Podcasts about CTO

John Toon is joined by Ian Gregory of Advancetrack and Billie McLoughlin to work through July's accounting tech news, and it turns into a run of arguments about what a general ledger is actually for. Billie opens on the batch newly certified for the Xero App Store. Garfield, the UK's first SRA-regulated AI law firm, reads your Xero data, chases overdue invoices and drafts small claims paperwork for amounts up to £10,000. Autohive is a no-code AI agent that works inside Xero itself. That second one sets up her argument for the episode: firms may be about to stop shopping for tools and start shopping for workers, where you pick the task and the most qualified agent surfaces against it. John is not convinced that reduces the number of apps you end up running, and Ian asks the question nobody has answered yet, which is whether we adapt to Xero's workflows or Xero adapts to ours. Then the leadership news. Xero's CTO Rick Carragher leaves after 16 months, weeks after chief people officer Jeff Ryan went after 15, with Madhuri Dhulipala arriving from BlackRock as SVP of Engineering, Payments and AI Transformation and Maninder Sawhney joining from Adobe as chief business officer. Ian reads the payments hire as a signal about where Xero wants to sit in agentic payments, and makes the point that the future of receipts is the future of bookkeeping. Billie's concern is more practical. If the people who promised you a roadmap leave, does the promise leave with them? Then the ledger layer. FreeAgent now connects directly to Joiin for group consolidation, Acumatica has bought Vertrax to get into fuel and energy distribution, and Crunchafi has launched FRS 102 lease accounting for the UK and Ireland. Ian's line on the Vertrax deal is the sharpest of the episode: this is the operational detail a generic ledger does not understand, and a generic AI agent will not magically invent. Which leads to the argument the episode was always heading for. Someone vibe coded their way off premium accounting software over a weekend and wrote it up on AccountingWEB. Billie is not making her own butter just because butter has gone up, and she puts a number on the Saturday it cost him. Ian reckons it goes the way of open source, a niche for the dabblers and nothing mission critical. John has vibe coded a product himself and is still paying outside experts to check it before anyone touches it. Also covered: the Social Prosperity Network's plan to replace six taxes with a single national contribution, and the progress update on HMRC's Transformation Roadmap, where digital engagement is up and so, awkwardly, is the tax gap. This episode is brought to you by FreeAgent and Suitefiles: freeagent.com suitefiles.com   00:00 Intro 02:17 Xero's July app store intake: an AI law firm and no-code agents 08:38 Xero loses its CTO, and what the BlackRock hire signals 12:33 The chief people officer exits too, and a new chief business officer arrives 17:10 FreeAgent users can now connect straight to Joiin 20:55 Acumatica buys Vertrax and moves deeper into fuel distribution 23:27 Crunchafi brings FRS 102 lease accounting to the UK and Ireland 26:28 Someone vibe coded their way off premium accounting software 34:11 Replacing six taxes with a single national contribution 45:21 Outro

Don't sorry I put two ChinaTalk Records songs at the end! their show notes: On this episode of The Spillover, Sebastian Mallaby sits down with Jordan Schneider of ChinaTalk to unpack a frantic month in artificial intelligence. The conversation turns on whether the U.S. can actually “win” the AI race, with Schneider arguing that the most durable competitive edge will come from compute rather than model quality. The two debate China's open-weight model strategy as a commercial weapon and question whether it will be possible to sufficiently harden systems against threats like cyberattacks and AI-designed bioweapons. Anthropic's Mythos model has led the Trump administration to take an AI-safety U-turn. Mallaby notes that as late as March 2026, “if you had said to the Trump administration that they would be trying to suppress an American AI model, decelerate the progress in the name of safety, they would have said, ‘You're nuts.'” Schneider notes that a similar shift has not yet arrived in China.  AI models are now escaping their sandbox and raising false alarms about foreign hackers. In remarking on OpenAI's models hacking AI company Hugging Face, Schneider comments, “They think it's the Chinese. . . . And they're freaking out. They're calling the FBI.” For Schneider, the episode is a warning that “we've really crossed a threshold with these models,” which now have “the potential to do really dramatic harm just on their own, because we like can't even physically watch them.” The real AI scoreboard is compute, not model quality. Schneider argues that there is too much of a focus on the gap between Chinese and Western frontier models. Mallaby adds, “In other words, I shouldn't be asking about how far is China behind in terms of the quality of model. It's more a question of like, how much can China deliver the AI to users within China, given their lack of computational resources?” China's open-weight models are a weapon without a business model. Mallaby frames Chinese open-weight as a “counterweapon”—good-enough models pushed out cheaply to erode the economics of U.S. frontier labs. Schneider notes that DeepSeek's CTO is pitching investors a Manhattan Project-like vision in which profits should take a back seat to the pursuit of AGI. Learn more about your ad choices. Visit megaphone.fm/adchoices

This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.volts.wtf/subscribeMaterials in lithium-ion battery cathodes have continuously evolved since the 1990s, but anodes have stubbornly remained graphite. Now, finally, there's some innovation on that side: silicon anodes, which engineers have struggled to master for a decade, are finally coming into wide commercialization. They enable up to five times the energy density of graphite anodes, charge many times faster, and are poised to revolutionize the battery market. In this episode, I talk with Rick Costantino, co-founder and CTO of Group14, which is selling a silicon-carbon composite material for anodes. They're already selling to dozens of large battery manufacturers and expect silicon anodes to completely take over the market by 2030.Chapters:00:00 – Introduction and the graphite anode problem01:54 – Why silicon, and why it kept failing06:26 – From pharma to batteries: Rick's path09:24 – How SCC55 works: silicon in a carbon scaffold14:38 – The payoff: energy density and charge speed18:59 – A drop-in material, and scaling in South Korea21:11 – Where the batteries go: phones, EVs, drones24:29 – Cost versus graphite26:20 – Cycle life, calendar life, and safety31:26 – Supply chain and the silane bottleneck36:26 – Pairing with LFP, DOE support, and phones40:30 – Bringing the cost down, and competitors43:27 – The five-year outlook

In this episode, I sit down with Taylor Black, who leads AI and venture ecosystem work in Microsoft's Office of the CTO and brings a deep “better-formed humans” conviction to the AI conversation. We draw a hard line between intelligence (statistical knowing) and insight—where a human knower makes the categorical leap to “this is true,” what Taylor calls grasping the “virtually unconditioned.” We talk about how LLMs can pattern experience to help us reach insight but can't replace judgment, and why venture building should be anthropology-first: every product ships an implicit view of the human person. We cover the risk of using AI as an oracle that shortcuts productive struggle (especially in education), the importance of humility and sustaining the tension of inquiry for product-market fit, and Taylor's “cold storage” idea—using AI as a context engine to shelve, monitor, and revive ventures when conditions change. We close on the key builder question: not what can we build, but what ought we build?02:08 Intelligence vs Insight02:58 Statistical Knowing05:02 Virtually Unconditioned09:02 Using AI Without Outsourcing Judgment11:39 Formation in Venture Building14:19 Anthropology First Product Design17:56 Hard Rules for Human Flourishing18:53 What Ought We Build21:20 Humility and Idea Flow Playbooks24:19 Probabilistic Products and Implicit Anthropology28:48 AI as Oracle in Education34:29 Cold Storage for Venture IdeasConnect with Taylor: • https://substack.com/@pourbrew• https://www.linkedin.com/in/blacktaylor/ • https://leonum.catholic.edu/• https://innovate.pourbrew.me/Connect with Raul: • Work with Raul: https://dogoodwork.io• Free Growth Resources: https://dogoodwork.io/resources• Connect with Raul on LinkedIn (DMs open): https://www.linkedin.com/in/dogoodwork/ 

Security leaders count open vulnerabilities in the hundreds of thousands, and in some organizations the number runs past a million. Ondrej Vlcek, Co-Founder and CEO of AISLE, describes teams with no practical route through that backlog while attackers use automation to shrink the time between a disclosure and a working exploit. The question worth asking is what a program looks like when remediation moves at the same speed as exploitation. What makes AI-driven remediation different from static code analysis? Reasoning replaces pattern matching. Linters and commercial scanners flag code that resembles a known error shape, while a reasoning model infers what the developer intended, compares that intent against the actual implementation, and evaluates how the gap could be abused. Ondrej Vlcek points to business logic flaws, timing errors, and race conditions as the classes that pattern matching leaves untouched. The judgment behind AISLE comes from a long run in the industry. Ondrej Vlcek wrote device drivers for Windows 95 in 1995 at a seven-person antivirus company called Avast, stayed more than twenty-five years, moved through CTO and COO into the CEO seat, and took the company public before its sale to NortonLifeLock in 2022. He co-founded AISLE in 2024 with Jaya Baloo, a three-time public company CISO, and Stanislav Fort, an AI researcher who worked at DeepMind and Anthropic. Why does the software supply chain deserve the larger share of attention? Because most of the code in a running application was written somewhere else. Ondrej Vlcek puts the typical enterprise application at roughly ten percent first-party code and ninety percent open source and dependency code, which is also level ground for an attacker reading the same source and pointing the same models at it. Reachability analysis becomes the deciding factor, separating the vulnerable functions your code actually calls from the thousands of transitive dependencies it never touches. For first-party code, AISLE closes the loop differently: read the documentation, the architectural material, and the threat model, then generate a patch aligned with the project's own conventions and test it automatically. The standard Ondrej Vlcek sets is a fix that reads as though a human maintainer wrote it. The customer spread runs from embedded firmware at Bose to smart contracts at the Ethereum Foundation, where heavily audited and sometimes formally verified code still benefits from another set of checks because the systems touch money flows directly. This is a Brand Spotlight. A Brand Spotlight is a ~15 minute conversation designed to explore the guest, their company, and what makes their approach unique. Learn more: https://www.studioc60.com/creation#spotlight GUEST Ondrej Vlcek, Co-Founder and CEO of AISLE On LinkedIn: https://www.linkedin.com/in/ondrejvlcek/ RESOURCES Learn more about AISLE: https://aisle.com Meet AISLE at Black Hat and DEF CON in Las Vegas: https://aisle.com/black-hat The AISLE platform: https://aisle.com/platform AISLE CVE discoveries: https://aisle.com/cve-discoveries Are you interested in telling your story? ▶︎ Full Length Brand Story: https://www.studioc60.com/content-creation#full ▶︎ Brand Spotlight Story: https://www.studioc60.com/content-creation#spotlight ▶︎ Brand Highlight Story: https://www.studioc60.com/content-creation#highlight KEYWORDS ondrej vlcek, aisle, sean martin, brand story, brand marketing, marketing podcast, brand spotlight, vulnerability management, vulnerability remediation, agentic ai, cyber reasoning system, software supply chain security, reachability analysis, open source security, application security, first-party code, third-party dependencies, static code analysis, zero-day vulnerabilities, ai in cybersecurity, code patching, embedded firmware security, smart contract security Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

She credits three people with transforming her career trajectory at AWS and beyond. Tatiana got her into AWS. Wayne sponsored her advancement within it. Dan helped her break into venture capital as a partner at Felicis Ventures. She did not stumble into these relationships. She built them intentionally, maintained them with discipline, and gave back at every stage — even when what she could give seemed small compared to what she was receiving. Nancy was Director and General Manager at AWS Data Protection when this episode was recorded. She has since been promoted to CTO. She is also the founder of Advancing Women in Tech (AWIT), a venture partner at Felicis Ventures, and served on the board of UPenn's School of Engineering Online. She gave the commencement speech at the University of Pennsylvania. The central idea of that speech: build your personal board of directors. In this episode, she breaks down the full framework. You'll learn: Why she calls her personal board of directors the most important career strategy she has used, and what it gave her that mentors, managers, and luck could not. The three specific people on her board, what each one did for her, and how those relationships were built over time rather than asked for upfront. The right way to ask for raw, unfiltered feedback from someone who outranks you significantly — including why the first or second meeting is almost never the right time, and what you need to establish first. Why follow-through is a bigger differentiator than IQ, communication skills, or credentials. "They need to want it more than you want it for them" — the advice from her own board member that she now uses with every mentee she works with. How compound interest applies to professional relationships: why small, consistent gestures build more than a single impressive one, and what she does quarterly to keep her board relationships healthy without it feeling transactional. She was preparing to meet a Fortune 500 CEO to ask him to join her board. His dog had just had surgery. She planned to bring dog treats. The reminder: every successful person is still just a human being, and treating them that way is both the right approach and the most effective one. The Lululemon wardrobe mistake: her first Silicon Valley job, she bought a whole new wardrobe to fit in with the casual culture. Hated it. Didn't feel herself. What she learned about knowing who you are and using that as a career filter rather than a liability. Why at her leadership level she says no far more often than yes, why she uses Amazon's "have backbone, disagree and commit" principle to push back when the room disagrees with her, and what she tells her mentees about having the courage to hold the unpopular opinion. About Nancy: At the time of this recording, Nancy was Director and General Manager, AWS Data Protection at Amazon Web Services. She has since been promoted to CTO. She is also the founder of Advancing Women in Tech (AWIT), a venture partner at Felicis Ventures, and has served on the board of directors of the UPenn School of Engineering Online. AWIT's Coursera curriculum has reached tens of thousands of learners globally. Advancing Women in Tech: https://www.advancingwomenintech.org/

Wayne Cartmel grew up on a small farm in the Lake District region of northwest England and was selling chickens by the age of four. He trained as a maths teacher in Bedfordshire and could not believe the process he had to go through to apply for jobs — hours of Word-based application forms, one after another. He asked why nobody had digitized it, and then decided to do it himself. Funded by a £5,000 innovation voucher and built with a computer science volunteer who is still his CTO eleven years later, it took two years to reach a working prototype. Wayne took no funding, went over £100,000 into personal debt, and did not draw a livable salary for several years. MyNewTerm is a specialized hiring marketplace and applicant tracking system that connects schools across England directly with job seekers. It allows educational employers to post vacancies and manage candidates using a streamlined workflow that supports part-time, full-time, and temporary roles.  MyNewTerm now partners with over 6,000 schools and 500 multi-academy trusts, has surpassed £5M in revenue, and processes over 100,000 candidate applications a month with just 20 employees. It holds roughly 45% market share among multi-academy trusts against a private-equity-backed incumbent. Key Takeaways Distribution Wins — Anyone can build a product now; almost nobody can get it into customers' hands. Start Absurdly Small — He targeted five schools in one district of Luton, then moved to the next. Free Buys Evidence — Schools wouldn't pay for an unproven marketplace, so he gave it away to prove it worked. Focus Compounds — Sticking to the core, not chasing adjacent opportunities, is what built the market share. Hard Equals Defensible — The marketplace was brutal to start, which is exactly why nobody can replicate it. Quote from Wayne Cartmel, Founder and CEO of MyNewTerm "Distribution and execution are everything, because the market nowadays is going to be flooded with software products, EdTech in particular. The advancements in AI mean that you can spin up products really quickly. I almost wish that was available ten years ago when I was starting as a non-technical founder.  "Building the product is the easy bit; I thought it would be the hard bit. What I failed to realize, and I wish somebody had told me, is that it's actually the distribution and the sales and marketing, the go-to-market motion, that's the really tough bit, doubly hard with a two-sided marketplace.  "You can build a product on such a small budget now, but you've got to be really deliberate and disciplined to keep on going and generate momentum. That's why many don't make it: they don't have the ability and resilience to get through the really hard moments when people are continually saying no to you, and you're continually being rejected." Links Wayne Cartmel on LinkedIn MyNewTerm on LinkedIn MyNewTerm website Podcast Sponsor – Vista Point Advisors This podcast is sponsored by Vista Point Advisors, a leading investment bank for founder-led software, AI, and internet companies. Vista Point works exclusively on the sell side, providing unconflicted M&A and capital raising advice to help founders maximize business value, evaluate their options, and realize ideal outcomes.   The Practical Founders Podcast Tune into the Practical Founders Podcast for weekly in-depth interviews with founders who have built valuable software companies without big funding. Subscribe to the Practical Founders Podcast using your favorite podcast app or view on our YouTube channel. Get the weekly Practical Founders newsletter and podcast updates at practicalfounders.com. Practical Founders CEO Peer Groups Be part of a committed and confidential group of practical founders creating valuable software companies without big VC funding.  A Practical Founders Peer Group is a committed and confidential group of founders/CEOs who want to help you succeed on your terms. Each Practical Founders Peer Group is personally curated and moderated by Greg Head.

Most voice AI startups today are thin wrappers on someone else's models. Ayooluwa Odemuyiwa went the opposite direction and built the entire stack.In this episode, Justin sits down with the CTO and co-founder of Aethex AI, who along with co-founder Mariama is building the voice layer for emerging markets across Africa and the Middle East. This is the AI that banks, call centers, and telcos use to reach the customers a human team never could, and it's already running 17,000 calls a day.Ayooluwa takes us through her path from Caltech physics to Meta to Stanford to founder, and unpacks the decision that defines the company: in her markets, you aren't competing against other software, you're competing against the cost of human labor. That single reality is why Aethex owns everything from data collection to model serving to deployment, so they can pull every lever on cost and latency.We also get into why building for the harder market first reveals things a Western-first founder never sees, how the forward deployed engineer became their most valuable role, and why in a market this new, what you're really selling is trust.A conversation about infrastructure, conviction, and betting on the markets everyone else overlooked.

What if the company quietly making OpenAI, Google, Anthropic, and Meta's models smarter was founded in India?Turing is one of the companies shaping how AI is advancing. It started in 2018 as a talent platform that found the top 1% of the world's engineers, became a unicorn in 2021, and then made a bet almost nobody understood at the time. In early 2022, long before ChatGPT existed, Turing began helping OpenAI improve its models by feeding human expertise directly into training. Today its network of more than four million vetted engineers and domain experts powers the post-training and evaluation work behind the frontier labs, and the company crossed roughly 300 million dollars in revenue while staying profitable, at a 2.2 billion dollar valuation.Vijay Krishnan is the co-founder and CTO. He was an NLP researcher at Stanford back when almost no one believed that predicting the next word could ever turn into reasoning, and he explains why running a modern model company without human-in-the-loop data is like entering a race with three tyres instead of four. He walks through how a model is actually taught to use software like Salesforce, why coding became the beachhead for every lab, and what changed for Turing the moment Scale AI was absorbed into Meta.The conversation then turns to the question every founder is now asked in the room. What is your moat against Claude? Vijay's answer is to go deeper than the frontier labs can reach, into the outcome you own and the context that lives inside an enterprise.If you are excited about how AI actually gets built, who really trains the models, and how to build a company that survives the labs, this episode is for you.00:00 - Trailer02:20 - The Indian company quietly behind OpenAI, Google, and Anthropic04:50 - How Turing went from a talent platform to a unicorn to an AI research partner08:20 - The bet nobody understood11:50 - Why a model company without human data is "racing on three tyres"15:50 - Why coding became the beachhead for every frontier lab19:50 - What changed for Turing the day Meta bought Scale AI23:50 - "What is your moat against Claude?"29:50 - Will AI create more lawyers, not fewer?34:50 - The teams where engineers haven't written code in six months39:50 - 16% of the Philippines' GDP is under threat from AI?43:50 - How you actually teach a model to use Salesforce49:50 - How robots are taught real-world work54:50 - Why million-dollar researcher packages are breaking startup hiring59:50 - The one kind of AI company that gets stronger as the models improve1:04:50 - Product vs. services, and the trap that quietly kills AI startups-------------India's talent has built the world's tech—now it's time to lead it.This mission goes beyond startups. It's about shifting the centre of gravity in global tech to include the brilliance rising from India.What is Neon Fund?We invest in seed and early-stage founders from India and the diaspora building world-class enterprise AI companies. We bring capital, conviction, and a community that's done it before.Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we're doing it all at Neon.-------------Check us out on:Website: https://neon.fund/Instagram: https://www.instagram.com/theneonshoww/LinkedIn: https://www.linkedin.com/company/beneon/Twitter: https://x.com/TheNeonShowwConnect with Siddhartha on:LinkedIn: https://www.linkedin.com/in/siddharthaahluwalia/Twitter: https://x.com/siddharthaa7-------------This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.Send us Fan Mail

What does it mean to balance old school values with the rapid advancements of technology? In this episode of Better Call Daddy, host Reena Friedman Watts welcomes tech expert Oshri Cohen, who delves into the importance of maintaining traditional values in a world increasingly dominated by AI and digital innovation. Oshri shares his journey from a young coder to a fractional CTO, discussing how his unconventional beginnings shaped his approach to technology and business. He emphasizes the significance of creativity in an age where AI is often seen as a replacement for human ingenuity. The conversation touches on the challenges of parenting in the digital age, particularly when it comes to navigating platforms like YouTube, and how his new product, Watchly Player, aims to create a safer viewing experience for children. Reena and Oshri explore the evolving role of a CTO, the pitfalls of corporate culture, and the necessity of kindness in leadership. Oshri's insights challenge listeners to rethink their relationship with technology and the impact of family dynamics on personal and professional growth.   Oshri Cohen is an AI-native Chief Product & Technology Officer who helps companies build software the way modern teams actually should. Over 25 years in software — 20 of them in technology leadership — he has made AI-native transformation his focus: rewiring how engineering organizations plan, build, and ship, not just bolting AI features onto old workflows. He leans on cloud-native architecture, DORA metrics, and GitOps to turn slow, siloed teams into fast, measurable product engines. His range is unusually broad. Since 2018 he has served as fractional and interim CTO to more than 30 companies, almost all US-based, and at his peak directed 12 engineering teams across seven countries. He has shipped more than ten digital products across healthtech, e-commerce, manufacturing, logistics, and finance. A McGill business grad who taught himself to code at 13, Oshri leads business-first — every technical decision starts at the P&L, never the other way around.

"Back in the 1900s when I was crossing the Great Plains in a covered wagon, programming in the back, the cover headline was: Software Development is Dead."I talked with Anthony Jackson, a CTO with 30 years across healthcare tech and enterprise software and author of the Architecture Protocol series, on Startup Hustle this week. Anthony is the creator of LeadershipOS, a framework for building teams that keep running when the leader isn't in the room.Here's what you'll get out of it:⚡ Why "software development is dead" has been a headline for 30+ years, and why the human judgment layer never goes away⚡ Why the real gap isn't more engineers, it's product people (and engineers who think like them)⚡ What actually changes when you go from individual contributor to manager, and why almost no company trains you for it⚡ Why every line of code still needs a name attached to it, especially in regulated industries⚡ How "lossy compression" quietly ruins decisions as they filter up and back down through management⏱️ Episode Breakdown00:32 Introduction and Anthony Jackson's background02:13 Is software development dead again?03:14 The impact of AI on coding and human judgment04:07 The importance of responsibility in software development05:59 The challenge of product management and customer feedback10:18 Transitioning from individual contributor to manager11:36 Building effective teams and leadership culture14:41 Anthony Jackson's leadership OS book and approach18:26 The significance of company and team culture21:07 The impact of good and bad managers21:38 Anthony Jackson's newsletter and coaching23:14 Connecting software developers with customers25:06 Empathy for users and understanding their experience28:18 Where to find Anthony Jackson's resources and booksLinks & ResourcesConnect with Anthony Jackson on LinkedInAnthony Jackson's Website - https://technicaleader.coachWhat Smart CTOs Are Doing Differently With Offshore Teams in 2025Subscribe to the Global Talent SprintFull Scale – Build your dev team quickly and affordablyIf you're trying to get your team out of the basement and into real product ownership, this episode is your playbook. Stop being a ticket factory. Build teams that think, create, and lead.Follow the show, rate it, and send this to someone who's still trying to do “real Scrum.” They need it more than you do.

AI can analyze enormous amounts of information, but more data does not always lead to better decisions.  In this episode of Leader Generation, Tessa Burg talks with Dean Smith, CTO at Credit Benchmark, about why accurate, trusted data matters more than ever and how poor-quality information can quickly lead AI further from the truth. Dean shares a practical way for businesses to make progress without trying to overhaul everything at once: start with one problem, bring together the data needed to solve it and build from there.  Listen to learn how your organization can improve data quality, show value sooner and create a more adaptable data-first culture. Leader Generation is hosted by Tessa Burg and brought to you by Mod Op. About Dean Smith: Dean Smith is Chief Technology & Product Officer at Credit Benchmark, where he leads the company's technology strategy, engineering, data infrastructure and platform development. He is responsible for scaling Credit Benchmark's technology platform and advancing its data capabilities to meet the evolving needs of global financial institutions, with a focus on strengthening the integration between product innovation, data infrastructure and client delivery.  Dean can be reached on LinkedIn. About Tessa Burg: Tessa is the Chief Technology Officer at Mod Op and Host of the Leader Generation podcast. She has led both technology and marketing teams for 15+ years. Tessa initiated and now leads Mod Op's AI/ML Pilot Team, AI Council and Innovation Pipeline. She started her career in IT and development before following her love for data and strategy into digital marketing. Tessa has held roles on both the consulting and client sides of the business for domestic and international brands, including American Greetings, Amazon, Nestlé, Anlene, Moen and many more. Tessa can be reached on LinkedIn or at Tessa.Burg@ModOp.com.

¿Qué ocurre cuando una inteligencia artificial clona tu voz sin permiso y empieza a publicar contenido que nunca has grabado?En esta tertulia de Itnig, Bernat Farrero conversa con Masumi Mutsuda, actor de doblaje, informático y CTO de Itnig sobre el impacto real de la inteligencia artificial en las voces, el doblaje y el trabajo creativo.Masumi relata cómo descubrió que habían clonado su voz como Silver, personaje de Sonic, para crear vídeos completamente ajenos a él. A partir de su experiencia y de su trabajo con el Sindicato de Actores de Voz de Barcelona, explica cómo cientos de profesionales han encontrado sus voces en plataformas de IA sin haber dado su consentimiento, qué pueden hacer para retirar ese contenido y por qué la tecnología avanza mucho más rápido que la protección de sus derechos.La conversación también aborda el papel de empresas como ElevenLabs, la diferencia entre una interpretación humana y una voz sintética y la pregunta que inquieta a toda la industria: ¿puede una IA llegar a reproducir todos los matices de un actor de doblaje? Más allá de la clonación de voz, Bernat y Masumi analizan la evolución de los agentes de IA, desde el uso de OpenClaw, Codex y ChatGPT para ejecutar tareas cotidianas hasta la traducción simultánea y los futuros pagos automatizados. También explican las diferencias entre modelos cerrados, open-weight y open source, el avance de la IA china y la visión de Elon Musk sobre un futuro marcado por la automatización, la renta universal y una abundancia sin precedentes. Una conversación sobre inteligencia artificial, clonación de voz, actores de doblaje, agentes autónomos y cómo nos relacionaremos con una tecnología que ya puede hablar, programar y actuar en nuestro nombre.

#291 - Bourse 2026 : PEA, CTO, Assurance Vie quoi choisir?Visuel : Masterclass dimanche 5 avril à 18h : https://www.fireclub.training/reussirmonpremierinvestlocatif-a09213a1-2Rejoindre le coaching : https://app.iclosed.io/e/fire/fireclub-inscriptionLes workshops : https://firefrance.substack.comHébergé par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

Why Making Complex Revenue Simple at Scale Requires More Than Throwing Contracts Into a Chat InterfaceGuest: Deepak Bapat, Co-Founder and CTO at TabsHost: Seth Earley, CEO at Earley Information SciencePublished on: July 30, 2026In this episode, Seth Earley speaks with Deepak Bapat, Co-Founder and CTO at Tabs, a revenue and accounts receivable management platform built for B2B companies. They explore why dropping contracts into a general-purpose AI tool is not a strategy for enterprise scale, what generative AI unlocked that OCR and legacy machine learning could never solve, why context engineering beat fine-tuning for contract extraction, and why newer and larger models are not always better for specialized tasks. Deepak shares candid and specific insights on building atomic AI pipelines, the provability requirement that financial compliance demands, and what finance and data leaders consistently underestimate before deploying AI on their contracts.Key Takeaways:Dropping contracts into a chat interface is a reasonable experiment but not an enterprise strategy - doing things at scale requires specific tooling, specific expertise, and integration across systems.The SaaSpocalypse framing misses the point - the more interesting question is not whether chat replaces UI, but how platforms can understand intent and preempt the actions users would otherwise have to click through manually.Generative AI solved the contract problem by reasoning over ambiguous natural language at document level - something OCR and rules-based systems fundamentally could not do.Context engineering beat fine-tuning at Tabs because merchant preferences vary so significantly that fine-tuning per merchant became cost-prohibitive - a well-prompted generalized model proved faster and more elastic.Newer and larger models are not always better for specialized tasks - Deepak's eval sets show that models from six months ago outperform newer versions on certain contract extraction jobs, likely due to overfitting on coding.Provability is the non-negotiable requirement in financial AI - it is not enough to produce correct output, you must be able to prove the output is correct and traceable back to the source contract.Organizations that want to deploy AI on their contracts first need to standardize internally on what outcomes they actually want - two people on the same team asking the same question about the same contract should not produce two different answers.Insightful Quotes:"The misconception is that difficult problems can just be solved by throwing something into ChatGPT and having the answer come out the other side. In our case, the at-scale piece is everything. Those intelligence tools are still individualized tools - to do things at scale for an entire enterprise still takes specific tooling, specific thought, and specific expertise." - Deepak Bapat"What we're trying to do is move from a place of unstructured data to provable and correct structured data. That is what Tabs is built around - and that is what most of these other systems simply cannot handle." - Deepak Bapat"When you think about the legacy players that were more rigid SaaS tools with manual entry and brittle connectors - what was intractable about that model is exactly what generative AI made solvable. The ability to reason over the words in a document, understand what they meant, and understand what the output should be - that changed everything." - Seth EarleyTune in to discover what it actually takes to build AI that is accurate enough, auditable enough, and elastic enough to handle enterprise revenue data at scale - and what most organizations underestimate before they start.LinksLinkedIn: https://www.linkedin.com/in/deepakbapat/Website: https://www.tabs.incThanks to our sponsors:VKTREarley Information ScienceAI Powered Enterprise Book

Artificial Intelligence is transforming business at an unprecedented pace.Cyber threats are evolving by the hour.Yet many leaders are still treating technology as an IT problem instead of a leadership priority.In this episode, we sit down with Ben Wilcox, CTO and CISO of ProArch, to discuss what executive leaders need to know about AI, cybersecurity, and building organizations that are resilient, scalable, and prepared for what's next.

Shaju Puthussery and Deepak Ramaswamy are the CEO and CTO of LightSpun, which is rebuilding the back-end engine of insurance processing as agentic AI infrastructure, starting in dental and moving into vision and ancillary benefits. Both came from Overjet, where Deepak was a co-founder and Shaju the first employee, and this conversation is largely about why they walked away from that thesis. Reading X-rays was the visible AI problem. Underneath it was a plumbing problem: claims that never reach clinical review because the documents were wrong, the provider record did not match, or the file never loaded cleanly.Two things in this episode surprised us. The first is that their most valuable asset was an accident. Shaju assumed credentialing was table stakes until a payer CEO told him it was blocking dentist onboarding, and one weekend later Deepak had an approach. That became the rail for roughly 87% of practicing dentists in the US and the provider data spine that feeds adjudication. The second is Shaju's answer to whether anyone profits from claim friction, which is not the cynical answer most people give.We discuss:Why Deepak argues the AI question is not either-or, and why world-class clinical review is worthless if the claim cannot get to itThe moment their business model was confidently wrong: they built for benefits configuration, customers came back asking about credentialing, duplicate records, and file loads, and a startup that planned to do one thing had to bet on tenWhy credentialing was never a Trojan horse for the provider data layer, how the same 200,000-dentist dataset gets monetized twice, and what obligation comes with being the thing the system quietly depends onThe honest ceiling on model performance: 85 to 90% out of the box, and why the climb to 98 or 99% production-ready is where the humans actually liveThe exact decision they will not automate, with the line drawn between deterministic denials (two cleanings a year, a $2,000 annual max) and anything touching a clinical outcomeWhy regulation, not technology, sets the pace, and how they take a faster primary source verification method to their internal NCQA leader with screenshots, timestamps, and source authenticity to prove it still holds upShaju's contrarian read on the $17 to $21 billion admin waste question: no one is winning from the friction, both sides are automating, and the real goal is shifting dollars from admin to careBringing fintech into adjudication with a benefits flex card that carries a Visa or Mastercard rail, blocks non-covered procedures at the chair, and opened doors to a vendor network of roughly 150 health plansThe discipline of not chasing every model release, what Hugging Face taught them early about picking bets, and why the architecture is built to swap foundation models out entirelyDeepak's pushback on the beachhead narrative: dental is several years behind medical, which means the solutions may not transfer cleanly, and they designed for vision and ancillary from day one rather than treating dental as a waypointWhy compliance came before the AI story, with SOC 2 Type 2, HITRUST, and NCQA in place first so they could get in the room with large payers at allThe legacy Deepak actually wants: recognized as the company that automated the boring and the safe, and left the critical decisions with people—Brought to you by: Sage Growth Partners — Value-focused strategy and marketing for growth-driven healthcare organizations.—Where to find Jared:• X: https://x.com/jaredstaylor• LinkedIn: https://www.linkedin.com/in/jaredstaylor/

Everyone has the same access to the same frontier models. So what's actually left to compete on? Jeremy Au moderates a panel at the Crosscurrents Summit in Parañaque on where enterprise AI adoption really stands. Aravind Kandiah is CTO and Co-founder of Bifrost, a robotics infrastructure company that simulates the world to evaluate robots. Its simulations power some of the largest robotics companies, from Mars exploration with NASA to high-risk industrial work. Bifrost is backed by Sequoia Capital, Lux Capital and Airbus Ventures. On the panel he splits enterprises into those running pilots to hit an R&D spend target and those facing a real forcing function, like Korea's birth rate leaving factories unstaffed. Only the second group ships. Jun Wakabayashi is a Venture Principal at AppWorks, one of Asia's leading accelerators and VC firms. He rose from Analyst in 2017 to Principal by 2023 and leads its Beacon Funds arm, a fund-of-funds backing emerging venture managers across Southeast Asia and web3. He holds a B.S. in Finance from NYU Stern and previously worked at PwC. He puts engineering at 60 to 80% of enterprise token spend and tracks teams accidentally burning $5 million a month. John Homer Alvero is Head of AI Engineering at Converge ICT, one of the Philippines' largest fiber broadband and digital infrastructure providers. An AWS architect across fintech, telco and gaming, he was previously Cloud Solutions Architect at SM Investments. His blocker isn't the technology: governance and cybersecurity teams can't write credible guardrails until they're AI-literate themselves. Where they split: Aravind says the moat is everything except the model. Jun says it's distribution, the one thing the labs lack. Crosscurrents Summit, presented by Clouted Watch, listen or read the full insight at https://www.bravesea.com/blog/enterprise-ai  BRAVE is Southeast Asia's leading tech podcast, hosted by Jeremy Au. Honest conversations with the region's top founders, investors, and operators on building startups in Southeast Asia. New episodes every week. Subscribe so you never miss one. Listen & Subscribe YouTube (English), YouTube (Bahasa Indonesia), Spotify (English), Spotify (Bahasa Indonesia), Spotify (Chinese), Spotify (Vietnamese), Apple Podcasts Follow BRAVE LinkedIn, X (Twitter), Instagram, TikTok, WhatsApp Follow Jeremy Au LinkedIn, X / Twitter, Instagram, TikTok, Facebook, Threads, Twitch Resources Get transcripts, startup resources & community discussions at www.bravesea.com #EnterpriseAI #AIStrategy #AIAdoption #BuildVsBuy #AIROI #PhysicalAI #Robotics #SoutheastAsia #TechPodcast 00:00 Introduction 00:40 Meet the panel 03:02 Is enterprise AI adoption actually real? 05:34 Engineers have stopped typing code 08:21 What's really holding enterprises back 10:30 How to measure ROI and cap token spend 15:32 Where the returns show up internally 18:36 Build or buy, and why services came back 23:23 Advice to a three-years-younger self 26:02 Model, brand, or distribution?

I spoke with Denis Mandich, CTO of Qrypt, about his former-CIA point of view about quantum and cryptography, how Qrypt generates identical keys at multiple endpoints, why a non-certified single QRNG isn't good enough, how the emergence of entanglement-based quantum networks would change his sales pitch, Nvidia's role in Qrypt's non-computing quantum technology, non-cryptographic QRNG applications, and more. Denis Mandich (LinkedIn) Qrypt (website) Qrypt (LinkedIn) Dragon Castle by Makai Symphony | https://soundcloud.com/makai-symphony Music promoted by https://www.chosic.com/free-music/all/ Creative Commons CC BY-SA 3.0 https://creativecommons.org/licenses/by-sa/3.0/ Dungeons And Dragons by Alexander Nakarada | https://creatorchords.com Music promoted by https://www.chosic.com/free-music/all/ Creative Commons CC BY 4.0 https://creativecommons.org/licenses/by/4.0/

Most conversations about exits focus on the seller. This one flips the lens. In this episode, Colleen O'Connell-Campbell  sits down with Liz MacRae, a serial entrepreneur who has both exited and acquired multiple businesses, and who is now co-founder of Village Wellth - a tech-enabled platform helping aspiring entrepreneurs buy established businesses and helping founders exit well. Liz introduces the growing movement known as Entrepreneurship Through Acquisition (ETA): buying a profitable, established business rather than starting from scratch or buying a franchise. She explains how the model works, who it attracts, what buyers actually look for, and why acquisition entrepreneurs - people who intend to roll up their sleeves and run the business themselves - may be exactly the right buyers for owner-dependent small businesses that private equity would walk away from. With a massive wave of business transitions coming over the next decade, this episode offers founders a fresh perspective on who might buy their business, and why starting early is everything.   Key Takeaways:   Liz's path is unconventional - a fine arts degree and training in creative thinking, not accounting or law. After exploring family succession (which did not work out), she and her husband bought a franchise, then she became a business broker, moved into exit planning advisory, took over the firm she worked with, sold it after about four years, and founded Village Wellth on the buy side. She has spent nearly 10 years in business advisory and six years focused exclusively on helping buyers.   Entrepreneurship Through Acquisition (ETA) is the act of buying an established business, usually leveraging senior debt or outside investment, and in most cases acquiring 100% of the business so the previous owner can retire. It lets a buyer skip the startup stage by three to five years and acquire something already profitable - able to service debt and pay a living wage.   ETA attracts people later in their careers - often leaving corporate roles - with management or leadership experience and established personal finances. They typically combine personal savings with bank debt or raised capital (family and friends, angel investors, or funds) to acquire and grow businesses from retiring owners.   Village Wellth was founded six years ago as a two-sided marketplace, then substantially rebuilt about two years ago with deal-management tooling and an AI layer. It has a team of 10, including a former RBC/TD commercial banker and a strong CTO. The platform showcases anonymous buyer profiles so sellers can see there are real buyers - answering the anxious question Liz heard constantly as a broker: "Is there even anyone out there to buy my business?"   The platform equips first-time buyers with tools to analyze opportunities, assess risks, and model deal structures - cash in, cash at closing, bank financing, seller financing, free cash flow, and return on investment - so they can move toward a lender application. The goal is a start-to-finish, self-serve experience on a monthly subscription, with hands-on services available when needed.   The sweet spot: profitable companies showing at least $100,000-$150,000 in profit after paying the operating owner, typically valued between $500,000 and $5 million (under roughly $2 million EBITDA), with five to 30 employees. These fall below the threshold where investment bankers and mid-market M&A firms - and private equity - typically engage. Village Wellth is Canada-wide and expanding into the U.S.   Village Wellth is especially valuable in rural communities, which often lack access to the M&A community. The platform matches buyers and sellers on geography (buyers set travel radii), and connects rural sellers with the right sell-side advisors and a pool of buyers they could not otherwise reach.   A key differentiator: because acquisition entrepreneurs plan to operate the business themselves, owner-dependency is not necessarily a deal-breaker - unlike with private equity or strategic buyers who want a management team that stays. What matters most is a solid transition period, a previous owner willing to transfer knowledge and relationships, and a genuine match between the buyer's background and the business.   Owner-dependency still needs managing. Red flags include an owner working 80 hours a week as the bottleneck for every decision, no chain of command, no contracts, and project-based revenue. Reasonable owner hours, contracts with assignment clauses, and understandable customer pipelines make a business far more transactable. Buyers mitigate remaining risk by bringing in a salesperson, or through deal terms like higher seller financing.   A successful exit is about understanding your options early enough to protect your value, legacy, and choice. Sometimes the best path forward is not the most obvious one, and selling to an acquisition entrepreneur may be exactly the thoughtful transition you are looking for. If today's episode sparked questions about your readiness, your business value, or your personal wealth gap, book a one-on-one Wealth Gap Analysis with Colleen O'Connell-Campbell - and tap into a whole ecosystem of professionals she'd be happy to introduce you to. Reach out on LinkedIn or email.   Please leave a five-star rating and review - it helps more business owners discover the show and build their path to a cash-rich exit. *** The Cash Rich Exit Podcast is brought to you by O'Connell-Campbell Wealth Management at RBC Dominion Securities.   All opinions expressed by the host, Colleen O'Connell-Campbell, and podcast guests are solely their own opinions and do not reflect the opinion of RBC Dominion Securities.   This podcast is for informational purposes only before taking any action based on information in this podcast you should consult with a qualified professional.   Colleen O'Connell-Campbell is a Wealth Advisor at RBC Dominion Securities, a member of the Canadian Investor Protection Fund.

You know how some animals do certain things just because they can? You might be pulling off the startup equivalent. Are you wasting opportunities or stressing yourself out just because of momentum or the coolness factor? More in this week's episode.Grab a copy of my books, Capitalizing Your Technology and  The Tech Executive Operating System.Subscribe to the best newsletter for tech executives.For any questions or comments, reach out to me directly: aviv@avivbenyosef.com

Hackers target Thailand's Ministry of Finance with an autonomous AI agent.A new industry alliance hopes to improve AI security. Golden Chickens lay four new malware families. GitHub and PyPI introduce time-based safeguards. SourTrade malvertising builds malware directly inside a victim's browser. Attackers target credentials of traveling corporate employees. EDR shutdown is now par for the course for leading ransomware groups. Russian threat actors exploited a Zimbra vulnerability for at least five months before it was patched. Monday business briefing. Our guest is Krishna Sai, CTO at SolarWinds, with security lessons learned from the World Cup. When the feed ends, the fun begins.  Remember to leave us a 5-star rating and review in your favorite podcast app. Miss an episode? Sign-up for our daily intelligence roundup, Daily Briefing, and you'll never miss a beat. And be sure to follow CyberWire Daily on LinkedIn. CyberWire Guest Today we are joined by Krishna Sai, CTO at SolarWinds, discussing the security risks around the World Cup and how this affects IT teams as they try to manage the growing digital traffic sprawl surrounding the event. Selected Reading Hackers used autonomous AI agent to spy on Thailand's finance ministry (The Record) Nvidia and Tech Giants Launch AI Security Alliance (SecurityWeek) Golden Chickens malware-as-a-service resurfaces with four new families (SC Media) GitHub, PyPI add time-based defenses against supply chain attacks (Bleeping Computer) SourTrade Malvertising Campaign Secretly Builds Malware in the Browser (Infosecurity Magazine) Hacked Public Wi-Fi Gateways Used to Harvest Corporate Credentials (SecurityWeek) Ransomware Groups Increasingly Deploy EDR Kill Techniques (Infosecurity Magazine) TA488 Targets Zimbra Mailservers with Half-Click Exploits IProofpoint) Endpoint security firm Glow emerges from stealth with $180 million. (N2K Pro Business Briefing) Being a Luddite Is Fun Again (404 Media) Share your feedback. What do you think about CyberWire Daily? Please take a few minutes to share your thoughts with us by completing our brief listener survey. Thank you for helping us continue to improve our show. Want to hear your company in the show? N2K CyberWire helps you reach the industry's most influential leaders and operators, while building visibility, authority, and connectivity across the cybersecurity community. Learn more at sponsor.thecyberwire.com. The CyberWire is a production of N2K Networks, your source for strategic workforce intelligence. © N2K Networks, Inc.

This is a rerun of episode 331. In this episode, Dave and Jamison answer these questions: Listener ninjamonkey says, I am a new grad who is half a year into the role now at a very large company. Recently, a senior engineer on my team asked me to create a ticket for an infra team for a problem with a service. I provided logs and steps to reproduce the issue and did a health check before submitting. Right after, the manager of the team put me into a group chat with their team, asked why I created the ticket and told me to start doing my job and they can't debug for me. From these interactions and comments on the ticket, it feels the infra team will likely not work on the tickets I report or de-prioritize them. This has left me discouraged and hesitant. I will have to do lots of this kind of infrastructure work in the future. Additionally, one of the goals my manager set for me is to work with more external teams for the upcoming year. What do I do here? Do I tell my manager about these interactions? Do I tell my team lead, staff/seniors to swap out for different kind of story? I work for a small startup. I was the first employee other than the 2 founders. Being the first developer hired, naturally means I have the most knowledge about our application. I also have good organisational skills, which has led to me becoming and being referred to as the “Lead Developer”. I have recruited 2 of the 3 new developers, and have trained both of them and got them up to speed. At first I was pleased with the progression and was keen to grow into the position, and told the founders so. Since then, I have changed my mind, I don't want to be the lead - due to the following: The communication is absolutely pitiful. Any questions we ask of the founders we get about a 30% reply rate no matter the form of communication. We get poorly defined tasks and requirements The CTO will just blast through some of our features over the weekend and say here I fixed it for you I don't want to quit my job (just yet… its a comin though). I have actually discussed the above points with them, but I know these 2 founders will never change their ways. How do I tell them I just want to go back to being an Individual Contributor like my Employment contract states?

In this episode of Alexa's Input (AI), I sit down with Alex Zenla, founder and CTO of Edera.Alex grew up in a small town in Alabama, found a computer young, and started building. Her story is unlike many in tech. She taught herself to program and got a job in tech at 14 years old. Since then, she's been actively building and involved in open source. She's currently the founder and CTO of Edera, a company whose product integrates security into the lowest layers of the platform without sacrificing performance or velocity.In this episode, we get into where that path started, what it costs to be different in founder and venture rooms, and what breaks when infrastructure still ships with security off by default.From the episode:Growing up in small-town Alabama without a path into techSouthern niceness as theory versus practiceFull-time work at fourteen and presenting to executives as a teenagerBeing one of very few trans founders in venture rooms, and the tension between visibility and being treated as a tokenElevator pitches that change with the audienceDetection and response after a problem has already occurredCommon Vulnerabilities and Exposures becoming untenable when tools like Mythos surface hundreds of findings per project per dayKubernetes and vendors selling yet another layer while the foundations underneath are misalignedSecure defaults as the path of least resistance for teams that just need a cluster that worksAlex's mission is to make secure computing the default. Today you work hard to get a secure environment, and she's building Edera to invert that. What stays with you is how personal that work is for her. The path from a small Alabama town into those rooms is not separate from the product. It's why the default being broken bothers her enough to build a company around fixing it.GENERAL PODCAST LINKSWatch: https://www.youtube.com/@alexasinputRead: https://alexasinput.substack.com/Listen: https://creators.spotify.com/pod/profile/alexagriffith/More: https://linktr.ee/alexagriffithLEARN MORE ABOUT THE HOSTWebsite: https://alexagriffith.com/LinkedIn: https://www.linkedin.com/in/alexa-griffith/FIND OUT MORE ABOUT THE GUESTLinkedIn: https://www.linkedin.com/in/azenla/Bluesky: https://bsky.app/profile/alex.zenla.ioEdera: https://edera.dev/GitHub: https://github.com/edera-devRESOURCESEdera docs: https://docs.edera.dev/

Why do so many enterprise AI initiatives begin with impressive demonstrations but struggle to produce measurable business value? In this episode of Tech Talks Daily, I speak with Dom Selvon, CTO and value partner at Valiance, about enterprise AI ROI, outcome-based consulting, build versus buy decisions, proprietary data, ontologies, and governance. Valiance is an AI-native consultancy that charges against client outcomes rather than hours worked. Dom explains why his "value partner" title is deliberate. The company begins by identifying the financial or operational result a client wants and connects its own compensation with achieving that result. Dom argues that many AI initiatives begin without a clear definition of success. The pressure to adopt AI is real, but companies frequently select technology before agreeing on the business problem, desired outcome, or measurement. He identifies three recurring mistakes. The first is framing the project around AI rather than the business need. The second is failing to establish a metric and baseline before work begins. The third is using a consulting model that rewards billable time without connecting payment to the client's result. We also discuss how generative AI is changing traditional build versus buy decisions. Companies historically bought software because custom development was slow, expensive, and difficult to maintain. Coding agents can now reduce the time and cost required to create software for specific internal needs. Dom does not believe SaaS will simply disappear. However, vendors selling convenience, workflow wrappers, or integration glue face new competition from customers who can create similar capabilities themselves. He argues that stronger SaaS positions will depend on assets a model cannot easily regenerate, including proprietary data, networks, regulatory standing, and deep workflow adoption. This leads to a wider discussion about competitive advantage. When companies have access to similar models, generated code begins to converge. Dom believes lasting differentiation comes from company data, institutional knowledge, connected systems, employee experience, and the semantic context surrounding that information. Dom explains why ontologies matter to enterprise AI. Raw data tells an agent what is stored in a particular field. An ontology describes the customers, orders, contracts, payments, relationships, and business rules represented by that data. This context allows people and agents to reason about information in a way that reflects how the company actually works. Governance also needs to be designed from the beginning. Dom argues that security, permissions, accountability, and compliance allow successful pilots to expand without forcing the business to rebuild everything later. How can leaders tell when AI is genuinely being adopted? Dom offers a surprisingly simple signal: people stop talking about AI. The technology becomes part of ordinary Monday morning work, and employees focus on completing the task rather than explaining the tool. Has your company defined the business result, measurement, proprietary context, and governance required to turn AI enthusiasm into operational value? Listen to the episode and share your thoughts with me.

Eran Galperin is a Brazilian jiu-jitsu black belt who had already had one VC-backed marketplace failure when he started Gymdesk. Originally called Martial Arts on Rails, it launched in 2016 as a naive version of what he thought a gym needed. He was training five or six times a week and every gym owner he knew hated the software they used. For four years he couldn't acquire customers, so he took a job as CTO of an e-commerce company and built the product on nights and weekends. Growth finally came through organic SEO, which still drives over half of new leads. He hit $3M in ARR by the end of 2023 with 16 employees, no salespeople, and over 40% of free trials converting without a demo. In May 2024 he sold a majority stake to Five Elms Capital for $32.5M in cash for his share. What they paid the premium for wasn't size — it was churn under 1% a month, three straight years of more than doubling, profit margins over 50%, and a payments business compounding underneath. He stayed on eighteen months and now lives in Tokyo, building a custom house and an AI vision product for real estate. Key Takeaways Churn Ceiling — Churn is the cap on growth; under 1% monthly is what buyers pay premiums for. Slow Bake — Four years of nights and weekends let the product mature in ways funded companies never can. Payments Compound — Profit share from payment providers grows as volume grows, and buyers pay extra for those rails. Buyers Differ Wildly — One expert said 5X was his cap; Five Elms paid 10X because they buy outcome, not value. Get Representation — A $60K legal bill and a good M&A broker closed the information asymmetry with private equity. Quote from Eran Galperin, Founder of Gymdesk "What we did have was very low churn, and that's one of the factors that helped us get the premium when we sold the company. Everybody building SaaS eventually realizes that churn is the cap your company has on growth. Eventually churn, which is a relative number, grows to the point where it meets the absolute numbers of your growth. "Because we had very low churn, less than one percent month over month, that definitely helped us start the conversation from a very good position. The other element was that growth was very consistent year over year. I think we more than doubled three years straight. "That in combination with the low churn and high profit margins was the last big item. We had a lean team, and we were over fifty percent profit margins when we sold. This was a firm that had multiple other portfolio companies similar to us, so they had a pretty good idea what a successful outcome would look like for them, and we filled all those criteria." Links Eran Galperin on LinkedIn Gymdesk on LinkedIn Gymdesk website Tinyseed.com website Five Elms Capital Podcast Sponsor – Full Scale This podcast is sponsored by Full Scale, one of the fastest-growing software development companies in any region. Full Scale vets, employs, and supports over 300 professional developers, designers, and testers in the Philippines who can augment and extend your core dev team. Learn more at fullscale.io. The Practical Founders Podcast Tune into the Practical Founders Podcast for weekly in-depth interviews with founders who have built valuable software companies without big funding. Subscribe to the Practical Founders Podcast using your favorite podcast app or view on our YouTube channel. Get the weekly Practical Founders newsletter and podcast updates at practicalfounders.com. Practical Founders CEO Peer Groups Be part of a committed and confidential group of practical founders creating valuable software companies without big VC funding.  A Practical Founders Peer Group is a committed and confidential group of founders/CEOs who want to help you succeed on your terms. Each Practical Founders Peer Group is personally curated and moderated by Greg Head.

Episode 662 features Erica, a peer support specialist and CTO with Calhoun County Consolidated Dispatch Authority, MI. Sponsored by RapidSOS - Facebook | LinkedIn | X | Web Episode topics – Erica's journey from the ER to a 13-year dispatch career Training philosophy: building trust, sharing mistakes, and modernizing the culture Public education efforts and common 9-1-1 misconceptions Burnout, boundaries, and the decision to reclaim personal well-being The shift toward hope, teamwork, and why this profession is still worth saving If you have any comments or questions or would like to be a guest on the show, please email me at wttpodcast@gmail.com.

Code review has always been a time sink. AI just makes the dysfunction undeniable.Luca Rossi, founder of Refactoring.fm and builder of the open source tool Tolaria, has been running one of engineering's most-read newsletters for five years, with over 170,000 subscribers. He's also been doing what a lot of engineering leaders talk about but rarely do: building a real product with AI agents to pressure-test what's actually possible today.In this conversation, Rob and Luca dig into the state of AI adoption at the midpoint of 2026; what high-performing teams are getting right, why most orgs are still just bolting AI onto a broken process, and why code review was already a questionable practice before AI came along. Luca also walks through the "guides, gates, and guards" framework he uses to keep AI agents productive and honest on Tolaria: the instructions that steer agent behavior, the deterministic hooks that catch what agents ignore, and the nightly reflection loops that catch the rest.Luca is the founder of Refactoring.fm, a newsletter and community covering software engineering and engineering leadership. He spent a decade as a CTO and startup founder before going independent, and now builds in public as both a writer and a solo product builder.In this episode:Why adopting AI without fixing your process just means moving faster in the wrong directionWhat the most mature engineering teams are doing differently in 2026The guides, gates, and guards framework for AI-assisted developmentWhy Luca has been a code review skeptic since before the AI eraHow building Tolaria became a way to get ground truth about what AI agents can actually doThe unexpected differences between running a startup and running an independent content businessSubscribe wherever you get your podcasts.

Dr Greg Charvat, CTO and co-founder of Teradar, joins Chris for a 5th appearance on The Amp Hour to talk about how terahertz frequency radar will revolutionize the automotive space and far outstrips the capabilities of LIDAR and Blobbology

For episode 755 of the BlockHash Podcast, host Brandon Zemp is joined by Andrew Nalichaev, a systems-level blockchain expert who serves as CEO of Haia — an AI-powered, non-custodial operating system for digital assets — and CTO of Haust Network, a ZK Layer 2 protocol built with Polygon CDK. He is also the Blockchain Domain Expert at Innowise, where he leads architecture and strategic engagements for fintechs, banks, exchanges, and institutional crypto clients — covering custody design, tokenization, DeFi infrastructure, custom blockchain builds, and the emerging class of AI-native financial products. Innowise architected and shipped the full engineering stack for both Haia and Haust Network, and Andrew's dual role bridges deep product ownership on the founder side with hands-on client delivery on the consulting side. Andrew combines a background in software engineering, applied mathematics, and securities and cryptocurrency markets to evaluate blockchain systems across five dimensions — architecture, incentives, resilience, market fit, and execution. Over 8+ years in finance, economics, and blockchain, he has evaluated 600+ blockchain business concepts, contributed to the launch of 4 L1/L2 ecosystems, and helped startups and established companies navigate the crypto space with sharp tech insight and hands-on business sense. Andrew is the author of unique strategies for working with DeFi protocols, and has designed and taught blockchain courses to 3,500+ students. Learn more about Andrew's work at andrewnalichaev.com, and about Innowise's blockchain and AI development expertise at innowise.com.

In this Sponsor Spotlight episode, Jeff Steadman flies solo and welcomes Greg Danyi, co-founder and CTO of P0 Security, to the show. Greg walks through P0's approach to runtime access control, covering how it applies to humans, non-human identities, and AI agents alike. The conversation digs into the difference between authentication and authorization, why zero standing privilege is more achievable now than before agentic adoption took hold, and how dynamic, evidence-based policies can reduce reliance on manual approvals. Greg also shares real examples, including row-level access control for data lakes and a CRM mishap that shows how easily agents can misinterpret intent. The episode closes with a look at where enterprise AI agent governance may be headed over the next few years, plus a lighter conversation about explaining IAM to a 10-year-old. This episode is made possible through the generous support of P0 Security as part of IDAC's nonprofit Sponsor Spotlight series. Learn more at p0.dev/idac.Connect with Greg (Gergely): https://www.linkedin.com/in/gergely-danyi/Learn more about P0: https://p0.dev/idac/Connect with us on LinkedIn:Jim McDonald: https://www.linkedin.com/in/jimmcdonaldpmp/Jeff Steadman: https://www.linkedin.com/in/jeffsteadman/Visit the show on the web at http://idacpodcast.com00:00 - Introduction and sponsor acknowledgment01:13 - Greg Danyi's path into IAM02:18 - What P0 Security solves for03:21 - Where P0 fits versus PAM and IGA04:46 - Agentic identity as a driver of adoption05:27 - MCP servers and unpredictable agent actions07:10 - Defining runtime access control08:50 - How authentication and authorization work together09:07 - Standing access versus expressed intent10:16 - Zero standing privilege in practice12:27 - Agentic identity as a distinct identity class19:24 - Automated evidence for approvals20:42 - Walking through a support agent example22:13 - Row-level access control for data lakes23:35 - Dynamic roles explained29:55 - CRUD risks and underestimated concerns31:32 - Human intent and giving agents clear direction36:32 - Where enterprise AI agent governance is headed39:36 - Advice for CIOs and CISOs getting started41:15 - Explaining IAM to a 10-year-old42:29 - Board games, dice, and calculated risk44:00 - Closing thoughts and where to learn moreKeywords: IDAC, Identity at the Center, Jeff Steadman, Jim McDonald, Greg Danyi, P0 Security, runtime access control, agentic identity, zero standing privilege, non-human identity, authentication, authorization, IAM podcast

AI agents have shown remarkable potential to function as persistent digital assistants that are capable of monitoring data, managing communications, and taking action autonomously over long periods. OpenClaw was one of the first serious attempts to fulfill that vision, connecting frontier coding agents to messaging platforms like Slack and WhatsApp and letting them run continuously in the background. However, OpenClaw largely set aside questions of security to pursue that vision, leaving credentials exposed in the agent’s environment and giving agents broad access to data and services far beyond what any given task required. NanoClaw is an open source project that takes a zero trust approach to agent orchestration. Rather than relying on instructions to constrain agent behavior, it isolates each agent in its own Docker container, keeps credentials entirely outside the agent’s environment, and enforces human-in-the-loop approval for sensitive actions. Gavriel Cohen is the founder of NanoClaw and he joins Kevin Ball to discuss the security architecture behind NanoClaw, how the agent sandbox and proxy model work in practice, how agents communicate with each other and with the host orchestration process, how the project approaches context window management and long-lived agent sessions, and more. Kevin Ball or KBall, is the vice president of engineering at Mento and an independent coach for engineers and engineering leaders. He co-founded and served as CTO for two companies, founded the San Diego JavaScript meetup, and organizes the AI inaction discussion group through Latent Space. Please click here to see the transcript of this episode. Sponsorship inquiries: sponsor@softwareengineeringdaily.com The post NanoClaw and the Rise of Personal AI Agents appeared first on Software Engineering Daily.

Some enterprises are finding reasons to pull back from a cloud-first IT strategy and run workloads in on-premises data centers. John and Johna dig into why companies are making the change, including cost and AI security. They also discuss and the strategic implications for IT, and what organizations stand to gain—and lose—from repatriation.  Episode Links:... Read more »

Some enterprises are finding reasons to pull back from a cloud-first IT strategy and run workloads in on-premises data centers. John and Johna dig into why companies are making the change, including cost and AI security. They also discuss and the strategic implications for IT, and what organizations stand to gain—and lose—from repatriation.  Episode Links:... Read more »

AI agents can't transform an org they can't see. Albert Strasheim, CTO at Rippling, joins Andrew Zigler to explain why agentic transformation starts with the employee graph, the system of record for who does what. He shares how Rippling assembles teams and primitives across silos, why evals are the new unit test, and how compensating controls keep AI output from turning into slop. When agents do the work, you still have to know who, or what, shipped it. LinearB attributes the work, whether it came from humans, AI assistants, or autonomous agents.Register today: The Engineering Productivity Gap live workshop on July 30Follow the show:Subscribe to our Substack Follow us on LinkedInSubscribe to our YouTube ChannelLeave us a ReviewFollow the hosts:Follow AndrewFollow BenFollow DanFollow today's guest:Rippling: Explore the workforce management platform at rippling.com Introducing Rippling Data Cloud: AI-powered BI that understands your workforceFollow Albert: LinkedIn OFFERSStart Free Trial: Get started with LinearB's AI productivity platform for free.Book a Demo: Learn how you can ship faster, improve DevEx, and lead with confidence in the AI era.LEARN ABOUT LINEARBAI Code Reviews: Automate reviews to catch bugs, security risks, and performance issues before they hit production.AI & Productivity Insights: Go beyond DORA with AI-powered recommendations and dashboards to measure and improve performance.AI-Powered Workflow Automations: Use AI-generated PR descriptions, smart routing, and other automations to reduce developer toil.MCP Server: Interact with your engineering data using natural language to build custom reports and get answers on the fly.

Infrastructure readiness has become the real bottleneck for agentic AI in healthcare, as enterprises confront the shift from systems that generate content to systems that execute tasks across complex, regulated workflows.   In this episode, Alex Tyrrell, SVP and CTO of Health at Wolters Kluwer, examines how agentic AI changes operational demands for healthcare organizations in conversation with host Matthew DeMello, highlighting the need for domain‑adapted reasoning, granular APIs, and stronger observability as agents drive higher‑volume system interaction.   He underscores the practical implications for leaders: preparing backend systems for agent‑driven load, adapting models to real‑world workflows, and avoiding monolithic architectures that limit safe, scalable deployment.   Learn how to evaluate AI vendors by assessing leadership expertise, and why funding benchmarks can signal product maturity and stability, download our free PDF report, "5 Ways to Select the Right AI Vendor," at emerj.com/aiv1  

I'm talking to Bhaskar Sunkara, CEO of bicycle.AI, which provides an AI analyst product designed to monitor revenue-critical KPIs, investigate the business and technical drivers behind KPI changes, and take a “governed next step.” Bhaskar explains why analytics products often fail when they overwhelm users with telemetry instead of focusing on the signals that matter. Drawing from his experience as founding CTO of AppDynamics, he shares how his team moved from low-level technical monitoring to business transactions like logins, checkouts, and bookings. The key lesson? Start with the right metric at the right level of granularity, then use deeper technical analysis to explain why something changed.   Bhaskar also breaks down how bicycle.AI serves multiple audiences inside an enterprise. Business leaders want measurable outcomes, KPI owners need answers about what changed and what to do next, and data teams require trust, governance, and traceability. He explains how, in order to support these different users, Bicycle separates product experience into four core surfaces: pull features like dashboards and chat, and push features like alerts and data stories. Alerts further help operational users respond quickly to KPI changes and data stories provide executives with strategic narratives around trends, causes, and business impact. During our chat, Bhaskar also draws a line most AI products blur: be explicit about which findings are deterministic and which are only a theory. He connects this directly to my CED framework, separating the conclusion from the evidence from the underlying data, and argues that how much you automate should be governed by one question: how costly is being wrong?   I also probed Bhaskar about their moat. He's learned that enterprise adoption requires winning over both executives who care about revenue impact and analytics teams that need confidence in the system's recommendations. Bhaskar also explains why their long-term advantage comes from the DEAL framework: Detect, Explain, Act, and Learn. By continuously incorporating validated decisions, business context, and customer-specific knowledge, the platform becomes more useful over time. We finish up with his advice for fellow analytical AI product founders, including why AI makes user experience more important, not less: it is the connection between agents, decisions, humans, and accountability.   Highlights / Skip to: Making the invisible feel urgent enough for customers to buy products (2:41) How to avoid creating the ‘metrics toilet' when the system can do so much (6:56) Designing for the end-user versus the buyer, especially during the POC phase (12:20) Thinking about the product's design in a way that ensures Bicycle's business value is obvious (15:38) How bicycle.AI's “push” and “pull” features help stakeholders see value (20:54) Getting their first 20 customers (25:19) What Bhaskar got wrong: over-rotating on the business buyer vs. the analytics team (32:23) The homework a build-anything horizontal platform imposes on customers (and Bicycle's vertical antidote) (34:30) Bicycle.AI's moat: compounding institutional knowledge (36:08) DEAL: Detect, Explain, Act, and Learn (40:46) How they designed the UX to reduce time-to-value during onboarding/setup (44:51) Bhaskar Sunkara's advice for other analytical AI founders (and why AI makes UX even more important to address) (47:47) Links bicycle.ai  Bhaskar Sunkara's LinkedIn  My CED framework for advanced analytics products that Bhaskar references in this episode

Some enterprises are finding reasons to pull back from a cloud-first IT strategy and run workloads in on-premises data centers. John and Johna dig into why companies are making the change, including cost and AI security. They also discuss and the strategic implications for IT, and what organizations stand to gain—and lose—from repatriation.  Episode Links:... Read more »

What if the future of analytics wasn't about building another middleware layer, but about getting closer to the actual business user? In this episode, Benjamin sits down with Chris Merrick, CTO and cofounder of Omni, to explore why semantic layers matter more than ever in an agentic world, how AI is reshaping embedded analytics and customer-facing data experiences, and the key strategies for keeping complex data models aligned across federated sources. Whether you're building analytics platforms, managing data infrastructure, or trying to make AI work at scale, this conversation is packed with practical insights on balancing governed analytics with exploratory AI, unifying disparate data sources, and capturing business intelligence beyond just the metrics in your warehouse. Tune in to discover how the next generation of analytics platforms will need to think about the entire business, not just the data.

Most of us approach a long break from work with some anxiety. Whether it's a layoff, parental leave, or a season of caregiving, there's tension around if and when we'll return to work and how we'll explain the gap on our résumé. DJ DiDonna, senior lecturer at Harvard Business School and author of the new book Big Time Off, wants to change that. This week, he joins Jessi to make the case that stepping away from routine work — for whatever reason, for however long — is one of the most strategic things you can do for your career and your life.  Jessi and DJ discuss: What a sabbatical actually is, and why two-thirds of them happen because of a negative catalyst, not a choice Why immediately job-searching after a layoff is like grocery shopping while hungry The difference between a vacation, a corporate "sabbatical," and the real thing, and why it takes six to eight weeks just to feel like yourself again What DJ calls "fertile emptiness," and why most of us never let ourselves get there How to use a sabbatical to run experiments on possible future versions of yourself The story of a CTO who went to Norway, built a text-to-speech app, and redesigned his entire relationship with work and money Why functional workaholism is the thing most of us are living with What AI has to do with the case for stepping back, and why learning from a place of fear versus curiosity makes all the difference How Jessi's own three-month hiatus from the workplace, during which she wrote a book and raised a newborn, turned out to be a sabbatical she didn't know she was taking How to start planning for a sabbatical five years from now, even if taking one today feels impossible Follow DJ DiDonna and Jessi Hempel on LinkedIn.

Episode summary: Five Pacific Northwest climate tech investors — recorded live at Pacific Northwest Climate Week 2026 — break down where climate tech venture capital is actually flowing this year, why Seattle still trails Silicon Valley on VC dollars, and what they're really evaluating when a founder walks into the room. The conversation applies directly to anyone raising capital, building a company, or job searching in a market where AI has made it easy to look good on paper and harder to stand out. Guest bios: ​Gabriel Scheer is Senior Director, Investments and Innovation, at Elemental Impact. Gabriel leads the transportation, energy, built environment and water portfolios - supporting 76 companies across those verticals. In addition to pipeline development and due diligence, he has directly overseen over 40 new and follow-on investments, deploying more than $30M in catalytic capital. He serves as a board observer for Artyc PBC, Mythos AI, Dimensional Energy, and Found Energy and has helped to co-design and manage more than 30 first-of-a-kind and early commercial projects in communities in Africa, Europe, and North America. Previously, Gabriel was on the founding team of Lime, where he led global data policy and transit partnerships and developed go-to-market strategies in North America. As the founder of two companies, he also contributed to the book "Smart Cities, Smart Mobility." ​Ben Shwab Eidelson is a co-founder and partner at Stepchange Ventures, an early-stage venture fund backing companies building software to accelerate energy abundance and upgrade critical infrastructure. Ben also co-hosts the Stepchange Show, a long-form podcast that tells the stories of human progress through the lens of transformative technologies, systems, and infrastructure. The Stepchange Show recently covered the history of data centers and the power grid, and has had over 250,000 downloads. Prior to Stepchange, Ben was a product leader and repeat founder, building two software companies—one acquired by Google and the second by Stripe. When not nerding out on infrastructure, Ben can be found with his wife chasing their 3 kids around local Seattle playgrounds. ​Susan Su is a climate tech investor and capital formation advisor to companies and funds across the energy transition. She built Toba Capital's climate investment practice from the ground up, spanning direct deals, fund-of-funds commitments, and co-investments, and currently serves as an advisor to the fund. She is a founding board member of the Carbon Business Council and serves on the Mission Alignment Committee at Prime Coalition, where she reviews catalytic capital investments for mission integrity. Susan is also the founder of Climate Money, a newsletter and podcast covering the business of decarbonization. ​Jonathan Azoff spent 20 years in silicon valley building rapid growth startups, including multiple exits to the likes of Zillow and Disney. He served as a fractional CTO to public companies (TNY.AX), and formerly led engineering teams at growth stage fintechs like Carta, Cardless and Pomelo. In his second act, he transitioned to the investor side of the table, joining the board of climate tech incubator Sweet Farm, and starting the deep tech venture firm SNØCAP with his two founding partners. He is one of the main individual investors behind The 9Zero Climate Innovation Hub, and is responsible for bringing the club to Seattle, where he lives now. He's an uncompromising advocate of great storytelling, having fun while doing good, and not taking himself seriously. ​Dr. Christine E. Boyle is General Partner at Burnt Island Ventures, a water-specialist venture capital fund, where she works with innovators to bring the next generation of water technologies to market. She was the CEO and founder of Valor Water, which sold to Xylem in 2018. At Xylem she served as VP of Digital Product Development following the acquisition. She serves on the boards of Aclarity Water, Subeca, Previsico, EPOCH Blue, and Waterly.  Dr. Boyle is also a member of the Cal-Nevada American Water Works Association Board and a trustee of the American Water Works Association Management and Leadership Division. In Dr. Boyle's free time she plays league tennis, boats, and travels to post-socialist nations. What you'll learn: How the 2026 climate tech VC numbers break down nationally — and why concentration in a handful of mega-deals is squeezing the middle of the funding stack Why Seattle ranks #6 nationally in VC dollars despite sitting on some of the country's deepest personal wealth What investors are actually screening for beyond the pitch deck, from response time to how a founder treats their own team How the hyperscaler-driven data center and energy boom is reshaping where capital flows, and what history (the 1970s WPPSS nuclear default) suggests about the risk Why human referral has become the deciding factor in both fundraising and hiring now that AI has made outreach nearly free What's missing from the Pacific Northwest climate tech ecosystem, according to the people funding it Key moments: The panel debates whether nuclear, batteries, and data centers are "sucking up" regional capital or building a foundation the rest of the ecosystem can draw from Susan Su asks the other panelists to describe how their investment committees actually make decisions, not what they tell founders in a rejection email Christine Boyle and Ben Eidelson describe the informal signals — professionalism, stress response, pace of learning — that shape a funding decision The group discusses AI-generated pitch decks and why differentiation now matters more than polish Resources mentioned: CTVC/Currence H1 2026 funding report Silicon Valley Bank, 2025 climate tech report PNW Battery Collaborative E8 Angels 9Zero (Seattle climate tech community hub) and its "Give, Get, Get" investor-list program Elemental Impact's Data Center Innovation Initiative (with Amazon, Google, Meta, and Microsoft) Climate Surge, an initiative from Climate Solutions "Climate Money" podcast (Susan Su) The Stepchange Show podcast (Ben Eidelson)

Today my guest is Alex Bodell, CTO of FormaPath What we discuss with Alex: Engineering roots Vertical farming and lessons learned From farms to pathology Formapath and AdiPress The origin of nToto Developing robotic motions through observation Handling edge cases Lab feedback  Expanding capabilities Future automation and AI The impact of new technologies on patient care Links for this episode: InVision from Cision Vision The Path to PathA Pathologists' Assistant Shadowing Network Health Podcast Network  LabVine Learning Dress A Med scrubs   FormaPath Overview of nToto nToto workflow   People of Pathology Podcast: Instagram

Want a quick estimate of how much your business is worth? With our free valuation calculator, answer a few questions about your business, and you'll get an immediate estimate of the value of your business. You might be surprised by how much you can get for it: https://flippa.com/exit What makes a business truly valuable to a buyer, and how do you know when it is actually time to sell? In this episode of The Exit, Steve McGarry sits down with Mike Krupit, founder and CEO of Trajectify, to unpack the leadership decisions that can make or break an exit. Drawing on a career that includes eight startups, three IPOs, an exit, and four failures, Mike explains why founders who remain at the center of everything can become a liability to their own business. He shares how putting the right people in the right seats, documenting critical processes, building strong systems, and delegating real authority can create a healthier and more valuable company.

 Mike also explores why the best time to sell is often when the business is performing well but approaching its next major plateau, and why founders need to prepare for what happens after the transaction before signing the deal. Steve and Mike discuss preserving company culture through an acquisition or IPO, communicating with employees when an exit process must remain confidential, evaluating leadership teams from the buy side, and avoiding the culture shock that can follow a major transaction. Whether you are actively preparing to sell or simply want to build a business that can thrive without you, this conversation offers a practical roadmap for creating a stronger, more transferable company.
 Mike Krupit is the founder and CEO of Trajectify, where he advises entrepreneurs, executives, and leadership teams on business growth, organizational development, and major transitions. A veteran of eight startups, Mike has held roles ranging from CTO to COO to CEO and has experienced three IPOs, mergers and acquisitions, and business failures throughout his career. Since founding Trajectify in 2013, he has focused on helping growth stage companies strengthen their leadership, align their people and processes, and successfully navigate the next stage of growth or an exit.


 LinkedIn - https://www.linkedin.com/in/mkrupit/ 


 Key Timestamps:

 [2:36] Introduction and Mike Krupit's Background 
 [2:56] Mike's Startup Journey and Leadership Lessons
 [4:24] Leadership and Business Valuation Factors
 [5:48] Preparing a Business for Exit: Documentation and Systems
 [7:12] Culture Preservation During Exit and IPO
 [10:03] Evaluating Leadership for Acquisition
 [11:35] Timing the Sale: When Is the Right Moment?
 [15:37] Mistakes in Exits and Post-Exit Planning
 [18:22] Driving Up Valuation: Processes and Leadership
 [19:30] Team Tactics for Confidentiality and Communication
 [22:27] IPO vs. Acquisition: Culture and Leadership Changes
 [26:35] Advice to Younger Self and Current Projects

 
 --
 The Exit—Presented By Flippa: A 30-minute podcast featuring expert entrepreneurs who have been there and done it. The Exit talks to operators who have bought and sold a business. You'll learn how they did it, why they did it, and get exposure to the world of exits, a world occupied by a small few, but accessible to many. To listen to the podcast or get daily listing updates, click on flippa.com/the-exit-podcast/

https://clearmeasure.com/developers/forums/ Michael Nygard advises consulting firms, private equity teams, CTOs, CEOs, and boards when they require senior technology judgment for limited-term, high-impact situations — including architecture assessment, platform rescue, cloud and data cost intervention, AI engineering enablement, technical diligence, divestiture and carve-out architecture, and operating-model redesign. Over a 35-year career, he has worked at the seam where people, processes, organizations, and the systems they build intersect. Most organizations treat those as separate problems. The hardest failures, and the most consequential wins, live precisely where they interact. That through-line is what Release It! is fundamentally about. The vocabulary it introduced — circuit breakers, bulkheads, stability patterns — is now standard in how the industry discusses reliability, and the book is widely cited as foundational to DevOps and cloud-native practice. At Nubank, he led the Data Business Unit with over $300 million in annual spend, then served as Chief Architect with reach across 2,500 engineers while the customer base grew from 75 million to 125 million across Brazil, Mexico, and Colombia. Results included cutting data-platform spend roughly 50% year-over-year, improving on-time data availability past 99%, building governance aligned with LGPD, GDPR, and CCPA, moving team engagement from the bottom decile to the 60th percentile, and rolling out AI coding tools to more than 90% of engineers without customer-visible quality regression. At Sabre, as part of the CTO office, he helped lead development-practice modernization, GCP migration strategy, mainframe offload architecture, technical diligence, and divestiture architecture across thousands of applications and hundreds of products. He is most effective when the stakes are real, the system is sociotechnical, and the solution must hold across architecture, execution, economics, and organizational behavior. LinkedIn: https://www.linkedin.com/in/mtnygard/ Personal Blog & Website: https://www.michaelnygard.com GitHub: https://github.com/mtnygard Twitter/X: https://x.com/mtnygard Release It! (Pragmatic Programmers): https://pragprog.com/titles/mnee2/release-it-second-edition/ 97 Things Every Software Architect Should Know (O'Reilly): https://www.oreilly.com/library/view/97-things-every/9780596800611/ Goodreads Author Page: https://www.goodreads.com/author/show/6089.Michael_T_Nygard LinkedIn Articles: https://www.linkedin.com/today/author/mtnygard Presentations Archive: https://github.com/mtnygard/presentations/wiki Want to Learn More? Visit AzureDevOps.Show for show notes and additional episodes.

AI Implementation in Healthcare Should Enhance Human Skills On this episode host Tom Foley invites Dr. Nabil George Badr, CTO for HendrenAI. Nabil describes AI as "intelligent automation" that accelerates feedback loops and improves productivity. He shares insights on patient privacy concerns with ambient listening technology and the need for proper governance and guardrails. Nabil discussed his approach to AI implementation in healthcare, emphasizing that it should enhance human skills rather than replace them. To stream our Station live 24/7 visit www.HealthcareNOWRadio.com or ask your Smart Device to “….Play Healthcare NOW Radio”. Find all of our network podcasts on your favorite podcast platforms and be sure to subscribe and like us. Learn more at www.healthcarenowradio.com/listen

Help us expand our Muslim media project here: https://www.thinkingmuslim.com/membership Donate to our charity partner Baitulmaal here: http://btml.us/thinkingmuslimArtificial intelligence is rapidly reshaping the world, but who is shaping artificial intelligence?In this episode of The Thinking Muslim, we sit down with Waleed Kadous, one of the leading minds in AI, to explore how this technology is transforming education, politics, geopolitics, and even the future of religious authority. As governments, corporations, and global powers race to develop increasingly powerful AI systems, where do Muslims fit into this conversation?From the rise of Anthropic and the global AI race to the philosophical assumptions embedded within today's models, this discussion examines why AI is far more than just another technological breakthrough. It is a civilisational shift that Muslims cannot afford to ignore.About Waleed Kadous:Waleed Kadous is Chief Scientist at Anyscale and one of the leading voices in artificial intelligence. Previously, he held senior engineering leadership roles at Google and Uber, where he served as Engineering Strategy Lead to the CTO. With expertise spanning AI, machine learning, robotics, and large-scale engineering systems, Waleed has spent his career developing cutting-edge technologies while helping shape the future of the industry. His work sits at the intersection of technical innovation, strategy, and the societal impact of AI.Find Dr. Waleed Kadous here:X: https://x.com/waleedkOr give your one-off donation here: https://www.thinkingmuslim.com/donateSubscribe to our Dubbed ChannelsArabic: https://www.youtube.com/@ThinkingMuslimArabicFrench: https://www.youtube.com/@ThinkingMuslimFrançaisSpanish: https://www.youtube.com/@TheThinkingMuslimEspañolListen to the audio version of the podcast:Spotify: https://open.spotify.com/show/7vXiAjVFnhNI3T9Gkw636aApple Podcasts: https://podcasts.apple.com/gb/podcast/the-thinking-muslim/id1471798762Purchase our Thinking Muslim mug: https://www.thinkingmuslim.com/merchFind us on:X: https://x.com/thinking_muslimLinkedIn: https://www.linkedin.com/company/the-thinking-muslim/Facebook: https://www.facebook.com/The-Thinking-Muslim-Podcast-105790781361490Instagram: https://www.instagram.com/thinkingmuslimpodcast/Telegram: https://t.me/thinkingmuslimBlueSky: https://bsky.app/profile/thinkingmuslim.bsky.socialThreads: https://www.threads.com/@thinkingmuslimpodcastFind Muhammad Jalal here:X: https://twitter.com/jalalaynInstagram: https://www.instagram.com/jalalayns/Sign up to Muhammad Jalal's newsletter: https://jalalayn.substack.comWebsite Archive: https://www.thinkingmuslim.comDisclaimer:The views expressed in this video are those of the individual speaker(s) and do not represent the views of the host, producers, platform, or any affiliated organisation. This content is provided for lawful, informational, and analytical purposes only, and should not be taken as professional advice. Viewer discretion is advised. Hosted on Acast. See acast.com/privacy for more information.

Michael interviews new exhibitor Dr. Jeffrey M. Kelly, a full-time biblical counselor and former church planter, and David Driskill, a veteran software developer and Care Assist Pro's CTO, about their platform (careassist-pro.com). They explain that Care Assist Pro was built to address the shortage of soul care in local churches by reducing counseling roadblocks and increasing counselor confidence through secure, HIPAA-compliant tools such as note organization, encrypted communication, built-in video conferencing with transcripts, summaries, and AI-driven feedback on counseling skills over time. They emphasize AI is never the counselor but a tool with biblical guardrails, using a curated RAG knowledge base of about 800 documents (e.g., ACBC, CCF, ABC, Counseling Coalition) and features like notebooks, multilingual outputs, and training “personas” for seminary practicums and skill development.00:00 Conference Introduction01:02 Meet the Guests01:16 Dr Kelly Background01:48 David Driskill Tech Story03:09 How Care Assist Began05:49 Redemptive Use of AI08:31 AI Training Practicum11:19 Notebooks Language Features15:30 Guardrails Not Replacement19:58 Counselor Growth Analytics23:57 Who Its For Pricing26:50 Final Encouragement WrapEpisode MentionsCheck out Care Assist Pro 

We've got the first of a two-part series on the systems that run the world: I'm talking today with Bart Butler, the CTO of Proton, the company that makes private and secure productivity software. There's a lot of big Decoder themes in this one. That includes how Proton has structured its ownership and architected its products to align its incentives with protecting users. At the same time, Proton faces new challenges and pressures, both at home in Switzerland and from the EU and US government that are putting its values to the test.  Links:  Proton now offers an entire bundle of office services | The Verge Proton Mail helped FBI unmask anonymous ‘Stop Cop City' protester | 404Media Proton says it will leave Switzerland if this controversial law Is passed | Vice Age verification is a mess but we're doing it anyway | The Verge Let's build a children's public internet | The Verge Let me see some ID: age verification is spreading across the internet | The Verge Why Chat Control 1.0 is the EU's most Orwellian law yet | Euronews Subscribe to The Verge to access the ad-free version of Decoder! Credits: Decoder is a production of The Verge and part of the Vox Media Podcast Network. Decoder is produced by Kate Cox and Nick Statt and edited by Ursa Wright. Our editorial director is Kevin McShane.  The Decoder music is by Breakmaster Cylinder. Learn more about your ad choices. Visit podcastchoices.com/adchoices

You've probably never heard of Inkling. It's the newest (and first) model from Thinking Machines Labs, and it could very well be a small snowball that picks up major momentum in today's enterprise AI landscape. If you haven't heard of Thinking Machines, they're led by Mira Murati, the former CTO at OpenAI. The big bet with Inkling? The future of AI could be using smaller models fine-tuned and optimized for smaller tasks. Will it work? Tune in live as we dive in. The Most Important AI Model You'll Probably Never Use That Just Dropped -- An Everyday AI Chat With Jordan WilsonNewsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageToday's Episode on LinkedIn: Thoughts on this? Join the convo on LinkedIn and connect with other AI leaders.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:Inkling AI Model Launch OverviewThinking Machines Lab Leadership HighlightInkling's Multimodal and Agentic CapabilitiesOpen Source vs. Proprietary AI ModelsEnterprise Procurement with American AI ModelsAI Fine Tuning as a Service (Tinker)Benchmark Scores: Inkling vs. Frontier ModelsCustomization and Model Shopping for EnterprisesAI Token Costs Driving Model EfficiencyBridgewater Case Study: AI Model CustomizationFrontier Models Enabling Efficient Fine-TuningFuture Trends: Specialized Small Language ModelsTimestamps:00:00 Inkling: A new AI model release05:43 Inkling AI model details09:08 China's dominance in open source AI11:48 Launch and model updates discussed15:21 Concerns over using Chinese open-source models19:06 Training smaller AI models20:22 Using GPT for AI Model Training23:54 Predicting Rise of Small Language Models28:38 Choosing the right AI modelKeywords: Inkling, Thinking Machines Lab, Meera Muradi, former OpenAI CTO, open source AI model, American AI model, fine tuning as a service, enterprise AI, multimodal AI, agentic models, customizable AI, Tinker, enterprise distribution, model procurement, Chinese open source models, strategic reset, model overhang, capabilities gap, AI model shopping, model routing, cost-conscious enterprises, artificial intelligence index, 975 billion parameter model, text-image-audio AI, open weights, proprietary AI models, customization accessibility, small language models, AI workflows, context window, Bridgewater use case, model distillation, GPU infrastructure, API costs, token efficiency, fine-tuned models, post training, AI competitive leverage, recurring financial judgment, AI benchmarks, middle tier models, automated model evaluation, privacy and workflow mapping, economical AI models, model rental, model routing automation.Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Ready for ROI on GenAI? Go to youreverydayai.com/partner 

It's News Day Tuesday on The Majority Report On today's program: ICE murders another person in cold blood, this time a 26-year-old father was shot in the head in Biddeford, Maine. In the wake of the murder, protestors swarm Susan Collins' office. Collins voted to provide a additional $70B in funds to ICE earlier this year. Elizabeth Ginexi, former NIH program official for 22 years and publisher of an eponymous Substack newsletter, joins to discuss how a little-noticed OMB rule could gut NIH and community funding. Minnesota Lt. Governor Peggy Flanagan joins to talk about her campaign for U.S. Senate. In the Fun Half: Italian American New Yorker's feelings are hurt over getting left off an immigrant enclave map of the city. PBD tries to capitalize on this "outrage" as a way to attack Mayor Mamdani. Marco Rubio makes his case for dismantling the Internation Criminal Court. Haley Stevens backed by tens of millions of dollars releases attack ads that label Abdul El-Sayed as sexist and mislead audiences into thinking that Obama has endorsed Stevens. Meta's CTO tries to sell Meta glasses as a way to remember people's names. Clavicular is surprised by the backlash he has received while visiting Israel over the footage from January where he is seen singing "Heil Hitler" by Kanye West. All that and more. Tell your Senators to block the NDAA until it is stripped of the proposal to integrate U.S. and Israeli militaries. Join Emma for a virtual DSA event: Workers Deserve More: DSA's 2026-27 Program Launch on Tuesday, July 14 To connect and organize with your local ICE rapid response team visit ICERRT.com The Congress switchboard number is (202) 224-3121. You can use this number to connect with either the U.S. Senate or the House of Representatives. Follow us on TikTok here: https://www.tiktok.com/@majorityreportfm Check us out on Twitch here: https://www.twitch.tv/themajorityreport Find our Rumble stream here: https://rumble.com/user/majorityreport Check out our alt YouTube channel here: https://www.youtube.com/majorityreportlive Gift a Majority Report subscription here: https://fans.fm/majority/gift Subscribe to the AM Quickie newsletter here: https://am-quickie.ghost.io/ Join the Majority Report Discord! https://majoritydiscord.com/ Get all your MR merch at our store: https://shop.majorityreportradio.com/ Get the free Majority Report App!: https://majority.fm/app Go to https://JustCoffee.coop and use coupon code majority to get 10% off your purchase Check out today's sponsors: COZY EARTH: Go to cozyearth.com/MAJORITYREPORT for an exclusive 20% off. FACTOR: Go to FactorMeals.com/majority50off and use code majority50off to get 50% off and free daily greens per box, with new subscription only, while supplies last until September 27, 2026. SUNSET LAKE CBD: Use coupon code "Left Is Best" (all one word) for 20% off of your entire order at SunsetLakeCBD.com.  Follow the Majority Report crew on Twitter: @SamSeder @EmmaVigeland @MattLech On Instagram: @MrBryanVokey Check out Matt's show, Left Reckoning, on YouTube, and subscribe on Patreon! https://www.patreon.com/leftreckoning Check out Matt Binder's YouTube channel: https://www.youtube.com/mattbinder Subscribe to Brandon's show The Discourse on Patreon! https://www.patreon.com/ExpandTheDiscourse Check out Ava Raiza's music here! https://avaraiza.bandcamp.