Podcasts about ctos

Welcome to AI Unraveled, Your daily briefing on the real world business impact of AIThe cost of sequencing a human genome has plummeted, but the challenge remains interpretation. We will explore how large AI models are moving from assisting diagnostics to actively designing novel drugs and personalized treatments, and what this means for enterprise R&D budgets and ethical guidelines.Setting the stage:Why is AI essential for genomics now?What is the current bottleneck in drug discovery?How are LLMs being fine-tuned for chemical and biological structures?Specific AI applications that are cutting discovery time.How is AI used in de novo protein design?What is a "digital twin" of a patient, and how does it speed up clinical trials?How do we secure massive genomic datasets (PII)?What happens when models discover biases in existing genetic research?Is personalized medicine an investment or an insurance policy?Which AI capabilities (e.g., small molecule prediction vs. large molecule discovery) yield the highest ROI?What is the single most important hire an R&D department can make in the next 12 months to prepare for the AI-native bio-future?

AI Daily Rundown: October 31, 2025:Welcome to AI Unraveled, Your daily briefing on the real world business impact of AIListen at https://podcasts.apple.com/us/podcast/ai-daily-news-rundown-amazon-ceo-says-layoffs-were/id1684415169?i=1000734511393In Today's edition:

AI is more powerful than ever, but companies are way overhyping this one feature. Today, we're talking to Bryan McCann, CTO and co-founder at You.com. We discuss why CTOs need to start asking deeper questions about meaning, how AI is forcing us to rethink consciousness and intelligence, and why treating AI with respect might actually help you become a better person. All of this right here, right now, on the Modern CTO Podcast!  Thank you to Digital Ocean for sponsoring this episode. For simple cloud and powerful AI that's built to scale, check out Digital Ocean here. To learn more about You.com, check out their website here.

AI Daily Rundown: October 29, 2025:Welcome to AI Unraveled, Your daily briefing on the real world business impact of AIIn Today's edition:

AI Daily Rundown: October 30, 2025:Welcome to AI Unraveled, Your daily briefing on the real world business impact of AIIn Today's edition:

Was passiert eigentlich auf der anderen Seite des Tisches, wenn Softwareanbieter ihre Preise erhöhen? Dr. Sebastian Voigt spricht mit Alexander van der Steeg, CTO von EntekSystems, über Softwarekostenkontrolle, Lizenzmanagement und die wachsende Preismacht großer Anbieter. Alexander erklärt, warum viele Softwarefirmen Flexibilität heute gezielt monetarisieren, wie indexbasierte Preismodelle funktionieren und weshalb Preissteigerungen oft versteckt in Tokens, Laufzeiten oder Feature-Paketen stattfinden. Er zeigt an Beispielen wie Microsoft (+25 % auf Teams), Adobe und Broadcom/VMware (+1000 %), wie stark Technologie die Preisgestaltung verändert und welche Folgen das für Unternehmen hat. „Ich finde, dass der Kunde eigentlich aus dem gesamten Portfolio auswählen sollte und es nur eine Metrik geben sollte, die ihm totale Transparenz gibt“, sagt van der Steeg im Gespräch. Außerdem geht es um den Trend zur digitalen Souveränität, die Renaissance von On-Premise-Lösungen und die Frage, warum CTOs zunehmend auch zu CFOs ihrer digitalen Assets werden. Über den Gast Alexander van der Steeg ist CTO der EntekSystems GmbH in Haibach bei Aschaffenburg. Mit Inventory360 entwickelt das Unternehmen eine Plattform für IT-Asset- und Software-Lizenzmanagement, die Unternehmen Transparenz über ihre IT-Landschaft verschafft und Softwarekosten steuerbar macht. Zuvor war Alexander Head of IT bei der TB International GmbH und leitete die Softwareentwicklung bei der Dedere Deutschland GmbH. Er verfügt über mehr als 15 Jahre Erfahrung in Full-Stack-Entwicklung, IT-Betrieb, Cloud-Architektur und DevOps und verfolgt mit EntekSystems das Ziel, IT-Management, Preis- und Vertragskontrolle auf eine gemeinsame datengestützte Basis zu stellen.

Businesses are spending millions on AI tools hoping to accelerate time-to-market but aren't seeing organizational-level results. Laura Tacho (CTO @ DX) explains why an "individual productivity" mindset fails and how AI merely accelerates the condition of the system it enters. She provides a framework for leaders to shift to a systems-level approach, find high-leverage ROI by looking outside the 20% of time spent coding, and understand what sets high-ROI orgs apart. Plus Laura shares data literacy tools to cut through the "whiplash" of conflicting AI reports and provides key considerations for 2026 budgeting, detailing where and how companies are planning to strategically invest.ABOUT LAURA TACHOLaura Tacho is CTO at DX, a developer experience company. She previously led teams at companies like CloudBees, Aula Education, and Nova Credit. She's an expert in building world-class engineering organisations that consistently deliver outstanding results. Laura has coached CTOs and other engineering leaders from startups to the Fortune 500, and also facilitates a popular course on metrics and engineering team performance.SHOW NOTES:Downsides to approaching organizational outcomes from an individual task level (2:59)Why individual product gains don't always equate to systems-level improvements (4:56)How the quality of existing systems impacts the improvements AI can foster (7:26)Strategies for shifting mental models from the individual to systems level (9:09)Implement training & enablement techniques as an organizational lever (11:22)Common workflows that can unlock new problem-solving methods (14:46)Understanding what impact you want to see / getting the most ROI from AI (18:40)How to interpret the data when it comes to AI & its true ROI (21:22)AI data literacy for engineering leaders (23:06)Interpreting the meter study & what it means for engineers using AI (25:49)Quality vs. quantity when it comes to AI implementation on the org level (28:43)Characteristics that high-ROI companies possess when it comes to AI (30:35)Strategies to invest in that may lead to higher ROI (32:29)Laura's observations on time & money budgeting / investments for 2026 (35:28)Embracing cost savings & opportunity generation as an eng org (38:08)Tackling fear / uncertainty when it comes to AI adoption, budgeting, & ROI (40:01)LINKS AND RESOURCESPrevious Episode with Laura TachoIntroducing the AI Measurement Framework from DXAtlassian State of DevEx ReportMETR StudyDORA Report (2025)This episode wouldn't have been possible without the help of our incredible production team:Patrick Gallagher - Producer & Co-HostJerry Li - Co-HostNoah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Ion Feldman, CTO at Rightway, has learned to love one thing about scaling a company from a kitchen table to nearly 1,000 employees: his job completely changes every six months. In this episode, Ion shares what it means to lead engineering when the role refuses to stay still—from writing code in the early days to building product, security, and data teams, and now shaping AI infrastructure. He explains how to stay hands-on without micromanaging, why he deliberately works himself out of roles by hiring people better than him, and how to preserve startup urgency inside a heavily regulated industry. If you've ever wondered how CTOs balance technical depth with business strategy while keeping their team fast and focused, this conversation delivers.Key TakeawaysTreat change as part of the job.Ion's leadership mindset centers on adapting to wherever the company needs him most—product, security, data, or AI. He views change as an opportunity to grow, not a disruption to avoid.Hire yourself out of the role.He dives deep into an area, builds it from scratch, then brings in experts who can take it to the next level. Once the right leadership is in place, he steps back completely and lets them own it.Hands-on time creates credibility.Ion makes sure every leader spends time building. Each quarter, his team takes a week off from meetings and Slack to focus on creating something new. It keeps them close to the work and sharp as technical leaders.AI adoption needs clarity and focus.Rightway avoids vague “use AI” goals by targeting clear use cases like unit test generation and onboarding to codebases. Sharing examples and results drives faster adoption than leaving teams to figure it out alone.Fail fast and move forward.Ion builds space for experimentation but expects quick recognition of failure. The goal is not to avoid mistakes but to learn, pivot, and evolve faster.Timestamped Highlights[02:10] The zero to one mindset – Why Ion thrives on constant reinvention and the satisfaction of building new functions from the ground up.[06:41] Three pillars of AI strategy – How Rightway is transforming work through AI enablement, applied projects, and bold experiments.[08:26] Delegating by design – How going deep before handing off creates clarity and trust across teams.[15:42] Skills that matter later – Ion reflects on learning public speaking and business fluency after years of technical focus.[17:48] Creating space for risk – How to give your team agency to take on big challenges and fail fast without fear.[21:22] Preparing successors – Why the best leaders hire people who will replace them and rethink everything they built.What Stuck With Us"I don't know, maybe I just get bored easily. I think a lot of people could view it as a burden and they want to stay in their lane of expertise, but I see it as an opportunity to learn and change things up."Pro Tips for Tech LeadersTake a week each quarter to build something with zero meetings or Slack. It reconnects you and your team with what you actually love about engineering.Wait to hire senior leadership until the need is undeniable. The role becomes meaningful, and you'll attract higher caliber talent.Give your engineers specific AI examples and let them experiment from there. Adoption follows clarity, not mandates.

Welcome to AI Unraveled, Your daily briefing on the real world business impact of AI.Today, we move beyond the office environment and into the real world, where billions in infrastructure, energy, and construction assets are managed. These foundational sectors face a relentless convergence of pressure: aging infrastructure, severe safety mandates, and non-negotiable ESG compliance. Reactive maintenance is no longer a viable strategy; it is a liability.This special episode is dedicated to the new standard: Intelligent Automation. We are examining the fusion of autonomous data capture via advanced drones with the cognitive power of AI to create a new data-driven rigor for heavy industry.We're reviewing the article, "Intelligent Automation: AI and Drones in Heavy Industry," breaking down how companies are using this combination to move from risky, manual inspections to predictive maintenance that detects cracks and corrosion days, even weeks, before catastrophic failure. This isn't just efficiency; it's about zero-trust infrastructure monitoring at scale.But first, a crucial message for the enterprise builders:

AI Daily Rundown: October 28, 2025:Welcome to AI Unraveled, Your daily briefing on the real world business impact of AIListen at https://podcasts.apple.com/us/podcast/ai-daily-news-rundown-amazon-axes-14-000-corporate/id1684415169?i=1000733899886In Today's edition:✂️Amazon Axes 14,000 Corporate Jobs because of AI

A speculative but grounded discussion on how companies should be restructuring their R&D and product teams today to capitalize on a future with highly capable agents.Welcome to AI Unraveled, Your daily briefing on the real world business impact of AI.Today, we go beyond the immediate quarter and focus on long-term strategic survival.When you operate at the executive level, you know the competitive "moat" built on data or scale is dissolving. This special episode is dedicated to the most critical question facing every CTO and investor: What happens after AGI?We're breaking down the article, "Beyond Moats: Analyzing the Next Wave of Post-AGI Business Models." We reveal how competitive advantage shifts entirely, forcing companies to pivot from gathering data to structuring proprietary workflows and coordinating autonomous agent fleets.This is not a theoretical discussion; it is a roadmap for future proofing your enterprise.Before we dive in, we have a critical message for the enterprise builders listening:

AI Daily Rundown: October 27, 2025:Welcome to AI Unraveled, Your daily briefing on the real world business impact of AIIn Today's edition:

AI Weekly Rundown From October 19th to October 26th 2025:Welcome to AI Unraveled, Your daily briefing on the real world business impact of AI

Darryl Pahl is the co-founder of DFnet, a Seattle-based company providing clinical trial data management software and services. Along with his wife and co-founder, Lisa Andrzejczyk, Darryl started the company more than 20 years ago after careers at Fred Hutchinson Cancer Research Center. They built DFnet around long-term client relationships in global health and clinical research. The company runs DFdiscover, an enterprise-grade electronic data capture and management platform used in clinical studies worldwide. With offices in the U.S., Canada, and South Africa, DFnet has grown to more than 50 employees and is approaching $10M in revenue. Clients range from the U.S. Department of Veterans Affairs to nonprofits like PATH and major universities. Still independent and bootstrapped, DFnet has made key moves to prepare for the future—such as bringing in a growth-focused CEO, diversifying beyond single-client risk, and shifting legacy software to SaaS and services. Darryl shares the lessons from running conservatively under debt, buying rather than building, and building a global company rooted in relationships and practical execution. Key Takeaways Stability First Growth – Carrying a 10-year SBA loan forced conservative growth and taught the discipline of stability over risky expansion. Buying Not Building – Acquiring DataFax brought 35+ new clients overnight and proved that buying legacy software can be smarter than reinventing. Services Plus Software – Unlike pure SaaS, DFnet thrives by combining consulting, hosting, and software in a regulated field. Spouse Founders Structure – Their 51/49 ownership split avoided deadlocks and kept marriage and business aligned. This Interview Is Perfect For SaaS founders balancing growth and control Founders considering succession or sale Bootstrapped entrepreneurs in niche B2B markets Anyone curious about global health data and impact-driven tech Quote from Darryl Pahl, co-founder of DFnet "The best position to be in is to say that in three to five years, we would be crazy to sell this company. It's doing so well. That would be the perfect thing. And what we're not looking for is a giant payout. We have a very modest lifestyle. “But is an asset, it is a business, and there's a business aspect. It would have to be the right type of buyer. It has to be the right fit. It has to be the right person or group that is respectful to our clients, our employees, and us as owners.  “So the ideal would be to have the luxury of either not selling or being more selective rather than responding to random emails from some financial buyer or search funder.” Links Darryl Paul on LinkedIn DFnet on LinkedIn DFnet website Podcast Sponsor – Fraction This podcast is sponsored by Fraction. Fraction gives you access to senior US-based engineers and CTOs — without full-time costs or hiring risks. Get 10 to 30 hours per week from vetted and experienced US-based talent. Find your next fractional senior engineer or CTO at fraction.work. You can start with a one-week, risk-free trial to test it out. 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.

AI Daily Rundown: October 24, 2025:Welcome to AI Unraveled, Your daily briefing on the real world business impact of AIListen at https://podcasts.apple.com/us/podcast/ai-daily-news-rundown-copilots-personality-upgraded/id1684415169?i=1000733385192In Today's edition:

Lenovo has been a global leader in computing for decades. Where are they heading next? Today, we're talking to Art Hu, SVP and CTO at Lenovo. We discuss Lenovo's transformation into a services-led company, the future of personal computing and AI twins, and how CTOs can prepare their organizations for the AI revolution. Thank you to Digital Ocean for sponsoring this episode. For simple cloud and powerful AI that's built to scale, check out Digital Ocean here. All of this right here, right now, on the Modern CTO Podcast!  To learn more about Lenovo, check out their website here.

AI Daily Rundown: October 23, 2025:Welcome to AI Unraveled, Your daily briefing on the real world business impact of AIIn Today's edition:

⚛️ Quantum Echoes: Verifiable Advantage and Path to ApplicationsListen to the podcast at https://podcasts.apple.com/us/podcast/quantum-echoes-verifiable-advantage-and-path-to/id1684415169?i=1000733017630Full article at https://enoumen.substack.com/p/quantum-echoes-a-path-towards-realWelcome to AI Unraveled, Your daily briefing on the real world business impact of AIToday Google announced a significant step forward in quantum computing with their latest Nature publication, “A verifiable quantum advantage.” They introduced a new quantum algorithm, “Quantum Echoes”, which measures out-of-time-order correlators (OTOCs), a new family of observables that describe how quantum dynamics become chaotic. This work represents the first quantum computing experiment measuring a quantum observable that is both verifiable and beyond the simulation capacity of known classical algorithms. Check the Nature publication: https://www.nature.com/articles/s41586-025-09526-6

AI Daily Rundown: October 22, 2025:Welcome to AI Unraveled, Your daily briefing on the real world business impact of AIIn Today's edition:

En este episodio recogemos los momentos clave del encuentro celebrado en Barcelona el 16 de octubre, donde un panel de expertos analizó cómo la tecnología impulsa ventajas competitivas reales en M&A. Desde la visión estratégica de líderes de innovación y desarrollo corporativo hasta la experiencia práctica de quienes ejecutan integraciones y transformaciones tecnológicas, exploramos el ciclo completo: due diligence tecnológica, valoración de activos digitales, integración post-adquisición, gobierno del dato, ciberseguridad, modernización de plataformas y uso de IA para acelerar sinergias. A lo largo de la conversación, desgranamos qué capacidades tech crean valor (y cuáles destruyen), cómo priorizar roadmaps en los primeros 100 días, y qué métricas ayudan a medir el éxito más allá del Excel. Cerramos con aprendizajes accionables y recomendaciones para equipos de corporate development, CTOs, CFOs y PE/VC que buscan convertir la tecnología en una palanca de creación de valor end-to-end. Si te interesan operaciones más rápidas, integraciones con menos fricción y sinergias tangibles, este episodio es para ti.

Trust isn't a “soft” metric—it's the conversion engine. Buyers don't buy products first; they buy us, then the solution arrives as part of the package. Below is a GEO-optimised, answer-first version of the core human-relations principles leaders and sales pros can use today.  How do top salespeople build trust fast in 2025? Start by listening like a pro and making the conversation about them, not you. When trust is low, buyers won't move—even if your proposal looks perfect on paper. The fastest pattern across B2B in Japan, the US, and Europe is empathetic listening that surfaces goals, constraints, and internal politics. Post-pandemic norms (hybrid work, async decisions) mean you must read what's said and what's unsaid: tone, pauses, body language on Zoom, and email subtext. In enterprise sales, this shifts you from “pitching” to “diagnosing.” You become the buyer's trusted business advisor—especially in consensus-driven cultures like Japan where ringi and nemawashi favour rapport and patience over pressure. Do this and high-stakes deals stop stalling because stakeholders finally feel safe to share the real blockers.  Do now: Open with one agenda question—“What outcome matters most by [date]?”—then listen without interrupting for 90 seconds. What questions reliably open buyers up? Use simple, human prompts that invite stories. Who have they worked for? What was it like? Where's the office? When did they start? Why choose this company? What do they like most? These “Who/What/Where/When/Why/How” prompts turn small talk into signal, revealing priorities (speed vs. safety), risk appetite, and decision cadence. Across SMEs, startups, and multinationals, these prompts work because they're culturally neutral, non-intrusive, and buyer-centred. In APAC, they respect hierarchy; in the US, they feel pragmatic; in Europe, they invite thoughtful context. The goal isn't to interrogate—it's to let people talk about themselves while you capture needs, metrics, and names of influencers you'll later engage.  Do now: Prepare six openers on a card; ask two, go deep on one, and mirror key phrases back. How do I remember personal details without being awkward? Use the “Nameplate → House → Family → Briefcase → Airplane → Tennis Racquet → Newspaper” memory chain. Visualise a giant nameplate smashing into a bright house; inside, a baby with a briefcase pulls out an old plane; its propellers are tennis racquets threaded with rolled newspapers. Each hook cues a safe, human topic: name, home, family, work, travel, hobbies, and industry news. This light mnemonic keeps first meetings natural across cultures. In Japan, it supports relationship-first norms (meishi exchange, hometown ties). In the US/EU, it avoids prying while still finding common ground (sports, routes, recent sector headlines). Use tact and sequence flexibly; skip topics if they feel private. The point is to remember them so follow-ups feel personal, not transactional.  Do now: Before calls, jot the seven cues; after calls, log one fact per cue in your CRM. What if I don't know the buyer's interests yet? Keep asking—then mirror their language and frame benefits in their terms. Early on, many buyers withhold interests until they decide you're trustworthy. That's normal. Persist with respectful questions, then translate features into “so-whats” they already value: uptime for CTOs, cycle-time for COOs, compliance for CFOs, psychological safety for HR. As of 2025, complex deals involve multi-threading (RevOps, Legal, IT, Security). Tailor each touch: startup CTOs want velocity and unit economics; enterprise VPs want risk mitigation and stakeholder alignment; Japanese heads of division may prioritise harmony and precedent. The win is relevance—your proposal reads like their strategy memo, not your brochure.  Do now: After each meeting, write one line: “They care most about ___ because ___.” Lead with that next time. How do I make someone feel important—without manipulation? Spot real wins and praise them sincerely and specifically. Most professionals get little recognition. When you catch people doing something right—clear brief, crisp data, fast feedback—name it. Never over-flatter; buyers detect tactics instantly. The goal is dignity, not drama. Practical example: “Your timeline reduced rework across Legal and IT—that saved us both weeks.” In Japan, sincere appreciation that acknowledges team effort (not just the individual) lands better; in the US, direct credit energises champions. Across sectors (SaaS, manufacturing, services), this fosters reciprocity and deepens trust far faster than discounts ever can.  Do now: In your next email, add one honest, specific thank-you sentence linked to a business outcome. What should leaders systemise so this sticks? Bake these principles into playbooks, onboarding, and CRM hygiene. Codify the seven memory cues, the open-question matrix, and a “buyer interest” field in CRM. Coach for silence (count to three before replying). Review call snippets for interrupt rate and question balance. Reward teams for discovery quality, not just revenue. Executives at firms from startups to conglomerates can run fortnightly “deal trust reviews”: is the sponsor heard, interests mapped, and recognition given? In Japan, align with nemawashi—map stakeholders and pre-wire decisions. In the US/EU, pressure-test value hypotheses with RevOps and Finance. Consistency beats charisma.  Do now: Add three fields to your CRM today—Interests, Stakeholders, Recognition Given—and make them required. Conclusion When you listen deeply, speak in the buyer's interests, and recognise people sincerely, you stop selling and start being chosen. Make this your firm's operating system and watch cycle times shorten and referrals grow.  FAQs Isn't this just “be nice” advice? No—these behaviours reduce friction, surface risks early, and accelerate consensus, which shortens sales cycles.  Do these tips work in Japan? Yes—especially the memory chain and sincere group-focused recognition, which fit relationship-first norms.  How do I measure progress? Track interrupt rate, number of stakeholder interests captured, and instances of specific recognition logged in CRM. Next Steps Add the seven-cue mnemonic and open-question set to your onboarding. Require “Interests” and “Recognition Given” fields in every opportunity. Coach teams to wait three beats before replying on calls. About the Author Dr. Greg Story, Ph.D. in Japanese Decision-Making, is President of Dale Carnegie Tokyo Training and Adjunct Professor at Griffith University. He is a two-time winner of the Dale Carnegie “One Carnegie Award” (2018, 2021) and recipient of the Griffith University Business School Outstanding Alumnus Award (2012). As a Dale Carnegie Master Trainer, Greg is certified to deliver globally across all leadership, communication, sales, and presentation programs, including Leadership Training for Results. He has written several books, including three best-sellers—Japan Business Mastery, Japan Sales Mastery, and Japan Presentations Mastery—along with Japan Leadership Mastery and How to Stop Wasting Money on Training. Japanese editions include ザ営業, プレゼンの達人, トレーニングでお金を無駄にするのはやめましょう, and 現代版「人を動かす」リーダー. Greg also publishes daily business insights on LinkedIn, Facebook, and Twitter, and hosts six weekly podcasts. On YouTube, he produces The Cutting Edge Japan Business Show, Japan Business Mastery, and Japan's Top Business Interviews, followed widely by executives seeking success strategies in Japan. 

AI Daily Rundown: October 21, 2025: Your daily briefing on the real world business impact of AI

The Geopolitics of Silicon and the Maturation of Intelligence:

AI Daily Rundown: October 17, 2025: Your daily briefing on the real world business impact of AI

In this episode, we're diving into the biggest problem plaguing long-running LLM deployments: context drift and brevity bias. Your models start strong, but they decay over time, demanding costly retraining and frustrating MLOps teams. Static prompt engineering is a dead end.Today, we're unlocking Agentic Context Engineering, or ACE—the future of production AI. Detailed in an essential article by the experts at Diztel, ACE is not just a better prompt; it's a fully operational system layer. It allows your LLMs to learn through adaptive memory and evolve instructions automatically, just like a human team member.Key Takeaways:1. Instead of static prompts, Agentic Context Engineering (ACE) enables LLMs to “learn” through instructions, examples, and adaptive memory.2. ACE directly tackles context drift and brevity bias, the two biggest killers of long-running AI performance.3. Think of ACE as turning prompt engineering into a system layer — a pipeline that evolves and curates instructions automatically.4. The real power of the framework? Evaluation and self-reflection are its core primitives, making it possible to benchmark and auto-improve agents over time, reducing the need for retraining.5. ACE can integrate into enterprise MLOps pipelines as a governance layer, giving teams visibility into how context evolves, and offering levers for optimization without costly model retraining.Tools / Tech : ACE (Agentic Context Engineering) is a conceptual framework with its own modular components:Generator → Creates new prompts, instructions, or candidate outputs.Reflector → Evaluates those outputs, identifies weaknesses, and provides structured feedback.Curator → Selects, organizes, and evolves the best instructions into a coherent, long-term context.“ACE doesn't just prompt models — it teaches them how to remember, reflect, and evolve without retraining.”The results are insane:→ 10.6% better than GPT-4 agents on AppWorld→ 8.6% on finance reasoning→ 86.9% lower cost and latencyIf this scales, the next generation of AI will be self-tuned. We are entering the era of living prompts.Link to research - https://www.arxiv.org/pdf/2510.04618Credit: The Diztel Team - https://diztel.com

In this episode of Convergence.fm, Ashok Sivanand sits down with Farhan Thawar, Head of Engineering at Shopify, to go behind the scenes of how Shopify not only keeps pace with rapid change but leads it.  The discussion explores how Shopify became one of the first platforms to allow merchants to sell products directly inside ChatGPT, why that move challenges Amazon's dominance, and what it takes to build a company that learns faster than it fails.  Farhan explains the systems that make being first repeatable rather than accidental, including Shopify's internal LLM proxy, MCP servers, experimentation culture, and democratized tooling.  If you are a CEO, COO, or CTO looking to scale through culture, systems, and intentional technology adoption, this episode shows what it looks like to operate with conviction and long-term relevance. Key Topics and Moments: Shopify and OpenAI's commerce integration. The same day OpenAI enabled in-chat shopping, Shopify merchants were already live. Farhan explains what it takes for a company of Shopify's size to move with that kind of speed Competing with Amazon through culture, not size. Shopify has 3,000 engineers compared to Amazon's 35,000+, yet continues to outpace bigger players by focusing on coherence, focus, and empowered execution rather than bureaucracy and scale. The meaning behind Tobi Lütke's April AI memo. Farhan discusses how Shopify operationalized its “AI is non-optional” stance, what baseline expectations look like, and how performance is evaluated in an AI-native organization. AI reflexivity and the “three buckets.” Farhan explains how teams are taught to recognize “AI not allowed,” “AI optional,” and “AI mandatory” problems so that employees develop instinct for when to reach for AI — and when to pick up the screwdriver. The risk of ‘vibe coding' and why hand tools still matter. Farhan shares lessons from real incidents inside and outside Shopify, like the Cloudflare outage caused by unreviewed AI-generated code, and how engineering leaders teach judgment, not just prompting. The LLM Proxy and MCP Servers. Inside look at how Shopify democratized AI across departments by building an internal platform that connects all major models and corporate data sources, enabling every employee to build workflows and ask intelligent questions — not just engineers. AI budgeting vs. SaaS budgeting. Farhan explains why AI usage isn't treated like traditional SaaS spend and how Shopify encourages heavy experimentation by rewarding impact rather than punishing token consumption. Experimentation as a system. How teams are encouraged to show work at 20%, not 80%, and why the speed of learning, not perfection, is the true productivity metric. Subtraction as leadership. Farhan shares how founders and executives must delete outdated processes, rules, and layers of bureaucracy to make room for new ideas — why process should only exist if it makes something possible or 10x better. Hiring and growing AI-native talent. Why Shopify doubled down on internships, hiring 1,000 interns this year and next, and how younger engineers push full-timers to stay current by being born AI-native “centaurs.” Responsibility versus accountability. Why leaders can delegate tasks but not responsibility, and how to stay in the work without disempowering the team. Certainty as intolerance. Farhan's reflection on why overconfidence kills creativity, and how leaders can replace fixed beliefs with wayfinding, curiosity, and adaptive decision-making. Rapid-fire reflections for CEOs. Ashok and Farhan close with lessons on showing unfinished work, modeling curiosity, and removing friction as a cultural operating system. Who Should Listen: Mid-market CEOs, COOs, and CTOs building adaptable organizations that can scale.  Leaders focused on culture and transformation, not just technology adoption.  Operators who want to apply product thinking and modern software practices to traditional industries. Notable Quotes: “We have a baseline expectation of using AI. If you have two people, one using AI and one not, they will both be evaluated the same.” – Farhan Thawar on AI usage expectations  “We don't like waste, but we don't have limits. If you believe in your workflow, use the best model for your problem solving.” – Farhan Thawar on AI token cost and consumption   “You can now buy directly in chat from Shopify merchants. That is a major shift in how people discover and buy online.” – Ashok Sivanand on Shopify launching all their merchants on ChatGPT's Shop feature on the very day it was launched  Related Reading and References: Shopify Blog: Shopify and OpenAI bring commerce to ChatGPT (official announcement) - https://www.shopify.com/news/shopify-open-ai-commerce?podconvergence   Reuters: OpenAI partners with Shopify, Stripe, and others to expand ChatGPT integrations - https://www.reuters.com/world/americas/openai-partners-with-etsy-shopify-chatgpt-checkout-2025-09-29/?podconvergence   TechCrunch: Inside Tobi Lütke's AI Memo and Shopify's Cultural Shift - https://techcrunch.com/2025/04/07/shopify-ceo-tells-teams-to-consider-using-ai-before-growing-headcount/?podconvergence  Farhan's opinions about token consumption - https://x.com/fnthawar/status/1930367595670274058  Farhan's article about “looking stupid”- https://medium.com/helpful-com/why-looking-stupid-is-my-superpower-2ee3fe00a748?podconvergence  The Convergence.fm first episode with Farhan in 2024 - https://convergence.fm/episode/from-code-to-culture-how-shopify-thrives-under-farhan-thawars-thought-leadership  The Convergence.fm Episode about Tobi Lütke's leaked AI memo mandate, and our 6 takeaways - https://convergence.fm/episode/shopifys-leaked-ai-mandate-explained-6-takeaways-for-your-product-team  Tobi's memo Tweet - https://x.com/tobi/status/1909231499448401946 Unreasonable Hospitality (book) - https://www.amazon.com/Unreasonable-Hospitality-Remarkable-Giving-People/dp/0593418573  Farhan's Twitter (public handle) - https://x.com/fnthawar  Reflection and Action Steps: Start with your mission. Before choosing tools, clarify what problem you are solving and what your business stands for.  Enable your team. Ask whether you are removing barriers or creating them.  Are employees empowered to experiment?  Model the change. Use AI tools yourself. Share your learnings, wins, and failures openly. F Foster learning. Consider introducing internal forums or “thinking clubs” that encourage curiosity and reflection across your team.  

Welcome to AI Unraveled, your daily briefing on the real-world business impact of AI.This episode provides an extensive overview of the dual existential threat posed by the convergence of Artificial Intelligence (AI) vulnerabilities and the impending power of quantum computing. It meticulously details numerous intrinsic AI attack vectors, such as data poisoning, model inversion, and evasion attacks, which exploit the unique nature of machine learning models. Concurrently, the show highlights the immediate danger of quantum decryption through the "Harvest Now, Decrypt Later" strategy, which threatens to render current classical encryption obsolete due to algorithms like Shor's. To counter these integrated risks, the podcast proposes a strategic Quantum-Resilient Zero-Trust AI framework built upon three pillars: Zero-Trust MLOps for securing the AI lifecycle, Verifiable Provenance using technologies like blockchain for integrity, and mandatory Crypto-Agility and Post-Quantum Cryptography (PQC) to future-proof the entire security foundation.Listen at https://podcasts.apple.com/us/podcast/zero-trust-ai-a-quantum-resilient-framework-for/id1684415169?i=1000732089288Sources and Full article at: https://enoumen.substack.com/p/zero-trust-ai-a-quantum-resilient

Coralogix CEO Ariel Assaraf reveals how their observability lake lets companies own their data, reduce costs, and use AI agents to transform monitoring into actionable business intelligence.Topics Include:Coralogix solves observability scaling issues: tool disparity, sprawling costs, limited control.Streama parses data pre-ingestion; DataPrime queries directly on customer's own S3 buckets.AI will generate massive unstructured data, making observability challenges exponentially worse.CTOs should ask: Can observability data drive business decisions beyond just monitoring?Observability lake lets you own data in open format versus vendor lock-in.OLLI designed as research engine, not another natural language database interface.Ask business questions like "What's customer experience today?" instead of technical queries.Trading platform unified tools, reduced resolution time 6x, now uses for business intelligence.Future: Multiple AI personas, automated investigations, hypothesis-driven alerts without human prompting.AWS partnership enables S3 innovation, Bedrock models, and strong co-sell growth motion.Data sovereignty solved: customers control their S3, remove access anytime, own encryption.Business data experience will match consumer AI tools within two years fundamentally.Participants:Ariel Assaraf – Chief Executive Officer, CoralogixBoaz Ziniman – Principal Developer Advocate - EMEA, Amazon Web ServicesSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

AI Daily Rundown: October 15, 2025: Your daily briefing on the real world business impact of AIListen at https://podcasts.apple.com/us/podcast/ai-daily-news-rundown-openai-to-allow-erotica-on-chatgpt/id1684415169?i=1000732041024Sources at Substack: https://enoumen.substack.com/p/ai-daily-news-rundown-openai-to-allow

Welcome to AI Unraveled, your daily briefing on the real world business impact of AI.Are you preparing for the challenging Google Cloud Professional Machine Learning Engineer certification? This episode is your secret weapon! In less than 18 minutes, we deliver a rapid-fire guided study session packed with 10 exam-style practice questions and actionable "study hacks" to lock in the key concepts.We cut through the complexity of Google's powerful AI services, focusing on core topics like MLOps with Vertex AI, large-scale data processing with Dataflow, and feature engineering in BigQuery. This isn't just a Q&A; it's a focused training session designed to help you think like a certified Google Cloud ML expert and ace your exam.In This Episode, You'll Learn:ML Problem Framing: How to instantly tell the difference between a regression and a classification problem.Data Preprocessing: When to use Dataflow for unstructured data vs. BigQuery for structured data.Feature Engineering: The best practice for handling high-cardinality categorical features in a neural network.Vertex AI Training: The critical decision point between using a pre-built or a custom training container.Hyperparameter Tuning: How to use Vertex AI Vizier efficiently when you're on a limited budget.Model Deployment: The key differences between online and batch prediction for real-world applications.MLOps Automation: How to orchestrate a complete, reproducible workflow with Vertex AI Pipelines.Model Monitoring: How to spot and diagnose training-serving skew to maintain model performance.Responsible AI: Using the What-If Tool to investigate model fairness and mitigate bias.Serverless Architecture: A simple, powerful pattern for building event-driven ML systems with Cloud Functions.

AI Daily Rundown: October 13, 2025: Your daily briefing on the real world business impact of AI

Welcome to AI Unraveled, your daily briefing on the real-world business impact of AI.Today, we're looking up... to the skies over American cities, where automated eyes are changing public safety. We're asking the question: Are AI drones America's newest cops?This show provides a comprehensive analysis of the adoption of AI-powered drones by American law enforcement, specifically focusing on the Drone as First Responder (DFR) model, which dramatically reduces emergency response times for scenarios like opioid overdoses. It explores the sophisticated technology involved, detailing hardware from companies like DJI and Skydio and integrated software ecosystems such as Axon Air, which moves policing toward a semi-autonomous model. Crucially, the show contrasts the humanitarian benefits with significant civil liberties concerns, arguing that current legal frameworks, particularly the Fourth Amendment, are inadequate for regulating persistent, sensory-enhanced surveillance. The analysis concludes by highlighting the risk of mission creep, the automation of algorithmic bias in policing, and the urgent need for a cohesive national strategy regarding transparency and community oversight to prevent the slide toward a pervasive surveillance state.Full Article and Sources at https://showupandplay.substack.com/p/ai-drones-policing-privacy-and-the

AI Weekly Rundown From October 06th to October 12th, 2025:Listen at https://podcasts.apple.com/us/podcast/ai-weekly-news-rundown-openai-ships-apps-agents-and/id1684415169?i=1000731382265

AI Daily Rundown: October 10, 2025: Your daily briefing on the real world business impact of AIListen at https://podcasts.apple.com/us/podcast/ai-daily-news-rundown-ai-will-drive-nearly-all-us-growth/id1684415169?i=1000731237526

AI Daily Rundown: October 09, 2025: Your daily briefing on the real world business impact of AIListen at https://podcasts.apple.com/us/podcast/ai-daily-news-rundown-samsung-ai-model-beats-models/id1684415169?i=1000731054984

AI Daily Rundown: October 08, 2025: Your daily briefing on the real world business impact of AIListen at https://podcasts.apple.com/us/podcast/ai-daily-news-rundown-googles-new-ai-can-browse-websites/id1684415169?i=1000730906373

We've entered what I call The Friction Era—a period where every organization, from the fastest-growing startup to the most entrenched enterprise, is advancing so rapidly that the internal systems meant to support growth are straining under their own ambition. Mergers, acquisitions, product expansions, tech integrations, AI disruption, competitive parity—all of it is hitting at once. And yet, none of it signals failure. Quite the opposite. It signals acceleration.But acceleration brings turbulence. And when the temperature inside an organization rises—not because things are breaking, but because the stakes are higher—you learn quickly who your real operators are. The CHRO, the CFO, and the CTO become the three anchors in the storm. They are the triad balancing the organization's emotional intelligence, financial discipline, and technological infrastructure. And if they're not in sync, the company drifts into chaos, no matter how strong the product or how brilliant the strategy.In this episode, we go behind the scenes into how these three executives navigate what most companies never talk about publicly—the fragile, high-stakes process of scaling without losing the core of what made the business great.We'll unpack:How CHROs are redefining their role from HR operator to cultural engineer—embedding trust, energy, and clarity into the revenue architecture itself, not just engagement programs.How CFOs are reframing financial discipline not as constraint, but as a creative tool to shape psychological safety, focus, and long-term decision-making velocity.How CTOs are engineering unification—breaking down redundant systems, harmonizing data, and turning technology stacks into living frameworks that guide behavior, not just performance.We'll also dive into what happens when growth gets ahead of structure: when a company's narrative outpaces its people systems, when speed starts to erode judgment, and when competing incentives fracture collaboration between sales, product, and finance. Because at that point, it's not just about “alignment”—it's about survival through sophistication.The most forward-thinking executives know that emotional discipline is operational discipline. They know that culture without commercial intent is theater—and that commercial intent without culture is chaos. So this conversation is about what it takes to build the internal architecture of a billion-dollar organization before you actually reach a billion.This is a raw, unfiltered look at the modern enterprise from the inside out. A masterclass in executive endurance, systemic awareness, and the courage to build stability inside complexity.Core Question: When your organization is in motion—growing, merging, integrating, evolving—how do you maintain the psychological precision, financial rigor, and operational unity to keep the whole thing from tearing apart at the seams?

AI Daily Rundown: October 07, 2025: Your daily briefing on the real world business impact of AIListen at https://podcasts.apple.com/us/podcast/ai-daily-news-rundown-openai-ships-apps-agents-agentkit/id1684415169?i=1000730639683

This show provides an extensive analysis of how OpenAI's launch of the integrated AgentKit stack threatens to fundamentally disrupt the workflow automation industry. This new stack, powered by the advanced o1 reasoning model, is positioned as a nascent "AI Operating System" that shifts the market from simple task automation to intelligent orchestration. The show details the existential threat AgentKit poses to established incumbents like Zapier, the no-code leader known for its vast integration library, and n8n, the developer-centric platform favoured for its self-hosting and control features. Essentially, the show argues that by vertically integrating superior intelligence, a visual builder, and a massive distribution channel, OpenAI is executing a classic platform encroachment strategy to commoditise the incumbent's core value propositions. Finally, the analysis explores the defensive strategies for both Zapier and n8n, suggesting they must pivot to become model-agnostic orchestration layers or secure, compliant enterprise infrastructure to survive.Listen at https://podcasts.apple.com/us/podcast/openais-agentkit-and-the-automation-apocalypse/id1684415169?i=1000730689980

On the latest episode of After Earnings, Ann sits down with Udemy CEO Hugo Sarrazin to discuss the company's pivot from a traditional online course marketplace to an AI-powered platform designed to reskill the global workforce. Highlights include: - Udemy's shift from one-off course sales to a subscription model - The company's enterprise push to reskill workforces at scale - The future of its instructor-driven marketplace - How AI can deliver mass personalization in learning 00:00 – Hugo Sarrazin Joins 01:12 – Why the online learning industry is under pressure 02:42 – Udemy's consumer vs. enterprise business explained 05:56 – How AI enables personalization in learning 08:00 – Marketplace model vs. proprietary content 11:58 – Transition to subscriptions and monetization challenges 15:02 – Is Udemy becoming a digital media company? 16:48 – Enterprise clients and “just-in-time” learning 20:27 – Selling to CTOs, HR, and business leaders 23:33 – Reskilling 92 million workers in the AI era 25:39 – ROI pressure vs. growth opportunity 27:11 – Margins, cash flow, and product investment 29:03 – Hugo Sarrazin's career journey: McKinsey to CEO 33:40 – Will AI replace consulting? 37:55 – The future of Udemy After Earnings is brought to you by Stakeholder Labs and Morning Brew. For more go to https://www.afterearnings.com Follow Us X: https://twitter.com/AfterEarnings TikTok: https://www.tiktok.com/@AfterEarnings Instagram: https://www.instagram.com/afterearnings_/ Reach Out Email: afterearnings@morningbrew.com $UDMY Learn more about your ad choices. Visit megaphone.fm/adchoices

AI Weekly Rundown From September 29 to October 05th, 2025:

What happens when a CTO and a CIO of a global tech company sit down together to talk about AI? That's the starting point of today's episode, where I'm joined by Jeremy Ung, CTO at Blackline, and Sumit Johar, the company's CIO. Rather than chasing the hype, we focus on what AI really means for executive decision making, governance, and business outcomes. Both leaders open up about how their partnership is blurring the traditional lines between product and IT, and why the board is demanding answers on topics that once sat deep in the technology stack. Jeremy and Sumit explain why AI is not just another SaaS subscription and why expectations have changed so dramatically. For decades, technology was seen as predictable, a rules-based engine that followed instructions without error. AI feels different because it speaks, reasons, and sometimes makes mistakes. That human-like experience is what excites employees, but it is also what unsettles them. This is where education and governance come in, helping teams learn how to question, verify, and trace AI outputs before they make critical decisions. We also explore how AI agents are beginning to work across tools like SharePoint and email, raising new compliance and security questions that CIOs and CTOs must answer together. The conversation turns to AI sprawl, a problem that mirrors the SaaS explosion of a decade ago. With new AI tools emerging every week, enterprises risk overlapping investments and fragmented initiatives. Sumit shares how Blackline uses two governance councils to keep projects aligned. One is dedicated to risk, pulling in voices from legal, security, and privacy. The other is focused on transformation, evaluating whether requests for new AI capabilities make sense, or whether they duplicate what already exists. The signal that sprawl is taking root, he says, is when requests for tools suddenly jump from a few each month to a dozen. We also tackle the build versus buy dilemma. Budgets haven't magically increased just because AI is hot. Jeremy argues that building only makes sense when it reinforces a company's core advantage. Everything else should be bought, integrated, and kept flexible so that organizations can pivot as the AI landscape changes. Both leaders stress that trust, auditability, and value delivery must sit at the center of every investment decision.  

Praveen Ghanta, founder of Fraction and former CEO of HiddenLevers, shares how he turned his experience scaling a bootstrapped SaaS company into a fast-growing fractional talent marketplace. After HiddenLevers reached $8M in ARR and sold for over $100M, he realized that senior fractional engineers were the secret to delivering efficiently without expensive full-time hires. Fraction now serves over 100 SaaS clients with a vetted pool of 500 senior U.S.-based engineers and CTOs. Typical engagements run 10–30 hours a week, helping founders tackle scaling challenges in vertical SaaS, AI engineering, DevOps, and legacy system conversions. The company has reached $10M ARR in just three years while keeping half its own team fractional. Praveen explains how clients use Fraction to save costs, speed development, and even prepare for M&A due diligence with fractional CTOs. He also highlights how AI has boosted senior developer productivity by 4x, why U.S.-only context matters, and how fractional-to-full-time hiring often becomes a win-win path. This interview is perfect for SaaS founders at $1M–10M ARR, hitting scaling issues, vertical SaaS leaders needing senior engineers without VC funding, and founders considering AI-powered product features and engineering talent. Key Takeaways Fractional Individual Contributors: Not just execs—senior engineers deliver hands-on code, marketing, and DevOps part-time. AI Productivity Boost: Senior developers using AI tools are delivering 2–4x more than peers without them. Cost Advantage: Starting at $5K/month, founders access senior dev talent without $200K+ full-time salaries. Best ICP Fit: Vertical SaaS companies at $1–10M ARR facing scaling issues or legacy migrations. Developer Productivity: Fraction leveraged its experience with over 100 clients to build DevHawk.ai, a tool that manages fractional talent and delivers results even more efficiently. This Interview Is Perfect For SaaS founders stuck at scaling challenges without a budget for big teams Bootstrappers and practical founders looking for senior engineering firepower Founders facing legacy code, scaling issues, or AI feature rollouts Non-technical founders struggling to manage offshore or junior dev teams Quote from Praveen Ghanta, founder of Fraction “There are a lot of very experienced engineers who get into a senior developer role, but if they're not going to become the manager of the team, there's not a really good and obvious career path for them. “They start to get bored because they know their job inside and out and it's relatively easy for them to keep delivering.  “So working on a startup on the side is actually a way for both for them to sort of enrich their career and see new things and have that creative satisfaction, but at the same time, not take the risk. There are plenty of folks that want to be full-time at the startup, but there's risk in being at a startup.”  Links Praveen Ghanta on LinkedIn Fraction on LinkedIn Fraction website (fraction.work) DevHawk website Podcast Sponsor – Fraction This podcast is sponsored by Fraction. Fraction gives you access to senior US-based engineers and CTOs — without full-time costs or hiring risks. Get 10 to 30 hours per week from vetted and experienced US-based talent. Find your next fractional senior engineer or CTO at fraction.work. You can start with a one-week, risk-free trial to test it out. 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.

Healthcare is in the middle of a great migration, moving out of traditional "on-prem" data centers and into the cloud. What does that mean for health systems, clinicians, and ultimately patients? Dr. Tim Calahan, Chief Technology Officer at Michigan Medicine, shares a bold vision about how cloud migration is reshaping healthcare infrastructure and unlocking innovation. Dr. Calahan also shares why he's passionate about “getting healthcare out of the data center business.” Watch the video version here. What you'll learn in this episode: Why healthcare organizations are moving out of traditional data centers The benefits of public cloud vs. private cloud in healthcare How Michigan Medicine is executing an unprecedented Epic EHR migration Built-in public cloud tools like AI, machine learning, and advanced security How shifting IT infrastructure to the cloud can move the workforce closer to patient care This episode is a must-listen for healthcare executives, CIOs, CTOs, IT leaders, and clinicians who want to understand the future of digital health, health IT, and healthcare infrastructure. Connect with Dr. Calahan on Linkedin at https://www.linkedin.com/in/dr-tim-calahan Find Dr. Calahan's work at https://www.uofmhealth.org Subscribe and stay at the forefront of the digital healthcare revolution. Watch the full video on YouTube @TheDigitalHealthcareExperience The Digital Healthcare Experience is a hub to connect healthcare leaders and tech enthusiasts. Powered by Taylor Healthcare, this podcast is your gateway to the latest trends and breakthroughs in digital health. Learn more at taylor.com/digital-healthcare About Us: Taylor Healthcare empowers healthcare organizations to thrive in the digital world. Our technology streamlines critical workflows such as procedural & surgical informed consent with patented mobile signature capture, ransomware downtime mitigation, patient engagement and more. For more information, please visit imedhealth.com   The Digital Healthcare Experience Podcast: Powered by Taylor Healthcare Produced by Naomi Schwimmer  Hosted by Chris Civitarese Edited by Eli Banks Music by Nicholas Bach  

AI and robotics are revolutionizing industrial work and automation by enhancing efficiency, reducing costs and safeguarding human workers from hazardous tasks. In this episode, Aaron Saunders, CTO of Boston Dynamics, delves into the transformative potential of AI-powered robotics, highlighting how robots are becoming safer, more cost-effective and widely accessible through Robotics as a Service (RaaS). He shares real-world applications of industrial robotics, insights into ROI and the shift from deterministic systems to open-ended technologies, while also addressing key challenges, such as managing expectations and ensuring data privacy. Timestamps:0:00 Intro03:03 The future of robots with generative AI07:22 Beyond warehouses: New uses for AI robots12:29 ROI from AI-powered robotics15:13 The next phase of AI and robotics18:41 Guidance for CTOs on AI and roboticsThe opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity. AI news is moving fast. Keep your business ahead with updates about AI advancements, strategies and expert perspectives → https://ibm.biz/BdnXVJ #AI #Robotics #IndustrialAutomation #RoboticsasAService #ReturnOnInvestment #SafetyInAutomation #FutureTech #AaronSaunders #DavidLevy

Lindsey S. Mignano is the founder of SSM Legal, an entrepreneurial Silicon Valley corporate lawyer representing emerging technology companies and industry-adjacent firms and small businesses. Her practice spans technology company business formation and expansion into US markets, M&A (flips, entity or asset sales), commercial and technology transactions, and venture financing. Lindsey has been recognized as a “Rising Star” by Super Lawyers every year from 2016-2024, an honor awarded to only 2.5% of attorneys under the age of 40. In 2025, she was awarded the Super Lawyers distinction for the first time at the age of 40, an honor awarded to only 5% of attorneys. Separate from her law practice, Lindsey speaks often about diversity issues in the fields of law, tech, and venture. In 2023, Lindsey founded Venture Betches, a venture fund of funds, and Syndicate Betches, a real estate syndicate fund of funds, both with a social justice mission to bring investment opportunities to historically underrepresented accredited limited partners who identify as female and/or BIPOC/minorities.

How do you apply your leadership skills to a new, mission-driven industry and effectively lead teams across multiple technical domains? In this episode, Simone Kalmakis (VPE @ Viam) shares her playbook for successfully transitioning between industries from health-tech and climate to her current work in robotics and AI. We deconstruct the leadership models she uses to prioritize her time, manage multiple technical experts, and why she focuses on "depth with 1-2 teams > breadth". Plus, her framework for onboarding in a new domain, the lifecycle of a leadership "deep dive," and communication practices that build trust and empower your entire organization to stay aligned and motivated.ABOUT SIMONE KALMAKISSimone Kalmakis is the VP of Engineering at Viam, a platform unlocking AI, data, and automation for devices in the physical world. She has deep experience applying AI and machine learning to big data and big missions, and is known for building healthy engineering organizations that drive business value and real-world progress.Prior to Viam, Simone was Senior Director of Engineering at Arcadia, a climate tech company building an API platform for residential utility data to power solutions that fight climate change. Before that, she served as Director of Engineering at Flatiron Health, where she helped accelerate the development of cancer treatments through real-world data.Simone began her career at Microsoft, developing machine-learned relevance algorithms for Bing. She's also a successful founder––after Microsoft, she built and sold Symbi, a roommate-matching startup. She holds a degree in Mathematics and Economics from Yale University. ToolHive Unlocks the Full Value of MCP & Your AI AgentsSo you've invested in AI agents for code generation, but they're limited to experiments or even stuck on the shelf. To do real, valuable work, those AI agents need access to your data and systems.ToolHive helps you confidently connect the pieces by making it simple and secure for you to use the Model Context Protocol (MCP).ToolHive includes a pre-vetted registry of MCP servers, containerizes every MCP server for consistency and leans on built-in security to keep your secrets safe.Leaders trust ToolHive to put MCP into production and put their AI agents to work.ToolHive is open source, so get started for free at toolhive.dev Join us at ELC Annual 2025ELC Annual is the premier event for engineering leaders. This is our biggest event of the year: 1,000+ CTOs, VPs & Directors in San Francisco @ ELC Annual 2025 for two days of leadership breakthroughs, tactical peer learning & curated connections!