Podcasts about enterprise ai

In this episode of Gradient Dissent, Lukas Biewald sits down with Arvind Jain, CEO and founder of Glean. They discuss Glean's evolution from solving enterprise search to building agentic AI tools that understand internal knowledge and workflows. Arvind shares how his early use of transformer models in 2019 laid the foundation for Glean's success, well before the term "generative AI" was mainstream.They explore the technical and organizational challenges behind enterprise LLMs—including security, hallucination suppression—and when it makes sense to fine-tune models. Arvind also reflects on his previous startup Rubrik and explains how Glean's AI platform aims to reshape how teams operate, from personalized agents to ever-fresh internal documentation.Follow Arvind Jain: https://x.com/jainarvindFollow Weights & Biases: https://x.com/weights_biasesTimestamps: [00:01:00] What Glean is and how it works [00:02:39] Starting Glean before the LLM boom [00:04:10] Using transformers early in enterprise search [00:06:48] Semantic search vs. generative answers [00:08:13] When to fine-tune vs. use out-of-box models [00:12:38] The value of small, purpose-trained models [00:13:04] Enterprise security and embedding risks[00:16:31] Lessons from Rubrik and starting Glean [00:19:31] The contrarian bet on enterprise search [00:22:57] Culture and lessons learned from Google [00:25:13] Everyone will have their own AI-powered "team" [00:28:43] Using AI to keep documentation evergreen [00:31:22] AI-generated churn and risk analysis [00:33:55] Measuring model improvement with golden sets[00:36:05] Suppressing hallucinations with citations [00:39:22] Agents that can ping humans for help [00:40:41] AI as a force multiplier, not a replacement [00:42:26] The enduring value of hard work

From idea to IPO and beyond. What does it take to back a company for nearly two decades?There are no written rules to navigate one of the most important relationships in a startup. One between a founder and an investor.This episode is an inside look at how one of India's longest founder-investor relationships was built and tested, between Yashish Dahiya (Policybazaar) and Sanjeev Bikhchandani (Info Edge).In 2008, a ₹20 crore cheque was signed for 49 percent of the company, based solely on a powerpoint idea.What followed were regulatory challenges, shifting business models, new investors on-board, and moments of disagreement. But through 17 years, six funding rounds, and an IPO, they stayed aligned.These are two entrepreneurs who built their first ventures a decade apart; Sanjeev in 1997, Yashish in 2008 and have seen the Indian startup ecosystem evolve from the ground up.If you are building or funding startups this conversation will resonate with you for its honesty and give takeaways for your own journey.0:00 – Infoedge Ventures X Policybazaar1:08 – Sanjeev's first memories of Yashish before Policybazaar5:33 – Pitching of the Policybazaar idea 11:08 – How Info Edge almost didn't invest in Policybazaar15:56 – What shaped Yashish as Founder & Sanjeev as Investor25:14 – How the founder–investor bond evolved 27:08 – The Boardroom Dynamics at Policybazaar31:08 – Moments of Disagreement: ₹840 Cr raised, ₹700 Cr still in the bank34:38 – What makes an investor-founder relationship work?46:02 – What We've Learned after 17 years of building together49:03 – How India can build Long-term founder-investor bonds-------------India's talent has built the world's tech—now it's time to lead it.This mission goes beyond startups. It's about shifting the center of gravity in global tech to include the brilliance rising from India.What is Neon Fund?We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that's done it before.Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we're doing it all at Neon.-------------Check us out on:Website: https://neon.fund/Instagram: https://www.instagram.com/theneonshoww/LinkedIn: https://www.linkedin.com/company/beneon/Twitter: https://x.com/TheNeonShowwConnect with Siddhartha on:LinkedIn: https://www.linkedin.com/in/siddharthaahluwalia/Twitter: https://x.com/siddharthaa7-------------This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.Send us a text

Watch on YouTube.In this edition of UC Big News, host Kieran Devlin is joined by leading UC analysts Zeus Kerravala and Blair Pleasant to unpack three headline-grabbing stories shaking up the collaboration world. First up, the team shares takeaways from Zoom Perspectives, where Zoom's vision of an AI-powered “Workplace” was more compelling than ever. Then they turn to the reported rift between Microsoft and OpenAI, and what it signals for enterprise AI partnerships. Finally, things get slightly more surreal with a discussion of Microsoft Teams meetings being enabled in Mercedes-Benz vehicles — and whether that's a productivity win or just a corporate boundary too far.Enterprise AI and collaboration took a weird and wonderful turn this week — and UC Big News is here for all of it. The trio takes stock of what's real, what's hype, and what IT leaders should watch closely.Here's what you'll learn in this episode:Zoom's AI Work Platform evolves — With live agent copilots and better cross-surface integration, Zoom's once-vague AI story is turning into a practical, productised vision for modern work.Microsoft and OpenAI tensions rise — Reports suggest growing disagreements over product direction and control. Blair and Zeus explore why betting everything on one AI partner could create long-term risks.Teams in your car? — Mercedes-Benz drivers can now take Microsoft Teams calls on the road. The panel asks: is this a helpful innovation for field workers, or a work/life balance killer on wheels?Next Steps:Still undecided about Teams in cars? Share your hot take in the comments.Curious about Zoom's evolving AI platform? We'll have more deep dives coming soon.Subscribe to UC Big News for sharp analysis and strong opinions on the future of enterprise comms.Thanks for watching, if you'd like more content like this, don't forget to SUBSCRIBE to our YouTube channel.You can also join in the conversation on our Twitter and LinkedIn pages.Join our new LinkedIn Community Group.

Is AI finally ready for the enterprise? In this AI Infra Summit 2025 interview, Luke Norris, CEO of Kamawaza, reveals how Fortune 500 and Global 2000 companies are moving beyond AI experiments to real-world, production-level deployments—saving millions and reshaping industries.Luke shares insights from Kamawaza's groundbreaking work with over 20 Fortune 500 clients, including a live demo with the Department of Homeland Security and massive cost savings for major enterprises. Learn why consulting firms are feeling the heat, how the AI partner ecosystem is evolving, and what's next for enterprise AI—including game-changing breakthroughs in open-source models like Quen 3.0 and the rise of Model Context Protocol (MCP).

What happens after AI helps you write code faster? You create a bottleneck in testing, security, and operations. In part two of their conversation, SADA's Simon Margolis and Google Cloud's Ameer Abbas tackle this exact problem. They explore how Google's AI strategy extends beyond the developer's keyboard with Gemini Code Assist and Cloud Assist, creating a balanced and efficient software lifecycle from start to finish. We address the burning questions about AI's impact on the software development ecosystem: Is AI replacing developers? What does the future hold for aspiring software engineers? Gain insights on embracing AI as an augmentation tool, the concept of "intentional prompting" versus "vibe coding," and why skilled professionals are more crucial than ever in the enterprise. This episode offers practical advice for enterprises on adopting AI tools, measuring success through quantitative and qualitative metrics, and finding internal champions to drive adoption. We also peek into the near future, discussing the evolution towards AI agents capable of multi-step inferencing and full automation for specific use cases. Key Takeaways: Gemini Code Assist: AI for developer inner-loop productivity, supporting various IDEs and SCMs. Gemini Cloud Assist: AI for cloud operations, cost optimization, and incident resolution within GCP. AI's Role in Development: Augmentation, not replacement; the importance of human agency and prompting skills. Enterprise Adoption: Strategies for integrating AI tools, measuring ROI, and fostering a culture of innovation. The Future: Agents with multi-step inferencing, automation for routine tasks, and background AI processes. Relevant Links: Blog: A framework for adopting Gemini Code Assist and measuring its impact Gemini Code Assist product page Gemini Cloud Assist product page Listen now to understand how AI is shaping the future of software delivery! Join us for more content by liking, sharing, and subscribing!

Building AI Agents that work is no small feat.In Agents in Production [Podcast Limited Series] - Episode Six, Paul van der Boor and Sean Kenny share how they scaled AI across 100+ companies with Toqan—a tool born from a Slack experiment and grown into a powerful productivity platform. From driving adoption and building super users to envisioning AI employees of the future, this conversation cuts through the hype and gets into what it really takes to make AI work in the enterprise.Guest speakers:Paul van der Boor - VP AI at Prosus GroupSean Kenny - Senior Product Manager at Prosus GroupHost:Demetrios Brinkmann - Founder of MLOps Community~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin our slack community [https://go.mlops.community/slack]Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register]MLOps Swag/Merch: [https://shop.mlops.community/]

AGNTCY - Unlock agents at scale with an open Internet of Agents. Visit https://agntcy.org/ and add your support.   Grammarly is no longer just a writing assistant. It's building an AI productivity platform that could rival Microsoft Copilot. In this episode, Luke Behnke, VP of Enterprise Product at Grammarly, shares how the company is moving beyond grammar correction into intelligent agents, enterprise workflows, and real-time AI tools.   We dive into Grammarly's new Authorship feature, why AI fluency is becoming essential at work, how Grammarly is integrating tools like Coda and Superhuman, and what the future of multi-agent systems looks like.   If you're curious about where AI at work is really heading, this conversation will give you a clear and powerful glimpse. (00:00) Preview and Intro (03:37) Meet Luke Behnke(05:00) Grammarly's Origin Story and Early Vision(09:11) Grammarly's UX Advantage(13:30) Competing With Microsoft Copilot and Built-In Assistants(17:48) What Is “Authorship” and Why It Matters(20:31) AI Detection vs Authorship Tracking(25:05) The Future of AI Transparency(27:43) Why AI Fluency Will Be a Job Requirement(32:04) Grammarly's Agentic Vision(34:11) The Rise of Context-Aware Enterprise Agents(38:24) Use Cases: Automating Tasks Across Tools with AI(40:21) The Coda Acquisition & Building the Agent Platform(44:48) The Future of Interoperable AI Agents(47:43) Why Agent Oversight Is Crucial in Enterprise AI(55:57) Measuring Grammarly's ROI in the Enterprise

Sam Johnson, Chief Customer Officer of Jamf, discusses the implementation of AI built on Amazon Bedrock that is a gamechanger in helping Jamf's 76,000+ customers scale their device management operations.Topics Include:Sam Johnson introduces himself as Chief Customer Officer from Jamf companyJamf's 23-year mission: help organizations succeed with Apple device managementCompany manages 33+ million devices for 76,000+ customers worldwide from MinneapolisJamf has used AI since 2018 for security threat detectionReleased first customer-facing generative AI Assistant just last year in 2024Presentation covers why, how they built it, use cases, and future plansJamf serves horizontal market from small business to Fortune 500 companiesChallenge: balance powerful platform capabilities with ease of use and adoptionAI could help get best of both worlds - power and simplicityAI also increases security posture and scales user capabilities significantlyCustomers already using ChatGPT/Claude but wanted AI embedded in productBuilt into product to reduce "doorway effect" of switching digital environmentsCreated small cross-functional team to survey land and build initial trailRest of engineering organization came behind to build the production highwayTeam needed governance layer with input from security, legal, other departmentsEvaluated multiple providers but ultimately chose Amazon Bedrock for three reasonsAWS team support, large community, and integration with existing infrastructureUses Lambda, DynamoDB, CloudWatch to support the Bedrock AI implementationAI development required longer training/validation phase than typical product featuresReleased "AI Assistant" with three skills: Reference, Explain, and Search capabilitiesParticipants:Sam Johnson – Chief Customer Officer, JamfFurther Links:Jamf.comJamf on AWS MarketplaceSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

“Data quality was the number one obstacle to AI success […]. It's like Groundhog Day: the biggest problem in data warehousing was data quality […] and now in AI it's still data quality.”

The global strategy consulting market stands at $39.5 billion, with Asia commanding $9.1 billion. India contributes just $1.09 billion. This is despite having the talent; Indians run global back-offices for McKinsey, BCG, Bain, Deloitte, and other consultancies. Yet, India continues to outsource strategy to the Big 4.Sanjeev Sanyal, PM Modi's Economic Advisor joins us to break this down.We discuss the factors helping and hindering India's growth opportunities. Sanjeev has long worked on improving the process reforms with the belief that this country needs small reforms that will bring huge impact.We also discuss AI, with a policymaker who strongly believes unregulated AI will be catastrophic. Sanjeev shares his opinions on what could be the government's approach to regulation, with acceptance of the limited predictability of future with AI.If you want to understand India from a policymaker's eye this episode is for you.0:00- Trailer0:55 – Why India Needs Many Small Reforms2:50 – Was WFH Technically Illegal Until 2000?3:57 – India as the GCC Capital for the world7:02 – How did India go from filing 6,000 to 1 Lakh Patents?13:45 – Why India Can't build Its Own Big 4+317:40 – When professional bodies in India don't work together21:05 – What happens when branding is banned?24:08 – Restrictions That need to stay27:11 – How India's IT Sector Grew Without a Governing Body30:06 – Are we risking catastrophic failure with Unregulated AI?36:10 – Can We Regulate AI Like the Stock Market?41:39 – Why India Must Shut down Population Control47:10 – Will AI Replace Lawyers and Accountants?49:14 – What India Isn't Ready For?51:31 – India as a historically risk taking nation54:31 – Why are professional bodies holding onto protection?56:55 – The Business Culture Problem in Kolkata58:32 – Sanjeev's Work in Agroforestry-------------India's talent has built the world's tech—now it's time to lead it.This mission goes beyond startups. It's about shifting the center of gravity in global tech to include the brilliance rising from India.What is Neon Fund?We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that's done it before.Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we're doing it all at Neon.-------------Check us out on:Website: https://neon.fund/Instagram: https://www.instagram.com/theneonshoww/LinkedIn: https://www.linkedin.com/company/beneon/Twitter: https://x.com/TheNeonShowwConnect with Siddhartha on:LinkedIn: https://www.linkedin.com/in/siddharthaahluwalia/Twitter: https://x.com/siddharthaa7-------------This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.Send us a text

Send us a textHow do you build AI governance that scales without becoming the innovation police? In our final conversation with tech lawyer Gayle Gorvett, we tackle the ultimate balancing act facing every organization: creating robust AI oversight that moves at the speed of business. From shocking federal court rulings that could force AI companies to retain all user data indefinitely, to the Trump administration's potential overhaul of copyright law, this episode reveals how rapidly the legal landscape is shifting beneath our feet. Gayle breaks down practical frameworks from NIST and Duke University that adapt to your specific business needs while avoiding the dreaded legal bottleneck. Whether you're protecting customer data or designing the future of work, this customer success playbook episode provides the roadmap for scaling governance without sacrificing innovation velocity.Detailed AnalysisThe tension between governance speed and innovation velocity represents one of the most critical challenges facing modern businesses implementing AI at scale. Gayle Gorvett's insights into adaptive risk frameworks offer a compelling alternative to the traditional "slow and thorough" legal approach that often strangles innovation in bureaucratic red tape.The revelation about the OpenAI versus New York Times case demonstrates how quickly the legal landscape can shift with far-reaching implications. A single magistrate judge's ruling requiring OpenAI to retain all user data—regardless of contracts, enterprise agreements, or international privacy laws—illustrates the unpredictable nature of AI regulation. For customer success professionals, this uncertainty demands governance frameworks that can rapidly adapt to new legal realities without completely derailing operational efficiency.The discussion of NIST and Duke University frameworks reveals the democratization of enterprise-level governance tools. These resources make sophisticated risk assessment accessible to organizations of all sizes, eliminating the excuse that "we're too small for proper AI governance." This democratization aligns perfectly with the customer success playbook philosophy of scalable, repeatable processes that deliver consistent outcomes regardless of organizational size.Perhaps most intriguingly, the conversation touches on fundamental questions about intellectual property and compensation models in an AI-driven economy. Kevin's observation about automating human-designed workflows raises profound questions about fair compensation when human knowledge gets embedded into perpetual AI systems. This shift from time-based to value-based compensation models reflects broader changes in how customer success teams will need to demonstrate and capture value in an increasingly automated world.The technical discussion about local versus hosted AI models becomes particularly relevant for customer success teams handling sensitive customer data. The ability to contain AI processing within controlled environments versus leveraging cloud-based solutions represents a strategic decision that balances capability, cost, and compliance considerations.Gayle's emphasis on human oversight—Kevin's offeringPlease Like, Comment, Share and Subscribe. You can also find the CS Playbook Podcast:YouTube - @CustomerSuccessPlaybookPodcastTwitter - @CS_PlaybookYou can find Kevin at:Metzgerbusiness.com - Kevin's person web siteKevin Metzger on Linked In.You can find Roman at:Roman Trebon on Linked In.

Why do so many enterprise AI initiatives stall? In this episode, we unpack the leadership gap most organisations overlook. Discover how Meta-Leadership drives real-time oversight, system-wide execution, and strategic fluency across silos. Learn the 7 disciplines transformation leaders use to scale AI effectively. Tune in to rethink leadership for the AI era—and lead beyond your team. 

AGNTCY - Unlock agents at scale with an open Internet of Agents. Visit https://agntcy.org/ and add your support. What if the most important AI conference in the world wasn't built by academics or hype merchants, but by operators who actually understand what businesses need? In this episode, Craig sits down with Andrew Blum, Co-Founder and COO of HumanX, the breakout AI conference that has quickly become the go-to gathering for enterprise leaders, AI builders, and government policymakers. Andrew shares the inside story of how HumanX went from an idea born in a VC incubator to hosting 3,300+ attendees, 350 speakers, and leaders from OpenAI, Anthropic, Mistral, Snowflake, and more, all within 18 months. You'll hear how HumanX is different from other conferences, why face-to-face connection matters more than ever, and how HumanX is creating the bridge between AI innovation and real-world business transformation. This is a behind-the-scenes look you won't want to miss. Like and subscribe for more! Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI

This episode is not just about Kerala; it is about how a state with limited land, strict environmental regulations, and a long history of outmigration is approaching investment and growth.Kerala is a small, densely populated state with limited land to spare, not the typical site for industrial expansion. Yet it's taking a distinct approach to building a knowledge based economy.P. Rajeev (Minister for Industries, Law and Coir, Govt of Kerala) joins us to break this down.We discuss how Kerala rose from the bottom to become the top-ranked state in Ease of Doing Business, what's behind the ₹1.5 lakh crore in investment pledges, and why the state is prioritizing high-value industries over land and labour-intensive manufacturing. We also unpack how Kerala plans to convert MOUs into functioning factories and real jobs, and why startups that once moved away are now beginning to stay. Tune in if you're curious about how Indian states are attracting investment and rethinking their development models.0:00 – Trailer1:18 – Is Kerala Still Fighting Old Perceptions?5:59 – Kerala to Focus on Value-Added Manufacturing7:45 – How to Start an IT Firm in Kerala & Where It Missed the Tech Bus10:35 – What's Blocking Startups from Scaling in the State?11:15 – Can Kerala Retain Its Best Talent?14:20 – Kerala's Vision for a Free-Thinking Knowledge Economy16:36 – Repositioning as an Investor-Friendly Destination19:22 – What the “Nature, People, Industry” Motto Really Means22:22 – Will Kerala Deliver on Its Investor Summit Promises?23:42 – Why Vizhinjam Could Be a Game-Changer26:00 – How Indian States Are Competing for Investments28:47 – Is Stagnation in Productive Sectors Slowing Development?32:38 – Is Kerala's Geography a Barrier to Growth?33:24 – Are Its Environmental Rules Too Rigid for Industry?34:22 – Is Communism Holding Kerala Back?37:48 – When the Communist Govt funded a Private Co.41:17 – The Real Kerala Story43:28 – The History Behind Kerala's Education Revolution45:14 – What the Kerala Model Must Fix48:06 – Internet as a Basic Citizen Right48:56 – Kerala's Health Workers on the Global Frontlines51:19 – Can Outsiders Easily Buy Land in Kerala?53:01 – The State's Only Unicorn Company54:21 – Can Startups from Kerala Go Public?-------------India's talent has built the world's tech—now it's time to lead it.This mission goes beyond startups. It's about shifting the center of gravity in global tech to include the brilliance rising from India.What is Neon Fund?We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that's done it before.Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we're doing it all at Neon.-------------Check us out on:Website: https://neon.fund/Instagram: https://www.instagram.com/theneonshoww/LinkedIn: https://www.linkedin.com/company/beneon/Twitter: https://x.com/TheNeonShowwConnect with Siddhartha on:LinkedIn: https://www.linkedin.com/in/siddharthaahluwalia/Twitter: https://x.com/siddharthaa7-------------This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.Send us a text

This episode is sponsored by Oracle. OCI is the next-generation cloud designed for every workload – where you can run any application, including any AI projects, faster and more securely for less. On average, OCI costs 50% less for compute, 70% less for storage, and 80% less for networking. Join Modal, Skydance Animation, and today's innovative AI tech companies who upgraded to OCI…and saved.    Try OCI for free at http://oracle.com/eyeonai   What if the future of enterprise wasn't human-driven, but agent-driven? In this groundbreaking episode, Steve Lucas, CEO of Boomi, unveils a radical vision for the next era of business: one where AI agents will power 75% of enterprise operations by 2026. From eliminating traditional user interfaces to transforming legacy systems with no-code automation, Steve walks us through how Boomi is building the infrastructure for a self-driving enterprise, and why businesses that fail to prepare will be left behind.   This episode will shift your perspective on where the enterprise is headed and who (or what) will be running it. Stay Updated: Craig Smith on X:https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI

Is generative AI just another tool in the belt, or is it a fundamental transformation of the developer profession? We kick off a two-part special to get to the bottom of how AI is impacting the enterprise. SADA's Associate CTO of AI & ML, Simon Margolis, sits down with Ameer Abbas, Senior Product Manager at Google Cloud, for an insider's look at the future of software development. They cut through the noise to discuss how tools like Gemini Code Assist are moving beyond simple code completion to augment the entire software delivery lifecycle, solving real-world challenges and changing the way we think about productivity, quality, and automation. In this episode, you'll learn: What Gemini Code Assist is and the broad range of developer personas it serves. The critical debate: Is AI augmenting developer skills or automating their jobs? How to leverage AI for practical enterprise challenges like application modernization, improving test coverage, and tackling technical debt. Why the focus is shifting from developer productivity to overall software delivery performance. Ameer's perspective on the future of development careers and why students should lean into AI, not fear it. The limitations of "vibe coding" and the need for intentional, high-quality AI prompting in a corporate environment.   Join us for more content by liking, sharing, and subscribing!

AGNTCY - Unlock agents at scale with an open Internet of Agents. Visit https://agntcy.org/ and add your support.   In this episode of Eye on AI, Craig Smith sits down with Jason Hardy, Chief Technology Officer for AI at Hitachi Vantara, to explore what it really takes to deploy AI at scale in the enterprise, beyond the hype.   Jason shares how Hitachi is building a pragmatic, outcomes-driven AI platform through Hitachi iQ. From working with NVIDIA to integrating agentic AI into operations, this conversation unpacks the infrastructure, mindset, and strategies needed to move AI projects from experimentation to production.   Whether you're navigating AI adoption, battling with data readiness, or looking to build your own LLM-powered applications, this episode offers invaluable insights from a company that's actually doing it globally, sustainably, and at scale.   Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI     (00:00) Preview (02:10) The Role of CTO for AI at Hitachi Vantara (05:38) Applying AI Across Manufacturing, Energy & Transport (09:54) What Is Pragmatic AI? (13:21) Infrastructure Demands of Generative AI (14:47) Why Most AI Projects Fail (20:25) Inside the Hitachi iQ Platform & NVIDIA Partnership (25:42) Building a Model-Agnostic, Hybrid AI Stack (32:08) Beyond Selling GPUs: Delivering Real AI Outcomes (38:09) Supporting Hybrid Deployments Across Cloud and On-Prem (42:02) Rethinking ROI: Failure as a Strategic Advantage (47:44) Agentic AI and the Future of Autonomous IT Workflows (49:37) Five Core Domains of Agentic AI at Hitachi (53:02) Making AI Infrastructure Sustainable (56:48) Hitachi's Vision for the Future of Enterprise AI

AI is changing how companies build and scale. But most pitch decks haven't caught up.Karthik Chakkarapani, CIO of Zuora, has heard plenty of startup pitches but only a few stand out. He shares why most pitches fall flat, how to fix them, and how to present both the founder and the company in a way that drives real interest.We unpack what should go into your 30-second elevator pitch, why “Time to Value” needs its own slide, and how to bring up AI without sounding like everyone else.SaaS is changing fast and it's no longer just about features, but about speed, clarity, and proof of value. We explore how the next wave of SaaS companies can truly differentiate themselves.Building a startup is different in a post-UI world, where users don't click through screens but simply prompt systems to act. We discuss what it takes to build in a world of API-driven AI agents, along with real lessons on what most founders get wrong about working with large companies.If you're building SaaS in 2025, this conversation is for you.0:00 – Trailer1:05 – How the CIO Role Has Changed3:21 – How Zuora Enables the Subscription Economy5:45 – Is SaaS Becoming Headless?7:55 – Are We Entering a Post-UI World?10:37 – What's the New Competitive Advantage?12:31 – Will Entry-Level Jobs Be Replaced by Tools?14:05 – What Metrics Will Matter in an Agentic AI World?15:55 – How to Measure AI Adoption in Your Company18:38 – What's the Hype-to-Reality Ratio for AI?20:19 – What Is the Biggest ROI AI Has Delivered?23:53 – How Startups Can Get Deployed in Enterprises27:10 – How Founders Should Use AI in Their Pitch28:45 – Bolt-On AI vs. Built-In AI32:26 – Most Common Myth About CIOs35:03 – Why You Need a Prompt Library36:04 – What to Avoid in Your Pitch Deck37:21 – How Atomic Work Came Onboard42:47 – The Underrated Soft Skills Founders Need47:55 – 3 Examples of Killer 30-Second Elevator Pitches51:59 – The “Time-to-Value” Slide Explained53:46 – What Founders Get Wrong About Enterprises54:58 – Top SaaS Misconceptions About Enterprise57:00 – Where Enterprises Adopt AI the Fastest59:45 – How the Next SaaS Companies Will Differentiate1:00:33 – Bay Area vs. Bangalore vs. Chennai1:03:33 – Rapid Fire Round-------------​​India's talent has built the world's tech—now it's time to lead it.This mission goes beyond startups. It's about shifting the center of gravity in global tech to include the brilliance rising from India.What is Neon Fund?We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that's done it before.Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we're doing it all at Neon.-------------Check us out on:Website: https://neon.fund/Instagram: https://www.instagram.com/theneonshoww/LinkedIn: https://www.linkedin.com/company/beneon/Twitter: https://x.com/TheNeonShowwConnect with Siddhartha on:LinkedIn: https://www.linkedin.com/in/siddharthaahluwalia/Twitter: https://x.com/siddharthaa7-------------This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.Send us a text

"You can try to develop self-awareness and take a beginner's mind in all things. This includes being open to feedback and truly listening, even when it might be hard to receive. I think that's been something I've really tried to practice. The other area is recognizing that just like a company or country, as humans we have many stakeholders. You may wear many hats in different ways. So as we think of the totality of your life over time, what's your portfolio of passions? How do you choose—as individuals, as society, as organizations, as humans and families with our loved ones and friends—to not just spend your time and resources, but really invest your time, resources, and spirit into areas, people, and contexts that bring you meaning and where you can build a legacy? So it's not so much advice, but more like a north star." - Sabastian V. Niles Fresh out of the studio, Sabastian Niles, President and Chief Legal Officer at Salesforce Global, joins us to explore how trust and responsibility shape the future of enterprise AI. He shares his journey from being a high-tech corporate lawyer and trusted advisor to leading AI governance at a company whose number one value is trust, reflecting on the evolution from automation to agentic AI that can reason, plan, and execute tasks alongside humans. Sabastian explains how Agentforce 3.0 enables agent-to-agent interactions and human-AI collaboration through command centers and robust guardrails. He highlights how organizations are leveraging trusted AI for personalized customer experiences, while Salesforce's Office of Ethical and Humane Use operationalizes trust through transparency, explainability, and auditability. Addressing the black box problem in AI, he emphasizes that guardrails provide confidence to move faster rather than creating barriers. Closing the conversation, Sabastian shares his vision on what great looks like for trusted agentic AI at scale. Episode Highlights [00:00] Quote of the Day by Sabastian Niles: "Portfolio of passions - invest your spirit into areas that bring meaning" [01:02] Introduction: Sabastian Niles, President and Chief Legal Officer of Salesforce Global [02:29] Sabastian's Career Journey [04:50] From Trusted Advisor to SalesForce whose number one value is trust [08:09] Salesforce's 5 core values: Trust, Customer Success, Innovation, Equality, Sustainability [10:25] Defining Agentic AI: humans with AI agents driving stakeholder success together [13:13] Trust paradigm shift: trusted approaches become an accelerant, not obstacle [17:33] Agent interactions: not just human-to-agent, but agent-to-agent-to-agent handoffs [23:35] Enterprise AI requires transparency, explainability, and auditability [28:00] Trust philosophy: "begins long before prompt, continues after output" [34:06] Office of Ethical and Humane Use operationalizes trust values [40:00] Future vision: AI helps us spend time on uniquely human work [45:17] Governance philosophy: Guardrails provide confidence to move faster [48:24] What does great look like for Salesorce for Trust & Responsibility in the Era of AI? [50:16] Closing Profile: Sabastian V. Niles, President & Chief Legal Officer, LinkedIn: https://www.linkedin.com/in/sabastian-v-niles-b0175b2/ Podcast Information: Bernard Leong hosts and produces the show. The proper credits for the intro and end music are "Energetic Sports Drive." G. Thomas Craig mixed and edited the episode in both video and audio format. Here are the links to watch or listen to our podcast. Analyse Asia Main Site: https://analyse.asia Analyse Asia Spotify: https://open.spotify.com/show/1kkRwzRZa4JCICr2vm0vGl Analyse Asia Apple Podcasts: https://podcasts.apple.com/us/podcast/analyse-asia-with-bernard-leong/id914868245 Analyse Asia YouTube: https://www.youtube.com/@AnalyseAsia Analyse Asia LinkedIn: https://www.linkedin.com/company/analyse-asia/

Send us a textReady to navigate the complex world of AI governance without getting lost in legal jargon? This episode delivers a masterclass in building ethical AI frameworks that actually work for your business. Global tech lawyer and fractional general counsel Gayle Gorvett breaks down the essential guardrails every company needs before diving headfirst into AI implementation. From her work with Duke University's AI working groups to real-world enterprise applications, Gayle reveals why treating AI like the "shiny new toy" without proper governance is a recipe for disaster. Whether you're protecting customer data or safeguarding your company's future, this customer success playbook episode provides the foundational knowledge to approach AI adoption with confidence and compliance.Detailed AnalysisThe AI revolution isn't just changing how we work—it's fundamentally reshaping the legal and ethical landscape of business operations. Gayle Gorvett's expertise in AI governance comes at a crucial time when companies are rushing to implement AI solutions without adequate safeguards. Her comparison of current AI hype to the blockchain frenzy of a decade ago serves as a sobering reminder that sustainable innovation requires thoughtful planning, not just technological enthusiasm.The multidisciplinary approach Gayle advocates represents a significant shift in how businesses should structure their AI initiatives. Gone are the days when technology decisions could be made in isolation. Modern AI governance demands collaboration between business functions, technical teams, and legal counsel—creating a new paradigm for cross-functional leadership in customer success organizations.For customer success professionals, the implications extend far beyond internal operations. When AI systems interact with customer data, handle support tickets, or predict customer behavior, the governance framework becomes a direct reflection of your company's commitment to customer trust. Gayle's emphasis on informing customers about AI usage highlights how transparency has evolved from a nice-to-have to a business imperative.The Duke AI Risk Framework and NIST guidelines she references provide actionable starting points for organizations feeling overwhelmed by the governance challenge. These resources democratize access to enterprise-level AI governance, making sophisticated risk assessment accessible to companies of all sizes. This democratization aligns perfectly with the customer success playbook philosophy of scalable, repeatable processes that drive consistent outcomes.Perhaps most importantly, Gayle's 26-year perspective in technology law offers historical context that many AI discussions lack. Her experience through previous technology waves—from the early internet boom to blockchain—provides valuable pattern recognition for identifying sustainable AI strategies versus fleeting trends. This wisdom becomes particularly relevant for customer success leaders who must balance innovation with the reliability their customers depend on.Now you can interact with us directly by leaving a voice message at htKevin's offeringPlease Like, Comment, Share and Subscribe. You can also find the CS Playbook Podcast:YouTube - @CustomerSuccessPlaybookPodcastTwitter - @CS_PlaybookYou can find Kevin at:Metzgerbusiness.com - Kevin's person web siteKevin Metzger on Linked In.You can find Roman at:Roman Trebon on Linked In.

Join host George Firican on the Lights On Data Show as he interviews John Kucera, Senior Vice President of Salesforce AI, to explore the transformative power of Agentforce. Learn how this technology is reshaping enterprise AI by automating digital labor, offering powerful new capabilities like observability and interoperability, and seamlessly integrating with the broader Salesforce ecosystem. Discover real-world success stories, best practices for implementation, and essential insights for tech and business leaders looking to leverage AI effectively.

Three failed startups. One of India's biggest B2B exits. Then returning 75% of investor money in the next venture. An entrepreneur who's lived that arc is bound to have insights for anyone building or thinking of building.Paras Chopra, founder of Wingify (sold for $200 million), Nintee, and now Lossfunk, joins us this week.We discuss the small decisions that quietly define your startup: what product to build, how to structure your team, and why setting the right communication culture early can help.Paras shares what most founders overlook early on : Pricing isn't about effort you put but about the value you create, why having competitors might actually be better than having none, and how financial metrics often distract from what really matters to customers.Paras talks about what changed between each attempt of building his startups, and why some lessons only reveal themselves the hard way and what shifts after you've seen both failure and success. Whether you're launching your first company or planning your next, this conversation will give you the clarity needed to tilt the odds in your favor.Check out The Book of Clarity by Paras Chopra.00:00 – Startups Should Be Like Cults02:25 – Building a Founder's Value System03:25 – Bet on What Won't Change in 10 Years05:15 – What AI Can't Do Well (Yet)10:00 – Do Humans Even Want Accuracy?10:57 – What Founders Should Not Build or Sell13:35 – Are many competitors better than none?19:47 – Why Repeating Success Is Hard21:20 – Customer Value Metrics > Financial Metrics23:35 – Why Paras's Startup after Wingify Didn't Work27:00 – What Is Micro Communication?30:41 – Writing Culture in a Startup32:50 – Obsess Over Organisational Design37:15 – Is Luck in Our Hands?41:24 – Why Bias Is Risky for Entrepreneurs42:35 – Great Startups Look Like Toys at First44:00 – Why Deep Tech Startups Struggle to Succeed46:09 – Paras's New Venture Lossfunk49:23 – Why Uncertainty Is a Startup Moat55:56 – What Most Founders Get Wrong About Pricing57:36 – Should Price be on Effort or Value?59:23 – Wingify Innovated on Just One Metric1:00:25 – What Is Failure for Paras?1:04:08 – Diversify Your Self-Worth Like a Portfolio1:05:21 – The Startup Game Is a Mental Game1:06:43 – Did Wingify Create Wealth or Just Money?---​​India's talent has built the world's tech—now it's time to lead it.This mission goes beyond startups. It's about shifting the center of gravity in global tech to include the brilliance rising from India.What is Neon Fund?We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that's done it before.Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we're doing it all at Neon.---Check us out on:Website: https://neon.fund/Instagram: https://www.instagram.com/theneonshoww/LinkedIn: https://www.linkedin.com/company/beneon/Twitter: https://x.com/TheNeonShowwConnect with Siddhartha on:LinkedIn: https://www.linkedin.com/in/siddharthaahluwalia/Twitter: https://x.com/siddharthaa7---This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.Send us a text

Send us a textThe final episode of this transformative series tackles the ultimate challenge: scaling AI experiences without sacrificing empathy. Jake McKee reveals why most companies approach AI transformation backwards—focusing on tools instead of relationships, replacement instead of enhancement. This customer success playbook episode demonstrates how successful AI transformation mirrors the digital transformation of the past decade, requiring fundamental changes to business processes, not just technology adoption. McKee's framework for maintaining authentic human connections while scaling AI across enterprise environments provides practical guardrails for companies navigating the complex balance between efficiency and empathy. From addressing AI hallucinations transparently to designing trust through micro-moments, this conversation offers a roadmap for AI implementations that enhance rather than diminish human relationships.Detailed AnalysisMcKee's perspective on AI transformation represents a sophisticated understanding of organizational change management applied to emerging technology. His comparison to digital transformation provides crucial context—just as companies had to fundamentally rethink business processes when moving from analog to digital, AI transformation requires reimagining workflows, decision-making processes, and human-machine collaboration models.The conversation reveals critical insights about trust-building in AI systems, emphasizing that trust develops through consistent micro-moments rather than singular grand gestures. This mirrors human relationship dynamics and provides a practical framework for designing AI experiences that build confidence over time. McKee's examples of internal process failures—particularly the 13-screen system requiring hours of work before allowing saves—illustrate how poor experience design destroys trust regardless of underlying functionality.Perhaps most valuable is McKee's nuanced approach to AI transparency and hallucination management. Rather than attempting to eliminate AI limitations, he advocates for honest communication about system capabilities and uncertainties. This customer success playbook approach recognizes that users can develop healthy relationships with imperfect AI systems when expectations are properly set and limitations are communicated clearly.The discussion also addresses the critical challenge of scaling empathetic AI across large organizations. McKee's emphasis on relationship design over feature development provides a sustainable framework for maintaining human-centric experiences even as AI implementations grow in scope and complexity. His insights about contextual AI behavior—understanding when users need speed versus thoughtful interaction—offer practical guidance for enterprise AI strategy.Now you can interact with us directly by leaving a voice message at https://www.speakpipe.com/CustomerSuccessPlaybookKevin's offeringPlease Like, Comment, Share and Subscribe. You can also find the CS Playbook Podcast:YouTube - @CustomerSuccessPlaybookPodcastTwitter - @CS_PlaybookYou can find Kevin at:Metzgerbusiness.com - Kevin's person web siteKevin Metzger on Linked In.You can find Roman at:Roman Trebon on Linked In.

In this episode of The New Stack Agents, Andrew Lee, co-founder of Shortwave and Firebase, discusses the evolution of his Gmail-centric email client into an AI-first platform. Initially launched in 2020 with traditional improvements like better threading and search, Shortwave pivoted to agentic AI after the rise of large language models (LLMs). Early features like summarization and translation garnered hype but lacked deep utility. However, as models improved in 2023—especially Anthropic's Claude Sonnet 3.5—Shortwave leaned heavily into tool-calling agents that could execute complex, multi-step tasks autonomously. Lee notes Anthropic's lead in this area, especially in chaining tools intelligently, unlike earlier models from OpenAI. Still, challenges remain with managing large numbers of tools without breaking model reasoning. Looking ahead, Lee envisions AI that can take proactive actions—like responding to emails—and dynamically generate interfaces tailored to tasks in real-time. This shift could fundamentally reshape how productivity apps work, with Shortwave aiming to be at the forefront of that transformation.Learn more from The New Stack about the latest insights of the power AI at scale:Why Streaming Is the Power Grid for AI-Native Data PlatformsCompanies Must Embrace BeSpoke AI Designed for IT WorkflowsJoin our community of newsletter subscribers to stay on top of the news and at the top of your game.

SaaStr 809: Why Enterprise AI Adoption Is Moving 5-10X Faster Than Cloud with Box's CEO and Co-Founder, IBM's VP for AI and SaaStr's CEO and Founder This conversation between Aaron Levie, CEO & Co-Founder of Box, Raj Datta, Global Vice President for Software and A.I. Partnerships at IBM and Jason Lemkin, CEO and Founder of SaaStr, covers the evolution from chat interfaces to digital labor models, the integration of AI to automate complex tasks, and the emergence of new paradigms for businesses deploying AI agents. Key topics include the distinction between AI agents and assistants, the development of proprietary data models, and the rapid pace of AI adoption. With real-world examples from companies like IBM and Box, this session offers insights into how AI is reshaping software ecosystems, enhancing enterprise capabilities, and potentially redefining market moats. ------------------ This episode of the SaaStr podcast is sponsored by: Attention.com   Tired of listening to hours of sales calls? Recording is yesterday's game. Attention.com unleashes an army of AI sales agents that auto-update your CRM, build custom sales decks, spot cross-sell signals, and score calls before your coffee's cold. Teams like BambooHR and Scale AI already automate their Sales and RevOps using customer conversations. Step into the future at attention.com/saastr   ------------------   Hey everyone, we just hosted 10,000 of you at the SaaStr Annual in the SF Bay Area, and now get ready, because SaaStr AI is heading to London! On December 2nd and 3rd, we're bringing SaaStr AI to the heart of Europe. This is your chance to connect with 2,500+ SaaS and AI executives, founders, and investors, all sharing the secrets to scaling in the age of AI.   Whether you're a founder, a revenue leader, or an investor, SaaStr AI in London is where the future of SaaS meets the power of AI. And we just announced tickets and sponsorships, so don't wait! Head to SaaStrLondon.com to grab yours and join us this December in London. SaaStr AI in London —where SaaS meets AI, and the next wave of innovation begins. See you there!

In this episode of Alter Everything, we chat with Alex Patrushev, Head of Product at Nebius. We discuss the gaps organizations face between data and business impact, strategies to bridge these gaps, and the role of AI in these processes. Alex explains Nebius' mission to make AI accessible, the challenges of building data centers and software from scratch, and innovative solutions like their data center in Finland. The conversation also covers key components for effectively bridging data and business impact, such as project selection, stakeholder communication, team skills, data quality, and tech stack.Panelists: Alexander Patrushev, Head of Product for AI/ML @ NebiusMegan Bowers, Sr. Content Manager @ Alteryx - @MeganBowers, LinkedInShow notes: NebiusData Version Control Interested in sharing your feedback with the Alter Everything team? Take our feedback survey here!This episode was produced by Megan Bowers, Mike Cusic, and Matt Rotundo. Special thanks to Andy Uttley for the theme music.

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50% of products and features built are never used.To build the right product, every founder must answer two questions:Are you solving a real problem? And are you solving it the right way?Technology has rarely been democratic, it's often elitist. So at times, it ends up solving made-up problems that don't really exist. Yet, some companies have built truly great products.What sets them apart? Do they share any similarities? Are there lessons for entrepreneurs?We have with us Krishna (Vasanth) Namasivayam who has previously worked on AI products at NVIDIA, Meta, and Dropbox.Vasanth is founder of Featurely.AI. Featurely is fixing how products get built. It does it by simulating users — not as bots, but as human-inspired digital twins.0:00 – Trailer02:10 – Why I chose NVIDIA in 2015?03:55 – Working on integrity at META04:23 – Rethinking AI for Dropbox04:51 – NVIDIA builds for the future05:45 – People loved working for Jensen08:16 – What makes META so special?10:57 – Decision-making at META was democratic11:41 – Dropbox was once the most VIRAL product12:55 – The power of founder-led companies14:28 – Tech is Elitist, Build for a Few16:43 – Silicon Valley trend of Solving Made-up problems19:27 – A magic wand that Finds the right problem22:17 – Synthetic users vs. perfect AI agents25:00 – Why synthetic users can fail (and why that matters)25:35 – What is the Future with AI agents & synthetic humans?26:30 – Why openAI can't/won't choose User research27:16 – The simplest explanation of LLMs28:36 – Why ChatGPT succeeded like no other31:04 – Bite-sized Info for 6-second attention span31:37 – The Next Frontier in AI: Predicting Human Behavior33:55 – Uses of Synthetic Humans from Product to Policy35:55 – The biggest surprise of building a startup37:00 – One Mistake Product folks make38:24 – One emotional truth about startups39:04 – What does Featurely do?42:51 – How Featurely will measure success46:36 – All future software will be hyper-personalized50:24 – 3 AI companies to admire (one not built yet)52:28 – How will Work be in 2025?53:59 – How AI gets things (almost) right every time57:02 – Why Featurely chose Neon Fund01:02:51 – What the Bay Area does differently01:04:54 – Learnings from Fundraising01:06:49 – The vision to Build a Category defining Company-------------​​India's talent has built the world's tech—now it's time to lead it.This mission goes beyond startups. It's about shifting the center of gravity in global tech to include the brilliance rising from India.What is Neon Fund?We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that's done it before.Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we're doing it all at Neon.-------------Check us out on:Website: https://neon.fund/Instagram: https://www.instagram.com/theneonshoww/LinkedIn: https://www.linkedin.com/company/beneon/Twitter: https://x.com/TheNeonShowwConnect with Siddhartha on:LinkedIn: https://www.linkedin.com/in/siddharthaahluwalia/Twitter: https://x.com/siddharthaa7-------------This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.Send us a text

74% of CEOs think their jobs are on the line because of AI. Not because AI might replace them, but because failing to implement it successfully could cost them everything.Merlin Bise, CTO of Inbenta and former Head of Technology at a firm acquired by the London Stock Exchange, joins us to share how Inbenta is helping enterprises modernise their customer experience. Merlin explains that so many AI deployments fail, not because the technology is lacking, but because companies often bet on the wrong frameworks, overlook data foundations, or underestimate the importance of testing. We explore how traditional rules-based systems give way to agentic frameworks that can reason, triage ambiguous queries, and even correct automation gaps in real time. Merlin walks us through the journey many enterprises take: beginning with deterministic rules, evolving to AI-powered agents, and ultimately orchestrating complex automation through agentic manager systems that oversee and improve themselves.Security and customer experience are front and centre in this episode. Merlin breaks down the cybersecurity concerns that make enterprises hesitate and why, in most cases, those fears are rooted more in perception than reality.Finally, we reflect on the broader trajectory of AI. While the race toward AGI dominates headlines, Merlin argues that the tools enterprises need to radically improve productivity are already here. The challenge is implementing what exists with purpose and precision.Shownotes:Check out Inbenta: https://www.inbenta.com/Subscribe to VUX World: https://vuxworld.typeform.com/to/Qlo5aaeWSubscribe to The AI Ultimatum Substack: https://open.substack.com/pub/kanesimmsGet in touch with Kane on LinkedIn: https://www.linkedin.com/in/kanesimms/ Hosted on Acast. See acast.com/privacy for more information.

In this episode, Greg Shove, CEO of Section and founder of Machine and Partners, joins us for a "where are they now" follow-up—and doesn't hold back. Greg walks through the rise of Pro AI, his new AI-powered coach, and why traditional upskilling is already obsolete.We explore the overlooked friction points in AI adoption, from cultural taboos (“it feels like cheating”) to failed enterprise rollouts. Greg challenges the prevailing mental models and warns that the real upheaval is still ahead: business model disruption, not product disruption.From royalty-based agents to outcome-based pricing, Greg lays out why service-heavy industries—from law firms to SaaS—are heading for a margin-crushing future. Plus: the moral responsibility of CEOs, the fallacy of lifelong learners, and why working with AI means holding onto your own judgment.A sharp, honest look at what it really means to work smarter—not just faster—in the age of AI.Key takeaways:AI use is no longer optional—it's the new baseline.Proficiency with AI tools isn't a competitive edge anymore—it's a basic requirement. Greg argues that “being in the AI class” is now table stakes, and organizations must rapidly close the gap between aspiration and actual adoption.Business model disruption will hit harder than tech disruption.Greg makes a compelling case that AI's biggest impact won't come from the tools themselves, but from entirely new ways of charging for value—like outcome-based pricing and AI-native service models that undercut human capital costs.Leaders must shift from AI policies to AI manifestos.Adoption is stalling because organizations lead with fear. Instead, Greg urges leaders to clearly message that using AI is smart, encouraged, and expected—and to model that behavior themselves.Most people won't be lifelong learners—so give them outputs, not courses.With Pro AI, Greg confronts a hard truth: most users don't want to learn; they want results. AI-powered coaching that delivers outcomes—not just education—is the future of upskilling.Linkedin: Greg Shove | LinkedInWebsite: Greg Shove | AI Strategist & Keynote Speaker for Enterprise LeadersSection: Section | AI workforce transformation for real ROIMachine & Partners: AI Consulting Services | Machine and Partners00:00 Embracing AI: Changing Work Culture00:29 Introduction: Meet Greg Shove01:10 AI in Daily Work: Tools and Changes03:59 Business Model Disruption: The Next Big Shift12:45 Training and Adoption Challenges19:14 The Future of Work: AI's Impact on Jobs32:02 Leadership and AI: Strategies for Success35:20 Embracing AI in the Workplace36:51 Workflow Redesign with AI39:39 The Role of AI Agents40:12 Challenges in AI Adoption45:14 Pro AI: The AI-Powered Coach51:03 Disrupting Business Models with AI57:52 Cognitive Offloading and AI01:03:02 Final Thoughts and Reflections

AGNTCY - Unlock agents at scale with an open Internet of Agents. Visit https://agntcy.org/ and add your support.     What's stopping large language models from being truly enterprise-ready?   In this episode, Vectara CEO and co-founder Amr Awadallah breaks down how his team is solving one of AI's biggest problems: hallucinations.   From his early work at Yahoo and Cloudera to building Vectara, Amr shares his mission to make AI accurate, secure, and explainable. He dives deep into why RAG (Retrieval-Augmented Generation) is essential, how Vectara detects hallucinations in real-time, and why trust and transparency are non-negotiable for AI in business.   Whether you're a developer, founder, or enterprise leader, this conversation sheds light on the future of safe, reliable, and production-ready AI.   Don't miss this if you want to understand how AI will really be used at scale.     Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI

Geopolitics is now measured in Nanometers. Anything with a battery or a plug has a semiconductor inside. But these chips aren't just tech anymore, they're shaping who becomes the next Superpower.In the 1980s, India was just two years behind the world in semiconductors. Today, we're 12 generations behind. What went wrong?India's top semiconductor expert, Raja Manickam, returns to The Neon Show to break it all down.We discuss how the U.S. lost the chip race it started, China's strategic rise, and how one visionary turned Taiwan into the most valuable island in the world.Raja Manickam dives into what the $10B India Semiconductor Mission is getting right and where we may fall behind. He explains why

Enterprise AI is evolving quickly. Budgets are rising, agents are becoming essential, and companies demand state-of-the-art AI as soon as possible. Here are 16 insights from Andreessen Horowitz's latest analysis on how AI transforms the enterprise.Source: https://a16z.com/ai-enterprise-2025/Get Ad Free AI Daily Brief: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://patreon.com/AIDailyBrief⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Brought to you by:KPMG – Go to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://kpmg.com/ai⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to learn more about how KPMG can help you drive value with our AI solutions.Blitzy.com - Go to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://blitzy.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to build enterprise software in days, not months AGNTCY - The AGNTCY is an open-source collective dedicated to building the Internet of Agents, enabling AI agents to communicate and collaborate seamlessly across frameworks. Join a community of engineers focused on high-quality multi-agent software and support the initiative at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠agntcy.org ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ -  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://agntcy.org/?utm_campaign=fy25q4_agntcy_amer_paid-media_agntcy-aidailybrief_podcast&utm_channel=podcast&utm_source=podcast⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Vanta - Simplify compliance - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://vanta.com/nlw⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Plumb - The automation platform for AI experts and consultants ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://useplumb.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The Agent Readiness Audit from Superintelligent - Go to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://besuper.ai/ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠to request your company's agent readiness score.The AI Daily Brief helps you understand the most important news and discussions in AI. Subscribe to the podcast version of The AI Daily Brief wherever you listen: https://pod.link/1680633614Subscribe to the newsletter: https://aidailybrief.beehiiv.com/Join our Discord: https://bit.ly/aibreakdownInterested in sponsoring the show? nlw@breakdown.network

"At IBM, we really work on two emerging technologies: hybrid cloud and AI for enterprise. These two are deeply connected. Hybrid cloud for us means that regardless of where the data sits whether the compute is on-premise, off-premise, or across multiple clouds. We believe the client should have the control and flexibility to choose where to run and place their data. If you look at the facts, a very high percentage of client data is still on-premise. It hasn't moved to the cloud for obvious reasons. So, how can you scale AI if you don't have proper access to that data? AI is all about the data. That's why we believe in a strategy that redefines and rethinks everything. We call it the Great Technology Reset." - Hans Dekkers Fresh out of the studio, Hans Dekkers, General Manager of IBM Asia Pacific, joins us to explore how enterprise AI is reshaping business across the region. He shares his journey with IBM after business school, reflecting on the evolution of personal computers to AI today. Hans explains IBM's unique approach combining hybrid cloud infrastructure with AI for Enterprise, emphasizing how their granite models and data fabric enable businesses and governments to maintain control over their data while scaling AI capabilities. He highlights customer stories from Indonesian telecoms company to internal IBM transformations, showcasing how companies are re-engineering everything from HR to supply chains using domain-specific AI models. Addressing the challenges of AI implementation, he emphasizes the importance of foundational infrastructure and governance, while advocating for smaller, cost-effective models over GPU-heavy approaches. Closing the conversation, Hans shares his vision for IBM's growing presence in Asia as the key to enterprise AI success. Episode Highlights: [00:00] Quote of the Day by Hans Dekkers [01:00] Introduction: Hans Dekkers from IBM [05:00] Key career lesson from Hans Dekker [06:51] IBM focuses on two emerging technologies: hybrid cloud and AI for Enterprise, deeply connected [09:27] "Your data needs to remain your data" - IBM's fundamental AI principle for enterprise clients [10:00] IBM's approach: Small, nimble, cost-effective AI models that can be owned and governed by clients [13:59] "The cost of AI is still too high. It's about a hundred times too high" - IBM CEO's perspective on AI costs [14:44] Small domain-specific models example: Banking AI trained for financial analysis, not Russian poetry [18:00] IBM's internal transformation: HR, supply chain, and consulting completely re-engineered with AI [21:18] Major partnership announcement: Indonesian telecom embracing IBM's watsonx platform [22:23] AI agents demo: Multiple agents (HR, finance, legal) debating and constructing narratives [25:00] "Everyone talks about AI equals GPU" - Hans wishes clients understood that inferencing is more important [27:00] IBM's Asia Pacific vision: Reestablishing growing presence and differentiated technology approach [28:00] Closing Profile: Hans Dekkers, General Manager IBM Asia Pacific and China: https://www.linkedin.com/in/hans-a-t-dekkers/ Podcast Information: Bernard Leong hosts and produces the show. The proper credits for the intro and end music are "Energetic Sports Drive." G. Thomas Craig mixed and edited the episode in both video and audio format. Here are the links to watch or listen to our podcast. Analyse Asia Main Site: https://analyse.asia Analyse Asia Spotify: https://open.spotify.com/show/1kkRwzRZa4JCICr2vm0vGl Analyse Asia Apple Podcasts: https://podcasts.apple.com/us/podcast/analyse-asia-with-bernard-leong/id914868245 Analyse Asia YouTube: https://www.youtube.com/@AnalyseAsia Analyse Asia LinkedIn: https://www.linkedin.com/company/analyse-asia/ Analyse Asia X (formerly known as Twitter): https://twitter.com/analyseasia Analyse Asia Threads: https://www.threads.net/@analyseasia Sign Up for Our This Week in Asia Newsletter: https://www.analyse.asia/#/portal/signup Subscribe Newsletter on LinkedIn https://www.linkedin.com/build-relation/newsletter-follow?entityUrn=7149559878934540288

There are No Checklists or Frameworks on HOW TO BE A VC?So how do you even know if it's the right path for you?Unlike most jobs, venture capital comes with an extremely long feedback loop. It can take years before you know whether the bets you made actually worked out. That's why most seasoned VCs say: only choose this path if you're in it for the long haul.This conversation will help you think through that choice. Whether you're considering VC as a career, love building businesses, or just want to understand who really calls the shots on a cap table.On The Neon Show, we have with us two operators turned investors:Gaurav Ranjan, Principal at Prime Venture Partners, has led deals including Dozee, Hitwikcet, Poshn and Gallabox.Naman Lahoty, Partner at Stellaris Venture Partners has been part of investments like Zouk, Nestasia, Dashtoon and Lumio.They share lessons from evaluating thousands of startups - what they've unlearned about pattern-matching in investing, why Excel projections mostly fail and why founder empathy might be the most underrated edge in venture capital.It's truly a conversation between three VCs on what it really takes to be a VC today.0:00 – Stellaris Partners X Prime Ventures0:43 – How Founders Turn Into VCs4:19 – Do VCs Need an MBA or Consulting Background?6:32 – Why Startup Projections Rarely Come True8:43 – Are VCs Naturally Good Founders?11:19 – Startups we Evaluated & Founders we Met14:51 – From First Pitch to Deal Close19:02 – Why VC Feedback Loops Are Extremely Long21:00 – No Checklists. No Frameworks.25:27 – Why On-Demand Rebranded as Quick Commerce Won?29:20 – The Stellaris Framework to Evaluate Founders35:53 – Why Indian VCs Must Think Independently38:28 – Rapid Fire: The Big One We Missed39:16 – The One We Loved But Didn't Back42:23 – Startups We Wish We'd Invested In43:55 – Investors We Admire the Most47:20 – Do We Believe Peter Thiel's Theory?52:35 – Startup Stories: Slack, Flickr, Dozee, Rupicard57:15 – The GTM Hack That Led to Product Discovery58:15 – Babygogo & Atomic Work59:55 – All-Nighter Code Sprint for the Demo1:00:55 – Lessons Founders Taught Us1:06:30 – What We Miss About Being a Founder1:10:28 – When Do You Decide If You Are a Good VC?1:13:28 – Building a Fund V/S Building a Startup-------------​​India's talent has built the world's tech—now it's time to lead it.This mission goes beyond startups. It's about shifting the center of gravity in global tech to include the brilliance rising from India.What is Neon Fund?We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that's done it before.Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we're doing it all at Neon.-------------Check us out on:Website: https://neon.fund/Instagram: https://www.instagram.com/theneonshoww/LinkedIn: https://www.linkedin.com/company/beneon/Twitter: https://x.com/TheNeonShowwConnect with Siddhartha on:LinkedIn: https://www.linkedin.com/in/siddharthaahluwalia/Twitter: https://x.com/siddharthaa7-------------This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.Send us a text

Mark Ericksen, creator of the Elixir LangChain framework, joins the Elixir Wizards to talk about LLM integration in Elixir apps. He explains how LangChain abstracts away the quirks of different AI providers (OpenAI, Anthropic's Claude, Google's Gemini) so you can work with any LLM in one more consistent API. We dig into core features like conversation chaining, tool execution, automatic retries, and production-grade fallback strategies. Mark shares his experiences maintaining LangChain in a fast-moving AI world: how it shields developers from API drift, manages token budgets, and handles rate limits and outages. He also reveals testing tactics for non-deterministic AI outputs, configuration tips for custom authentication, and the highlights of the new v0.4 release, including “content parts” support for thinking-style models. Key topics discussed in this episode: • Abstracting LLM APIs behind a unified Elixir interface • Building and managing conversation chains across multiple models • Exposing application functionality to LLMs through tool integrations • Automatic retries and fallback chains for production resilience • Supporting a variety of LLM providers • Tracking and optimizing token usage for cost control • Configuring API keys, authentication, and provider-specific settings • Handling rate limits and service outages with degradation • Processing multimodal inputs (text, images) in Langchain workflows • Extracting structured data from unstructured LLM responses • Leveraging “content parts” in v0.4 for advanced thinking-model support • Debugging LLM interactions using verbose logging and telemetry • Kickstarting experiments in LiveBook notebooks and demos • Comparing Elixir LangChain to the original Python implementation • Crafting human-in-the-loop workflows for interactive AI features • Integrating Langchain with the Ash framework for chat-driven interfaces • Contributing to open-source LLM adapters and staying ahead of API changes • Building fallback chains (e.g., OpenAI → Azure) for seamless continuity • Embedding business logic decisions directly into AI-powered tools • Summarization techniques for token efficiency in ongoing conversations • Batch processing tactics to leverage lower-cost API rate tiers • Real-world lessons on maintaining uptime amid LLM service disruptions Links mentioned: https://rubyonrails.org/ https://fly.io/ https://zionnationalpark.com/ https://podcast.thinkingelixir.com/ https://github.com/brainlid/langchain https://openai.com/ https://claude.ai/ https://gemini.google.com/ https://www.anthropic.com/ Vertex AI Studio https://cloud.google.com/generative-ai-studio https://www.perplexity.ai/ https://azure.microsoft.com/ https://hexdocs.pm/ecto/Ecto.html https://oban.pro/ Chris McCord's ElixirConf EU 2025 Talk https://www.youtube.com/watch?v=ojL_VHc4gLk Getting started: https://hexdocs.pm/langchain/gettingstarted.html https://ash-hq.org/ https://hex.pm/packages/langchain https://hexdocs.pm/igniter/readme.html https://www.youtube.com/watch?v=WM9iQlQSFg @brainlid on Twitter and BlueSky Special Guest: Mark Ericksen.

This episode is sponsored by Oracle. OCI is the next-generation cloud designed for every workload – where you can run any application, including any AI projects, faster and more securely for less. On average, OCI costs 50% less for compute, 70% less for storage, and 80% less for networking. Join Modal, Skydance Animation, and today's innovative AI tech companies who upgraded to OCI…and saved.   Try OCI for free at http://oracle.com/eyeonai   What if you could fine-tune an AI model without any labeled data—and still outperform traditional training methods?   In this episode of Eye on AI, we sit down with Jonathan Frankle, Chief Scientist at Databricks and co-founder of MosaicML, to explore TAO (Test-time Adaptive Optimization)—Databricks' breakthrough tuning method that's transforming how enterprises build and scale large language models (LLMs).   Jonathan explains how TAO uses reinforcement learning and synthetic data to train models without the need for expensive, time-consuming annotation. We dive into how TAO compares to supervised fine-tuning, why Databricks built their own reward model (DBRM), and how this system allows for continual improvement, lower inference costs, and faster enterprise AI deployment.   Whether you're an AI researcher, enterprise leader, or someone curious about the future of model customization, this episode will change how you think about training and deploying AI.   Explore the latest breakthroughs in data and AI from Databricks: https://www.databricks.com/events/dataaisummit-2025-announcements Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI  

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This week, I'm speaking with Kevin Weil, Chief Product Officer at OpenAI, who is steering product development at what might be the world's most important company right now.We talk about:(00:00) Episode trailer(01:37) OpenAI's latest launches(03:43) What it's like being CPO of OpenAI(04:34) How AI will reshape our lives(07:23) How young people use AI differently(09:29) Addressing fears about AI(11:47) Kevin's "Oh sh!t" moment(14:11) Why have so many models within ChatGPT?(18:19) The unpredictability of AI product progress(24:47) Understanding model “evals”(27:21) How important is prompt engineering?(29:18) Defining “AI agent”(37:00) Why OpenAI views coding as a prime target use-case(41:24) The "next model test” for any AI startup(46:06) Jony Ive's role at OpenAI(47:50) OpenAI's hardware vision(50:41) Quickfire questions(52:43) When will we get AGI?Kevin's links:LinkedIn: https://www.linkedin.com/in/kevinweil/Twitter/X: @kevinweilAzeem's links:Substack: https://www.exponentialview.co/Website: https://www.azeemazhar.com/LinkedIn: https://www.linkedin.com/in/azharTwitter/X: https://x.com/azeemOur new show:This was originally recorded for "Friday with Azeem Azhar", a new show that takes place every Friday at 9am PT and 12pm ET. You can tune in through Exponential View on Substack.Produced by supermix.io and EPIIPLUS1 Ltd.

Why do so many AI initiatives stall after the strategy phase? In this episode, we unpack a practical AI implementation plan that moves beyond theory to real execution. Discover how enterprise leaders structure, govern, and deliver AI at scale — with measurable impact. Learn how to align AI with business value, manage risk, and ensure accountability across the organisation. If you're serious about embedding AI into your business strategy, this is your blueprint. Tune in for more insights on AI leadership and digital transformation. 

Vertical SaaS customers don't buy software for 10 months, they buy it for 10 years. That's the opportunity and the challenge. Switching costs are high, which makes it hard to get in but once you're in, you're in.But regular SaaS playbooks don't work here. Forget PLG. Forget design partners. These industries have been burned too many times by bad software. Here, Trust defines GTM. Think warm introductions and on-site meetings, not cold emails and Zoom calls.But for founders building in vertical SaaS, there's little to learn from. So in this episode of The Neon Show, we bring together three founders who are building in the trenches of Vertical SaaS.Omkar Patil, Co-founder of Pienomial, helping biopharma companies run faster clinical research and unlock insights from complex drug data.Kumar Siddhartha, Co-founder of Merlin, rebuilding ERP from the ground up for the US construction industry.Divyaanshu Makkar, Co-founder of WizCommerce, modernising sales and commerce tools for wholesale distributors.If you're building SaaS for niche markets or wondering why traditional playbooks are failing, this episode is for you.0:00- Pienomial X WizCommerce X Merlin0:51 – What are we building in Vertical SaaS?4:29 – Vertical SaaS buyers are sticky by nature6:57 – How to build for industries used to Below-Par Tech?10:46 – Fix what your customer hated about the last vendor12:17 – Why these industries pay billions for implementation?13:38 – How we got our First customers?20:03 – Warm intros and word-of-mouth still win23:56 – Why Design Partners don't work in Vertical SaaS?27:17 – Why you should never sell your first product for free?30:29 – Can you Co-build products with early customers?34:33 – Building Your Own Platform Vs Building on Top of one39:33 – Building alongside Legacy players or innovating around them?44:31 – SaaS isn't going anywhere, AI will amplify it46:49 – Can AI agents really be reliable?48:42 – Which roles shouldn't be automated?52:16 – How to approach GTM where users guide you?54:43 – Why trust is everything here?58:54 – How to sell softwares used for 10 years?1:01:02 – How to win when the product demo comes last?1:03:16 – Why NOW for traditional industries with unsolved problems1:09:17 – Thoughts on agentic workflows1:13:02 – Why be Bearish on the “AI Employee Concept”?1:16:57 – Rapid Fire : Google or Perplexity?1:17:37 – LLMs: Open-source or Closed?1:18:19 – Favorite work software + We're hiring!1:19:42 – One business buzzword that should disappear1:20:55 – A Vertical SaaS company we admire (and why)-------------​​India's talent has built the world's tech—now it's time to lead it.This mission goes beyond startups. It's about shifting the center of gravity in global tech to include the brilliance rising from India.What is Neon Fund?We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that's done it before.Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we're doing it all at Neon.-------------Check us out on:Website: https://neon.fund/Instagram: https://www.instagram.com/theneonshoww/LinkedIn: https://www.linkedin.com/company/beneon/Twitter: https://x.com/TheNeonShowwConnect with Siddhartha on:LinkedIn: https://www.linkedin.com/in/siddharthaahluwalia/Twitter: https://x.com/siddharthaa7-------------This video is for informational purposes only. The views expressed are thosSend us a text

If you've ever wondered how to actually navigate the AI revolution—without getting crushed by it—then you must hear this one. John Girard, serial tech CEO and modern-day philosopher, breaks down what most businesses are getting dangerously wrong about AI adoption—and what to do instead.This isn't just about optimizing workflows—it's really about whether your business survives the next decade. We unpack the AI enablement wave, why it's eerily similar to the dot-com boom (and bust), and how solopreneurs and Fortune 50s alike can avoid becoming obsolete. Whether you're a curious founder, a hesitant exec, or a policy-overwhelmed leader, this convo is your wake-up call.

How does a top AI company scale massive clusters and build AI for the enterprise? In this episode of The Liftoff with Keith, we talk to Ted Shelton, COO of Inflection AI, from the AI Infra Summit 2025. Ted shares how their team pivoted from consumers to enterprise after their Microsoft deal, why seamless infrastructure is key, and what it takes to build AI models that run on NVIDIA, AMD, and Intel.Learn why “getting to the no” is the smartest move for founders, how enterprises can embrace sovereign AI, and how Inflection's approach to model customization unlocks massive business value.

SHOW NOTESGuest: Andrew AmannWebsite: ninetwothree.coLinkedIn: Andrew AmannX/Twitter: @andrewamannKey topics:Andrew's pivot from mechanical engineering to AI and software development Early experiments with digital transformation, including VBA-coded automations Founding 923 Studio and delivering 150+ innovative AI and ML products Ideal clients: established brands with innovation labs and funded startups How Andrew and his team win business through SEO, conferences, and LinkedIn outreach Stabilization and growth goals for 923 Studio in 2025 How AI can be implemented in enterprise businesses, starting with a knowledge base Balancing business growth with a holistic lifestyle for employees Andrew's best advice: become an apprentice, learn from both good and bad bosses The 923 Studio name: inspired by their early days working 9 PM to 3 AM Tips for building AI solutions that truly solve real-world problems Key Questions(01:19) Can you tell us a bit about how you ended up where you are today?(03:15) Who would be your ideal client these days?(04:03) How do you get in front of these people?(04:35) Do you have repeat customers?(05:55) What are some big goals that you'd like to achieve in the next year?(06:45) Do you use AI within your business?(08:07) So your goals that you have, how would that affect your business?(08:55) What do you feel is the number one roadblock from you guys getting there?.(09:20) Can you talk a little bit about successful AI transformation in enterprise companies?(11:33) Do you have any tips or anything about how to build AI solutions that will solve our real problems like you were talking about?(12:55) How about running a holistic agency that uses profit to enhance the lifestyle of all employees?(13:49) What is the best piece of advice that you've ever received?(15:13) How did you come up with the business name?(15:54) What's the best advice you have ever given?(17:54) Is there anything else that you would like to touch on?(18:02)  Where can we go to learn more about you and what you're doing?Andrew Amannwww.ninetwothree.coAndrew Amann | LinkedInx.com/andrewamannVirginia PurnellFunnel & Visibility SpecialistDistinct Digital Marketing(833) 762-5336virginia@distinctdigitalmarketing.comwww.distinctdigitalmarketing.comwww.distinctdigitalmarketing.co

Today's guest is Chris Tapley, Vice President and Head of Financial Services Consulting for North America at EPAM Systems. EPAM is a global digital engineering company that provides software development and consulting services across industries, including financial services, healthcare, and media. With deep experience guiding AI adoption in regulated industries, Chris joins Emerj Editorial Director Matthew DeMello on the show today to unpack the foundational challenges facing financial institutions as they move from experimentation to production. He explores the technical and organizational barriers that often stall AI projects, from legacy systems and cloud limitations to gaps in data strategy and executive alignment. Chris shares lessons from EPAM's recent market research on AI maturity in financial services — including how long it typically takes to establish enterprise-ready AI governance and why business leaders must prioritize infrastructure, collaboration, and oversight well before model deployment. Want to share your AI adoption story with executive peers? Click emerj.com/expert2 for more information and to be a potential future guest on the ‘AI in Business' podcast! This episode is sponsored by EPAM. Learn how brands work with Emerj and other Emerj Media options at emerj.com/ad1.

This episode features an interview with Bruce Cleveland, author of the best-seller “Traversing the Traction Gap" and CEO of Traction Gap Partners, a Market Engineering advisory firm.In this episode, Bruce outlines why most startups fail and explains market engineering, a term he coined  to represent the ideas around category design. He shares insights into creating a category and what goes into startup success. Key Takeaways:Market engineering involves the ideas around category design or redefinition thought leadership to create a category.There are distinct advantages to being a category leader; the category leader generates about 76% of  all the profits from a category. While there is a first-mover advantage, there are also some associated challenges.Thought leadership is an essential component of creating a category. People want to be around peers they admire, so gathering the right people together leads to an eventual tipping point that makes it easier for a company to sell.Quote:  One of the reasons that you need to actively be involved in the thought leadership part of category creation is people wanna hang out with other people who they think are smart, who have some cool ideas. And that I think happens with companies as well. So eventually some companies kind of climb out of the morass, the cacophony of, fighting the marketing battle and begin to emerge as the thought leaders in those. And then they collectively gather more people and more people. And finally there's a tipping point where that company is perceived as the category leader. And so it becomes really easy for those companies to then sell more.Episode Timestamps: *(02:26) The Trust Tree: Traversing the Traction Gap *(07:31) The importance of category design*(26:05) Thought Leadership in category creation*(35:39) How to evaluate startupsSponsor:Pipeline Visionaries is brought to you by Qualified.com. Qualified helps you turn your website into a pipeline generation machine with PipelineAI. Engage and convert your most valuable website visitors with live chat, chatbots, meeting scheduling, intent data, and Piper, your AI SDR. Visit Qualified.com to learn more.Links:Connect with Ian on LinkedInConnect with Bruce on LinkedInLearn more about Traction Gap Partners or Traversing the Traction GapLearn more about Caspian Studios

Aaron Levie, CEO & co-founder of Box, joins Azeem Azhar to explore how an “AI-first” mindset is reshaping every layer of Box – from product road-maps to pricing – and what that teaches the rest of us about building faster, smarter organisations.Timestamps:(00:00) Episode trailer(02:04) The "lump of labor fallacy" in sci-fi books(07:37) When individual productivity gains don't translate to teams(12:32) Box's Friday AI demos(21:23) How agents might redefine 100 years of management science(26:37) A lesson on AI innovation from the early days of Ford(29:52) Sundar Pichai, Satya Nadella, and Sergey Brin are coding again?(35:16) Pricing in a post-AI agent world(38:43) Cheaper tokens, heavier usage: AI's margin math(43:02) Solving AI's verifiability problem(48:24) How Aaron uses AI in his personal lifeAaron's links:Box: https://www.box.com/LinkedIn: https://www.linkedin.com/in/boxaaron/X/Twitter: https://x.com/levieAzeem's links:Substack: https://www.exponentialview.co/Website: https://www.azeemazhar.com/LinkedIn: https://www.linkedin.com/in/azharX/Twitter: https://x.com/azeemThis conversation was recorded for “Friday with Azeem Azhar”, live every Friday at 9 am PT / 12 pm ET. Catch it via Exponential View on Substack.Produced by supermix.io and EPIIPLUS1 Ltd

The buzz in Silicon Valley around AI agents has many asking: What's real and what's hype? Box's co-founder and CEO, Aaron Levie, joins Rapid Response to help decipher between fact and fiction, taking listeners inside the fast-paced evolution of agents and its impact on the future of enterprise AI. Plus, Levie unpacks how AI is really being adopted in the workplace, what it takes to legitimately build an AI-first organization, and what political leaders across both parties misunderstand about creating the best environment for technology to thrive. Visit the Rapid Response website here: https://www.rapidresponseshow.com/See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Customer expectations have skyrocketed—people now demand instant, personalized, and seamless interactions across every touchpoint. But are companies truly meeting these expectations, or are they still stuck in reactive customer service models? What if AI could completely transform the customer experience into something proactive, predictive, and even empathetic? Joining me today is Vinod Muthukrishnan, VP & COO of Webex Customer Experience at Cisco. Vinod is a leader in the future of customer experience (CX), helping organizations use AI to anticipate customer needs, deliver seamless automation, and create personalized interactions at scale. Vinod Muthukrishnan is the VP & COO for the Webex Customer Experience Business Unit, overseeing Go To Market, Customer, and Business Operations. In this role he collaborates with Cisco field teams, partners, and customers to deliver innovative solutions. His passion lies in creating products that solve real customer pain points and providing a seamless customer experience. He also values building strong communities, teams, culture, and operating rhythms.Previously, Vinod spent three years in Enterprise AI at Uniphore, a Cisco Investments Portfolio Company, where he developed a product enabling Citizen Developers to create AI and automation solutions. He managed Uniphore's customer functions, including Delivery, Technical Support, Customer Success, and AI consulting, helping enterprises align their business goals with AI roadmaps.Vinod was also VP & COO at the Webex Contact Center Business Unit during a period of significant growth and innovation. During his tenure at the BU, the IMI CPaaS business was acquired, and Webex Contact Center was launched. These two initiatives now serve as the foundations of the Webex Customer Experience Business Unit. Vinod oversaw all GTM functions.He joined Cisco when his startup, CloudCherry, was acquired in 2019. As Co-Founder and CEO of CloudCherry, he and his team developed a Customer Experience Platform that became Webex Experience Management. They also built the foundations of the Customer Journey Data Service, essential to the Webex Portfolio today.Coming from a military family, Vinod began his career in the Merchant Marine at 18, becoming a certified First Officer with Maersk Line and sailing to over 60 countries. He later joined the founding team at MarketSimplified, which introduced mobile trading to major brokerages like TD Ameritrade and OptionsExpress. RESOURCESCisco: https://www.cisco.com Catch the future of e-commerce at eTail Boston, August 11-14, 2025. Register now: https://bit.ly/etailboston and use code PARTNER20 for 20% off for retailers and brandsOnline Scrum Master Summit is happening June 17-19. This 3-day virtual event is open for registration. Visit www.osms25.com and get a 25% discount off Premium All-Access Passes with the code osms25agilebrandDon't Miss MAICON 2025, October 14-16 in Cleveland - the event bringing together the brights minds and leading voices in AI. Use Code AGILE150 for $150 off registration. Go here to register: https://bit.ly/agile150Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregkihlstromDon't miss a thing: get the latest episodes, sign up for our newsletter and more: https://www.theagilebrand.showCheck out The Agile Brand Guide website with articles, insights, and Martechipedia, the wiki for marketing technology: https://www.agilebrandguide.com The Agile Brand podcast is brought to you by TEKsystems. Learn more here: https://www.teksystems.com/versionnextnowThe Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. https://www.missinglink.company

You prolly missed this HUGE AI drop.Google quietly updated its NotebookLM behemoth to a thinking model and went FULL on multilingual. Millions of people are instantly getting a AI assistant overnight, but probably don't even know. So.... we're breaking it down. Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Thoughts on this? Join the conversation.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:NotebookLM's Major 2024 AI Tool UpdatesGoogle's Gemini 2.5 Flash Multilingual FeaturesNotebookLM's Gemini Model Integration DetailsAI Reasoning Models in NotebookLM ExplainedAI Audio Overviews in 50+ LanguagesExploring NotebookLM's Mind Map FeatureDiscover Sources Function in NotebookLMUsing Deep Research with NotebookLMTimestamps:00:00 "Google Notebook AI Updates"06:27 ChatGPT-Controlled IBM Updates Demo08:48 Notebook LM Gains Global Attention13:18 Modeling Challenges and Learning Paths14:01 "Gemini 2.5 Flash: Powerful & Affordable"18:55 AI Struggle: Defining Chicago21:49 "Notebook LM Source Integration Guide"26:30 "Notebook LM: Studio and Mind Map"29:47 Watson x AI Updates Overview31:36 Mind Map: Chaos to Clarity36:39 "Adding Sources: Manual vs. Auto"39:02 Analyzing Watson x Updates Monthly41:08 IBM Watson x Trends Overview44:25 Evaluating John's Performance in Marketing48:05 "Leveraging Data with AI"Keywords:NotebookLM, Google Gemini, AI update, Gemini 2.5 flash model, Multilingual audio overviews, Large Language Model, Deep research tools, Google AI Studio, AI-powered deep dives, Gemini 2025, OpenAI, ChatGPT, AI-driven mind maps, IBM Watson x, Enterprise governance, AI reasoning model, Language support, AI-powered conversation, Audio overview features, AI flash model, Multimodal AI, Data protection, AI Studio integration, AI capabilities, Gemini reasoning, Machine learning advancements, AI feature updates, Enterprise AI solutions, Google Gemini thinking model, AI-driven insights, Language model updates, AI-driven research.Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Ready for ROI on GenAI? Go to youreverydayai.com/partner