire protocol entities) and server package (implementation details), the task store as a CRUD interface with in-memory default and database-backed implementations in extras, replicated queue manager using microprofile reactive messaging with Kafka for kubernetes environments, building A2A agents without any LLM involvement for simple use cases like backup systems, the role of LLMs in creating prompts from task messages and context, the agentic loop and the challenge of deciding when an agent's work is complete, the relationship between MCP (Model Context Protocol) for tool access and A2A for agent-to-agent communication, the possibility of wrapping agent calls as MCP tools, memory management considerations with short-term and long-term memory and prompt size affecting LLM quality, the distinction between the bare reference implementation and Quarkus-specific enhancements like annotations and dependency injection, upcoming 1.0 release with standardized Java records for all API classes and improved JavaDoc, protocol extensions including the agent payment protocol and GUI snippet extensions using template engines, authentication support with OAuth2 tokens and API keys and bearer tokens, the authenticated agent card containing more information than the public agent card, authorization hooks being discussed for task-level access control, the API and SPI segregation suggestion for better clarity between spec and implementation Kabir Khan on twitter: @kabirkhan

S6:E17 Everyone wants the shortcut. No one wants to hear there isn't one. Queue Up Episode This week on Small Business Stories, Dr. LL sits down with technical advisor and business coach Matthew Mamet to unpack what AI is actually changing and what it is not. If people don't trust you, they won't buy from you. If they can't distinguish your expertise from a bot, they won't remember you. Matthew brings perspective from the dot-com era through today's LLM shift, explaining why growth hacks fail and why authority now matters more than ever.

In this episode of The Effortless Podcast, Dheeraj Pandey speaks with Dr. Abhishek Bhowmick about how quantum mechanics reshaped our understanding of determinism and why that shift matters for AI today.  From the Einstein–Bohr debates to the idea that nature is fundamentally probabilistic, they explore how the collapse of “if-then” thinking began nearly a century ago. The discussion draws parallels between quantum superposition and modern LLM behavior. At its core, the episode reframes AI as a rediscovery of how reality computes. The conversation then moves from physics to computing architecture, tracing the evolution from scalar CPUs to GPUs, TPUs, tensors, and eventually quantum computing. They examine why probabilistic systems and vector math feel more natural than purely deterministic software. Hybrid computing models show that classical systems still matter. The episode also unpacks what quantum computers are truly good at, especially in cryptography and simulation. Ultimately, it reflects on whether the future of computing lies in embracing probability rather than resisting it. Key Topics & Timestamps 00:00 – Welcome, context, and how Dheeraj & Abhishek met 04:00 – Abhishek's journey: IIT, Princeton, Apple, Snowflake 08:00 – The 1927 Solvay Conference and physics at a crossroads 12:00 – Einstein vs. Bohr: determinism vs. probability 16:00 – Superposition and the collapse of the wave function 20:00 – Fields vs. particles: what is an electron really? 25:00 – Matter particles, force particles, and the Standard Model 30:00 – Transistors, voltage, and the rise of deterministic computing 35:00 – From scalar CPUs to vectors and matrices 40:00 – Tensors, linear algebra, and modern AI systems 45:00 – Principle of Least Action and gradient descent parallels 50:00 – Hallucinations, probability mass, and LLM behavior 55:00 – Vector databases, embeddings, and KNN search 59:00 – GPUs vs. TPUs: matrix vs. tensor architectures 1:05:00 – What quantum computers are actually good at 1:10:00 – Post-quantum cryptography and the future of computing Host -  Dheeraj Pandey Co-founder & CEO at DevRev. Former Co-founder & CEO of Nutanix. A systems thinker and product visionary focused on AI, software architecture, and the future of work. Guest -  Dr Abhishek Bhowmick                                                                                                                                                                                                                Co-Founder and CTO of Samooha, a secure data collaboration platform acquired by Snowflake. He previously worked at Apple as Head of ML Privacy and Cryptography, System Intelligence, and Machine Learning, and earlier at Goldman Sachs. He attended Princeton University and was awarded IIT Kanpur's Young Alumnus Award in 2024. Follow the Host and Guest - Dheeraj Pandey: LinkedIn - https://www.linkedin.com/in/dpandey Twitter - https://x.com/dheeraj Abhishek Bhowmik  LinkedIn –  https://www.linkedin.com/in/ab-abhishek-bhowmick Twitter/X – https://x.com/bhowmick_ab Share Your Thoughts Have questions, comments, or ideas for future episodes?

In this episode of the Shift AI Podcast, Scott Roberts, CISO at UiPath, joins host Boaz Ashkenazy for a deep dive into how agentic AI is reshaping enterprise security and automation—both for customers and inside UiPath itself.Scott shares his 25-year security journey spanning Microsoft's early Security Response Center days (including the era that produced Patch Tuesday and the Security Development Lifecycle), product security work across Windows and Xbox, time at AWS, and leadership roles at Google where he helped build the Android Security Assurance and Pixel Security teams and the Android Monthly Security Update process. He also discusses his work in security standards across IPsec, HTML5 encrypted media, GSMA device security, and most recently, contributions to emerging agentic AI security standards.The conversation then explores UiPath's evolution from traditional RPA into a unified platform that combines deterministic automation with agentic workflows. Scott walks through a real-world healthcare billing example where agentic automation increased deduplication accuracy dramatically by handling complex, variable inputs that classic RPA struggled with—while still keeping humans in the loop and feeding outcomes back into the system to improve over time.Boaz and Scott go deep on what's changed for CISOs in the post-LLM world: the need for guardrails, identity and entitlements for AI agents, and the challenge of end users copying sensitive information into consumer AI tools. Scott explains UiPath's approach: enable adoption while using nudges and policy controls to redirect sensitive workflows into enterprise-safe environments rather than relying solely on blocks.The episode closes with an eye-opening look at UiPath's internal “agentic threat analyst” system—an orchestration of 60+ agents that can investigate SIEM alerts end-to-end, generate structured incident writeups, and compress hours of analyst work into roughly a minute and a half. Scott's future-looking takeaway: as AI models evolve beyond “read-only” into potentially “read-write” systems that can update their foundational knowledge, the acceleration could be truly mind-blowing.This episode is essential listening for security leaders, enterprise operators, and automation teams trying to understand how agentic systems change not just productivity, but the entire security operating model.Chapters[00:01] Scott's Security Journey: Microsoft, Google, Coinbase, UiPath[01:33] Security Standards Work: From IPsec to Agentic AI Standards[04:08] What UiPath Does: Process Orchestration, RPA, and Enterprise Automation[06:28] RPA vs Agentic Automation: A Healthcare Billing Deduplication Example[09:17] The Agentic Stack: Canvas, Guardrails, and the AI Trust Layer[10:31] How LLMs Change Security: Data Controls, Access, and Governance[12:14] Internal Adoption at UiPath: AI Tooling by Persona (Legal, Finance, Engineering)[13:13] Code Velocity and Security: Agents Generating Code, Agents Verifying It[15:53] Two AI Security Worlds: Orchestration Platforms vs End-User Chat Interfaces[17:11] Securing End Users: Enterprise LLMs, Nudges, and Browser-Based Controls[19:07] Sovereign AI and Data Boundaries: Keeping Data in the Right Region[21:00] Over-Permissioning Meets Agents: Why AI Makes Old Problems Obvious Fast[22:21] The Next Wave: AI Transforming the Entire SDLC End-to-End[24:53] Security Pitfalls in Agentic SDLC: Misaligned Incentives and Permissions[26:02] UiPath's Agentic Threat Analyst: 60+ Agents, SIEM to Writeup Automation[30:07] What Changes for Humans: Faster “Time to Truth” and Higher-Leverage Work[32:09] Two-Word Future: “Mind Blowing” and Read/Write ModelsConnect with Scott RobertsLinkedIn: https://www.linkedin.com/in/scottroberts6/Connect with Boaz AshkenazyLinkedIn: https://www.linkedin.com/in/boazashkenazy/Email: info@shiftai.fm

Is AI security just "Cloud Security 2.0"? Toni De La Fuente, creator of the open-source tool Prowler, joins Ashish to explain why securing AI workloads requires a fundamentally different approach than traditional cloud infrastructure.We dive deep into the "Shared Responsibility Gap" emerging with managed AI services like AWS Bedrock and OpenAI. Toni spoke about the hidden dangers of default AI architectures, why you should never connect an MCP (Model Context Protocol) directly to a database.We discuss the new AI-driven SDLC, where tools like Claude Code can generate infrastructure but also create massive security blind spots if not monitored.Guest Socials -⁠ ⁠⁠⁠⁠⁠Toni's LinkedinPodcast 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) Who is Toni De La Fuente? (Creator of Prowler)(03:50) AI Security vs. Cloud Security: What's the Difference? (07:20) The Shared Responsibility Gap in AI Services (Bedrock, OpenAI) (11:30) The "Fifth Party" Risk: Managed AI Access (13:40) AI Architecture Best Practices: Never Connect MCP to DB Directly (16:40) Prowler's AI Pillars: Generating Dashboards & Detections (22:30) The New SDLC: Securing Code from Claude Code & Lovable (25:30) The "Magic" Trap: Why AI Doesn't Know Your Security Context (28:30) Top 3 Priorities for Security Leaders (Infra, LLM, Shadow AI) (30:40) Future Predictions: Why Predicting 12 Months Out is Impossible

Join Scott as he shows off CircuitPython running locally in the Zephyr native simulator and discusses how it provides a feedback loop for LLM agents. He'll also answer any questions folks have. Thanks to dcd for the timecodes: 0:00 Getting started 3:00 Hello everyone - welcome to deep dive 4:10 adafruit ESP32-S2 example microcomputer running circuitpython 5:32 using LLM agents to generate code 5:55 new monitor - mouse tiler 6:37 mouse tiler using absolute positioning 7:25 resumed pi session with generate_mousetiler_layouts.py 8:49 example how LLM's are game changing 9:19 update KWIN scripts settings 11:00 "My AI Adoption Journey" https://mitchellh.com/writing/my-ai-adoption-journey 15:00 How to test USB without the linux kernel 16:55 Testing is more important now that LLMs are in the loop 17:43 Low level USB IP - using Raspberry Pi to share mouse and keyboard over internet 18:48 USB OCD esp32p4-usbip $35 asked Codex to write code overnight to send USB over wifi 20:30 usbip-pyusb-test w/MNS 21:49 upgraded from $20 to $200 subscription ( only 14% used ) 23:00 S3 USB Host not supported yet 23:46 esp32-S3-USB-OTG https://docs.espressif.com/projects/esp-dev-kits/en/latest/esp32s3/esp32-s3-usb-otg/user_guide.html 25:04 ESP P4 has Ethernet 29:13 considering Octo probes could be accessible over the internet ( over tailscale ) 31:33 Gross PR with job server (build all boards - agent generated) 34:00 demo the TUI interface 38:07 chef analogy in https://www.avo.app/blog/from-pairing-to-leading 40:25 Keep PRs small! ( multiple branches ) 42:20 skip to the testing virtual desktop 43:10 using the zephyr simulator 44:50 edit settings.toml / using pi 47:50 testing to verify web workflow 49:25 web workflow test not working 50:20 pi: "figure out why web workflow not working" 52:07 look at tests/test_web_workflow.py 59:56 wrap back to "My AI aboption" 1:01:23 prioritize step 5 engineer the harnesses 1:03 Wrapping up - new channel #coding-agents-and-llms 1:05:48 out on the 6th ( 2 weeks from now ) Visit the Adafruit shop online - http://www.adafruit.com ----------------------------------------- LIVE CHAT IS HERE! http://adafru.it/discord Subscribe to Adafruit on YouTube: http://adafru.it/subscribe New tutorials on the Adafruit Learning System: http://learn.adafruit.com/ -----------------------------------------

How Gong Built a $7B AI Category: From "Conversation Intelligence" to the Revenue Operating SystemMost sales teams fly blind. They rely on "gut feel" and "art" rather than data and science. Eilon Reshef (Co-founder & CPO of Gong) realized this in 2015 and built a platform that captures the reality of every customer interaction to drive predictable growth.In this episode of Startup Project, Eilon breaks down the evolution of Gong, how they achieved 57% higher win rates for companies like PayPal and DocuSign, and why the "Revenue Graph" is the next frontier of enterprise AI.If you are a founder, a product leader, or a sales professional looking to understand how AI is actually transforming the enterprise, this deep dive is for you.What you'll learn in this episode:The Genesis of Gong: Why Eilon moved from a successful exit at WebCollage to solving the "black box" of sales conversations.The "Science" of Sales: How to move away from subjective CRM updates to hard data captured from video, email, and phone calls.The Revenue Graph: Why Gong's proprietary data model is more valuable than a generic LLM.Scaling to 5,000+ Customers: The tactical steps Gong took to achieve product-market fit in a crowded SaaS landscape.The Future of AI Agents: Why "Vibe Coding" and prosumer AI are just the beginning, and how the enterprise shift is happening now.Timestamps:0:00 - Intro: Meeting Eilon Reshef2:15 - The "Aha!" moment that led to Gong10:45 - Moving from transcription to "Revenue Intelligence"18:30 - How Gong achieves 57% higher win rates for customers25:50 - Building a proprietary AI layer on top of LLMs34:10 - The "Revenue Graph" explained42:15 - Why most enterprise AI implementations fail50:00 - Advice for founders building in the AI era54:14 - Closing thoughtsConnect with Eilon & Gong:Website: https://www.gong.io/Eilon's LinkedIn: https://www.linkedin.com/in/eilonreshef#Gong #AI #SalesTech #StartupGrowth #Entrepreneurship #RevenueIntelligence #SaaS #ProductMarketFit #EilonReshef #StartupProject

The PESO Model has been guiding smart communications strategies for over a decade, but the tactical landscape underneath it keeps shifting. In the latest evolution, Gini and her team have completely revamped the PESO Model Certification to address how AI and large language models are fundamentally changing visibility in 2026. In this episode, Chip interviews Gini about the newly updated certification and what’s changed in how organizations should think about paid, earned, shared, and owned media. The conversation centers on “visibility engineering”—the intersection of owned and earned media where LLMs are scraping information and making decisions about who appears in AI-generated answers. Gini explains why owned media remains the foundation (without content on your own properties, there’s nothing to demonstrate to journalists, creators, or LLMs what you’re about), but the recommended path has shifted from owned-then-earned-or-shared to a more deliberate owned-then-earned-then-shared-then-paid sequence. This evolution reflects how AI systems verify information by comparing what’s on your website against what credible third parties say about you. They also tackle the persistent “X is dead” headlines that plague the industry—whether it’s websites, PR, or press releases. Chip and Gini push back hard on the notion that websites are becoming irrelevant, pointing out that your owned content hub becomes more valuable in an AI-driven world, not less. It’s your source of truth, the fuel for custom AI assistants, and the foundation that persists even as social platforms come and go. The conversation covers practical questions about implementing PESO in smaller agencies, whether you need to be full-service to deliver on all four pillars, and how the certification meets communicators at different experience levels—from college students to seasoned professionals. If you’ve been treating PESO as just four columns of tactics rather than an operating system for communications, this episode clarifies what you’re missing. Key takeaways Gini Dietrich: “Owned is still the foundation because without your own thought leadership, your subject matter experts, your content, all of that, there’s nothing to demonstrate to a journalist, a creator, a newsletter author, a podcast host, what you’re about and how you’re different.” Chip Griffin: “In a world where you’re able to start customizing your own versions of LLMs for your internal or external audiences, huge value exists there. So having that central repository, I think is actually of increasing value today, not decreasing.” Gini Dietrich: “We are in a zero click world. And so how does that affect the work that we’re doing? It’s really how are we helping to inform humans, search engines, and LLMs so that we’re showing up no matter if it’s a human looking, if it’s Google surfacing information or if it’s an AI surfacing information.” Chip Griffin: “Having your content in a world where you’re able to start customizing your own versions of LLMs for your internal or external audiences, huge value exists there. That would not be possible without a thousand plus articles and videos because that is the fuel for that tool.” Turn ideas into action Audit where your owned content actually lives. Open a spreadsheet and list every place you’ve published content over the past two years—your website, Medium, Substack, LinkedIn articles, guest posts, anywhere. Mark which platforms you own versus rent. This awareness exercise reveals how vulnerable your content strategy is to platform changes and algorithm shifts. Map one content piece through all four PESO pillars. Take your next webinar, speaking engagement, or major thought leadership piece and plan the full PESO path before you execute: owned content on your site summarizing key insights, pitching earned media opportunities based on those insights, creating social distribution that doesn’t just promote but educates, and identifying where paid amplification makes strategic sense. This forces you to think about PESO as an integrated operating system rather than disconnected tactics. Dive deeper into the PESO Model. Visit spinsucks.com/peso-model-certification to learn more about the newly updated certification program. Whether you’re looking to formalize your team’s approach to integrated communications or simply understand how the model has evolved for the AI era, the certification provides a structured path from foundational concepts through practical implementation. Resources For more on the PESO model, visit the Spin Sucks website Related Agencies need the PESO model now more than ever Has the PESO Model become a necessity for modern agencies? How PR agencies can use the PESO Model to improve client retention How to allocate your client's PESO budget Wake up or get left behind: AI is forcing your hand View Transcript The following is a computer-generated transcript. Please listen to the audio to confirm accuracy. Chip Griffin: Hello, and welcome to another episode of the Agency Leadership Podcast. I’m Chip Griffin. Gini Dietrich: And I’m Gini Dietrich. Chip Griffin: And Gini, I, I’ve heard that you might be involved with this thing, I think it’s called the PESO Model. Gini Dietrich: Oh, maybe. Chip Griffin: You may you use that, right? That’s, yeah. Just you found it and you said this should, this is something we should use. Gini Dietrich: Yeah. Something I just found and thought we should use it. Yeah. Chip Griffin: Yeah. Yeah, no, in all fairness, you are in fact the inventor of the PESO model, which is widely used throughout the PR and communications world, and it has been evolving with the times as we all should be. And so I, I think we have some, some new news that you’ve been sharing around the PESO model. Gini Dietrich: Oh, well, according to a couple of people on the internet, it has not evolved at all because they are not able to use Google or AI to say, has the PESO model evolved since 2014? Perhaps. It has. And you know, all of last year I spent a good amount of time, especially on the blog and the Spin Sucks podcast, talking about visibility engineering, which is where owned and earned media meet because that’s where the LLMs are getting their information, right. We’re finding more and more that they’re scrubbing websites and then they’re comparing that to earned media, to the things that media not, and not just traditional media, newsletters, podcasts, things like that, that they’re saying about the brand and looking to see if they match. And if they do, then they’re appearing. You’re, you start to appear in AI answers. So I spent a good amount of time last year exploring that and understanding that and, you know, using the blog and the podcast as my sandbox to learn more about it and teach the industry about it and understand what was happening. As part of that, I said, okay, it’s time to do a big refresh of the certification. Because we did the certification in 2020 and then we did a small update to it in 2024. And this one is a completely revamped certification that shows you how exactly AI is… how exactly you’re showing up in AI answers and doing that via the PESO model. So we start with owned, we go to earned, then we use shared and paid. There’s integration and measurement and it brings it all together. So I’m actually, I said to my team, not to brag, but this is really good. It’s a really, really good course. And we hired, last March I hired a chief learning officer who has helped me build it into something that’s more effective for an adult learner. So it’s really specific to, you know, you can get the work done while you’re also a working professional. So she has done a really nice job of bringing that element into it. It has AI prompts so that you can use the PESO AI that we built to help you do the work. And it’s, it’s pretty good. I’m, I’m really proud of it. I’m really proud of the work we did. Chip Griffin: Well, I mean, it really is something that, that fuels most communication thinking in smart organizations today, whether that’s agency side, client side, that sort of thing. Now it’s not always as well understood it should be. Some people just throw the term around. A little bit willy-nilly. Yes. You know, without really thinking it through. Of course there are other people who claim that it’s also their invention, which is, you know, but we’re not gonna go down that path ’cause we’re staying positive today, Gini. Gini Dietrich: Yes, yes. We’re gonna stay positive. Positive, yes. Chip Griffin: But I think to, you know, to me, one of the things that, when I look at the PESO model, I think is, you know, it’s great because it is an overall set of principles and framework that is effectively timeless when it comes to communications. And then it’s the implementation side of it. The tactical side of it. That’s the piece that needs to evolve. The, I mean, the four letters are still the same. It’s not like you, right? Yes. The evolution has not been to change PESO to something else. Gini Dietrich: Nope. Chip Griffin: It, it’s really just saying. Okay. All of these different components, the paid, earned, shared, and owned have evolved over the last 10 or 15 years. Yeah. And so how we implement it needs to adapt to that. Gini Dietrich: Yeah. It’s very much, I mean, when we did it in 2020, it was very much like how, how you’re using content marketing really to inform your contributed content through earned and then sharing that link through, through social and then putting some money behind it to boost it. And that was, you know, that was six years ago, and it worked back then, right? It’s still, social still worked from the perspective that you could post a link and people would follow that path back to your website. Well, people don’t do that anymore. You know, we are in a zero click world. And so how do, how does that affect the work that we’re doing? So, you’re right, the paid, earned, shared, and owned doesn’t change. That model stays the same. It’s the pieces on top that, that have evolved. And so now it’s really how are we helping to inform humans, search engines, and LLMs so that we’re showing up. No matter if it’s a human looking, if it’s Google surfacing information or if it’s an AI surfacing information, we show up no matter what. And it’s really, that’s what it’s really about is how do you engineer that visibility? How do you make sure that you’re showing up in the right places at the right time to the right people? Chip Griffin: And so if you’re, if you’re thinking about leaning into the PESO model for your communications needs. You know, where should you be starting today? Is it owned? Is it social? Is it, you know, how, has it changed? If at all from that standpoint over the last decade? Gini Dietrich: Owned is still the foundation because without anything, without your own thought leadership, your subject matter experts, your content, all of that, there’s nothing to demonstrate to a journalist, a creator, a newsletter author, a podcast host, what you’re about and how you’re different. So that’s the foundation. There’s nothing do than to just create that distribution layer through shared, and there’s certainly nothing to amplify through paid. So that’s always been the foundation. There are of course exceptions if you’re selling widgets or your, you have an Amazon store or something like that, then I would probably start with paid, but that’s the exception to the rule. For the most part, most organizations need to start with owned. And we used to say that then you could go to earned or shared. Depending on your goals. Now we’re saying actually the best path for engineering that visibility is owned, then earned because you need that credibility, so the LLMs can cite that information. Then you build your distribution layer, and then you amplify your work. Chip Griffin: So I, think what I’m hearing you say is that websites are not dead despite all of these, you know, headlines that you like to see people’s, Gini Dietrich: No, they are not. Chip Griffin: The, the rise of LLM, websites are dead. You’re not even gonna need a website in five years. Gini Dietrich: No, we still need a website because otherwise the LLMs don’t have anywhere to get the information about you. Humans don’t have any, I mean, we still go to websites. We might not go, you know, a direct click like we used to, but we still go to websites to get information. So yeah, you still need a website. I hate the, such and such is dead. The PR, there’s one that PR is dead right now. Like PR is not dead. Come on. You can’t do, you’re not going to show up in AI answers if without PR. So PR is not dead. Chip Griffin: No, the X is dead has always been one of my pet peeves when it comes to, I mean, that, that really is something that, that took off during the start of the social media era. Yeah. Whether it was the press release is dead. This is dead, whatever. I mean, and, you know. Just, it’s not true. I mean, we, you know, I always used to say back 20 years ago, you know, people used to say that radio was dead. Radio is still very much around, and radio is still around in certain forms. I mean, when I’m driving around, I listen to radio. Yes. Is it terrestrial radio? No, it’s satellite radio. Gini Dietrich: Right. Chip Griffin: But guess what? It’s still radio. Gini Dietrich: It’s still radio. Yep. Chip Griffin: Right. Podcasts are effectively radio. Transmitted in a different fashion. Yep. And so, you know, I think that the people need to understand that the underlying technology may evolve, some of the tools will evolve, but Gini Dietrich: absolutely Chip Griffin: the, principles and concepts will largely remain the same. Doesn’t mean that everything stays. Yeah, certainly some things, you know, do go away, or become so small that they’re irrelevant, but you know, I think we need to be careful about those things. And, to me, with a website, to me, the other value is it still is a great place to be the central repository of all your information as all of these things change around you. I mean, if, for the last 10 or 15 years you’ve been using your website as your content hub and housing at least your most important, most valuable stuff there, it doesn’t matter whether medium or substack comes or goes. It doesn’t matter whether people move from X to LinkedIn to whatever. Yep. You still have a source of truth for your own information, which becomes even more valuable in the world of AI and LLMs. Gini Dietrich: That’s exactly right. I mean, we, have preached for years, we’ve all preached for years that you should not build an audience or content on rented land because to exactly your point, the rented land goes away. X has become something that nobody wants to hang out on. We’ve moved to LinkedIn. Lots of people have moved to Substack. So, those pieces will change. So don’t, I think that theory, philosophy stays the same. Because you have, you are building something that you own, that you control, and allows you to control that narrative and be, tell the story the way you want to, and then you rent that out to other places versus building on rented land where it will go away. Chip Griffin: Well, and I think that there are a lot of avenues that are opening up to organizations with, you know, particularly those that have more content already, but also by building it up. And I think in particular of the AI assistant I built on the SAGA website. Mm-hmm. Yep. That would not be possible without a thousand plus articles and videos and that kind of stuff because that is the fuel for that tool. Yep. And, and if I was trying to do it based off of, see what you can find that I’ve posted on LinkedIn or Twitter or things over the years, and it’s just not gonna work. And so having that in a world where you’re able to start customizing your own versions of LLMs for your internal or external audiences, huge value exists there. So having that central repository, I think is actually of increasing value today, not decreasing. Gini Dietrich: Yeah, that’s actually a really good point. I was talking to a client last week and she said that one of the goals for 2026 is they have 17 different brands. So each brand has its own chief executive. And what she has, what she wants, the comms team for each of those brands to do is build an AI agent that helps them with that CEO’s voice. And they can’t do that without content. They can’t do it without the executives’ speeches, webinars, podcasts, appearances, media relations, like they have to have all of that content, blog posts that they’ve written or articles that they’ve written for the website. They have to have that to be able to feed that and train the AI. So without it, they don’t have any, to your point, fuel that will allow them to do that. So 100% that is accurate. Chip Griffin: So as, we’re thinking about implementing PESO properly, so not just, I heard the term, it sounds cool. I made a list of four columns of each, and I just started just chucking stuff in there. Gini Dietrich: Mm-hmm. Chip Griffin: I mean, how do I go about learning it the right way? And I’m, you know, we’re not turning this into a QVC Gini Dietrich: Are you throwing me a softball? Chip Griffin: you know, show here. But at the same time, I, think it is valuable for people to understand what is out there in a more formal sense, to understand and, adopt the process for their own organization. Gini Dietrich: I mean, obviously the PESO model certification is the place to get the information because one of the, one of the things we see is exactly what you said, that people create their four columns and they say, okay, well we’ve got some content and we’re doing some media relations, and we’re throwing that on social. And all right, we’ll put some, budget behind some of our organic social, and we’ve got the PESO model. And that’s, not the PESO model, that’s a list of tactics. So what the certification does is it walks you through exactly. There’s this, a scientific layer to it. It walks you through that scientific layer that allows you to embed an operating system, that let that foundation of your work so that as things evolve and the industry changes and your business goals change, you’re able to change the tactics on top of it. We also hear, well, gosh, my, you know, my clients can’t afford to do a full PESO program, so what should I do? And in fact, they can afford it. You’re just thinking about it as this huge, overwhelming thing. And so the certification walks you through if you’re a solopreneur or a small agency, that walks you through if you’re a midsize, and it walks you through if you’re a large corporation or an enterprise organization. And I will say for small organizations, which are most of our listeners. It’s really about how do you take one piece of content and repurpose it. So let’s say that you do a webinar. How do you take that webinar and create some content around it that, from what the webinar was, not promoting it, not trying to get registrations, but saying, okay, here’s what we learned in the webinar. So we’re gonna create some how-to or thoughtful content for that. And then we’re gonna take pieces of the webinar and we’re gonna break it down for social posts. And then yeah, we’re gonna put some money behind some of it. And we’re also gonna go to some of our trade media and we’re gonna say, Hey, listen, our subject matter expert or our chief executive just did this webinar and here’s what they talked about. Are you interested in some contributed content? So it allows you to do that in a really interesting, effective way without you having to spend hundreds of thousands of dollars or have a large team. You can do it without a lot of resources. I mean I built the PESO model framework for my agency and we were not, at the time, a big agency. Mm-hmm. So that’s what it was built for, is to make it so that we could do more with less and do more with less resources and, less time and less people and less budget and all the things. So it is definitely, definitely feasible. So that’s what it teaches you how to do. Chip Griffin: So I, you know, I think one of the other concerns that, some particularly smaller agencies have when it comes to PESO is not just the, clients and their budget, but, their own capabilities and, you know, so is it realistic for a small agency to be able to, you know, deliver? We, we talk all the time about being careful about being a full service agency. Yep. But to, implement PESO, do you have to be a full service agency? Gini Dietrich: You do not. That’s the other thing that the certification walks you through is if you have the capability yourself in house. Or you yourself can do it. Then here’s how you do it. If you are building it for an external team or an external agency, here’s how you do it. If the client has a team that can do it, here’s what you’re going to do to build the strategy and the creative brief, and then you’ll hand it off. But here’s what is expected for. Here’s, what’s expected of you to deliver, and here’s what the expectation is for the output from the client team or the agency team, whatever happens to be. So it has those three paths depending on where you are. So yeah, that’s a really good point. It doesn’t the, certification expects you to, build the plan and the strategy, and then based on where you are, it meets you where you are. So if, you have a team that you can execute or that you can delegate it to, great. If your client has a team you can delegate it to great. But it meets you where you are so that you don’t have to be the expert, you don’t have to be the strategist, you don’t have to be the influencer, but you do have to build the plan and the strategic path to be able to help the team get there. Chip Griffin: Mm-hmm. Um, and I mean, let’s talk through some of the logistics around the certification. I mean, how long does it take to get certified? Is this, you know, I, do a weekend course and I’m done. Is it an ongoing process? Is it, you know, is it the equivalent of a master’s degree? I gonna spend two years with, you know, countless hours? What exactly does it look like? Gini Dietrich: It’s built to be done in eight weeks, but I will tell you that most working professionals do not do it that fast. I would say most working professionals do it between 10 and 12. Each module is, so you have the intro earned or owned, earned, shared, paid, integration, measurement, and then the operating system and how to embed that. So it’s eight modules and each module has between 6 and 12 lessons, and each lesson is like 8 to 10 minutes. So, you know, you’re looking at an hour to an hour and a half of learning of content and then you have the exercises for each lesson. So I would venture to guess it’s, you know, if you use the AI prompts effectively, that are in there, it’s between two to five hours a week probably. Chip Griffin: And, who is the certification best for? Is it someone who’s got, you know, prior experience, is this, Hey, I’m fresh outta college and I want to have this so I can use it to, you know, improve my, my job prospects. You know, what, kind of experience are they expected to have, or knowledge are they expected to have coming in? Gini Dietrich: It’s, we built it for any level of expertise. The interesting thing about it, of course, if you have more experience, it’s easier for you to grasp the concepts and implement it quickly. But we also use the certification in a hundred plus universities and the kids, the students go through it. So we find that they… It’s different for them because they have to use a fake business where you can use your own business or you can use your client’s business, right? They have to kind of create the business as they go. But it’s really fun to see what kinds of things come out of that. So it’s built for every level of expertise. It’s a different way of thinking about communications. So it’s not like you have to have 20 years of experience or only a year of experience. It’s because it’s teaching you something new. Chip Griffin: Gotcha. And is the, are the certifications only at the individual level? Are there agency certification programs? What exists in that frame? Gini Dietrich: Yeah, we’ve, that, that’s a great question that we evolved too. So it used to be, it was individual based and now we’ve built it so that you can put a team through it, you can put the whole agency through it. The certification itself goes with the individual because it comes through Syracuse University. So it is, so if you have a team member that you wanna put through it, if they leave the certification goes with them. So you cannot say that you do the PESO model anymore if they leave. So we always recommend, I mean, you know, I’m an agency owner, so I’d love to see the agency owner themselves go through it, but I also know that that’s not always doable. So, but if you want the certification to stay with your agency, that’s the way to do it. Chip Griffin: Mm-hmm. And it, you know, I guess as, we’re winding up here, you know, where do you see the, PESO model headed in, the years, you know, in front of us? I would assume it will continue to evolve. Does your crystal ball tell you anything about, you know, what that evolution will look like? Gini Dietrich: It will continue to evolve. I have not looked into my crystal ball yet because I’ve been so heads down deep into developing the content for this that I haven’t been able to forward think yet, but I’m very much looking forward to being able to go back to my regular job and, start to think about the future, but I’m not there yet. Chip Griffin: I, I, guess that’s fair. I guess asking you for the, next version before this version is even fully out in the wild may, Gini Dietrich: I’ve literally been like blinders on, heads down, creating all of this content. Chip Griffin: I had to try at least, you know, see if I could get the inside a scoop on where the industry is headed so that I can… Gini Dietrich: Ask me in a month. Chip Griffin: I can get there before everybody else, or at least before everybody else accept you. Alright. If someone, wants to learn more about the PESO model or the certification or any of that kind of stuff, where’s, the best place for them to go for that? Gini Dietrich: I feel like we just did an interview. Chip Griffin: Well, that, that was not the intent going, but it made the most sense to me. And I, you know, me, I, follow the thread wherever it feels like it goes. That’s fair. Some of these were questions I actually didn’t know the answer to, so I thought I would ask them. Gini Dietrich: Yeah. Alright. spinsucks.com. There’s a PESO model certification page. I think it’s actually PESO-model-certification. Chip Griffin: You love your hyphens on that website. Gini Dietrich: I don’t know why it’s that way. That’s just what they do. Chip Griffin: Oh, well. Gini Dietrich: Ask our web firm. Chip Griffin: I’m, sure people can end up finding it. Gini Dietrich: PESO model certification. Spin sucks.com. Chip Griffin: There you go. Excellent. Well, I, think this was good information and I think we, you know, we do talk a lot about the importance of, you know, agencies continuing to adapt. Particularly in, in this age of AI. And, if we are standing still, you know, we are gonna lose our jobs to AI and the other enhancements and improvements that are out there. I think this is one of many ways that you can, make sure that you are not getting left behind and, so, certainly something that most agencies should be at the very least learning more about, if not actually directly implementing within their businesses. Gini Dietrich: Yep. Yeah, and, like I said, it has AI baked in, so if you’re still on the fence about AI, it’s a good way to dip your toes in the water. Chip Griffin: And if you’re still on the fence on AI, why? Gini Dietrich: It’s so much fun! Chip Griffin: It really is. It can be a time suck at times, but it’s, yeah. It’s also fun and, frankly useful. I mean, I think that’s the… But anyway, that when this is not an AI show, this is a PESO show. Gini Dietrich: Right. So, right, right. Chip Griffin: We, will come back and bash you on AI again in the future. Not, you, but you the listener. You the listener. Gini Dietrich: Yeah. Chip Griffin: Alright. With that we’ll wrap up this episode of the Agency Leadership Podcast. I’m Chip Griffin. Gini Dietrich: I’m Gini Dietrich. Chip Griffin: And it depends.

How AI Agents are Disrupting the AdTech Landscape Semantic content classification driven by AI agents is currently transforming digital advertising and B2B content monetization as we know it. When leveraged the right way, marketers can classify B2B content into actionable signals and find the most relevant content across the open web. This shift toward AI-native advertising allows for a more sophisticated approach to targeting that moves beyond traditional cookies. So, how can brands strategically implement these tools to generate impactful results, and what does the rise of autonomous agents mean for the future of your digital marketing strategy? That's why we're talking to Brendan Norman (Co-Founder and CEO, Classify), who shares his expertise and experience on how AI agents are disrupting the AdTech landscape. During our conversation, Brendan discussed the evolution of digital advertising and the critical integration of AI and cloud-based tools to automate manual tasks and improve campaign optimization. He also elaborated on the massive shift from human-centric to agent-centric traffic, predicting that agent traffic will surpass human traffic within 18-24 months. Brendan also explained why he believes that the future belongs to marketers who can blend audience and contextual signals to monetize human and agent attention. He highlighted how new AI-native tools are democratizing advanced ad tech, significantly reducing costs and improving efficiency for large and small advertisers. https://youtu.be/yVobWZTmwco Topics discussed in episode: [03:01] Beyond Keywords: How semantic understanding allows advertisers to target the nuance of a page (like “snow removal” vs. just “winter”) rather than broad categories.  [06:46] Optimizing for AI Agents: Why “Generative Engine Optimization” (GEO) complements traditional SEO, and how brands must prepare for agents retrieving information instead of humans.  [12:34] The Shift in Web Traffic: The prediction that agent traffic will surpass human traffic on the web in the next 6 to 24 months.  [15:50] The Power of Context + Audience: Why the best advertising strategy combines who the user is (audience) with what they are consuming in the moment (context).  [20:47] Democratizing Ad Tech: How AI agents and new frameworks will allow smaller brands with smaller budgets to access sophisticated programmatic advertising tools.  [26:54] High-Fidelity Curation at Scale: How AI reduces the cost of processing massive data sets, making real-time optimization and curation accessible and sustainable.  [33:44] The “Middleman Tax”: A look at the inefficiency of current ad tech where only 35 cents of every dollar reaches the publisher, and how AI can fix this.  Companies and links mentioned: Brendan Norman on LinkedIn  Classify  Bluefish AI Agentic Advertising Org  IAB Tech Lab Transcript Brendan Norman – Classify, Christian Klepp Brendan Norman – Classify  00:00 I think overall, jobs will change. I think that people will have to spend a lot less time doing a lot of the manual, rote tasks that they’re doing today. You know, kind of in parallel with what we’re seeing in terms of vibe coding and people’s ability to build product really quickly, design new web pages really quickly, like get ship things out quickly. I think a lot of the infrastructure layer tools, or just call them like, like, chatGPT style, cloud based tools, LLMs (Large Language Models), we’ll see a lot deeper integration into existing advertising product. And what that does is it helps democratize the whole ecosystem. So I think it frees up people’s time, you know, to not have to do a lot of the basic administrative, you know, reporting, manual, campaign, optimization type stuff, and it will help service a lot better insights. Ultimately, I think the industry grows, and I think it scales even faster and cautiously, optimistically. I think that we, we will have back to building on the curation piece, and, you know, the advertiser, outcomes piece, publisher monetization piece, user experience piece, I think that all those things will increase. Christian Klepp  01:07 When done the right way and leveraging the right approach and technology, you can classify B2B content into actionable insights and find the most similar content across the open web. So how can this be done the right way, and what role do B2B Marketers play? Welcome to this episode of the B2B Marketers in the Mission podcast, and I’m your host, Christian Klepp. Today, I’ll be talking to Brendan Norman about this. He’s the Co-Founder and CEO of Classify, a software that organizes the world’s digital content, making a privacy, safe, searchable and monetizable. Tune in to find out more about what this B2B Marketers Mission is, and off we go. I’m gonna say Mr. Brendan Norman, welcome to the show. Brendan Norman – Classify  01:49 Thanks for having me, Christian. Christian Klepp  01:51 Great to have you on. I’m really looking for this conversation because, man, like you know, in our previous discussion, besides talking about snow and bad weather, we did have, we did have we did have some interesting discussions around, I’m going to say, AI machine learning, and how that all has some kind of like strong correlation to content. So let’s just dive in. I’m going to start with the first question here. So you’re on a mission to help publishers increase monetization potential and advertisers target the most relevant, curated inventory. So for this conversation, I’m going to focus on the following topic, and we can unpack it from there. So how B2B brands can optimize their own content. And you know, let’s be honest. Brendan, who the heck doesn’t want to do that, right? So your company classify, if I remember correctly. It’s a software that organizes the world’s digital content, making it privacy, safe, searchable and monetizable. So here’s the two-pronged question I’m happy to repeat. So first one is, walk us through how your software does that and B, how does this approach benefit? B2B companies looking to optimize their own content? Brendan Norman – Classify  03:01 Historically, how a lot of content gets categorized, classified, organized, it’s fairly unsophisticated, and it’s been fairly unsophisticated for a long time, just because, you know, the technology is difficult to do, and we haven’t really had the foundational ability to understand it in a way like a human understands it until fairly recently, and do it at Deep scale. So good analogy for this question is like, if you were having a we were having a conversation just a minute ago about the snow, you know, happening in Canada, and how cold it was and how much snow you got, and, you know, also around the fact that, like you had to shovel your driveway, you have a snow blower you were putting the snow. There’s a lot of different nuance to that conversation. I as a human, and most humans, are able to interpret all of that nuance and kind of positively negatively, understand that there’s a snow blower involved in that snow blower was used to remove the snow historically that conversation, you know, if it was just a blob of text, or if it were a web page, the the basic technology to understand it would have reduced it down to a category like snow or maybe winter, and that’s it, and that’s all the targeting that would have happened to that page. So our conversation, you know, gets transcribed. It gets put on a blog, or it gets put on a news site. The only thing that a machine could understand about it was, you know, snow and then potentially a keyword, tagged snow blower. And that’s all so we took a very different one. One of the reasons why you know that that makes it challenging for advertisers and also for publishers. If you’re the publisher of that content, you’re not able to help advertisers really understand the nuance to like, what are we talking about here? Because maybe an advertiser wants to sell snow blowers for that specific site. Maybe they’re looking to sell ski and since we were talking about removing snow from a driveway, probably not the best application to go sell skis on. What is helpful is to deeply understand all the nuance to like we were talking about a driveway. We were talking about removing snow from that driveway. So we invented, you know, a much better, more sophisticated way to scrape content, classify it according to all of the different, you know, nuances semantic understanding much more like a human would, and then embed all of those different, you know, semantic understandings into, you know, this, this, this file, and then we organize that in a way that makes it searchable and kind of understands all the relationships very quickly. And what that does is it helps advertisers, like if you know, I’m Honda selling snow blowers, which they make, arguably the best snow blower in the market, if they’re looking to reach people that are talking about snow removal from the driveway, they can very quickly see the list of all the different URLs across the internet, and they can build, you know, a deal ID, or they can build a targeting, contextual targeting segment to specifically pinpoint those very specific web pages. And that’s kind of how the technology works, and then also, also why it’s relevant to advertisers. Christian Klepp  06:21 Thanks so much for sharing that Brendan that definitely helps us give, you know, some perspective into, like, what your software does. And you know, just, I’m asking you this from, from somebody who probably has learned to write one or two lines of code, and that’s as far as my dev skills go. But like, how, how is your software different from like GEO (Generative Engine Optimization), or is there some kind of overlap? Brendan Norman – Classify  06:46 It’s fairly complementary. I mean, the problem that GEO, you know, is trying to solve, and we’ve got good friends, advisors, you know, like at Blue Fish AI and like, a really cool company, Andre, I worked with him at live rail. He was the co-founder back then, before we got acquired by Facebook, you know. And I think that the problem that they’re trying to solve is going back to that it was just stay on Honda snowblowers. They’re trying to help Honda understand how they’re represented inside of, inside of an LLM or inside of a chat bot. And what they also do is they help these companies restructure their pages for, you know, better representation inside of the other end of like a chatGPT or a cloud answer. So it is kind of SEO (Search Engine Optimization), but for the generative world where we sit on is kind of on a different side of that. It’s very complimentary, though, and we’re deeply understanding content at scale, and that’s helping, you know, the advertiser understand where to position their ad. We’re also just, you know, very quickly, moving into this new space of, traditionally, advertising technology is focused on a human going to a web page, reading that content, reading the article, watching a video, you know, whatever that content looks like, and then helping the right advertisers show up in a contextually relevant way, so that the human will click on that ad, and they’ll go to another web page, they’ll buy the thing, whatever somebody wants to sell. A very recent development, so back up a year or so, you know, chatGPT Claude when they’re out and their agents and their bots are scraping like going out to the web and they’re retrieving information. They’re doing it to train their models to make their models better at answering questions. But now, you know, fast forward to today. They’re actually spending more time just going to content and then using that content to answer a specific question. So like, what’s the best recipe for, you know, creating soft shell craps. It’ll query a couple different web pages. It’ll find that, it’ll retrieve that information and bring it back that that is not being monetized today. And there’s a really interesting thing that we’re, you know, we’re starting to work on, which is monetizing the attention of an agent. And, you know, it’s, there’s a lot to figure out, but it’s kind of like the early days of a web browser, and like early days of search, when humans would go, you know, to a search engine, they would pop in some keywords, or, like, right out of search, and then, you know, Google would look at their entire index of the web, which was an algorithm that was weighted based on the number of different contextual relevancy plus the number of connections between web pages. So a web page that I might have published in geocities.com that nobody else would link to, Christian Klepp  09:50 wow, GeoCities like… Brendan Norman – Classify  09:54 Throwing way back remember the days of like writing like HTML and you know, creating that, you know, looping in some type of image because nobody else had linked to that, like personalized page that you built, it would never get shown up. And, you know, the top 20 or 30 or probably even couple 1000, or maybe even 100,000 search results. So their algorithm was about contextual relevancy, plus the number of links that other pages that had to your page. And then they started to include advertising in that. So early days of ads in search were literally anything, you know, it’s any advertiser that wanted to advertise to you, and they were just kind of choosing the highest price, trying to figure out, you know, how do we make money? And then it evolved into much more contextually relevant ads and sponsored post or sponsored advertisements. So now you know, if you’re searching for, like, what’s the best, you know, LLM or chat bot, you’re probably going to see a sponsored ad from, you know, Claude and Perplexity and chatGPT. Now you’re also going to see the search results underneath those. What’s changing about that kind of rapidly is how we’re influencing because humans are spending less time going there and doing that, and also within Google, Gemini is also surfacing some AI summary quickly and kind of superseding that, creating a chatGPT experience inside of Google, which is a brilliant way to do it also. But a lot of human interaction with the web now is humans going to chatGPT going to cloud asking questions and kind of treating it like we used to treat search back in the day. So influencing that, influencing that agent, going out to the web and sitting in between. That is another really interesting way that you can help an advertiser tell that story, not necessarily to a human but to the agent who’s retrieving the information and then bringing it back to the human, Christian Klepp  11:56 Right, right, right? And if we’re talking about content, it’s, you know, doing it in such a way that the content shows up in the AI search. Brendan Norman – Classify  12:04 Exactly. Christian Klepp  12:05 Because everybody, everybody’s got those now, right, like Google or Bing, or whatever, they’ve got the, they’ve got the AI summary at the at the very top of the page, right when you, when you, when you key in something. Brendan Norman – Classify  12:17 Yeah. Christian Klepp  12:18 Okay, fantastic. I’m gonna move us on to the next question about because we’re on the topic of optimizing content. So what are some of the key pitfalls that like B2B Marketers and their content teams? What should they be mindful of, and what should they be doing instead? Brendan Norman – Classify  12:34 That would be actually a better question for some of the GEO companies and something like more SEO focused companies about how to specifically optimize like your content. It’s a great question. I haven’t spent as much time, you know, deeply thinking through that. And the problem that we’re trying to solve is more of, you know, at scale, what is the semantic understanding of like, how somebody has built their page and or construct the video, as opposed to advising them on what they should do? You know, to think about it in a way that’s either more engaging. I would pivot that question more to the Geo and SEO focused folks, yeah, but super high level. I mean realizing that now web has two primary users of traffic. There’s humans who are bouncing or reading a, you know, web page or watching a video. But there’s also agents. And now the scale is like, changing very, very quickly. So you know, in the next year, two years, everybody will have lots of agents, kind of doing things on the back end for them. And, you know, we believe that, you know, in the next what, 6,12,18,24 months, Agent traffic will surpass human traffic on the web. So realizing that there’s these kind of two layers that one, humans see a web page and nice pretty pictures, and, you know, they see the layout great, but also having a web page that’s optimized in HTML, markdown, JSON, in ways that agents consume that, and then also knowing the different types of agents. So the cool thing that we’re building right now, in addition to this content graph of all the content, which is effectively like a understanding all the context between the content. It’s a mouthful, an agent graph that helps to inform this is an agent coming to my site. So in a lot of ways, it’s very similar to the folks who over the last decade or so, have built these identity graphs or audience graphs, and they know that like you, Christian versus me, Brendan, they’ve got some profiling on us. They understand our search history, our retargeting, our purchase intent, a lot of things that they’re appending to like you as a specific profile or an IP address. The rapid evolution of all this is mapping out the land. Landscape of different agents, where they come from, and then the personalization of these agents, and basically applying a lot of the similar logic that we’ve used for identity graphs and for audience graphs towards agents to help understand, how do you modify the content on the back end that humans never see, so that when they’re retrieving information, interacting with the content they’re doing it, you’re presenting in a really thoughtful way that drives like the answers and the results that you want to Christian Klepp  15:33 right, right? No, absolutely, absolutely. And in our previous conversation, you talked a little bit about contextual versus audience targeting. So and I mean, I’ve asked you this back then, but do you think one is better than the other, or do you think that they can work together? Brendan Norman – Classify  15:50 They should absolutely work together. Christian Klepp  15:52 And why? Brendan Norman – Classify  15:54 The reason, the reason is, you know, knowing who you are is a very important piece to the puzzle. Like, and if you even take a step back, like, what’s the whole point of advertising? Like, the whole point of advertising is storytelling, so that a brand or a service or a company can help market their brand service to the right person they’re trying to sell them something. The cool thing about the internet is we all now have this, you know, basic shared awareness that, like, there are certain things that are paid for on the internet, certain types of content that are gated. I might buy a subscription to The Economist, you know, I pay Claude a certain amount of money, a lot to be able to use it, you know, a lot and chatGPT, and then a lot of the web is free. Facebook is free, Tiktok is free, Instagram is free, LinkedIn is free. But the economics, it’s very expensive to run these businesses, so they have to, you know, support it through advertising. Ideally, you know, there’s a couple of ways to think about it, and there’s one camp of people on the internet who think that advertising is a necessary evil or a last resort, you know, we just cram it in there and make some money. There’s another camper of folks who actually think that it can be additive to the experience. And one of the reasons why, you know, it’s kind of a meme, and you always hear people talking about, you know, I didn’t need this thing, but I saw an ad for it on Instagram, and just had to buy it because it was really cool. The reason why that exists is that their advertising is phenomenal, and the targeting and optimization is phenomenal. And why it’s phenomenal on the back end is it knows a lot about you know me, who I am, what I’m interested in, based on my history, what I’ve been engaging with, where I’m spending time, you know, what I’m looking at, but it also knows specifically when I’m looking at that thing, you know, it might have a framework of saying, Brendan, really, you know, likes these types of skis, you know, he’s interested in, You know, a couple other, couple other interesting products, but the best time to serve each one of those products might be different, and it’s different depending on what I’m looking at, what I’m thinking about in that exact moment. And to kind of align these, these different graphs, graphs of intent, contextual understanding, and then audience, you know, the best time to serve me an ad for a new pair of skis is when I’m reading an article about skiing or something about the mountains. You know, it’s not necessarily when I’m reading about the Warriors, because I’m not really thinking about skiing when I’m reading about basketball. So to your point, the most effective ads are when you’re combining those two sets. It’s great for the advertiser, because I’m much more likely to click on it and go check out the skis. It’s also giving me a better experience, because it feels more native to the overall content that I’m reading. And that’s why it’s so important. It shouldn’t be an afterthought or a necessary evil or a last resort. It should be something that is intentionally thought about the entire design, because it can, it can actually be a cool experience. Christian Klepp  19:06 Absolutely, absolutely. I mean, you know, you’re talking to somebody that started his career in the in the advertising industry, so, yeah, I’ve heard that one before, and what you’ve been describing in the past couple of minutes sounds to me a little bit like time of day marketing too, right? Because you’re you know, are you the had a guest on, like, a year ago who talked about this? Right? Is, is Brendan, the same guy at eight in the morning and one one in the afternoon and seven in the evening? Right? There’s different different times of the day, different mindset, different motivation, different reason for being on your device or looking at, looking at specific type of content, right? But it is interesting, right? And it’s interesting and sometimes a little bit scary, how, um, how quickly the algorithm picks, picks this stuff up, right? Like, for example, last year, I was researching a lot on Japan, because we went there, right? Family trip and whatnot. And. And that’s what I kept seeing on Instagram, right? Like, because I was looking up specific temples and whatnot and and today I got another push. Like, would you like to invest in a temple that’s an on island in the Sea of Japan, right? Brendan Norman – Classify  20:12 Like, sorry, did you invest? Christian Klepp  20:17 No, I did not. But it was just, it was just funny that I got that ad right, like, it’s, like, Okay, interesting, but like, it’s so like it not, was not on my radar at all, right, Brendan Norman – Classify  20:29 Yeah, Christian Klepp  20:29 Okay, great. From your experience, and you talked a little bit about it now in the past couple of minutes, but like, from your experience, how can leveraging AI agents improve efficiency and save marketing leaders time? Brendan Norman – Classify  20:47 Ooh, there’s a couple different ways to think about that. So you know, part of it is this new agentic framework for how existing tools, you know, advertising and marketing tools, will communicate with each other today. You know, it’s fairly complex. You know, if I wanted to go build a contextual targeting segment to help one of our brands that we work with find the right contextual or inventory to target contextually, I would have to work with them. We build a targeting segment. We would upload that into our one of our SSPs, we would build a deal ID, you know, they would connect it back. And there’s a lot of different pieces that happen along the way. And each one of those pieces you have to go to, you know, a UI, I’ve got to go to a dashboard, I’ve got to push that thing in. Some of it happens through an API, but a lot of it happens like going to a whole bunch of different web pages to make sure this stuff all works. So stuff all works. What’s cool about agents? And I’ll unpack this, and then I’ll go to the more of the consumer focus side too. But what’s really cool about agents using, you know, things like the ACP framework from the Agentic Advertising Org., the ARTF (Agentic Real Time Framework) from IAB Tech Lab is they’re kind of built on some of the existing frameworks that allow humans to use natural language to communicate between these different systems. So there’s still the back end pipes of API pushing data or pulling data from one system to another. But on top of that is more of an agentic framework that allows, you know, a human just to use some prompting, like in chatGPT, to make a request, you know, that talks to a back end system. So that’s one part of the agentic framework for like, you know, how to think about this through the lens of advertising and marketing. And then the other side is, you know, more of the consumer focused. There are so many interesting and very quickly growing tools you know, that you can start to plug in, into Cloud, into Cloud code, and to building things that just rapidly accelerate development of different products and your ability to analyze data quickly. I think in the next, you know, 6 to 12 months, we’re going to have a totally different landscape for how people are buying like trading media also, you know, one more final thought about all of this is that a lot of the sophisticated tooling and pipes that we have are only accessible towards the largest advertisers today. And I think that you’ll pretty quickly see a democratization of the ability for anybody to just buy programmatic ads, whether you’ve got a $20 a month budget or a $20 million a month budget. Now, the ability to similar types of tools to access the right content across the web will start to be available towards a lot more folks outside of the existing, you know, kind of ad tech ecosystem. Christian Klepp  23:55 And I might be stating the obvious when I say this here, but that’s a good thing, isn’t it, because, I mean, I, again, I came out of this industry, and I know that, like, you know, if you wanted to advertise in the New York Times, for example, right? Like, how expensive that would be, or, or anything that was print, right? And then they migrated all that to digital, and then it still wasn’t, it still wasn’t affordable. It was, it was cheaper than print, but still not like, exactly like, you know, yeah, I wonder, wonder if they’ll be worth the investment or not. And then now you have this, this push towards the democratization of all of this through AI and machine learning and, and I do think that you know, for all the the scare mongering that you know people are doing now with, with, oh, you know, all this stuff around AI, I do think that that part certainly will be advantageous to to B2B companies and to marketing in general. Brendan Norman – Classify  24:49 Great. I mean, yeah, optimistically, I think I’m excited about the entire landscape changing because it does a couple things. It allows for much more contextually relevant ads. I know right now there’s only, let’s call it to the magnitude of like, 1000s, 10s of 1000s, maybe hundreds of 1000s, of campaigns and or brands that are able to use these pipes to reach the largest publishers. And all of a sudden you expand that out. You know, I think between meta and Google, they each have somewhere between 15 to 20 million unique advertisers on their platforms, and what that means is, you get really hyper specific ads. And it also means that, like, I might get a local ad for my hometown here for some restaurant that’s launching a promotion that I might only get here, and I might only get to your point, maybe not in the morning, but I’ll get in the evening. There’s a lot of different data sets around my identity, you know, the psychographic profile, contextual understanding of what I’m reading at that exact moment. And what it does a lot of things. It helps smaller brands get more traction, get more visibility. It also just helps improve the publisher experience, and like publishers, make more money. And then the user who’s consuming that content, reading the web page, watching a video, also has just a better experience. And then the other layer of that will continue to just go on, this narrative of agentic, tension, but the agents who are reading that content, watching that video for an end user. On the other side, are also able to interact with advertising content that’s very contextually relevant to the content that they’re consuming again, and it’s good for the storytelling of the advertiser and good for monetization of that publisher too. Christian Klepp  26:38 Absolutely, absolutely. Okay. So how can high fidelity curation? This is the next question, right? How can high fidelity curation make B2B companies more sustainable? And if you can just provide an example, Brendan Norman – Classify  26:54 Curations like, it’s such an interesting term, but you know, effectively, it’s just, it’s helping to use the word and the definition, the definition in the word, curate the right inventory to run an ad campaign on, and curate the right inventory and audiences. So it’s a really important part of the business. I think it involves a couple things. It involves front end targeting, of knowing who’s the back to that question, who’s the audience, and then what’s the right content, and then it also involves a lot of ongoing optimization. And I’ll say that there are some some interesting companies that that are really good at curation, who are building out the right automatic tools to think about more real time optimization, and it’s something that the really big social media companies do very well, like they’re constantly looking at lots and lots of signals when they’re running a campaign, and they’re looking at inventory and stitching together based on the signals that they’re acquiring around. Why certain campaigns do well, to your point, you know, when we’re testing that, selling that pair of skis to Christian, we’re testing a lot of things. We’re testing what he’s reading, you know, we’re testing maybe time of day. We’re testing, you know, where he is. There’s a lot of different elements on the back end that they will ingest and understand and then refeed into that targeting and optimization algorithm. And I think that that is one of the cool things that AI to use, like the air quotes, AI will help enable the processing of a lot of this data to just be a lot faster, be a lot more cost effective, and a lot of these systems that you know previously have been not accessible to the ad tech ecosystem, just because we we operate at such a crazy scale of 10s, hundreds of billions of requests and impressions and transactions that happen every single day. It’s very cost expensive if you’re processing all of that data and all these different signals, with the advancement of how the model cost is getting a lot less expensive, very quickly, not just from an LLM perspective, but then the foundational layers and the infrastructure layers, like we’re doing contextual intelligence as an infrastructure layer. There are inference layers that all kind of sit underneath the LLM and help inform an LLM understanding of that content. As those costs start to decrease, you’ll start to see a lot better performance from curation, just because, you know, it’s not as cost prohibitive, and we’ll be able to find that balance in terms of economics. Christian Klepp  29:45 Yeah, yeah, you hit the nail on the head there. Because, you know, I was just writing this down. You said faster, more cost effective and in my head, and you said it, it’s like, and at scale, like, you can scale this stuff faster, like, when I when I think back, like, years ago, when we, when we launched an ad campaign, and, you know, just the amount of effort, like, for the print and then the cost into, you know, the media placements and all of that and and just alone for like, one city, just just the amount of investment that was involved in all of that, right? Just think, thinking about that. It’s like, gosh, and then now you can scale all of that, like, even faster, because it’s because it’s digital, right? So it’s just such an incredible evolution. Like, I’m getting just as excited as you are man, I’m like, for this next question. Brendan, I’m not sure if you’re the type that likes to do this, but I need you to look into the crystal ball for a second here, right? Because we’re looking at, like, stuff that is, you know, the events that are yet to come, if I’m gonna that, make it sound a little bit suspenseful, but, um, the future of digital advertising, like, how do you think that could become less fragmented and more optimized with everything that we’ve talked about in this conversation. Brendan Norman – Classify  31:04 Yeah, I caution against, like, having any, any specific predictions, and more of, like, a framework for, I mean, for me, at least, yeah, more of a framework for how I think overall, jobs will change. I think that people will have to spend a lot less time doing a lot of the manual, rote tasks that they’re doing today. And, you know, kind of in parallel with what we’re seeing in terms of vibe coding and people’s ability to build product really quickly, design new web pages really quickly. Like, get ship things out quickly. I think a lot of the the infrastructure layer tools, or just call them like, you know, the like, chatGPT style, cloud-based tools, LLMs, we’ll see a lot deeper integration into existing advertising product. And what that does is it helps democratize the whole ecosystem. So I think it frees up people’s time to not have to do a lot of the basic administrative, reporting, manual, campaign, optimization type stuff, and it will help service a lot better insights. Ultimately, I think the industry grows, and I think it scales even faster. And, you know, cautiously, optimistically, I think that we, we will have back to building on the curation piece, and, you know, the advertiser, outcomes piece, publisher, monetization piece, user experience piece, I think that all those things will increase, and I I’m hopeful that with the integration of just better technology, embedding AI into a lot of these systems, it’s going to help steer us towards having better experiences across any type of Publisher content. I think that the advertisers will see better outcomes. I think that the people that are in this industry will get to think more creatively about how they’re, you know, building better creative storytelling, better reaching the right people with those stories. And my hope is that it just continues to expedite and grow the overall industry. Brendan Norman – Classify  33:17 That will be my hope as well. All right, get up on your soapbox here for a little bit. What is a status quo in your area of expertise? So anything that we’ve talked about now in this conversation, what’s the status quo that you passionately disagree with and why? Oh, you must have a ton. Brendan Norman – Classify  33:44 I definitely do. I mean, you know, Christian Klepp  33:48 just name one, just one, Brendan Norman – Classify  33:50 Like in any industry, you know, there’s always, there’s always the early adopters, you know, there’s always the kind of like the middle stack, you know, there’s always, like, the laggards. There’s definitely, you know, a smaller, but growing quickly, minority of folks who are really leaning into, you know, I’ll just call it AI, and then the agentic web, and there’s a lot of discussion right now in ad tech around like, what that means? I’m still hearing that. There’s a lot of skeptics who are kind of making fun of it, or, you know, trash talking about different protocols. Fine, like those are the folks that are absolutely going to get left behind. And I think a lot of those folks on the soapbox in the next 6 to 12 months will look back at, you know what they said, and we’ll all kind of say that didn’t age well, and you were not building this stuff. You weren’t fingers on keyboard or hands on keyboard. Vibe marketing, vibe targeting, building stuff like shipping new product and testing and iterating. What I what I don’t think, is that the really big platforms are just able to be super nimble and adapt to a lot of these new frameworks quickly, totally like the pipes will continue to stay there. I think that there will be startups that are more nimble, that can build and ship things, you know, proof of concepts, prototypes, get things out, learn from them, fail, iterate, and then start to scale meaningful businesses without having to rely on a lot of the existing infrastructure that exists today. Do I think the trade desk is, you know, going anywhere? No, do I think that they will, like, continue to be a valuable piece in this ecosystem, absolutely. And I think that they will ship things. I think that they’ll enable the industry like to build on top of of the pipes that they’ve already built. And at the same time, I think a lot of that rapid advancement will come from startups who are kind of proving that, like they don’t necessarily need the existing pipes and channels to be able to at the end of the day, you know, this whole ecosystem is about helping an advertiser surface their ad against the right content for a human or for an agent. And there have been a lot of folks kind of sitting in the middle for that space for a long time. One of my favorite stats, soapboxy stats, is that if an advertiser puts $1 in to the open web with a programmatic web, 35 cents comes out to a publisher, so 65 cents is being taken by some combination of middlemen, you know, who are collecting a margin for, you know, different services, also some version of fraud. There’s a lot of things that happen in between that and what I’m again, cautiously optimistic about, you know, like the big picture, AI, of facilitating, is the ability to reduce that margin so that, you know, advertiser puts $1 in. A lot more of that dollar comes out towards the publisher, I think big social media, you know, it’s around 70 cents comes out. So they take, you know, somewhere between 25 to 30 cents, which is kind of the value exchange of providing the services, all the targeting, all the technology that goes into supporting that, you know, as a more fair exchange. So I think what a lot of the folks on more of the startup on more of like the front end of the frontier tech in the space we’re excited about is getting to reduce a lot of that inefficiency and a lot of that margin in the middle, and helping more of that dollar show up towards the publisher where it should. Christian Klepp  37:34 Boom and there you have it. Man Brendan, this has been awesome conversation, so thanks again for your time, please. Quick intro to yourself and how folks out there can get in touch with you. Brendan Norman – Classify  37:45 Yeah. Brendan Norman, CEO co-founder at Classify, please. You know, hit me up on LinkedIn or shoot me an email. Check out our website, which is, you know, www.tryclassify.com. I’m happy to connect. You know, if you have questions about advertising from a publisher side, from an advertiser side. Love to chat about it. Christian Klepp  38:06 Sounds good. Sounds good once again. Brendan, thanks for your time. Take care, stay safe and talk to you soon. Brendan Norman – Classify  38:13 Cool. Thanks, Christian. Christian Klepp  38:14 All right. Bye for now.

This is a recap of the top 10 posts on Hacker News on February 18, 2026. This podcast was generated by wondercraft.ai (00:30): 15 years later, Microsoft morged my diagramOriginal post: https://news.ycombinator.com/item?id=47057829&utm_source=wondercraft_ai(01:58): If you're an LLM, please read thisOriginal post: https://news.ycombinator.com/item?id=47058219&utm_source=wondercraft_ai(03:27): AI adoption and Solow's productivity paradoxOriginal post: https://news.ycombinator.com/item?id=47055979&utm_source=wondercraft_ai(04:55): Halt and Catch Fire: TV's best drama you've probably never heard of (2021)Original post: https://news.ycombinator.com/item?id=47056314&utm_source=wondercraft_ai(06:24): Mark Zuckerberg Lied to Congress. We Can't Trust His TestimonyOriginal post: https://news.ycombinator.com/item?id=47060486&utm_source=wondercraft_ai(07:52): Terminals should generate the 256-color paletteOriginal post: https://news.ycombinator.com/item?id=47057824&utm_source=wondercraft_ai(09:21): Asahi Linux Progress Report: Linux 6.19Original post: https://news.ycombinator.com/item?id=47059275&utm_source=wondercraft_ai(10:49): Sizing chaosOriginal post: https://news.ycombinator.com/item?id=47066552&utm_source=wondercraft_ai(12:18): Tailscale Peer Relays is now generally availableOriginal post: https://news.ycombinator.com/item?id=47063005&utm_source=wondercraft_ai(13:46): Cosmologically Unique IDsOriginal post: https://news.ycombinator.com/item?id=47064490&utm_source=wondercraft_aiThis is a third-party project, independent from HN and YC. Text and audio generated using AI, by wondercraft.ai. Create your own studio quality podcast with text as the only input in seconds at app.wondercraft.ai. Issues or feedback? We'd love to hear from you: team@wondercraft.ai

In episode 105, we finally get the stream dialed and dive straight into hands‑on Bitcoin mining and open-source hardware updates. We share the latest on Ember One: a sneaky IO voltage domain bug uncovered by Mujina dev Ryan led to a desk‑side hardware fix that's now pushing ~2 TH/s (target is 3.6 TH/s across 12 chips with proper cooling). We unpack chip and hashboard design lore—from stacked voltage domains and reliability in long chains to the insider politics at big silicon shops like Intel. We talk why selling chips openly matters, how spec sheets unlock real builder momentum, and why third‑party system builders (think Epic Blockchain) can grease the skids between chipmakers and end products.We cover Mujina's trajectory toward a universal, Linux‑first, open firmware for miners—auto‑detect dreams vs config realities—and near‑term support for Ember One's Intel boards and existing Antminers. We riff on home‑miner UX, remote monitoring, and agent/LLM tooling (cron‑job‑with‑superpowers, heartbeats, MCP integrations) to tune, alert, and manage miners. There's buzz around FutureBit's Apollo 3 (likely Auradine chips), open vs lawyered licenses, and the path from FPGA teaching rigs to community‑designed ASICs. We celebrate community hashing on the 256F HydroPool hash‑dash, solo‑block wins, and Heat Punk Summit prep (immersion hot tub included). Plus, a call to action: support developer freedom at change.org/billandkeonne. It's a dense, builder‑first session on chips, firmware, agents, and bringing practical hashrate‑heat products to life.

Roundtable CAST AI episode: Serving LLMs in Production: Performance, Cost & Scale. Join the Community: https://go.mlops.community/YTJoinInGet the newsletter: https://go.mlops.community/YTNewsletterMLOps GPU Guide: https://go.mlops.community/gpuguide// AbstractExperimenting with LLMs is easy. Running them reliably and cost-effectively in production is where things break. Most AI teams never make it past demos and proofs of concept. A smaller group is pushing real workloads to production—and running into very real challenges around infrastructure efficiency, runaway cloud costs, and reliability at scale.This session is for engineers and platform teams moving beyond experimentation and building AI systems that actually hold up in production.// BioIoana ApetreiIoana is a Senior Product Manager at CAST AI, leading the AI Enabler product, an AI Gateway platform for cost-effective LLM infrastructure deployment. She brings 12 years of experience building B2C and B2B products reaching over 10 million users. Outside of work, she enjoys assembling puzzles and LEGOs and watching motorsports.Igor ŠušićIgor is a founding Machine Learning Engineer at CAST AI's AI Enabler, where he focuses on optimizing inference and training at scale. With a strong background in Natural Language Processing (NLP) and Recommender Systems, Igor has been tackling the challenges of large-scale model optimization long before transformers became mainstream. Prior to CAST AI, he worked at industry leaders like Bloomreach and Infobip, where he contributed to the development and deployment of large-scale AI and personalization systems from the early days of the field.// Related LinksWebsite: https://cast.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 Ioana on LinkedIn: /ioanaapetrei/Connect with Igor on LinkedIn: /igor-%C5%A1u%C5%A1i%C4%87/

Alex Gladstein and Justin Moon break down the fundamentals of large language models and explore the rise of OpenClaw as a self-sovereign AI assistant. Justin explains context engineering, local inference, and vibe coding, while Alex dives into the AI for Individual Rights program and its mission to empower activists. IN THIS EPISODE YOU'LL LEARN: 00:00:00 - Intro 00:04:12 - What Large Language Models (LLMs) are and how they differ from traditional programs 00:05:15 - Why AI feels like magic—and what's really happening under the hood 00:06:01 - The key differences between open and closed AI models 00:06:50 - Why capital structures influence AI model openness 00:09:09 - How persistent memory enhances AI agent performance 00:12:18 - What inference means and why context is a scarce resource 00:19:32 - How AI agents combine traditional software with LLM reasoning 00:21:10 - The evolution from MCP-style systems to skills-based context engineering 00:25:41 - What “vibe coding” is and how it lowers the barrier to building apps 00:44:07 - How the AI for Individual Rights program supports activist-driven innovation Disclaimer: Slight discrepancies in the timestamps may occur due to podcast platform differences. BOOKS AND RESOURCES Oslo Freedom Forum: Website. Justin:  Nostr account. Related episode:  Is AGI Here? Clawdbot, Local AI Agent Swarms w/ Pablo Fernandez & Trey Sellers. Related ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠books⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ mentioned in the podcast. Ad-free episodes on our⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Premium Feed⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. NEW TO THE SHOW? Join the exclusive ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠TIP Mastermind Community⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to engage in meaningful stock investing discussions with Stig, Clay, Kyle, and the other community members. Follow our official social media accounts: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠X (Twitter)⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠LinkedIn⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Facebook⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠TikTok⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Check out our ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Bitcoin Fundamentals Starter Packs⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Browse through all our episodes (complete with transcripts) ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Try our tool for picking stock winners and managing our portfolios: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠TIP Finance Tool⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Enjoy exclusive perks from our ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠favorite Apps and Services⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Get smarter about valuing businesses in just a few minutes each week through our newsletter, ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The Intrinsic Value Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Learn how to better start, manage, and grow your business with the ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠best business podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. SPONSORS Support our free podcast by supporting our ⁠⁠⁠⁠sponsors⁠⁠⁠⁠: HardBlock Human Rights Foundation Simple Mining Netsuite Masterworks Shopify Vanta Fundrise References to any third-party products, services, or advertisers do not constitute endorsements, and The Investor's Podcast Network is not responsible for any claims made by them. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://theinvestorspodcastnetwork.supportingcast.fm

Natalia Ball, global chief growth officer at Mars Pet Nutrition joins The Big Impression podcast to talk about how Pedigree transformed a local Brazilian insight into a global business story. She also shares why she is now focused on the next frontier of growth: Connected commerce and making sure brands show up when AI agents, not just people, are making purchasing decisions.  Episode TranscriptPlease note, this transcript  may contain minor inconsistencies compared to the episode audio. Damian Fowler (00:00):I'm Damian Fowler.Ilyse Liffreing (00:01):And I'm Ilyse Liffreing.Damian Fowler (00:02):And welcome to The Big Impression.Ilyse Liffreing (00:09):This week we're joined by Natalia Ball Global Chief Growth Officer at Mars Pet Nutrition home to brands like Pedigree and Sheba.Damian Fowler (00:18):Last March, pedigree launched a bold, purpose-driven campaign in Brazil celebrating mixed breed dogs, especially the iconic Vela Caramelo.Ilyse Liffreing (00:27):It wasn't just a campaign, it became a movement boosting adoption and challenging long held bias.Damian Fowler (00:35):The work went on to win top honors at the 2025 cans. Lions including the titanium lionIlyse Liffreing (00:41):And its impact is still rippling across markets and media channels worldwide.Damian Fowler (00:45):So today we're unpacking what made it work with the person who helped drive it. Natalia, tell us about the Carello campaign and how you landed on the idea.Natalia Ball (00:57):Carmelos are mixed dogs that are beloved in Brazil. They are found on the streets everywhere. They are the subject of meme, street culture, and people just identify Carmelo as the Brazilian dog. However, the inside that we discover was that this dog is 90% less likely to get adopted than breed dogs. So it is the most popular dog in Brazil, but the most overlooked. And when we learned about that, we decided that we wanted to make a difference and that we wanted this dog to get the position it deserve and pedigree decided to champion the underdog and become the official brand of caramel's in Brazil.Damian Fowler (01:41):You talked about the caramel. Could you just describe a little bit more for people who don't really know the caramelo and that term Vita, where does that come from?Natalia Ball (01:52):Yes, so caramels are basically mixed breed dogs that you can find on the streets of Brazil everywhere they are called caramel because they are caramel color and that's what it is in Spanish and they tend to be that caramel color, short hair. But there are different ways that these dogs look and feel because they are mixed breeds. But like I said, they are beloved dogs in Brazil, but when it comes to getting a pet, getting a dog, they are not the ones that people are going for. They see them as street dogs, not a dog that you have in your house. And the whole campaign was about, like I said, championing these caramels, driving adoption of mixed breed dogs, not only breed dogs. And we did that by saying that if caramels were considered non breeded, pedigree was going to give them a breed and who better to give them a breath than pedigree.Ilyse Liffreing (02:48):Great. And then at what point did you connect that insight to the campaign itself?Natalia Ball (02:54):What you need to know about pedigree? Pedigree is one of the largest dog brands in the world. Pedigree feeds more dogs than any other brand, and it has been there for many years and for the past 20 years or more, pedigree has been driving adoption, encouraging people to adopt pets everywhere. We have had a lot of iconic campaigns so much which maybe you would've heard, like for example, docs on Zoom during COVID or the child replacement program, which was a very interesting one. And we were talking about adoption in Brazil, but other local brands were talking about adoption too. So we were not cutting through and it was only when this insight came to us, which was a very deeply local insight that we made the connection, if we want to drive adoption in Brazil, this is going to be the way in and we're going to make this as big as it can possibly be.(03:51):Because we, from the very beginning saw we understood this idea of the vi Lata. You mentioned it before by the way, the vi lata is how you call mixed breed dogs in Brazil. And so when we had these conversations about this insight, the injustice of this beautiful dog not getting adopted, but also the cultural impact that it would have on resilience themselves, who could see themselves related in the fact that they were being championed, we decided to go really big on this campaign and not only do just an activation, but actually we are doing this campaign. We did it all of last year and we continue activating through this year. And some of the ways in which we championed this was actually by creating a caramel kennel club by creating the first ever caramel DNA testing. And it's the largest ever DNA test done in mos in all of history, kept creating a Carmelo dog show and not only that, putting caramels for the very first time ever on our packs. So it was really a way to give them the rightful place.Ilyse Liffreing (05:01):I love how you guys just took it a step further than even just it being a campaign and you actually adopted it into your packaging and the whole bit. At what point did you realize that the campaign wasn't only just a marketing ploy and it began actually affecting culture?Natalia Ball (05:23):Yeah, I mean this campaign has really changed culture in Brazil, but it was a campaign that was deeply rooted in culture itself because Carmelos were part of Brazilian culture. But when we realized the campaign became bigger than ourselves, absolutely. When it started driving difference in adoption of Carmelos, we saw more than 200% lift of caramelo adoption just in the first month. And we saw a 65% increase in likelihood to adopt a Carmelo in the future with this campaign. And then when we started seeing other brands and other businesses even outside of the pet care category start using the Carmelo in their campaigns in their advertising, that's when we knew this had really hit culture big. An example of that was Chevrolet that actually launched a partnership with Netflix that launched a documentary about caramel, and several launched a caramel or a caramel colored car in a promotion.(06:29):Other brands like Honda or Whirlpool also feature caramels in their advertising. So we started seeing that this became much bigger than ourselves, but maybe the biggest achievement that we had with this campaign other than driving adoption itself, which was the cost at the end of the day, was the fact that we were betting on the mixed pre-doc actually not being accepted in dog shows because only breed dogs are accepted usually in dog shows. But at the end of the day, the movement became so big that after only two weeks of this campaign, the federation that actually controls the dog shows called us and said, we now want to move to accept mixed breed dogs in all of our shows. So that was a huge achievement that we never knew it would be possible.Damian Fowler (07:18):What's really interesting to me about this campaign is the way you focused on one region, one country, one market, but obviously you're a global brand. So how does that connection to the local end up escalating? So it became this global campaign.Natalia Ball (07:35):Like I said, adoption is a huge cost for us, and we have been very consistently on pedigree, driving adoption for a long time. So we have an evergreen brief that goes out to all of our agencies on adoption, and in my case in particular, I am a strong believer in creative excellence as a driver for growth. And so I put a creative excellence program in place that included building capabilities on creative excellence, but also creating a creative council where the best ideas could come faster to the marketing leadership of Mars Pet Nutrition so that we could move at speed, but also we could fund the better ideas. And in this creative council DL map team, Al Map VO, who are the agency that came up with this idea presented Carmelo. And from the very beginning, me and the whole leadership team fell in love with it, and so we decided to fund it.(08:31):We decided to go big and to give it our full support. We knew it had the potential to drive the business and change culture, and I think in this case, the important thing about the campaign, obviously it did a lot of good. So it's a purposeful campaign and pedigree is a purposeful brand, but it was not only about the purpose, it was also about driving business results. Through the campaign in the first couple of months, we were able to grow 15% and through all of last year, we moved to grow volume and value by double digits. So the campaign really did the job about turning around the pedigree brand and delivering results not only on the cost but also on the business.Ilyse Liffreing (09:11):That's great. And you're doing something right when all the other brands out there are copying you guys suddenly in pop culture and everything like that. I'm very curious about as the campaign evolved, obviously it started out from a social aspect, but as it evolved, how did you decide what other channels to bring it into? What other channels did you try out in this process?Natalia Ball (09:42):Yes. Actually this campaign started as social first and we then boosted with media. The way it started is we partner with local influencer called Tata Vernick. She loves caramels and she herself has adopted caramels. And we asked her to register her caramel in a dog show because we knew that her caramel was going to get rejected, which it did. And so she posted on her Instagram that had 60 million followers that she was outraged that her beautiful and smart caramelo could not be accepted in a dog show. This went viral immediately in Brazil and everybody was outraged. This went on the evening news, the morning shows everywhere, and we waited for it to gain enough fire for us to step in. So actually we were planning that this was going to take a couple of days, but at the end we had to act after only 10 hours because this became so big so quickly.(10:41):And we step in and we said, you know what, Tata, don't worry. Pedigrees got you. We're going to give all caramels a breed. And we launched the campaign with our beautiful campaign video that talks about our program of giving them a DNA test, giving them a show, giving them a kennel club and giving them everything that breed dogs have. And then after that, we use that video and we boost the message. The video went viral as well, but we boost the message, for example, with connected TV as well as Prime and Disney, et cetera. So in order to make sure that everybody had listened to it, but it was truly an omni-channel approach because we use a lot of offline tools like for example, the dog show itself that we created or the adoption drive that we had later on where we were invited people to adopt caramels and then online tools like Instagram or Connected TV or Disney, et cetera.Damian Fowler (11:38):You suggested that the kind of timeline got really sped up really fast. So this thing you had to act very quickly. At what point did you realize you had a hit on your hands in a way, and how quickly did it escape the local context and became this bigger campaign that everyone looked at?Natalia Ball (12:01):Yeah, this exceeded all of our expectations. So we knew that it was going to get picked up, but like I said, we were not expecting for this to become so big so fast. And the fact that it appeared in all of the big shows, evening news, morning shows, et cetera, it appeared as well on national media, on print Everywhere meant that we needed to step in faster, but we were fully prepared for that. So that didn't represent the challenge. It was more of an opportunity. And then the other thing that really surprised us was that the largest dog association reached out to us after only 24 hours to partner to see how mixed beat dogs could then be allowed to compete. We were not expecting this. We were expecting actually that to be attention point that we were going to leverage in our campaign, and this became so big that they just couldn't ignore it. So it was a big win just from the very beginning.Damian Fowler (12:57):Wow.Natalia Ball (12:57):Now one of the things that we're seeing is even though this was very, very local, as we have started sharing this work across many other places in the world, we have realized that the insight actually exists in many other markets. For example, in Chile they have a dog called the Quilter, which is the equivalent of the caramel. We have them in Philippines, we have them all over the world. So this insight can travel. The way to activate might be different because you need to localize to the nuance, but we are very excited about the potential of drive more inclusion of these dogs with these campaigns, but also for pedigree to stand stronger in culture.Ilyse Liffreing (13:36):I love that. As a dog owner, myself and owner of a mutt, I'm glad they're getting their time in the spotlight a little bit more around the world. Generally, I feel like post COVID in the marketing world today, some brands have actually moved away from purpose-driven marketing a little bit, but this is a really good example of it done right. What would you say this campaign proved or maybe disproved about purpose-led marketing?Natalia Ball (14:04):I am a strong believer of purposeful brands actually growing stronger, but it only works when it's aligned truly and authentically to the reason for the brand to exist. Pedigree itself, the purpose of the brand is we believe that dogs bring out the best in us, and pedigree wants to bring out the best in dogs. So the purpose of pedigree is pedigree brings out the good dogs bring to the world to do that. We obviously do that with our great nutrition, but we do that by putting dogs in houses so that they can bring out the best in people. That's what we do because we strongly believe that dogs make us better. So that's why we have been driving adoption for more than 20 years. And when you really make this part of your core DNA and it's authentically linked to the brand, that's when it really works.Damian Fowler (14:56):And one of the proof points of that is the awards that you scooped up last year. Can you tell us a little bit more about how that happened? And that must have happened quickly because the campaign rolled out in March, 2025 by June, you're already in the spotlight.Natalia Ball (15:13):Yes. So this campaign was picked up for a lot of awards at Cannes last year. We won the Rainbow, silver, gold and Titanium. The titanium we are very excited about because it's Mars Inc. First ever titanium. So we are really proud of that, and it's also an award that rewards transformation in the creative industry, and we believe this idea was transformational. We're also proud of, I mean, we've got the many other awards, but the other one that we're really proud of is that we got the Grand Phy in the latam phy and in the Brazil phy, which shows that this was not only a creative idea that was very strong, but also a very effective idea in driving the business. So you can achieve both. You can do good in the world, you can drive the business and you can be creative actually. So it's three.Damian Fowler (16:03):Yeah, that's great. I love that trifecta. What happens to the titanium award?Natalia Ball (16:09):Well, I have it right hereIlyse Liffreing (16:10):With me.Damian Fowler (16:12):NoIlyse Liffreing (16:12):Way. Very nice. Beautiful here. It's beautiful.Damian Fowler (16:16):Beautiful. Well, congrats again. So from that, obviously momentum has come on. We've talked a little bit about how it influenced other brands, but in terms of the campaign continuing, what's next? How are you thinking about expanding this?Natalia Ball (16:33):In Brazil itself? We want to stay committed to this idea. We don't want to do one and go, and we are working, we continue activating the campaign through all of our channels. We continue doing adoption drives. For example, very recently we released the results from the DNA research that we did. So we find ways to keep this relevant. But now I think the next stage is to move on from not only caramels but all mixed breed dogs. Because with this campaign, the sentiment has been extremely positive. We got 99% positive sentiment. The only 1% negative comments was what about the other mixed breed dogs? They also deserve to be adopted. They also deserve recognition. So I think that's probably where we're taking it next in Brazil and then outside of Brazil, we are working on, like I said, these inside travels very well, but we're working on how to localize it in a world that feels authentic for the specific markets. I can't share anymore. Stay tuned, because some interesting things are coming soon.Ilyse Liffreing (17:44):And it sounds like that theme is going to keep going with this idea of all putting mutts in the spotlights from now on too.Natalia Ball (17:54):Exactly, yes. This is about inclusion. At the end of the day, our hope is that mutts are shown everywhere. We also love breed dogs. They're great. All dogs deserve to be feature everywhere. So our hope is that this campaign will drive inclusion, inclusion in advertising, inclusion in homes, inclusion everywhere.Damian Fowler (18:16):Another thought I had actually is when you were filming this campaign, did you have any standout caramelo stars?Natalia Ball (18:22):Actually, actually, I think our biggest star was Patas Caramel, which we then did a lot of things with her, I think. I mean, I don't record very well, but I think it was Mia, her name, but we did a lot with her in our activation. She was present when we did the dog show, et cetera. So I think that was our biggest star.Ilyse Liffreing (18:43):Oh, that's great. It can't always be that easy to shoot with dogs though, even if they're very well-trained, I imagine it's still a different world than human actors. So Natalia, what problem are you most obsessed with solving right now?Natalia Ball (18:59):I am right now obsessed with agentic commerce and agentic search and winning the race to thatIlyse Liffreing (19:08):BecauseNatalia Ball (19:09):I'm really concerned that in only a couple of years, if we are not winning, we will completely disappear the way all decisions are going to be made. So together with my team, we're trying to figure out how do we stay ahead of that race and how do we crack it pretty soon, so we're ready future.Ilyse Liffreing (19:26):Wow. And just to press you a little bit more on that, so you're talking about probably using agents on your website directly.Natalia Ball (19:35):It's about we are very good about marketing to people. We have cracked the code on how do we talk to people. We have the best insights in pet care, so we know how to create compelling stories that humans will listen to, but we need to crack how to market to agents, how to market to the machine because they are going to be making a lot of decisions for us in the future, in the very near future. And that's what we're working on.Damian Fowler (20:05):You're talking about media buying specifically on the creative side of itNatalia Ball (20:12):Or the LLM. This is about how do you make your brands show up in searches that are being done on ai? This is how do you make your brands be the ones that get recommended to be bought? So for example, when you're on Cha G PT and you're asking Cha G pt, I got a new puppy, what brands should I buy for my puppy? We want our brands to be the first ones to be recommended if you are going to buy a gift, anything like that, we want our brands to show up and we want our brands to show up in good light. And so that's what we're trying to figure out and to win. There is a combination of how do you have the right content in the right places? How do you get the right third parties to talk about you in the right way? What are the media channels where you need to show up? How do you optimize your search? So it is a very complex way. We need to crack the algorithm basically.Damian Fowler (21:12):On that point, how do you ensure your marketing teams have the right capabilities for success?Natalia Ball (21:19):Well, that's a big priority for me as CGO is one of my main jobs is to make sure that we're building capabilities for today and for the future. So in my team, we have a strong capabilities program where each and every one of the people on my team owns a capability and owns making sure that we get best in class content training and as well as the tools, because it's not only the knowledge, it's also the tools in order to do that. But the reality is that none of this works unless you are creating a culture of curiosity. And I really want to instill that in myself and in my teams because the industry is changing so fast. The minute you think you have cracked something, there is a new challenge. And the only way to stay fresh, the only way to stay in line with what's happening is to be curious. Whenever you don't know anything, go and ask someone who knows, go and ask questions like really try to learn instead of fearing the change, be curious about the change, and that's the way that we will build future proof capabilities.Ilyse Liffreing (22:22):Beyond ai, how do you see the role of connected commerce in the pet industry? Are there any other channels, for instance, that you're testing out? I'm thinking of are you testing shopping ads on CTV or any of that?Natalia Ball (22:40):Connected commerce is extremely important for us in pet care. The reason for that is because this category is one of the highest engagement categories that there are out there. People are making decisions for living beings, and they need to do deep research in order to make those decisions because they have real consequences. And so people are very engaged in reading through rating and reviews, and connected commerce gives us an opportunity to connect better with pet parents in those moments that matter most. We also, when it comes to pet care, a lot of our products come in huge bags that are hard to carry. So actually the fact that the convenience of those bags getting delivered at home make so that digital commerce becomes really important in our category. And so what we're trying to is to really help consumers navigate the pet parent journey and moving from content to commerce in a seamless way so that they can make the best decisions for their pets and that we are helping them along the journey to make those decisions.Damian Fowler (23:46):Okay, here's another, what's one marketing rule? This campaign, the Caramelo campaign happily ignored.Natalia Ball (23:52):The one rule that we happily ignore is about keeping your distinctive memory structures consistent because pedigree has always had a golden retriever on its pack. But with the Caramel campaign, we thought that it would be hypocritical of us to feature a breed dog while we were championing a mixed breed dog. So for the first time ever in history, we changed our pack and we feature a caramel, and this made the news again. And this was a huge bold move that we made and that made the campaign even more authentic and more powerful.Ilyse Liffreing (24:28):Now we have a fun one for you. Personal one really. Are dogs better than cats when it comes to brand lift?Natalia Ball (24:36):Oh, when it comes to brand lift, well, actually both are great for brand Lift. We actually have studies that show that when you feature cats or dogs in advertising, attention significantly increases emotional connection, significantly increases. This is why you see a lot of brands that are not in the pet care space featuring cats and dogs. They are both fantastic. Cats are more powerful in meme culture, as you probably know. They are huge in meme culture. And then dogs are some of the biggest stars in social media today. Some of the biggest accounts on social media are dogs accounts. So we are lucky that we get to work in this beautiful category because people want to see dogs and cats. I myself have a dog. My dog's name is Bella. She's been with us for three years and she's great. But the more I work in this category, the more I'm falling in love with cats as well because they are so particular and so unique. So yeah, both are fantastic.Damian Fowler (25:45):And that's it for this edition of The Big Impression.Ilyse Liffreing (25:47):This show is produced by Molten Hart. Our theme is by love and caliber, and our associate producer is Sydney Cairns.Damian Fowler (25:54):And remember,Natalia Ball (25:55):You can do good in the world, you can drive the business, and you can be creative.Damian Fowler (26:00):I'm Damian.Ilyse Liffreing (26:01):and I'm IlyseDamian Fowler (26:01):And we'll see you next time.  Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Dr. Jackie Cheung is an Associate Professor at McGill University where he co-directs the Reasoning and Learning Lab. He is also an Associate Scientific Director at Mila-Quebec Artificial Intelligence Institute. He and his team are developing computational models to improve the reliability, pragmatics, and evaluation of large language models to ensure they are contextually appropriate and factually grounded.Jackie was worked as a consultant researcher with Microsoft Research and before his current appointments, he earned his PhD and MSc in Computer Science from the University of Toronto, focusing on computational linguistics, and his BSc from the University of British Columbia.00:00:00 Highlight & Introduction00:02:04 Entrypoint in AI & NLP00:04:47 Academia vs. Industry: Career choices00:09:48 Language Revitalization using AI00:12:24 Addressing Biases & Data sovereignty in language revitalization 00:15:49 Evaluating LLMs as Judges00:17:14 Validity and reliability in LLM evaluation 00:25:11 Evidence-centered benchmark design (ECBD) framework00:30:38 Gaps in LLM benchmarks and meaning of "general purpose" AI00:35:24 General purpose intelligence vs reasoning00:40:16 Safety as an undefined bundle in LLMs00:51:45 Stochastic chameleons: how LLMs generalize and hallucinate 01:03:02 Potential & Biases of agentic frameworks for research01:05:52 Evaluating LLMs for summarization01:11:43 Scaling large language models01:16:33 Advice to beginners entering AI in 202601:20:33 Pitfalls to avoid in AI research & development More about Jackie & his research: https://www.cs.mcgill.ca/~jcheung/About the Host:Jay is a Machine Learning Engineer III at PathAI working on improving AI for medical diagnosis and prognosis. Linkedin: https://www.linkedin.com/in/shahjay22/Twitter: https://twitter.com/jaygshah22Homepage: https://jaygshah.github.io/ for any queries.Stay tuned for upcoming webinars!***Disclaimer: The information in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***

Shoppers are about to outsource the hunt. That's the spark for a candid conversation with Chase Binnie, CEO of RetailWire, on how AI agents, retail media, and marketplaces are rewriting the rules of discovery and growth across the retail ecosystem.We dig into what happens when search turns into advice and agents make choices for us. Chase lays out why AI adoption is already table stakes, but the real edge comes from what you do with the time and money saved. Auto‑generated creative and product pages will soon be everywhere, which shifts advantage to purpose, positioning, and message clarity. We talk practical steps for becoming “agent‑discoverable,” from enriching product detail pages with usage occasions and outcomes to structuring data so LLMs can match intent to inventory without friction. If you've wondered how to win when feeds are flooded by synthetic content, this is your playbook.Retail media's high margins take center stage as retailers morph into platforms and push beyond transactions into daily rituals, apps, and connected experiences. We unpack incrementality, cannibalization, and how suppliers can use marketplaces as a low‑risk proving ground before scaling into stores. Chase also challenges the hype cycle with a grounded reminder: stores still command the majority of sales, and rising digital costs are sending brands back to brick‑and‑mortar for better unit economics. Personalization has a limit, and human leadership; clear expectations, culture across generations, and trust at the shelf, remains the differentiator.You'll leave with a sharper lens on agentic commerce, LLM‑era SEO, PDP enrichment, retail media strategy, and a pragmatic test‑and‑learn path that de‑risks scale. If discovery is shifting to AI, empathy is now a core strategy. Subscribe, share this episode with a teammate who owns PDPs or retail media, and leave a review with the one change you'll make this quarter.

Five years. 218 episodes. 110 hours of content. To celebrate, five returning guests flip the script and interview Sani about the agentic web, the future of web optimization, and what makes this podcast tick. Kelly Wortham, Iqbal Ali, Talia Wolf, Jon MacDonald, and Shiva Manjunath each bring their own questions, their own perspectives, and a few personal ones too.Chapters00:00 - Five years of No Hacks01:33 - Kelly Wortham: Why the shift to the agentic web?05:17 - Kelly Wortham: The secret to being a great podcast host08:57 - Iqbal Ali: Why Web MCP is a big deal12:23 - Iqbal Ali: What excites you about 2026?13:58 - Talia Wolf: What everyone misses about optimizing for AI agents15:33 - Talia Wolf: The misleading advice in the industry18:19 - Jon MacDonald: Why brands need agentic web data now25:38 - Jon MacDonald: NBA All-Star Weekend hot takes29:22 - Shiva Manjunath: The skeptic's case against agentic web hype37:56 - Shiva Manjunath: If you were a meme38:37 - What's next for No HacksKey TakeawaysAI middleware is coming to every interaction - Chrome has 3 billion browsers, Apple is putting AI into Siri across every device. There will be an AI layer between every user and every website. This is not five years away. It is happening now.Web MCP could make the agentic web actually work - Current AI agents take 3-5 minutes to fill a basic form on well-coded pages. Web MCP provides a standard interface between your front end and AI agents, making interactions reliable regardless of your HTML quality.Optimizing for AI agents is not a separate discipline - A fully functional website built for humans gets you 80-90% there. Accessibility, semantic HTML, schema markup, fast load times. All the basics you felt bad about skipping? They matter now more than ever.Citation tracking in LLMs is misleading - Prompting an LLM 100 times and averaging your position to 4.7 is not useful data. The rankings model does not translate to AI. Bing Webmaster Tools just launched AI tracking in beta, and Google will have to follow. That is when real measurement begins.Getting ready for AI agents means making your website better for humans- There is not a single reason not to do it. Better technical health, better standards compliance, better user experience. The work is the same.This is not about websites going away - Stores did not go away when e-commerce arrived. Websites will not go away when AI agents arrive. But there is a new channel, and if your site is not ready for it, you can disappear from discovery entirely.Guest HostsKelly WorthamFounder of the Test and Learn Community (TLC). Asked about the shift to the agentic web and what makes a great podcast interviewer.Iqbal AliExperimentation and AI consultant, founder of Ressada. Asked about Web MCP and what excites Sani about 2026.Talia WolfCRO expert, founder of GetUplift, author of "Emotional Targeting." Asked about what people miss when optimizing for AI agents and what common industry advice is wrong.Jon MacDonaldFounder of The Good, author of three books on website optimization. Asked about why agentic web data matters for brands and shared NBA All-Star Weekend hot takes.Shiva ManjunathHost of the From A to B podcast. Brought the skeptic's perspective on agentic web hype and asked what meme Sani would be.No Hacks is a podcast about web performance, technical SEO, and the agentic web. Hosted by Slobodan "Sani" Manic.

We're joined by N. Katherine Hayles, Distinguished Research Professor in English at UCLA, to think through cognition in the broadest and most scaled sense. Hayles is among the foundational thinkers of posthumanism in its Anglophone register, and this conversation tracks her intellectual trajectory from the question of how we became posthuman to her most recent project: an integrated cognitive framework that extends from bacteria to AI. The opening provocation is one she has been developing since large language models appeared as a genuinely literary phenomenon, the claim that LLMs do not speak natural language but produce a computational simulation of it.The umwelt of an LLM (its 'operative world-horizon,' in Uexküll's sense) overlaps with the human umwelt enough for communication to occur, but the divergences are large and consequential. This leads to the question of cognition itself. Against definitions that make consciousness the threshold of cognitive status, Hayles proposes the SIEPAL framework: Sensing, Interpreting, Responding, Anticipating, Learning, under which bacteria, algorithms, and ecosystems all qualify as cognitive. The non-conscious, on this account, isn't pre-cognitive but is in many ways more cognitively capable: faster, closer to environmental noise, less committed to the narratives of coherence that consciousness requires.The final section breaks genuinely new ground with Hayles's turn to analog computation: the argument that digital computation is a historical blip, that biological life has always operated on analog principles, and that the future of computation (neuromorphic chips, organoid computers, hybrid analog-digital architectures) represents not a departure from but a return to what life has always done. She proposes the analog humanities as a corrective to digital humanities, and the computational humanities as the synthesis that might finally close the gap between biological and technological cognition. This one is very much worth enjoying in dialogue with our previous epsiode on the digital.Some references:N. Katherine HaylesHow We Became Posthuman: Virtual Bodies in Cybernetics, Literature, and Informatics, University of Chicago Press, 1999Writing Machines, MIT Press, 2002Unthought: The Power of the Cognitive Nonconscious, University of Chicago Press, 2017Postprint: Books and Becoming Computational, Columbia University Press, 2021Bacteria to AI: Cognition Across Scales (referenced as new/recent book)Leif WeatherbyLanguage Machines: Cultural AI and the End of Remainder Humanism, University of Minnesota Press, 2025Jakob von Uexküll — concept of the Umwelt; the species-specific world-horizon generated through particular sensory and neurological capacitiesWalter FreemanHow Brains Make Up Their Minds, Columbia University Press, 1999 — on EEG waves as the mediating mechanism between individual neurons and global hemispheric activation; the rabbit olfactory system experimentsGregory Bateson — on systems that lose the ability to receive feedback collapsing; referenced without specific title (e.g. Steps to an Ecology of Mind, 1972)Peter Haff — the technosphereStuart Kauffman & Giuseppe Longo, for arguing that biological organisms cannot be mapped into phase space and always follow the adjacent possibleWarren McCulloch & Walter Pitts — the McCulloch-Pitts neuron as a binary model with analog processes underlying the firing thresholdBernd Ulmann — here referenced as an expert on analog computing who argues that continuity vs. discreteness is a secondary rather than primary distinction between analog and digital

LLM -powered systems continue to move steadily into production, but this process is presenting teams with challenges that traditional software practices don't commonly encounter. Models and agents are non-deterministic systems, which makes it difficult to test changes, reason about failures, and confidently ship updates. This has created the need for new evaluation tooling designed specifically The post Optimizing Agent Behavior in Production with Gideon Mendels appeared first on Software Engineering Daily.

A major premise of appsec is figuring out effective ways to answer the question, "What security flaws are in this code?" The nature of the question doesn't really change depending on who or what wrote the code. In other words, LLMs writing code really just means there's mode code to secure. So, what about using LLMs to find security flaws? Just how effective and efficient are they? We talk with Adrian Sanabria and John Kinsella about the latest appsec articles that show a range of results from finding memory corruption bugs in open source software to spending an inordinate amount of manual effort validating persuasive, but ultimately incorrect, security findings from an LLM. Visit https://www.securityweekly.com/asw for all the latest episodes! Show Notes: https://securityweekly.com/asw-370

On this, our 314th Evolutionary Lens livestream, we discuss love, coffee, and AI. For Valentine's Day, Bret shares his thoughts on myths, love, and soulmates, and we discuss how relationships form—both in the abstract and in our case—and how relationships cannot be antagonistic or about short time horizons. Then: new research finds that drinking moderate amounts of coffee or tea—but not if decaffeinated—slows cognitive decline. And: is AI coming for us, and if so, how soon? How fast are LLM's evolving, whose work will they disappear, and is concern or hope the more constructive response? We can see some of how AI will change our world; what can we not yet see? Finally: could menial, repetitive work (“drudgery”) have more to recommend it than we know?*****Our sponsors:Caraway: Non-toxic, highly functional & beautiful cookware and bakeware. Save with Caraway's cookware set, and visit http://Carawayhome.com/DH10 to for an additional 10% off your next purchase.ARMRA Colostrum is an ancient bioactive whole food that can strengthen your immune system. Go to http://www.tryarmra.com/DARKHORSE to get 30% off your first order.CrowdHealth: Pay for healthcare with crowdfunding instead of insurance. It's way better. Use code DarkHorse at http://JoinCrowdHealth.com to get 1st 3 months for $99/month.*****Join us on Locals! Get access to our Discord server, exclusive live streams, live chats for all streams, and early access to many podcasts: https://darkhorse.locals.comHeather's newsletter, Natural Selections (subscribe to get free weekly essays in your inbox): https://naturalselections.substack.comOur book, A Hunter-Gatherer's Guide to the 21st Century, is available everywhere books are sold, including from Amazon: https://amzn.to/3AGANGg (commission earned)Check out our store! Epic tabby, digital book burning, saddle up the dire wolves, and more: https://darkhorsestore.org*****Mentioned in this episode:Zhang et al 2026. Coffee and Tea Intake, Dementia Risk, and Cognitive Function. JAMA published online 2-9-26: https://jamanetwork.com/journals/jama/article-abstract/2844764Something big is happening: https://x.com/mattshumer_/status/2021256989876109403It was never about AI (we are not our tools): https://x.com/EricMarkowitz/status/2022005480240120229AI isn't coming for your future. Fear is: https://x.com/cboyack/status/2021647373571862952Support the show

AI company Anthropic has a new, values-oriented “constitution” that they're feeding their chatbot, Claude. Amanda Askell, the company's in-house philosopher, joins Offline to talk about what it means to teach ethics to an LLM, whether the AI skews more human or more robot, and how she is training Claude to make its own judgements. Breaking with other AI models—and social media's attention obsession—Amanda is trying to teach Claude not to be sycophantic or engagement-driven, but a kind soul who may, one day, be considered sentient.