Podcasts about ai ml

In this episode of Pitch Cafe, we sit down with Jeel Patel, a young and ambitious entrepreneur who, just 1.5 years out of college, is already working on his third startup, FieldCamp. His latest venture is building the first fully AI-powered software for SMBs, tapping into a $3 billion market that even VCs struggle to understand. But what makes jeel confident in his success? It's not just the idea—it's his deep industry knowledge, his experienced team, and his ability to leverage real connections with SMBs. Tune in to hear jeel's insights on AI, startup challenges, and why this time, he's betting big! ------------------------------------------------------------------------------ ✨ ABOUT ME ✨ Hello, my name is Vidyangi (Vida) Patil. I am a mindset coach, author, and speaker. Five years ago when I started understanding success hacks for individuals, startups, and larger organizations little did I know I would end up working with mentors hail from Silicon Valley at Stanford University, MIT Media Lab, Singularity University, and incubators and accelerators. All the way from guiding AI/ML startup founders in winning pitch competitions, and bagging investor appointments to helping youth entrepreneurs and women land their dream job or promotion, I plan to spill the beans of wisdom to launch you higher wherever you are in your life. I have successfully coached communities in social impact initiatives during COVID. Every week you will see new videos from me on career, personal growth, and technology trends to onboard your rocket ship to success!

Welcome to another powerful episode of Pitch Cafe Podcast!

Welcome to a special episode covering everything happening at the RSAC 2025. Meet Sameer Ahirrao, Founder & CEO of Ardent Privacy, with 25+ years of experience working with global giants like Deloitte, Lockheed Martin, and Symantec. Joining him is Nick Salian, CISO at Cantor Fitzgeraldic, and an AI regulation expert who's played key roles at Wipro and Palo Alto Networks. In this episode, we dive deep into how AI is transforming the cybersecurity landscape, the biggest trends at RSA 2025, and why AI governance solutions are the next big thing. We also break down the concept of Data Bill of Materials and how Ardent Privacy helps organizations protect critical data infrastructures—whether you're launching new software or safeguarding legacy IT. Sameer's reference in the interview • "AI Ethics by Design Is the Way Ahead to P...

Her early inspiration while growing up in Goa with limited exposure to career options. Her Father's intellectual influence despite personal hardships and shift in focus to technology.Personal tragedy sparked a resolve to become financially independent and learn deeply.Inspirational quote that shaped her mindset: “Even if your dreams haven't come true, be grateful that so haven't your nightmares.”Her first role at a startup with Hands-on work with networking protocols (LDAP, VPN, DNS). Learning using only RFCs and O'Reilly books—no StackOverflow! Importance of building deep expertise for long-term success.Experiences with Troubleshooting and System Thinking; Transitioned from reactive fixes to logical, structured problem-solving. Her depth of understanding helped in debugging and system optimization.Career move to Yahoo where she led Service Engineering for mobile and ads across global data centers got early exposure to big data and machine learning through ad recommendation systems and built "performance and scale muscle" through working at massive scale.Challenges of Scale and Performance Then vs. Now: Problems remain the same, but data volumes and complexity have exploded. How modern tools (like AI/ML) can help identify relevance and anomalies in large data sets.Design with Scale in Mind - Importance of flipping the design approach: think scale-first, not POC-first. Encourage starting with a big-picture view, even when building a small prototype. Highlights multiple scaling dimensions—data, compute, network, security.Getting Into ML and Data Science with early spark from MOOCs, TensorFlow experiments, and statistics; Transition into data science role at Infoblox, a cybersecurity firm with focus areas on DNS security, anomaly detection, threat intelligence.Building real-world ML model applications like supervised models for threat detection and storage forecasting; developing graph models to analyze DNS traffic patterns for anomalies and key challenges of managing and processing massive volumes of security data.Data stack and what it takes to build data lakes that support ML with emphasis on understanding the end-to-end AI pipelineShifts from “under the hood” ML to front-and-center GenAI & Barriers: Data readiness, ROI, explainability, regulatory compliance.Explainability in AI and importance of interpreting model decisions, especially in regulated industries.How Explainability Works -Trade-offs between interpretable models (e.g., decision trees) and complex ones (e.g., deep learning); Techniques for local and global model understanding.Aruna's Book on Interpretability and Explainability in AI Using Python (by Aruna C).The world of GenAI & Transformers - Explainability in LLMs and GenAI: From attention weights to neuron activation.Challenges of scale: billions of parameters make models harder to interpret. Exciting research areas: Concept tracing, gradient analysis, neuron behavior.GenAI Agents in Action - Transition from task-specific GenAI to multi-step agents. Agents as orchestrators of business workflows using tools + reasoning.Real-world impact of agents and AI for everyday lifeAruna Chakkirala is a seasoned leader with expertise in AI, Data and Cloud. She is an AI Solutions Architect at Microsoft where she was instrumental in the early adoption of Generative AI. In prior roles as a Data Scientist she has built models in cybersecurity and holds a patent in community detection for DNS querying. Through her two-decade career, she has developed expertise in scale, security, and strategy at various organizations such as Infoblox, Yahoo, Nokia, EFI, and Verisign. Aruna has led highly successful teams and thrives on working with cutting-edge technologies. She is a frequent technical and keynote speaker, panelist, author and an active blogger. She contributes to community open groups and serves as a guest faculty member at premier academic institutes. Her book titled "Interpretability and Explainability in AI using Python" covers the taxonomy and techniques for model explanations in AI including the latest research in LLMs. She believes that the success of real-world AI applications increasingly depends on well- defined architectures across all encompassing domains. Her current interests include Generative AI, applications of LLMs and SLMs, Causality, Mechanistic Interpretability, and Explainability tools.Her recently published book linkInterpretability and Explainability in AI Using Python: Decrypt AI Decision-Making Using Interpretability and Explainability with Python to Build Reliable Machine Learning Systems  https://amzn.in/d/00dSOwAOutside of work, she is an avid reader and enjoys creative writing. A passionate advocate for diversity and inclusion, she is actively involved in GHCI, LeanIn communities.

Second guest episode of the SP era - with a guy living the dream. Akash worked in the front offices of the New York Yankees and Miami Dolphins as well as a Google data scientist before leaving it all behind to be a full-time bettor.This builds on our recent modeling episodes as we take a jump from simple/ regression based models into the AI/ML blackbox.You can find Akash in the GP Discord under the name joshroyale00:00 Show Intro 01:50 Yankees Front Office 11:05 Transition from Sports Analytics to Betting  23:30 Data Pipelines, Friction Reduction and Useful Features  39:45 AI vs. Pro Sports Bettor49:50 Modeling Philosophy: Transparency vs. Black Boxes  1:11:35 Handling Downswings and Model Validation  1:17:00 News Roundup: IL Tax, FanDuel Ban, Polymarket x Twitter  1:30:50 Listener Q&A Welcome to The Risk Takers Podcast, hosted by professional sports bettor John Shilling (GoldenPants13) and SportsProjections. This podcast is the best betting education available - PERIOD. And it's free - please share and subscribe if you like it.My website: https://www.goldenpants.com/ Follow SportsProjections on Twitter: https://x.com/Sports__ProjWant to work with my betting group?: john@goldenpants.comWant 100s of +EV picks a day?: https://www.goldenpants.com/gp-picks

June 10, 2025 | This episode of The Chain features a panel discussion from May's PEGS Boston. Moderated by Peter Tessier, Albert M. Mattocks professor of Pharmaceutical Sciences and Chemical Engineering at the University of Michigan, the panelists include Sarel Fleishman, professor of Biomolecular Sciences at the Weizmann Institute of Science; Kadina Johnston, senior specialist of Discovery Biologics at Merck & Co.; Vincent Ling, chief business officer of Morphocell Technologies; Arvind Rajpal, SVP of Xaira; and Max Vasquez, chief computing officer of Adimab. Together they discuss benchmarking AI/ML methods compared to traditional approaches, development of human-relevant training data, identifying and addressing core challenges in de novo designs, and more. Links from this episode:  PEGS Boston Conference & Expo Engineering Bispecific Antibodies University of Michigan University of Michigan Chemical Engineering Weizmann Institute of Science Scala Biodesign Merck & Co., Inc. Morphocell Technologies Bill & Melinda Gates Foundation Xaira Adimab LLC 

Guest: Jim Boyd, Founder of Cirrus Group Consulting & EO Sydney Member since 2023 Host: Linh Podetti, Founder of Outsourcing Angel & EO Sydney Member since 2022 Meet Jim Boyd, with 25+ years of experience in IT staffing, who went from managing recruiters to becoming one himself, when a business crisis forced him to rebuild everything from scratch. After launching Cirrus Group Consulting just before COVID, Jim weathered early chaos only to face a second shock in 2022, his entire recruiting team quit. Instead of giving up, Jim learned to recruit himself, restructured the business, and self-implemented EOS to create sustainable systems. Then in 2024, he made a cross-continental move from the US to Australia, managing clients, staff, and systems across time zones while deepening his leadership through the Entrepreneurs' Organization (EO). Whether you're a founder, a recruiter, or someone in a season of rebuilding, this episode offers powerful insights on what it takes to survive and scale. ABOUT JIM BOYD Jim Boyd is the Founder and CEO of Cirrus Group Consulting, an IT staffing firm specialising in cloud computing, cybersecurity, and AI/ML roles. With over two decades in tech staffing, Jim is passionate about specialisation, process improvement, and people-first leadership. He's also an EO Sydney member, originally from Orange County, USA. CONNECT WITH JIM BOYD 

Brett Ewing is the Founder and CEO of AXE.AI, a cutting-edge cybersecurity SaaS start-up, and the Chief Information Security Officer at 3DCloud. He has built a career in offensive cybersecurity, focusing on driving exponential improvement. Brett progressed from a Junior Penetration Tester to Chief Operating Officer at Strong Crypto, a provider of cybersecurity solutions. He brings over 15 years of experience in information technology, with the past six years focused on penetration testing, incident response, advanced persistent threat simulation, and business development. He holds degrees in secure systems administration and cybersecurity, and is currently completing a Masters in cybersecurity with a focus area in AI/ML security at the SANS Technology Institute. Brett also holds more than a dozen certifications in IT, coding, and security from the SANS Institute, CompTIA, AWS, and other industry vendors. In this episode… Penetration testing plays a vital role in cybersecurity, but the traditional manual process is often slow and resource-heavy. Traditional testing cycles can take weeks, creating gaps that leave organizations vulnerable to fast-moving threats. With growing interest in more efficient approaches, organizations are exploring new AI tools to automate tasks like tool configuration, project management, and data analysis. How can cybersecurity teams use AI to test environments faster without increasing risk? AXE.AI offers an AI-powered platform that supports ethical hackers and red teamers by automating key components of the penetration testing process. The platform reduces overhead by configuring tools, analyzing output, and building task lists during live engagements. This allows teams to complete high-quality tests in days instead of weeks. AXE.AI's approach supports complex environments, improves data visibility for testers, and scales efficiently across enterprise networks. The company emphasizes a human-centered approach and advocates for workforce education and training as a foundation for secure AI adoption. In today's episode of She Said Privacy/He Said Security, Jodi and Justin Daniels speak with Brett Ewing, Founder and CEO of AXE.AI, about leveraging AI for offensive cybersecurity. Brett explains how AXE.AI's platform enhances penetration testing and improves speed and coverage for large-scale networks. He also shares how AI is changing both attack and defense strategies, highlighting the risks posed by large language models (LLMs) and deepfakes, and explains why investing in continuous workforce training remains the most important cyber defense for companies today.

Open-source intelligence has historically been used to augment government intelligence about our adversaries.  Government is relying more heavily on commercial data but how does that lend to resiliency, transparency, and deterrence? How should commercial data become more integrated and more trusted? What role does AI/ML have in the future of warfare? This episode features Colonel Lina Cashin (USAF, ret.) from The Aerospace Corporation speaking to USSF Deputy Chief of Space Operations for Intelligence Chief Master Sergeant Ronald Lerch and Clinton Clark, Vice President at data supplier ExoAnalytic Solutions.  This episode is part of the Going Faster Series that discusses various facets of speed, agility, innovation, and rapid deployment in national security, civil, and commercial space.   The Space Policy Show is produced by The Aerospace Corporation's Center for Space Policy and Strategy. It is a virtual series covering a broad set of topics that span across the space enterprise. CSPS brings together experts from within Aerospace, the government, academia, business, nonprofits, and the national labs. The show and their podcasts are an opportunity to learn about and to stay engaged with the larger space policy community. Subscribe to our YouTube channel to watch all episodes!

Go to https://cozyearth.com and use code HUMANHR for 40% off their best-selling sheets, pajamas, towels, and more. And if you get a post-purchase survey? Let them know you heard about Cozy Earth right here.In this episode, Traci Chernoff interviews Eric Charran about his book 'Have You Ever Had a Boss That Succeeded in a Dysfunctional Workplace'. They discuss the impact of toxic leadership on employee well-being and productivity, the archetypes of dysfunctional managers, and practical strategies for navigating these challenges. Eric shares personal experiences that inspired his book and emphasizes the importance of understanding and addressing unhelpful managerial behaviors to foster a healthier workplace culture. In this conversation, Traci Chernoff and Eric Charran delve into the complexities of workplace dynamics, focusing on emotional responses, the importance of managing up, and the necessity of empathy in leadership. They discuss various archetypes of managers, particularly the 'surprised' archetype, and how these behaviors impact team dynamics. The conversation emphasizes the importance of building trust, understanding emotional reactions, and developing coping strategies to navigate workplace challenges effectively. Eric shares insights from his book, encouraging listeners to empower themselves and recognize their worth in professional settings.Chapters00:00 Introduction to Dysfunctional Workplaces02:59 The Genesis of the Book05:53 Understanding Manager Archetypes09:00 The Impact of Toxic Leadership01:53 Breaking the Cycle of Dysfunction14:55 Exploring Manager Archetypes17:46 The Emergency Broadcaster Archetype21:54 Coping with Chaos: Understanding Emotional Responses24:13 Managing Up: The Art of Diplomacy28:43 Building Trust: The Importance of Empathy31:47 The Surprised Archetype: Navigating Unexpected Challenges36:51 Empowerment Through Understanding: Knowing Your WorthWe hope you enjoyed this episode with Eric Charran. If you found our discussion insightful, we'd like you to take a moment to rate our podcast. Your feedback helps us grow and reach more listeners who are passionate about these topics. You can also leave a review and tell us what you loved or what you'd like to hear more of - we're all ears!Don't forget to rate, review, and subscribe! Plus, leave a comment if you're catching this episode on Spotify or YouTube.About Our Guest: Eric Charran is a visionary data and AI executive with over 25 years of experience transforming global organizations through innovative data strategies, AI/ML solutions, and scalable enterprise platforms. He has led the design of next-generation data ecosystems—including lakehouse, mesh, and fabric architectures—driving $250M+ in revenue, reducing time-to-insight by 45%, and boosting marketing ROI by 20%. His expertise spans Generative AI, traditional AI/ML, and multi-cloud strategies that have delivered $30M in annual savings while ensuring resilience and compliance. A recognized thought leader, Eric is passionate about ethical AI, data governance, and building cultures of innovation that align technology with business impact.Connect with Eric Charran here:LinkedIn: https://www.linkedin.com/in/ericcharran/ Connect with Traci here: ⁠https://linktr.ee/HRTraci⁠Disclaimer: Thoughts, opinions, and statements made on this podcast are not a reflection of the thoughts, opinions, and statements of the Company by whom Traci Chernoff is actively employed.Please note that this episode may contain paid endorsements and advertisements for products or services. Individuals on the show may have a direct or indirect financial interest in products or services referred to in this episode.

On this episode of That Tech Pod, Laura and Kevin sit down with Alexander Patrushev, Head of Product for AI/ML at Nebius, a European cloud platform focused on machine learning infrastructure. Kicking things off, we unpack the buzz around China's fully AI-powered “Agent Hospital,” raising questions about what role AI should play in medicine. Laura also shares a personal rant about navigating the healthcare system in search of real answers.Then, Alex joins from Luxembourg to explain what Nebius does, who it's built for, and how it helps companies tackle ML workloads. He breaks down the common mistakes teams make when launching ML projects and why success depends more on people and processes than just tech. The conversation also goes into whether companies should host their own LLMs or use pay-per-token APIs, and how to approach that decision. Looking ahead, Alex challenges the idea that AI is inherently hard and shares what businesses should really be focusing on, from smarter software to evolving hardware needs, as AI infrastructure continues to grow. It's a thoughtful, practical look at the future of AI from someone who builds the tools to power it.Alexander Patrushev is an experienced IT leader with over 15 years in the industry, including the past six focused on artificial intelligence. He currently serves as Head of Product for AI/ML at Nebius, a European cloud platform designed for building and deploying machine learning workloads. Based in Luxembourg, Alexander is known for his practical approach to solving real-world challenges faced by AI practitioners. He's especially focused on delivering user-centric, innovative solutions, and believes strongly in the importance of in-house R&D to drive product excellence and stay ahead in a fast-moving space.

Looking for CPQ solutions and expert advice? In this episode of the CPQ Podcast, we're joined by Julian Hodges, Co-Founder of Sneeyeg, a ServiceNow system integrator specializing in CPQ, billing, and enterprise transformation. With over 20 years of experience from Amdocs, CloudSense, and Salesforce, Julian shares invaluable insights on achieving CPQ success. Discover why strong governance and effective modeling are crucial, and how focusing on business outcomes drives project success. Julian also discusses AI/ML in CPQ for cross-sell and up-sell, the challenges of customization versus configuration, and why large enterprises trust Sneeyeg for CPQ leadership. Tune in for essential CPQ guidance! He also dives into: Sneeyeg's 100% focus on ServiceNow and partnerships with ISVs like Logik.ai and Aria Systems The challenges of customization vs. configuration in modern CPQ implementations How AI/ML is transforming CPQ—especially in cross-sell, up-sell, and retention strategies Why large enterprises in telco, tech, and utilities look to Sneeyeg for CPQ leadership What makes productization a smart move for services firms—and what Sneeyeg is planning next This episode is packed with real-world advice for CPQ professionals, ServiceNow customers, and anyone interested in scaling smarter with AI, governance, and business-led configuration.

Episode 382 of The @Venturefizz Podcast features Abe Murray, General Partner at AlleyCorp. I recently had Matthias Hofmann, the Co-Founder & CEO of Eyebot on the podcast and when I was doing my research on the company, I realized that their recent investment from AlleyCorp was led by one of their partners who was located in the Boston area. It made me pause, as I didn't realize that AlleyCorp had someone in the local Boston area. If you are not familiar with AlleyCorp, it is the venture fund started by Kevin Ryan who is a tech icon in NYC. Kevin led DoubleClick's growth to an IPO and acquisition by Google. He's also a co-founder of MongoDB, Business Insider, Zola, Gilt Groupe, and many others. AlleyCorp was backed as a family office by Kevin until last year when it became an institutional VC firm through the announcement of its $250M Fund I which includes outside LPs for the first time. Abe is leading AlleyCorp's deep tech investments, so it just makes sense that he is based in the the Boston area, as there is such a high concentration of innovation and companies in the Northeast. In this episode of our podcast, we cover: * Abe's background story which includes dropping out of high school to run fishing boats & factories in the family aquaculture business and the importance of growing up with a chip on your shoulder. * Starting his career at BAE Systems where he worked on Generative AI and advanced technologies for the defense industry. * Going to Harvard Business School and working on a startup called Doodbleboard, an online whiteboard. * Landing at Google, then later Alphabet, where he worked on various AI/ML initiatives, as well as the Android mobile team with Rich Miner. * Taking on the healthcare industry and leading the Boston office for Verily, an Alphabet company. * Getting into angel investing and how he landed at AlleyCorp. * All the details about AlleyCorp and the investments they are making across the firm, plus the specifics about what Abe is targeting. * The importance of storytelling and advice on how to get great at it. * And so much more. Eyebot interview: https://venturefizz.com/insights/episode-368-matthias-hofmann-co-founder-ceo-of-eyebot/

 ABOUT PRASHANT RAMARAOPrashant is a hands-on technology executive with extensive experience in software engineering, leading large organizations, specializing in AI / ML, and large-scale systems architecture. With advanced degrees in computer science and engineering leadership, he excels at defining technical strategies that align with business goals, delivering results, and fostering high-performing, cross-functional teams. He cares about engineering excellence, leveraging cutting-edge technology to solve complex problems and scale operations for long-term growth. He has a lifelong passion for learning and looks for opportunities to challenge the status quo to drive change. He loves the outdoors and is a self-proclaimed podaholic - going on long hikes in Bay Area while listening to his podcasts is one of his favorite activities.This episode is brought to you by Side – delivering award-winning QA, localization, player support, and tech services for the world's leading games and technology brands.For over 30 years, Side has helped create unforgettable user experiences—from indies to AAA blockbusters like Silent Hill 2 and Baldur's Gate 3.Learn more about Side's global solutions at side.inc. SHOW NOTES:Behind Prashant's rapid leadership evolution (3:26)Transitioning from IC to management: early steps and surprises (5:51)Navigating the mindset shifts from tech expert to people leader (7:31)Friction points in moving from informal to formal leadership (11:00)Skills for communicating with less technical audiences (13:46)Learning to talk with GMs & other non-technical leaders (16:32)Frameworks for effective meeting planning (19:03)Examples of communicating technical work to execs (20:08)Learning the impact of the “observer effect” (21:59)Incorporating feedback gathered by observing (27:03)Strategies for maintaining technical credibility as a senior leader (29:29)Why personal projects and experimentation matter for leadership growth (32:21)How Prashant's personal projects enhance technical credibility & leadership skills (36:59)Rapid fire questions (37:57)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/

Demetrios and Mohan Atreya break down the GPU madness behind AI — from supply headaches and sky-high prices to the rise of nimble GPU clouds trying to outsmart the giants. They cover power-hungry hardware, failed experiments, and how new cloud models are shaking things up with smarter provisioning, tokenized access, and a whole lotta hustle. It's a wild ride through the guts of AI infrastructure — fun, fast, and full of sparks!Big thanks to the folks at Rafay for backing this episode — appreciate the support in making these conversations happen!// BioMohan is a seasoned and innovative product leader currently serving as the Chief Product Officer at Rafay Systems. He has led multi-site teams and driven product strategy at companies like Okta, Neustar, and McAfee. // Related LinksWebsites: https://rafay.co/~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreMLOps Swag/Merch: [https://shop.mlops.community/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with Mohan on LinkedIn: /mohanatreyaTimestamps:[00:00] AI/ML Customer Challenges[04:21] Dependency on Microsoft for Revenue[09:08] Challenges of Hypothesis in AI/ML[12:17] Neo Cloud Onboarding Challenges[15:02] Elastic GPU Cloud Automation[19:11] Dynamic GPU Inventory Management[20:25] Terraform Lacks Inventory Awareness[26:42] Onboarding and End-User Experience Strategies[29:30] Optimizing Storage for Data Efficiency[33:38] Pizza Analogy: User Preferences[35:18] Token-Based GPU Cloud Monetization[39:01] Empowering Citizen Scientists with AI[42:31] Innovative CFO Chatbot Solutions[47:09] Cloud Services Need Spectrum

I recently read a blog post on AI/ML performance on top of VCF, and figured it was time to invite Frank Denneman back to the podcast. During the episode we discuss VMware Private AI Foundation with NVIDIA, and Frank also mention Ollama as a great starting point.Disclaimer: The thoughts and opinions shared in this podcast are our own/guest(s), and not necessarily those of Broadcom, VMware by Broadcom, or SAP.

This episode provides a detailed guide for individuals preparing for the AWS Certified AI Practitioner (AIF-C01) exam. It outlines the certification's target audience and validated skills, emphasizing a foundational understanding of Artificial Intelligence (AI), Machine Learning (ML), and particularly Generative AI within the AWS cloud. The document breaks down the exam content into five domains, covering everything from basic AI/ML concepts and the machine learning lifecycle to generative AI fundamentals, applying foundation models, responsible AI practices, and security and governance considerations. It also includes practical preparation tips, highlighting key AWS services, recommended study resources (including official AWS materials and third-party practice exams), the importance of hands-on experience, and advice for the exam day, along with sample questions and testimonials from successful candidates.

Sales enablement isn't just a support function anymore; it's a measurable, strategic driver of revenue growth. In this episode of Coach2Scale, Pam Dake, Senior Director of Go-To-Market Enablement at Menlo Security, shares how enablement must evolve from ad hoc product training into a disciplined, data-driven engine that shrinks sales cycles, improves pipeline velocity, and makes forecast calls more predictable. Pam challenges outdated views of enablement as an "art" form and shows why top organizations are treating it as a science rooted in customer outcomes, operational consistency, and frontline manager empowerment.Listeners will walk away with clear strategies for transforming enablement into a competitive advantage: focusing on buyer needs instead of product specs, creating scalable and repeatable coaching frameworks, driving real behavior change at the rep level, and equipping frontline managers to move beyond firefighting into true people development. If you're a CRO or sales leader under pressure to deliver results faster and with fewer resources, this conversation is a must-listen.Key TakeawaySales Enablement Is a Science, Not an ArtEnablement must be tied to measurable business outcomes like deal velocity, quota attainment, and reduced stage duration times, not just soft skills or training events.Product Training Is Not Go-To-Market EnablementTrue enablement focuses on customer challenges, value selling, and behavioral change, not just teaching reps how to pitch features.Frontline Managers Are Overwhelmed and UnderequippedManagers today are drowning in administrative tasks and deal management, leaving little time or structure for effective rep coaching and skill development.Consistency Beats Random Acts of EnablementScalable, repeatable programs with predictable operating cadences outperform sporadic, one-off training initiatives every time.Enablement Needs to Be a Strategic Business PartnerWhen properly positioned, enablement acts as the connective tissue across product, marketing, customer success, and sales, driving better internal alignment and faster revenue cycles.Coaching Is the Unlock for Talent Development and RetentionTeaching managers how to coach systematically, not just manage deals, creates higher performing teams and reduces regrettable attrition.Data Should Guide Enablement, Not Just Support ItAccess to CRM, conversation intelligence, and engagement data enables the diagnosis of root causes of performance gaps and the prescription of targeted, timely interventions.The Inflection Point for Hiring Enablement Is Process PredictabilityCompanies should invest in enablement when there is some repeatability in the sales motion, ensuring that coaching scales what's working rather than patching what's broken.Enablement Can and Should Tip the Scales in Competitive DealsOrganizations that embed enablement into product launches, account strategies, and deal execution cycles are better equipped to win high-stakes opportunities.Ways to Tune In:Spotify: https://open.spotify.com/show/0Yb1wPzUxyrfR0Dx35ym1A Apple Podcasts: https://podcasts.apple.com/us/podcast/coach2scale-how-modern-leaders-build-a-coaching-culture/id1699901434 Google Podcasts: https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy50cmFuc2lzdG9yLmZtL2NvYWNoMnNjYWxlLWhvdy1tb2Rlcm4tbGVhZGVycy1idWlsZC1hLWNvYWNoaW5nLWN1bHR1cmU Amazon Music: https://music.amazon.com/podcasts/fd188af6-7c17-4b2e-a0b2-196ecd6fdf77 Podchaser: https://www.podchaser.com/podcasts/coach2scale-how-modern-leaders-5419703 YouTube: https://www.youtube.com/@Coach2Scale CoachEm™ is the first Coaching Execution Platform that integrates deep learning technology to proactively analyze patterns, highlight the "why" behind the data with root causes, and identify the actions that will ultimately improve business results going forward.  These practical coaching recommendations for managers will help their teams drive more deals, bigger deals, faster deals, and loyal customers. Built with decades of go-to-market experience, world-renowned data scientists, and advanced causal AI/ML technology, CoachEm™ leverages your existing tech stack to increase rep productivity, increase retention, and replicate best practices across your team.Learn more at coachem.io

In this episode of Add To Cart, we chat to Luke Matthews, Head of IT at Camilla, the iconic Australian fashion brand known for its vibrant prints, celebrity fans, and big name collaborations with the likes of Disney and White Lotus. Luke shares how he's building the tech foundations that are powering Camilla's global expansion, from Australia to the US and beyond. He lifts the lid on the hidden challenges of running a best-of-breed tech stack with NetSuite, Shopify and CDP and explains why data discipline, system resilience and seamless customer experience are critical to scaling a creative brand. This episode was brought to you by: Shopify PlusKlaviyoAbout your guest:Luke Matthews is an experienced technology executive with over a decade leading digital transformation and innovation in retail. As Head of IT at Camilla Australia, he drives technology initiatives that enhance customer experience, streamline operations and support growth across physical and online stores. A former CTO at Kitchen Warehouse Australia, Luke championed digital advancements, including website optimisation, data-driven marketing, and click-and-collect solutions. He has also led major projects at Retail Directions, delivering software development and system localisation for global retailers. Luke's expertise spans cybersecurity, AI/ML in retail, data analytics, cloud architecture and business process re-engineering. With a results-driven mindset, he consistently delivers solutions that boost profitability, efficiency and customer engagement.About your host:Nathan Bush is the host of the Add To Cart podcast and a leading ecommerce transformation consultant. He has led eCommerce for businesses with revenue $100m+ and has been recognised as one of Australia's Top 50 People in eCommerce four years in a row. You can contact Nathan on LinkedIn, Twitter or via email.Email hello@addtocart.com.au We look forward to hearing from you! Hosted on Acast. See acast.com/privacy for more information.

In this episode of Coach to Scale, sales trainer and former Olympic trials athlete Neil Wood joins Matt Bonelli to challenge one of the most pervasive mistakes CROs and sales leaders make: reserving coaching only for the bottom performers. Drawing from decades of real-world experience and high-performance athletics, Neil makes the case for why top sales reps need consistent, skill-based coaching just as much as, if not more than, struggling reps.From tactical strategies to improve frontline manager execution to the psychological traps that stall rep development, Neil and Matt explore why most sales training fails to stick, what a real coaching culture looks like, and how reinforcement (not rah-rah) builds consistent revenue teams. If you're serious about sales performance, this episode breaks down what separates good teams from elite ones and why your top talent should be the first to get coached.Key Takeaways 1. Training without reinforcement is a waste of money. Neil argues that without structured follow-up, most sales training is forgotten within days and never translates to behavior change2. Coaching should start with your top performers, not your bottom 20%. Investing in your best reps delivers the highest ROI and accelerates performance gains that actually move the revenue needle.3. Frontline managers aren't equipped — or supported — to coach well. Most FLMs were great reps, not trained coaches, and they're overwhelmed with data, admin tasks, and deal reviews that crowd out skill development.4. The sales profession suffers from a lack of real coaching. Neil defines true coaching as helping reps develop long-term skills, not just managing pipelines or offering encouragement.5. Consistency matters more than intensity. Regular coaching conversations — even 30 minutes every two weeks — drive more lasting impact than sporadic bursts of inspiration or annual sales kickoffs.6. Behavior change happens through accountability and shared success. Neil's approach includes peer story sharing post-training to reinforce skills and inspire adoption through social proof, not just instruction.7. You can't improve what you don't inspect. Many managers accept rep narratives at face value; Neil stresses the importance of inspecting behaviors, not just outcomes, to drive improvement.8. Coaching isn't a sign of weakness — it's what elite performers seek. From Olympic athletes to UFC champions, Neil reminds us that the best in the world all have coaches — and they invest in sharpening their edge.9. A good 1:1 isn't a therapy session or a deal inspection — it's a coaching moment. Neil reframes 1:1s as intentional moments for skill growth, not check-the-box meetings or emotional downloads.10. Similarities don't sell — differences do. Sales reps must stand out with a differentiated value proposition, and so must sales organizations when it comes to coaching their teams.Ways to Tune In:Spotify: https://open.spotify.com/show/0Yb1wPzUxyrfR0Dx35ym1A Apple Podcasts: https://podcasts.apple.com/us/podcast/coach2scale-how-modern-leaders-build-a-coaching-culture/id1699901434 Google Podcasts: https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy50cmFuc2lzdG9yLmZtL2NvYWNoMnNjYWxlLWhvdy1tb2Rlcm4tbGVhZGVycy1idWlsZC1hLWNvYWNoaW5nLWN1bHR1cmU Amazon Music: https://music.amazon.com/podcasts/fd188af6-7c17-4b2e-a0b2-196ecd6fdf77 Podchaser: https://www.podchaser.com/podcasts/coach2scale-how-modern-leaders-5419703 YouTube: https://www.youtube.com/@Coach2Scale CoachEm™ is the first Coaching Execution Platform that integrates deep learning technology to proactively analyze patterns, highlight the "why" behind the data with root causes, and identify the actions that will ultimately improve business results going forward.  These practical coaching recommendations for managers will help their teams drive more deals, bigger deals, faster deals, and loyal customers. Built with decades of go-to-market experience, world-renowned data scientists, and advanced causal AI/ML technology, CoachEm™ leverages your existing tech stack to increase rep productivity, increase retention, and replicate best practices across your team.Learn more at coachem.io

In this episode we are going to discuss Model Context Protocol (MCP) in context of Agentic architecture with Mona - Gen AI Specialist Solutions Architect at AWS.We will cover the challenges of implementing Agents and how MCP can help. We will try to simplify it with an example of MCP with Agents and further delve deep into LangGraph adapters such as FastMCP and FastAPI.You will also learn about implementing MCP architecture on AWS.Apart from her daily job, Mona has published two books Natural Language Processing with AWS AI Services: Derive strategic insights from unstructured data with Amazon Textract and Amazon Comprehend and Google Cloud Certified Professional Machine Learning Study Guide. She has authored multiple on AI/ML and cloud technology and a co-author on a research paper on CORD19 Neural Search. She is also a frequent speaker at multiple conferences such as ISMB 2022, AWS Re:Invent. Links https://www.amazon.com/Natural-Language-Processing-AWS-Services/dp/1801812535https://a.co/d/7rlkZwnBlog - Implement MCP in SageMaker AI https://aws.amazon.com/blogs/machine-learning/extend-large-language-models-powered-by-amazon-sagemaker-ai-using-model-context-protocol/Blog - Implement MCP with Bedrock Agents https://aws.amazon.com/blogs/machine-learning/harness-the-power-of-mcp-servers-with-amazon-bedrock-agents/AWS Hosts: Nolan Chen & Malini ChatterjeeEmail Your Feedback: rethinkpodcast@amazon.com

In this episode of Coach to Scale, we sit down with Tony Burnside, SVP of APJ at Netskope, to dismantle the outdated playbook on sales leadership. Tony challenges the myth that effective managers need to lead through pressure, fear, or control. Instead, he shares his approach to building high-performing, culturally aligned teams, starting with hiring good humans, creating space for accountability, and making coaching a non-negotiable part of the manager's role. With over 200 reps across 15 countries under his leadership, Tony's insights are battle-tested and globally relevant.We dig into what it takes to scale culture across borders, what most leaders miss in their 1:1s, and why every resignation is, as Tony puts it, “a performance review for leadership.” Whether you're a CRO trying to stabilize performance or a frontline leader drowning in deals and check-the-box coaching, this episode delivers practical frameworks and hard-earned lessons for leveling up your org without burning out your team.Key Takeaways:1. Culture drives performance, not charisma or controlBurnside argues that strong sales cultures don't emerge from aggressive personalities but from clarity, consistency, and mutual respect across the organization.2. Good human first" is a hiring filter, not a luxuryHe prioritizes character over credentials, explaining that people who want to win as a team outperform lone wolves in the long run.3. Every resignation is a leadership review.Attrition isn't just HR's concern; Tony reframes it as direct feedback on your leadership brand and your managers' effectiveness.4. Yes, you can be friends with your reps  if you're still willing to hold them accountableBurnside pushes back on the false tradeoff between camaraderie and performance, noting that trust and accountability aren't mutually exclusive.5. Global coaching cultures require local empathy.Leading in APJ taught him that you can't copy-paste U.S. management styles into Japan or India; success comes from adjusting expectations and coaching cadence to cultural norms.6. Managers need a litmus test for connection and respectHe shares a personal test: if you wouldn't grab a drink with a rep while traveling, they may not be the right cultural fit for your team.7. Most managers don't know how to coach because they were never taughtTony calls out the common pattern of promoting star reps without equipping them to lead, which leads to tactical, deal-centric 1:1s instead of skill development.8. He invests personally in his own growth and expects others to do the sameFrom Dale Carnegie to Sandler, Tony's career changed after he paid out of pocket for training; he sees self-investment as a signal of leadership potential.10. Coaching must be operationalized, not left to chance or personalityInformal, unstructured coaching creates inconsistency and lost opportunities; managers need frameworks and tools to coach effectively at scale.Ways to Tune In:Spotify: https://open.spotify.com/show/0Yb1wPzUxyrfR0Dx35ym1A Apple Podcasts: https://podcasts.apple.com/us/podcast/coach2scale-how-modern-leaders-build-a-coaching-culture/id1699901434 Google Podcasts: https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy50cmFuc2lzdG9yLmZtL2NvYWNoMnNjYWxlLWhvdy1tb2Rlcm4tbGVhZGVycy1idWlsZC1hLWNvYWNoaW5nLWN1bHR1cmU Amazon Music: https://music.amazon.com/podcasts/fd188af6-7c17-4b2e-a0b2-196ecd6fdf77 Podchaser: https://www.podchaser.com/podcasts/coach2scale-how-modern-leaders-5419703 YouTube: https://www.youtube.com/@Coach2Scale CoachEm™ is the first Coaching Execution Platform that integrates deep learning technology to proactively analyze patterns, highlight the "why" behind the data with root causes, and identify the actions that will ultimately improve business results going forward.  These practical coaching recommendations for managers will help their teams drive more deals, bigger deals, faster deals, and loyal customers. Built with decades of go-to-market experience, world-renowned data scientists, and advanced causal AI/ML technology, CoachEm™ leverages your existing tech stack to increase rep productivity, increase retention, and replicate best practices across your team.Learn more at coachem.io

Jason Brink is the CEO and co-founder of Datagram, a decentralized real-time communication (RTC) infrastructure platform that leverages underutilized network resources to provide secure, scalable, and cost-effective communication solutions.  Why you should listen Datagram is a decentralized real-time communication (RTC) infrastructure platform that leverages underutilized resources to provide scalable and cost-effective connectivity solutions. It operates as a DePIN (Decentralized Physical Infrastructure Network) baselayer, utilizing an AI-driven, Hyper-Fabric Network to enable fast and scalable connectivity across various applications, including gaming, AI, and telecom. By unifying idle hardware bandwidth into a global decentralized network, Datagram delivers fast, secure, and scalable connectivity for modern internet applications. ​ One of the key features of Datagram is its AI-driven coordination, which dynamically optimizes traffic, congestion control, and scalability while predicting traffic patterns to balance network loads for peak efficiency. This ensures that the network can adapt to varying demands and maintain optimal performance. Additionally, Datagram offers cross-network interoperability through standardized DePIN cross-network communication, ensuring seamless interoperability, improved efficiency, and optimal resource utilization while scaling effortlessly.  Datagram's decentralized architecture eliminates the need for central servers, reducing the risk of single points of failure and enhancing privacy and security. It provides a multifunctional platform with RTC, CDN, GPU compute, and storage functionalities, supporting mission-critical connectivity across the next generation of digital applications. Use cases include distributing AI/ML workloads, enabling seamless real-time audio and video communication, powering multiplayer gaming with ultra-low latency, and accelerating content delivery through a global node network. Supporting links Stabull Finance Datagram Andy on Twitter  Brave New Coin on Twitter Brave New Coin If you enjoyed the show please subscribe to the Crypto Conversation and give us a 5-star rating and a positive review in whatever podcast app you are using.  

In this episode, Carlos Gonzalez de Villaumbrosia interviews Nicholas Daniel, Chief Product Officer at Etsy — the world's largest marketplace for unique and handmade items. Founded in 2005, Etsy has grown into a global platform connecting over 6 million sellers with 90 million buyers worldwide, featuring more than 130 million unique items.Nicholas leads Etsy's product organization, overseeing 30+ product squads that drive innovation across the marketplace. His 11-year tenure at Etsy has been instrumental in transforming the platform from a web-centric marketplace to a multi-platform powerhouse while staying true to its core mission of "keeping commerce human."We explore how Etsy manages its massive scale of unique inventory, leverages AI for better discovery, and maintains the delicate balance between growth and marketplace identity. Nicholas shares insights on structuring product teams around business challenges, measuring seller success, and fostering innovation through features like "Spaces" that enhance browsing experiences.What you'll learn:How Etsy structures its product organization to tackle marketplace challengesStrategies for managing and categorizing millions of unique itemsKey metrics for measuring seller success and platform healthApproaches to balancing automation with maintaining human connectionsThe role of AI in understanding and surfacing unique inventoryKey Takeaways

Tom Young, VP of Sales at BMC Software, joins Matt Benelli to challenge outdated assumptions about how enterprise sales should work. Drawing on decades of experience and a recent moment on the other side of a buying decision, Tom reveals how sellers often leave buyers to navigate complex purchasing decisions alone, leading to stalled deals, weak adoption, and low rep confidence. The problem isn't buyer intent. It's a lack of structure, coaching, and guidance.This conversation gets tactical and strategic. Tom breaks down the myth that buyers know how to buy, why seller-led engagement models outperform passive following, and how high-performing FLMs simplify complexity through coaching, not control. CROs and sales leaders will appreciate the clear through line: when managers teach reps how to lead a buying journey, not just chase a number, sales cycles shorten, win rates improve, and performance becomes repeatable. If you're building a scalable sales org, this is a must-listen.Top TakeawaysEnterprise buyers often don't know how to buy software Despite assumptions, many buyers lack a defined decision process, which means sellers must guide, not follow, their journey.The best salespeople act as guides, not followers When sellers proactively lead buyers through a structured engagement model, the experience improves and adoption increases.Mutual Action Plans need to go beyond the PO date Ending your plan at "PO received" signals self-interest; the real impact comes from aligning with the customer's go-live and success milestones.Effective FLMs sell the engagement model, not the product first Top-performing managers train reps to win by selling how the decision will be made, not just what to buy.Sellers must ask the questions buyers should be asking themselves High-quality discovery isn't just fact-finding; it helps buyers clarify their own thinking, build confidence, and reduce internal friction.Sales cycles fail when reps abdicate process control Letting the buyer “drive” often results in delays, missed stakeholders, and no decision; a structured engagement keeps momentum.Managers must balance pressure with coaching Pushing deals without guiding reps through skills and behavior leads to burnout and underperformance.You can't outsource coaching and rep development Even strong enablement and RevOps support can't replace the day-to-day behavioral coaching frontline managers must deliver.One-on-ones are not for pipeline inspection—they're for skill development Coaching isn't about the forecast; it's about improving rep effectiveness so the forecast becomes more predictable.Every manager needs a consistent, inspectable operating rhythm Without structured 1:1s and repeatable frameworks, rep development becomes ad hoc, and performance becomes unpredictable.Ways to Tune In:Spotify: https://open.spotify.com/show/0Yb1wPzUxyrfR0Dx35ym1A Apple Podcasts: https://podcasts.apple.com/us/podcast/coach2scale-how-modern-leaders-build-a-coaching-culture/id1699901434 Google Podcasts: https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy50cmFuc2lzdG9yLmZtL2NvYWNoMnNjYWxlLWhvdy1tb2Rlcm4tbGVhZGVycy1idWlsZC1hLWNvYWNoaW5nLWN1bHR1cmU Amazon Music: https://music.amazon.com/podcasts/fd188af6-7c17-4b2e-a0b2-196ecd6fdf77 Podchaser: https://www.podchaser.com/podcasts/coach2scale-how-modern-leaders-5419703 YouTube: https://www.youtube.com/@Coach2Scale CoachEm™ is the first Coaching Execution Platform that integrates deep learning technology to proactively analyze patterns, highlight the "why" behind the data with root causes, and identify the actions that will ultimately improve business results going forward.  These practical coaching recommendations for managers will help their teams drive more deals, bigger deals, faster deals, and loyal customers. Built with decades of go-to-market experience, world-renowned data scientists, and advanced causal AI/ML technology, CoachEm™ leverages your existing tech stack to increase rep productivity, increase retention, and replicate best practices across your team.Learn more at coachem.io

In this episode of The New Stack Makers, recorded at KubeCon + CloudNativeCon Europe, Alex Williams speaks with Ville Aikas, Chainguard founder and early Kubernetes contributor. They reflect on the evolution of container security, particularly how early assumptions—like trusting that users would validate container images—proved problematic. Aikas recalls the lack of secure defaults, such as allowing containers to run as root, stemming from the team's internal Google perspective, which led to unrealistic expectations about external security practices.The Kubernetes community has since made strides with governance policies, secure defaults, and standard practices like avoiding long-lived credentials and supporting federated authentication. Aikas founded Chainguard to address the need for trusted, minimal, and verifiable container images—offering zero-CVE images, transparent toolchains, and full SBOMs. This security-first philosophy now extends to virtual machines and Java dependencies via Chainguard Libraries.The discussion also highlights the rising concerns around AI/ML security in Kubernetes, including complex model dependencies, GPU integrations, and potential attack vectors—prompting Chainguard's move toward locked-down AI images.Learn more from The New Stack about Container Security and AIChainguard Takes Aim At Vulnerable Java LibrariesClean Container Images: A Supply Chain Security RevolutionRevolutionizing Offensive Security: A New Era With Agentic AI Join our community of newsletter subscribers to stay on top of the news and at the top of your game. 

Your favorite podcast about nothing continues to find things to talk about. Whatever you do, DO NOT e-mail me at podcast@searls.co or else I will read it on air and tell everyone how smart you sound and how good you look. Video of this edition of the show is up on YouTube. Links to follow: Loving my Tariffmas gifts: external SSD array and pool skimmer, especially My first taste of GitHub Copilot's Agent mode Me putting Agent mode to the test in a fun little screencast Aaron's puns, ranked Videogame consoles like the Switch 2 are NOT exempt from tariffs Digital Foundry's technical analysis of Mario Kart World The stunning Marathon cinematic trailer Star Wars Zero Company is the X-Com game I want Almost 19% of Japanese people in their 20s have spent so much money on gacha they struggled with covering living expenses, survey reveals A bunch of Vision hardware leaks and rumors: 1, 2, 3, 4 People at Apple were calling the AI/ML group AIMLess, lol React Native might not be as popular as you think Boarding passes and check-in could be scrapped in air travel shake-up Incredible plot to print every single possible ticket to win the Texas lotto A Lack of Intelligence, Not Training, May Be Why People Struggle With Computers AI models still struggle to debug software, Microsoft study shows LLM bots + Next.js bankrupting people who design their sites badly Apps are being paid to install frameworks that sell users' bandwidth to proxy providers for AI scrapers OpenAI o3 and o4-mini announced (they also hallucinate more) GPT 4.1 is better at coding Codex CLI is OpenAI's answer to Claude Code Extremely long read: OpenAI is a Systemic Risk to the Tech Industry GPS magnetic quantum is 50x more accurate and unjammable The Gorge is good but takes a sharp left turn into horror town I went to Epic Universe and have opinions

In today's episode, Chandra Kapireddy, head of generative AI, machine learning, and analytics at Truist, delves into the evolving landscape of AI with a particular focus on how GenAI tools reshape the way Truist and similar organizations must navigate model risk management and regulations. GenAI is more versatile than traditional AI, he notes, yet its flexibility introduces new challenges around ensuring model reliability, validating outputs, and making sure that AI-driven decisions don't lead to unfair or opaque outcomes. Chandra's responsible AI approach at Truist is focused on risk mitigation while emphasizing the importance of human oversight in high-stakes decision-making. He points out that while GenAI can vastly improve productivity by handling repetitive or analysis-heavy tasks, it's essential to properly train employees in order to use the tools effectively and not over-rely on their outputs, especially given their tendency to hallucinate or produce inaccurate results. Read the episode transcript here. Guest bio Chandra Kapireddy is head of generative AI, machine learning, and analytics, at Truist. He brings over 27 years of experience building and leading world-class data, analytics, and artificial intelligence teams to the financial services firm. Kapireddy has held key leadership positions at some of the industry's leading companies, including Capital One, Wells Fargo, Bank of America, Oracle, and Amazon Web Services. Most recently, he served as managing director and head of AI/ML products for JPMorgan Chase, where he served on the firm's AI Executive Council, which influences its strategy, products, controls, and governance. Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the executive producer is Allison Ryder. Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.

Today, I'm talking with Natalia Andreyeva from Infor about AI / ML product management and its application to supply chain software. Natalia is a Senior Director of Product Management for the Nexus AI / ML Solution Portfolio, and she walks us through what is new, and what is not, about designing AI capabilities in B2B software. We also got into why user experience is so critical in data-driven products, and the role of design in ensuring AI produces value. During our chat, Natalia hit on the importance of really nailing down customer needs through solid discovery and the role of product leaders in this non-technical work. We also tackled some of the trickier aspects of designing for GenAI, digital assistants, the need to keep efforts strongly grounded in value creation for customers, and how even the best ML-based predictive analytics need to consider UX and the amount of evidence that customers need to believe the recommendations. During this episode, Natalia emphasizes a huge key to her work's success: keeping customers and users in the loop throughout the product development lifecycle.   Highlights/ Skip to What Natalia does as a Senior Director of Product Management for Infor Nexus (1:13) Who are the people using Infor Nexus Products and what do they accomplish when using them (3:01) Breaking down who makes up Natalia's team (4:15) What role does AI play in Natalia's work? (5:42) How do designers work with Natalia's team? (7:27) The problem that had Natalia rethink the discovery process when working with AI and machine learning applications (10:38) Why Natalia isn't worried about competitors catching up to her team's design work (14:34) How Natalia works with Infor Nexus customers to help them understand the solutions her team is building (23:17) The biggest challenges Natalia faces with building GenAI and machine learning products (27:35) Natalia's four steps to success in building AI products and capabilities (35:03) Where you can find more from Natalia (36:59)   Quotes from Today's Episode “I always launch discovery with customers, in the presence of the UX specialist [our designer]. We do the interviews together, and [regardless of who is facilitating] the goal is to understand the pain points of our customers by listening to how they do their jobs today. We do a series of these interviews and we distill them into the customer needs; the problems we need to really address for the customers. And then we start thinking about how to [address these needs]. Data products are a particular challenge because it's not always that you can easily create a UX that would allow users to realize the value they're searching for from the solution. And even if we can deliver it, consuming that is typically a challenge, too. So, this is where [design becomes really important]. [...] What I found through the years of experience is that it's very difficult to explain to people around you what it is that you're building when you're dealing with a data-driven product. Is it a dashboard? Is it a workboard? They understand the word data, but that's not what we are creating. We are creating the actual experience for the outcome that data will deliver to them indirectly, right? So, that's typically how we work.” - Natalia Andreyeva (7:57) “[When doing discovery for products without AI], we already have ideas for what we want to get out. We know that there is a space in the market for those solutions to come to life. We just have to understand where. For AI-driven products, it's not only about [the user's] understanding of the problem or the design, it is also about understanding if the data exists and if it's feasible to build the solution to address [the user's] problem. [Data] feasibility is an extremely important piece because it will drive the UX as well.” - Natalia Andreyeva (11:00) “When [the team] discussed the problem, it sounded like a simple calculation that needed to be created [for users]. In reality, it was an entire process of thinking of multiple people in the chain [of command] to understand whether or not a medical product was safe to be consumed. That's the outcome we needed to produce, and when we finally did, we actually celebrated with our customers and with our designers. It was one of the most difficult things that we had to design. So why did this problem actually get solved, and why we were the ones who solved it? It's because we took the time to understand the current user experience through [our customer] interviews. We connected the dots and translated it all into a visual solution. We would never be able to do that without the proper UX and design in that place for the data.” - Natalia Andreyeva (13:26) “Everybody is pressured to come up with a strategy [for AI] or explain how AI is being incorporated into their solutions and platform, but it is still essential for all of my peers in product management to focus on the value [we're] creating for customers. You cannot bypass discovery. Discovery is the essential portion where you have to spend time with your customers, champions, advisors, and their leads, but especially users who are doing this [supply chain] job every single day—so we understand where the pain point really is for them, we solve that pain, and we solve it with our design team as a partner, so that solution can surface value. ” - Natalia Andreyeva (22:18) “GenAI is a new field and new technology. It's evolving quickly, and nobody really knows how to properly adapt or drive the adoption of AI solutions. The speed of innovation [in the AI field] is a challenge for everybody. People who work on the frontlines (i.e. product, engineering teams), have to stay way ahead of the market. Meanwhile, customers who are going to be using these [AI] solutions are not going to trust the [initial] outcomes. It's going to take some time for people to become comfortable with them. But it doesn't mean that your solution is bad or didn't find the market fit. It's just not time for your [solution] yet. Educating our users on the value of the solution is also part of that challenge, and [designers] have to be very careful that solutions are accessible. Users do not adopt intimidating solutions.” - Natalia Andreyeva (27:51) “First, discovery—where we search for the problems. From my experience, [discovery] works better if you're very structured. I always provide [a customer] with an outline of what needs to happen so it's not a secret. Then, do the prototyping phase and keep the customer engaged so they can see the quick outcomes of those prototypes. This is where you also have to really include the feasibility of the data if you're building an AI solution, right? [Prototyping] can be short or long, but you need to keep the customer engaged throughout that phase so they see quick outcomes. Keep on validating this conceptually, you know, on the napkin, in Figma, it doesn't really matter; you have to keep on keeping them engaged. Then, once you validate it works and the customer likes it, then build. Don't really go into the deep development work until you know [all of this!] When you do build, create a beta solution. It only has to work so much to prove the value. Then, run the pilot, and if it's successful, build the MVP, then launch. It's simple, but it is a lot of work, and you have to keep your customers really engaged through all of those phases. If something doesn't work [along the way], try to pivot early enough so you still have a viable product at the end.” - Natalia Andreyeva (35:03)   Links Natalia's LinkedIn

In this conversation of Coach the Scale, host Matt Benelli sits down with Michael Janes, CRO, investor, and co-founder of Rapid Commercialization Partners, to explore why top sales leaders are shifting their focus upstream. Janes unpacks his core philosophy: Sell to the strategy behind the capital, revealing how understanding a company's ownership structure, whether private equity, venture-backed, or founder-led, can dramatically reshape how reps position value, influence internal champions, and align with executive priorities.From myth-busting the idea that activity volume alone drives results to challenging how most one-on-ones miss the mark, Janes offers a grounded yet forward-looking perspective on what it takes to lead high-performance sales organizations. Listeners will walk away with practical insights on coaching beyond the forecast, the dangers of “super rep” management, and why the real leverage often starts at the board level, not the buying committee. If you're a CRO or sales leader aiming to uplevel your team and shorten the path to influence, this conversation is required listening.Key Takeaways:1. Sell to the strategy behind the capitalDon't just “follow the money”—understand the investor's goals and align your sales motion to how capital is deployed, managed, and expected to grow.2. Coaching needs to shift from deal review to skill developmentMost one-on-ones are ineffective because they focus on forecasting instead of developing the behaviors that lead to consistent performance.3. One-on-ones are broken when they lack preparation and structureGreat coaching starts with preparation; otherwise, reps get a therapy session or a pipeline interrogation, not actual development.4. Sales managers are overwhelmed and under-equippedFLMs are juggling too many priorities with little training on how to coach or drive rep performance—this gap undermines quota attainment.5. Activity without purpose is a myth that needs killingThe old-school mindset of “just make more calls” misses the point; consistency only matters if it's paired with relevance and precision.6. Start high and cascade down—not the other way aroundThe most strategic salespeople begin with senior-level conversations, understanding investor priorities, then work downward to shape the internal sale.7. Internal champions are built through strategic guidance, not feature pitching.Could you make sure to provide your buyers with the narrative they need to sell internally by aligning your message with capital goals and business outcomes?8. Overlay roles only work when they add real valueJanes proved that overlays focused on investor relations can be a force multiplier—but only if they help reps access decision-makers and frame deals through a capital lens.9. Respect the chain of command—but don't ask permissionWhen engaging PE or VC boards, it's critical to keep execs in the loop without letting them gatekeep the conversation.10. Managers need enablement, too—not just repsThe assumption that great reps make great managers is flawed; without systems, training, and coaching support, FLMs can't scale performance across the team.Ways to Tune In:Spotify: https://open.spotify.com/show/0Yb1wPzUxyrfR0Dx35ym1A Apple Podcasts: https://podcasts.apple.com/us/podcast/coach2scale-how-modern-leaders-build-a-coaching-culture/id1699901434 Google Podcasts: https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy50cmFuc2lzdG9yLmZtL2NvYWNoMnNjYWxlLWhvdy1tb2Rlcm4tbGVhZGVycy1idWlsZC1hLWNvYWNoaW5nLWN1bHR1cmU Amazon Music: https://music.amazon.com/podcasts/fd188af6-7c17-4b2e-a0b2-196ecd6fdf77 Podchaser: https://www.podchaser.com/podcasts/coach2scale-how-modern-leaders-5419703 YouTube: https://www.youtube.com/@Coach2Scale CoachEm™ is the first Coaching Execution Platform that integrates deep learning technology to proactively analyze patterns, highlight the "why" behind the data with root causes, and identify the actions that will ultimately improve business results going forward.  These practical coaching recommendations for managers will help their teams drive more deals, bigger deals, faster deals, and loyal customers. Built with decades of go-to-market experience, world-renowned data scientists, and advanced causal AI/ML technology, CoachEm™ leverages your existing tech stack to increase rep productivity, increase retention, and replicate best practices across your team.Learn more at coachem.io

Industrial Talk is onsite at PowerGen 2025 and talking to Buddy Lee, Artificial Intelligence SME at Mesa Associates about "AI and Asset Management". Scott MacKenzie hosts an industrial podcast from Power Gen in Dallas, Texas, celebrating industry professionals and discussing innovations. Buddy Lee from Mesa Associates, an AI subject matter expert, shares his background in electrical engineering and reliability engineering. Buddy discusses the application of AI in asset management, particularly in detecting anomalies and predicting failures in industrial machinery. He highlights the importance of having a good data set for AI models, emphasizing the need for accurate and reliable data. Buddy also touches on the cultural challenges of implementing AI in industrial settings and the potential for AI to improve operational efficiency and reduce maintenance costs. Action Items [ ] Reach out to Buddy Lee to discuss further details on Mesa's AI-powered asset management solutions. [ ] Explore opportunities to instrument industrial equipment and collect relevant sensor data for AI/ML model development. [ ] Assess current maintenance practices and failure modes to determine if an FMEA-based AI approach could provide value. Outline Introduction and Welcome to Industrial Talk Podcast Scott MacKenzie introduces the Industrial Talk Podcast, emphasizing its focus on industry professionals and their innovations. Scott welcomes listeners to the platform, highlighting the importance of industry professionals in solving global problems. The podcast is broadcasting from Power Gen in Dallas, Texas, showcasing the latest innovations in the power generation industry. Scott mentions the excitement of the event and the opportunities to explore new technologies on the show floor. Introduction of Buddy Lee and His Background Scott introduces Buddy Lee from Mesa Associates, who has previously been a guest on the show. Buddy shares his background, mentioning his education at the University of Tennessee and Carson Newman College. Buddy discusses his degrees in church music, electrical engineering, MBA, and Masters of Engineering in reliability engineering. Scott notes Buddy's enthusiasm for Tennessee and his support for the University of Tennessee's football team. Discussion on Power Generation and AI in the Industry Buddy talks about his positive experience at the Power Gen conference, highlighting the technical information and new equipment available. They discuss the advancements in small modular reactors and AI in the hydro industry. Scott and Buddy touch on the role of AI in driving power demand, particularly in data centers. Buddy explains his role as the AI subject matter expert at Mesa Associates, focusing on industrial applications. Buddy's Thesis on AI Models and Data Sets Buddy shares his thesis on using AI models with limited data sets, specifically vibration analysis from a paper machine. He explains the process of comparing AI models to human analysts using a seven-year database of vibration data. Buddy highlights the accuracy of five AI models in predicting bearing failures, achieving 95% accuracy. Scott and Buddy discuss the differences between large language models and small data sets in AI applications. AI Applications in Industrial Asset Management ...

This blog defines the governance requirements that streaming data pipelines must meet to make artificial intelligence/machine learning (AI/ML) initiatives successful. Published at: https://www.eckerson.com/articles/streaming-data-governance-three-must-have-requirements-to-support-ai-ml-innovation

Hello Las Vegas — we've arrived for Google Cloud Next 2025!Arthur C. Clarke's third law, "Any sufficiently advanced technology is indistinguishable from magic"Hot drop coming through! The Cloud Realities podcast team has landed in electric Las Vegas—and you know what they say: what happens in Vegas normally stays in Vegas... but in this case, we're bringing 8 incredible conversations in the coming days with inspiring Google guests who are shaping the future of cloud, data, and AI.On the first day, we have 3 separate episodes lined up to discuss Google AI strategy & vision, practical implementations, and exciting use cases.In the second conversation, Dave, Esmee, and Rob, talk with Charlotte Gistelinck, Machine Learning / AI Partner Engineer at Google, on how strategic thinking and visioning in AI/ML are key to driving innovation and long-term success.TLDR00:24 Introduction of Charlotte Gistelinck 04:12 Key announcements from the Google Cloud Next Keynote 07:17 Main conversation with Charlotte about Strategic Thinking and Visioning in AI  37:14 Who's your favorite magician?GuestCharlotte Gistelinck: https://www.linkedin.com/in/charlottegistelinck/HostsDave Chapman: https://www.linkedin.com/in/chapmandr/Rob Kernahan: https://www.linkedin.com/in/rob-kernahan/ProductionMarcel van der Burg: https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman: https://www.linkedin.com/in/chapmandr/SoundBen Corbett: https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:  https://www.linkedin.com/in/louis-corbett-087250264/'Cloud Realities' is an original podcast from Capgemini

Hello Las Vegas — we've arrived for Google Cloud Next 2025!Arthur C. Clarke's third law, "Any sufficiently advanced technology is indistinguishable from magic"Hot drop coming through! The #CloudRealities podcast team has landed in electric Las Vegas—and you know what they say: what happens in Vegas normally stays in Vegas... but in this case, we're bringing 8 incredible conversations in the coming days with inspiring guests who are shaping the future of cloud, data, and AI.On the first day, we have 3 separate episodes lined up to discuss Google AI strategy & vision, practical implementations, and exciting use cases.In the third conversation, Dave, Esmee, and Rob talk with Jim Anderson, VP, NA Partner Ecosystem & Channels at Google, on how customers are using Cloud, AI/ML, and Data Analytics to power digital transformation. From real-world success stories to the trends shaping the year ahead—this one's packed with actionable insights.TLDR00:23 Introduction of Jim Anderson04:17 Key announcements from the Google Cloud Next Keynote06:44 Main conversation with Jim Anderson about Driving Digital Transformation with Customers 24:50 Who's your favorite magician?GuestJim Anderson: https://www.linkedin.com/in/jimmya/HostsDave Chapman: https://www.linkedin.com/in/chapmandr/Rob Kernahan: https://www.linkedin.com/in/rob-kernahan/ProductionMarcel van der Burg: https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman: https://www.linkedin.com/in/chapmandr/SoundBen Corbett: https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:  https://www.linkedin.com/in/louis-corbett-087250264/'Cloud Realities' is an original podcast from Capgemini

Discusses the importance of fostering AI literacy in research and higher education. Our guest today is Sarah Florini who is an Associate Director and Associate Professor in the Lincoln Center for Applied Ethics at Arizona State University. Sarah's work focuses on technology, social media, technology ethics, digital ethnography, and Black digital culture. Among other things, Sarah is dedicated to fostering critical AI literacy and ethical engagement with AI/ML technologies. She founded the AI and Ethics Workgroup to serve as a catalyst for critical conversations about the role of AI models in higher education.  Additional resources: Distributed AI Research Institute: https://www.dair-institute.org/ Mystery AI Hype Theater 3000: https://www.dair-institute.org/maiht3k/ Tech Won't Save Us: https://techwontsave.us/ CITI Program's Essentials of Responsible AI course: https://about.citiprogram.org/course/essentials-of-responsible-ai/ 

In this episode, bestselling author and CEO of Blind Spots, Kevin McCarthy, shares a deeply personal story of how unchecked blind spots, not bad intent, can quietly derail careers, culture, and company performance. After spending 33 months in federal prison for a white-collar crime he didn't knowingly commit, Kevin emerged with a mission: help leaders see what they're not seeing before it costs them everything.When top performers become first-line managers, most are handed the title without the tools. We explore why so many sales managers default to deal reviews instead of skill development, how perception gaps fracture team trust, and why most coaching is misnamed and misdirected. Kevin breaks down the cognitive science behind decision-making under pressure and explains how poor coaching hygiene is driving regrettable attrition. This conversation hits directly at the heart of today's frontline execution crisis and offers a clear path forward for CROs who want to scale with integrity.Top Takeaways: Blind spots—not bad intentions—derail leaders. Kevin's story underscores that well-meaning leaders can still make costly mistakes if they lack self-awareness and critical thinking under pressure.Perception gaps destroy trust and performance. The difference between how a manager intends to communicate and how it's received can lead to misalignment, demotivation, and attrition.Sales managers are promoted, not prepared. High-performing reps are often elevated into management without training in people leadership, coaching skills, or emotional intelligence.Most sales coaching isn't actually coaching. Managers default to forecasting and deal reviews, missing the opportunity to develop reps' skills in a systematic and personalized way.One-size-fits-all management breaks teams. Kevin explains how failing to adapt your coaching style to each rep's communication style and mindset leads to disengagement.The hardest job in the company is being ignored. First-line managers juggle execution, admin, and development but rarely get the support, tools, or training to coach effectively.Reps leave when they don't feel developed. Talent walks when managers only talk numbers. Real coaching connects with reps' goals, strengths, and growth trajectory.Self-awareness is the most underdeveloped leadership skill. Kevin makes the case that improving self-awareness and emotional intelligence in managers is the single best lever for improving sales culture.Frontline execution problems are strategic risks. What looks like a rep issue is often a management system failure—CROs must prioritize manager enablement if they want predictable performance.Ways to Tune In:Spotify: https://open.spotify.com/show/0Yb1wPzUxyrfR0Dx35ym1A Apple Podcasts: https://podcasts.apple.com/us/podcast/coach2scale-how-modern-leaders-build-a-coaching-culture/id1699901434 Google Podcasts: https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy50cmFuc2lzdG9yLmZtL2NvYWNoMnNjYWxlLWhvdy1tb2Rlcm4tbGVhZGVycy1idWlsZC1hLWNvYWNoaW5nLWN1bHR1cmU Amazon Music: https://music.amazon.com/podcasts/fd188af6-7c17-4b2e-a0b2-196ecd6fdf77 Podchaser: https://www.podchaser.com/podcasts/coach2scale-how-modern-leaders-5419703 YouTube: https://www.youtube.com/@Coach2Scale CoachEm™ is the first Coaching Execution Platform that integrates deep learning technology to proactively analyze patterns, highlight the "why" behind the data with root causes, and identify the actions that will ultimately improve business results going forward.  These practical coaching recommendations for managers will help their teams drive more deals, bigger deals, faster deals, and loyal customers. Built with decades of go-to-market experience, world-renowned data scientists, and advanced causal AI/ML technology, CoachEm™ leverages your existing tech stack to increase rep productivity, increase retention, and replicate best practices across your team.Learn more at coachem.io

Join us on "Beyond the Numbers: Leadership, Diversity, and Data with Natalie Cramp, Partner at JMAN Group," where we dive deep into the intersections of data science, leadership, and advocacy for diversity. Each episode, hosted by Natalie Cramp, offers an exploration of how data-driven strategies can reshape industries and enhance decision-making processes. Natalie brings nearly two decades of experience across private, public, and third sectors, providing unique insights into mobilizing technology and people to address complex challenges. In this series, we'll uncover the transformative power of data in driving business success and societal change. Natalie will share her expertise in scaling organizations, entering new markets, and leading significant transformations. Additionally, we focus on her passionate work in promoting gender equality in healthcare through data, offering listeners actionable insights and inspiration to leverage data for impactful change. Whether you're a CEO looking to harness the potential of AI, a data professional aiming to advance in the tech field, or someone interested in the crucial role of data ethics and education, this podcast will equip you with the knowledge and perspectives needed to lead effectively in today's data-centric world. Tune in to gain leadership insights from one of the data industry's most influential figures and learn how you can contribute to a more diverse and inclusive data science landscape. Learn more about Leadership in AI/ML at DSS SEA on April 16 https://www.datascience.salon/seattle/

Welcome to the TestGuild Automation Podcast! In this episode, host Joe Colantonio sits down with Gaurav Mittal, a cybersecurity, data science, and IT expert with over two decades of experience. Gaurav, recognized for his thought leadership in AI and automation with multiple industry awards, shares his insights on making How To Optimize your Automation CI/CD Pipelines in DevOps more cost-effective. Whether you're a test automation engineer or security professional or work with AI/ML, you'll want to hear Gaurav's take on implementing DevOps pipelines that reduce licensing costs and enhance flexibility without sacrificing your team's productivity. Learn about his experiences with GitHub Actions, Jenkins, and the innovative ways he's optimized CI/CD pipelines to save resources and automate extensive testing processes, all while incorporating strong security measures. Join us as we delve into the innovative strategies and practical advice that can help transform your DevOps practices.

Matt Benelli sits down with Mike Montague, sales and marketing expert at Avenue9 and host of the Human-First AI Marketing podcast, for a candid conversation about what sales managers are still getting wrong about coaching. From the myth that leaders need to have all the answers to the burnout caused by "super reps" turned managers, Mike breaks down why most 1:1s fail and how asking better questions can flip the script on team performance. If you're still equating pipeline reviews with coaching, this one's for you.They also unpack the critical gap between coaching and execution and why online learning and conversation intelligence tools fall short without behavior change. Mike shares his "Iron Man vs. Terminator" analogy to help sales leaders reframe their use of AI and makes the case for exposure therapy and tough love as the missing ingredients in most sales organizations. Whether you're trying to scale performance or stop regrettable attrition, this episode gives frontline and senior leaders a roadmap for more effective, accountable teams.Top Takeaways:Coaching is about asking questions, not giving answers. Managers who try to “know it all” become bottlenecks; real coaching empowers reps to think for themselves.The best leaders make themselves irrelevant. Like elite sports coaches, great sales leaders build systems and skills so teams can operate independently.AI won't replace salespeople, but it will replace those who don't use it. Sales leaders need to think like Ironman, using AI as an enhancement tool to increase awareness and execution, not as a replacement for human strategy.The frontline sales manager (FLM) role is the hardest in the company. FLMs are overwhelmed by tasks, undertrained in coaching, and lack the time or tools to develop their teams effectively.Selling someone what they need and can afford isn't cheating—it's your job. Sales should focus on qualified buyers with budget, authority, and urgency, not on convincing disinterested prospects.Coaching fails when it focuses only on deals, not skills. Most coaching sessions are just pipeline reviews; they don't address the behaviors that improve performance in the long term.Exposure therapy is essential for growth. Managers need more reps, not more theory, to improve at hard conversations or high-stakes moments.Online learning is helpful but only if it's paired with feedback and behavior change. Asynchronous learning tools often reinforce what reps already know; without coaching moments, they don't close performance gaps.Managers who need approval frequently avoid necessary conversations. Leadership requires discomfort, and effective managers must overcome the urge to be liked to hold reps accountable.Coaching is different from managing—and most people don't know how to do it. There's a widespread misunderstanding of coaching; most FLMs were never taught how to develop others, and it shows.Ways to Tune In:Spotify: https://open.spotify.com/show/0Yb1wPzUxyrfR0Dx35ym1A Apple Podcasts: https://podcasts.apple.com/us/podcast/coach2scale-how-modern-leaders-build-a-coaching-culture/id1699901434 Google Podcasts: https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy50cmFuc2lzdG9yLmZtL2NvYWNoMnNjYWxlLWhvdy1tb2Rlcm4tbGVhZGVycy1idWlsZC1hLWNvYWNoaW5nLWN1bHR1cmU Amazon Music: https://music.amazon.com/podcasts/fd188af6-7c17-4b2e-a0b2-196ecd6fdf77 Podchaser: https://www.podchaser.com/podcasts/coach2scale-how-modern-leaders-5419703 YouTube: https://www.youtube.com/@Coach2Scale CoachEm™ is the first Coaching Execution Platform that integrates deep learning technology to proactively analyze patterns, highlight the "why" behind the data with root causes, and identify the actions that will ultimately improve business results going forward.  These practical coaching recommendations for managers will help their teams drive more deals, bigger deals, faster deals, and loyal customers. Built with decades of go-to-market experience, world-renowned data scientists, and advanced causal AI/ML technology, CoachEm™ leverages your existing tech stack to increase rep productivity, increase retention, and replicate best practices across your team.Learn more at coachem.io

Ever wondered how companies like Amazon or Pinterest deliver lightning-fast image search? Dive into this episode of MongoDB Podcast Live with Shane McAllister and Nenad, a MongoDB Champion, as they unravel the magic of semantic image search powered by MongoDB Atlas Vector Search!

In this Light Reading Extra podcast, SES' Nadine Allen explains how the satellite operator is applying AI, ML and SDN to improve application and network performance, and how the company is providing connectivity to underserved areas. Hosted on Acast. See acast.com/privacy for more information.

Rooshana Purnyn, Director of Data Architecture and Platform Engineering at Hyatt, discusses the potential of Generative AI in the hospitality sector, and how Hyatt is integrating AI to enhance guest experiences in their 1300 properties worldwide. She also emphasizes the need for balancing technology with human interaction, and fostering a culture of continuous learning within her team. Key Takeaways: How AI is used to understand, anticipate, and enhance the unique needs and travel habits of each guest. How Hyatt leverages AI to deliver seamless, highly personalized guest experiences across its 1,300 worldwide properties. The critical role of robust data architecture and pipeline design in supporting hospitality analytics. How a culture of innovation and a growth mindset drive the recruitment and development of Hyatt's teams. Guest Bio: Rooshana Purnyn is an innovative and strategic technology leader with extensive experience across the hospitality, healthcare, retail, finance, and marketing sectors. With over a decade of expertise in data and analytics, Rooshana serves as the Director of Data Architecture and Platform Engineering at Hyatt, where she is celebrated for designing, building, and managing large-scale, cutting-edge technology platforms that support data-driven decision making. A visionary in leveraging technology for business growth, Rooshana led the development of an advanced analytics platform optimized for AI/ML and generative AI workloads, enabling real-time data processing and supporting algorithmic product development to drive revenue and customer engagement. In her role, Rooshana has overseen the deployment of secure, globally accessible analytics applications, including the implementation of an AI-powered self-service analytics tool that empowers stakeholders with data insights. Her work in the AI/ML and generative AI space includes establishing scalable infrastructure and pipelines for machine learning operations (MLOps), allowing for seamless deployment of personalized customer experiences. Rooshana's commitment to innovation keeps her at the forefront of industry trends, while her customer-focused and data-centric approach consistently drives value and growth. ---------------------------------------------------------------------------------------- About this Show: The Brave Technologist is here to shed light on the opportunities and challenges of emerging tech. To make it digestible, less scary, and more approachable for all! Join us as we embark on a mission to demystify artificial intelligence, challenge the status quo, and empower everyday people to embrace the digital revolution. Whether you're a tech enthusiast, a curious mind, or an industry professional, this podcast invites you to join the conversation and explore the future of AI together. The Brave Technologist Podcast is hosted by Luke Mulks, VP Business Operations at Brave Software—makers of the privacy-respecting Brave browser and Search engine, and now powering AI everywhere with the Brave Search API. Music by: Ari Dvorin Produced by: Sam Laliberte  

In this episode, we sit with security leader and venture investor Sergej Epp to discuss the Cloud-native Security Landscape. Sergej currently serves as the Global CISO and Executive at Cloud Security leader Sysdig and is a Venture Partner at Picus Capital. We will dive into some insights from Sysdig's recent "2025 Cloud-native Security and Usage Report."Big shout out to our episode sponsor, Yubico!Passwords aren't enough. Cyber threats are evolving, and attackers bypass weak authentication every day. YubiKeys provides phishing-resistant security for individuals and businesses—fast, frictionless, and passwordless.Upgrade your security:https://yubico.comSergj and I dove into a lot of great topics related to Cloud-native Security, including:Some of the key trends in the latest Sysdig 2025 Cloud-native Security Report and trends that have stayed consistent YoY. Sergj points out that while attackers have stayed consistent, organizations have and continue to make improvements to their securitySergj elaborated on his current role as Sysdig's internal CISO and his prior role as a field CISO and the differences between the two roles in terms of how you interact with your organization, customers, and the community.We unpacked the need for automated Incident Response, touching on how modern cloud-native attacks can happen in as little as 10 minutes and how organizations can and do struggle without sufficient visibility and the ability to automate their incident response.The report points out that machine identities, or Non-Human Identities (NHI), are 7.5 times riskier than human identities and that there are 40,000 times more of them to manage. This is a massive problem and gap for the industry, and Sergj and I walked through why this is a challenge and its potential risks.Vulnerability prioritization continues to be crucial, with the latest Sysdig report showing that just 6% of vulnerabilities are “in-use”, or reachable. Still, container bloat has ballooned, quintupling in the last year alone. This presents real problems as organizations continue to expand their attack surface with expanded open-source usage but struggle to determine what vulnerabilities truly present risks and need to be addressed.We covered the challenges with compliance, as organizations wrestle with multiple disparate compliance frameworks, and how compliance can drive better security but also can have inverse impacts when written poorly or not keeping pace with technologies and threats.We rounded out the conversation with discussing AI/ML packages and the fact they have grown by 500% when it comes to usage, but organizations have decreased public exposure of AI/ML workloads by 38% since the year prior, showing some improvements are being made to safeguarding AI workloads from risks as well.

In this episode of the TestGuild Automation Podcast, host Joe Colantonio chats with machine learning engineer Lakshmithejaswi Narasannagari, who boasts over fourteen years of experience working with tech giants like Intuit, Incom, and Poshmark. Check out App Automate: https://testguild.me/appautomate2 Lakshmi delves into her fascinating career journey from Oracle developer to transitioning into machine learning operations and test automation. The conversation covers best practices for ML pipelines, testing at scale, and how to integrate testing effectively in the AI ML space. Lakshmi shares insights on understanding machine learning models, navigating various roles within AI and machine learning, and setting up guardrails to ensure model performance and accuracy. Please tune in to gain valuable knowledge from Lakshmi's expertise and learn how to approach testing in our AI-driven world.

In this episode, we dive into the evolving landscape of logistics missions and the need for innovation in navigating disruption. Drawing insights shared by industry leaders at GDIT, we explore how organizations can leverage technology, data, and agile strategies in an increasingly complex environment. Tune in for expert perspectives on overcoming challenges and driving operational excellence in modern logistics missions.In Voices of Innovation—a podcast by GDIT—we bring you into conversations with the thinkers, innovators, and mission experts who are shaping some of the most complex government, defense, and intelligence projects across the country. We explore cutting-edge technologies, from artificial intelligence to quantum computing, that are crucial for leading and accelerating government missions.   Each episode features insights and stories from GDIT, government, and industry technologists. They are at the helm, leveraging groundbreaking technology to drive missions that matter most. Join us as we  dive into a world where technological innovation meets strategic execution. Subscribe now to never miss an episode.   GDIT is a global technology and professional services company that delivers technology and mission services to every major agency across the U.S. government, defense and intelligence community. Our 30,000 experts extract the power of technology to create immediate value and deliver solutions at the edge of innovation. We operate across 30 countries worldwide, offering leading capabilities in digital modernization, AI/ML, Cloud, Cyber and application development.     

How is AI changing the game for creative teams? Find out in this episode of Cloud and Clear! Simon Margolis, Associate CTO, AI/ML at SADA and Amy Clark, Director of Content and Product Ops at The Sherlock Company dive into how AI streamlines content creation, saves resources, and empowers brands to manage global content at scale. Discover the innovative software and AI solutions that are transforming creative workflows. Join us for more content by liking, sharing, and subscribing!

This article breaks down the evolving landscape of AI/ML platforms, from AutoML to full-stack AI workbenches, and provides a structured tool evaluation framework to cut through vendor ambiguity. Published at: https://www.eckerson.com/articles/the-ai-ml-tool-evaluation-template-a-guide-to-smarter-selection

In this episode, Craig Jeffery shares insights from his experience with driverless cars and connects it to the use of AI/ML in treasury. He highlights three key essentials for implementing AI/ML tools in financial decision-making. How can these new technologies boost efficiency, accuracy, and decision-making in treasury operations, and why is it crucial to understand and guide these tools? Listen in to learn more.

This episode is sponsored by https://WE-PN.com Become your own VPN provider.To get 50% off enter promo code: kingraam50-------------------------This episode is sponsored by BetterHelp. Give online therapy a try at https://betterhelp.com/MASTYORASTY and get on your way to being your best self.-------------------------Farshad is senior director of AI/ML at Betterhelp. In this episode he talks to Raam about his journey to the United States, the different companies he has worked at, and the development of artificial intelligence and machine learning.-------------------------To learn more about psychedelic therapy go to my brother Mehran's page at: https://www.mindbodyintegration.ca/ or to https://www.legacyjourneys.ca/ for his next retreat.***Masty o Rasty is not responsible for, or condone, the views and opinions expressed by our guests ******مستی و راستی هیچگونه مسولیتی در برابر نظرها و عقاید مهمان‌های برنامه ندارد.***--------Support the showhttps://paypal.me/raamemamiVenmo + Revolut: @KingRaam Hosted on Acast. See acast.com/privacy for more information.