Earley AI podcast

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16:56

Two women, tired of working dead end jobs, try their hand at the dark art of Bloodsinging. When they kidnap a small boy for a ritual sacrifice, they learn that they have far more to worry about than the police. WARNING: This episode contains graphic violence, strong language, and mature themes. The 100 Handed is an audio drama intended for mature audiences. Listener discretion is advised. Listen ad-free and find bonus material at https://www.patreon.com/the100handed And remember, leave us a 5-star review to help spread the word. Weep at the wonder and howl at the horror! Please support our sponsors at: https://fableandfolly.com/partners/ Learn more about your ad choices. Visit megaphone.fm/adchoices…

Earley AI Podcast

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In this podcast hosts Seth Earley invites a broad array of thought leaders and practitioners to talk about what's possible in artificial intelligence as well as what is practical in the space as we move toward a world where AI is embedded in all aspects of our personal and professional lives. They explore what's emerging in technology, data science, and enterprise applications for artificial intelligence and machine learning and how to get from early-stage AI projects to fully mature applications. Seth is founder & CEO of Earley Information Science and the award-winning author of "The AI Powered Enterprise."

77 episodes

Earley AI Podcast

updated il y a environ 17 jours

maison des série•Feed

77 episodes

#Tech #Business #Earley Information Science

Tous les épisodes

Earley AI Podcast

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Earley AI Podcast Ep 77: Leading Through Digital Transformation: Data, Change, and AI in Retail 29:29

il y a environ 17 jours29:29

29:29

This episode of the Earley AI Podcast features Betsy Mello, a seasoned retail executive whose career includes leadership roles at Dorel Home, Levi’s, Old Navy, Sears, and several retail startups. With deep expertise in merchandising, inventory management, and eCommerce strategy, Betsy brings a pragmatic perspective shaped by years of leading digital transformation and managing major marketplace relationships with Amazon, Bed Bath & Beyond, and others. Host Seth Earley talks with Betsy about how retail leaders can navigate the ongoing shift from traditional operations to AI-driven business models. Their discussion explores how structured data, process discipline, and organizational alignment form the foundation of successful digital and AI initiatives—and why the fundamentals still matter, even in the age of automation. Key Takeaways: How the move from brick-and-mortar to digital commerce has transformed consumer expectations and the pace of retail innovation. Why marketplaces are data supply chains—and how brands must adapt content, taxonomy, and product positioning across diverse channels. The importance of clean data, standardized terminology, and clear use cases before adopting AI solutions. Strategies for breaking down silos, aligning KPIs, and ensuring cross-functional collaboration around data and insights. Leading through change: the value of transparency, experimentation, and learning from failure during AI-driven transformation. What leaders often overlook when preparing for AI—and how to make foundational data work visible and measurable. The building blocks for sustainable AI success: information architecture, governance, and accountable data ownership. Show Quotes: "You need to have everything standard. You need to have clean data and very clear workflows and accountabilities... The key is having the team set in place and very clear defined processes and roles and responsibilities. It’s incredibly critical to make sure your foundation is correct. You need to be always starting at the basics." – Betsy Mello "Supply chain is an information supply chain. And every time you have a new way of distributing your product, you have to think about, how do I distribute the data with that product?" - Seth Earley Tune in to hear how retail and eCommerce leaders can turn complexity into clarity—and build the cultural and data foundations that make AI work. Links LinkedIn : https://www.linkedin.com/in/betsymello/ Website : https://www.dorelhome.com Thanks to our sponsors: VKTR Earley Information Science AI Powered Enterprise Book…

Earley AI Podcast

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Earley AI Podcast – Ep 76: How AI and Clean Data Power Smarter Search 45:29

il y a 4 weeks45:29

45:29

Bharat Guruprakash, Chief Product Officer at Algolia, joins host Seth Earley on this episode of the Earley AI Podcast. With years of experience helping organizations leverage AI to connect people with information, Bharat brings deep insight into the evolving world of AI-powered search, retrieval, and agentic technologies. At Algolia, a global leader in AI-driven search and retrieval, he helps shape what’s next in unifying data, building intelligent systems, and designing platforms that understand real-time context. Key Takeaways: Misconceptions about Search and AI: Many organizations think large language models (LLMs) can handle all search needs, but true effective AI solutions require robust retrieval systems beneath the surface. The Role of RAG and Memory: Retrieval Augmented Generation (RAG) remains important, but the future is moving toward agentic architectures that require "memory" and stateful interactions, not just stateless search. Clean, Structured Data is Crucial: The importance of having clean, accessible, and normalized data stores as the backbone for any successful AI and search initiative. Experimentation and Innovation: Enterprises struggle with a culture of experimentation and face challenges in safely running and scaling AI experiments. Autonomous experimentation, where AI can test and optimize different approaches, is emerging as a solution. The Rise of Agentic Technologies: The distinction between generative AI (focused on content creation) and agentic AI (focused on task automation and execution), and how agents will soon drive more dynamic, event-driven workflows. Guardrails and Risk: Implementing proper protocols (like MCP and Google’s A2A SDKs) and guardrails is essential to ensure agents act safely and within business parameters. Privacy and the Future: As agents learn more about users than users know about themselves, privacy, transparency, and identity become critical concerns. The speed of change is challenging, but small, iterative steps help organizations evolve responsibly. Insightful Quote from the Show: "It's very risky to say, let's just boldly go forth into the unknown, right? I think you have to have experiments, right? You have to control them, experiments, but you have to Be careful about that and have a mechanism for managing that and for controlling it and for monitoring the results." Seth Earley "It's okay to start small. Find the small places where you can improve...and keep multiplying them. Over time, when you look back after a year or two, you'll have a very different company from when you started." – Bharat Guruprakash Tune in for a thoughtful deep dive into the challenges, opportunities, and responsible strategies for embracing AI, search, and agentic technologies in your organization. Links: LinkedIn : https://www.linkedin.com/in/bharatguruprakash/ Website : https://www.algolia.com Thanks to our sponsors: VKTR Earley Information Science AI Powered Enterprise Book…

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Earley AI Podcast - Ep 75 Why Data Quality Matters for AI and Digital Maturity in B2B Enterprises 41:48

il y a 6 weeks41:48

41:48

In this episode of the Earley AI Podcast, host Seth Earley welcomes Eric Rehl, Vice President of Digital Customer Experience in North America at Schneider Electric. With over 25 years of expertise in digital strategy and customer experience, Eric has guided global organizations through complex digital transformations, always keeping business outcomes and customer needs at the core. Drawing on his deep industry knowledge, Eric shares how large enterprises can move beyond buzzwords like “digital transformation” and “AI,” instead choosing a pragmatic, data-driven approach to drive real business value. Join Seth and Eric as they discuss the evolving role of digital capabilities in business strategy, the foundational importance of high-quality data, the unique challenges faced by B2B organizations, and how AI can power truly personalized customer experiences—from the ground up. Key Takeaways: Digital transformation should be rooted in business outcomes, not technology hype; focus on the “so what” for your customer and organization. Strong, clean, accessible data is critical for scaling digital experiences and enabling AI-driven personalization—without it, even the best tools will fail. B2B companies often lag in digital maturity due to legacy data architectures and complex customer relationships, but can catch up by investing strategically in foundational capabilities. A robust digital journey relies on operationalizing and continually improving product and customer data, rather than one-off fixes. Maturity in B2B digital experiences evolves from simply “doing no harm,” to enabling ease of business, and ultimately leveraging digital platforms for growth and commercial impact. AI’s promise lies in moving from segmented personalization to real-time, dynamic customer engagement powered by integrated data and knowledge. Preparing for AI-driven customer discovery means syndicating high-quality, semantically-structured content across channels—both on and off your own domain. The next frontier is operationalizing knowledge (not just product or customer data) to fuel AI tools for differentiation and problem-solving. Continuous experimentation and responsible opportunism allow organizations to discover new outcomes and business value. Insightful Quotes: "I think as you start building maturity, you're learning how to orchestrate those pieces. You're getting more of that harmonization of organizing principles across those disparate departments, across knowledge and content and customer experience and product information. And so that becomes kind of the holistic journey that you're thinking about." - Seth Earley “We always start with the outcome. Like, why are we talking about capabilities here? Why are we talking about AI? What are we actually going to do with it to get to what the business outcome we’re trying to drive or the experience outcome we’re trying to drive?” - Eric Rehl Don’t miss this in-depth conversation packed with practical advice and forward-looking insights for anyone leading or navigating digital transformation initiatives in the AI era. Links LinkedIn: https://www.linkedin.com/in/ericrehl/ Website: https://www.se.com/us/en/ Thanks to our sponsors: VKTR Earley Information Science AI Powered Enterprise Book…

Earley AI Podcast

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Earley AI Podcast - Episode 74: AI in B2B Commerce: From Data Challenges to Differentiation 42:47

il y a 7 weeks42:47

42:47

This episode of the Earley AI Podcast features Rudy Abitbol, a recognized expert in B2B commerce and AI. With years of hands-on experience helping global enterprises with digital transformation—especially around product information management, large-scale AI adoption, and making cutting-edge technology truly practical—Rudy brings a pragmatic view to how AI is revolutionizing B2B e-commerce. He’s passionate about making AI accessible and effective for tackling real-world business challenges. Key Takeaways: AI-Driven Transformation: AI is dramatically streamlining the content generation and management process in B2B commerce, especially when dealing with vast, complex product catalogs. Platform Flexibility Matters: Tools like Shopify are lowering barriers for B2B companies by offering user-friendly interfaces and robust ecosystems that allow for rapid configurations—often with no coding required. Vibe Coding & Rapid Prototyping: “Vibe coding” empowers product owners to quickly move from conversations and requirements to working wireframes and functional specs, tightening feedback loops and boosting innovation. Balancing Efficiency & Differentiation: While AI tools help standardize processes, true competitive advantage comes from infusing proprietary business knowledge into digital solutions. Data Readiness & Quality: AI can enrich incomplete or messy data, but organizations must still focus on good data structure and master data management to fully capitalize on AI and automation. AI Adoption Hurdles: The most common blockers are cultural—resistance to change and undertraining. Hands-on learning, POCs, and fostering a culture of curiosity are essential. Empowering Teams: True AI readiness isn’t just about tools but about giving teams the time, training, and encouragement to experiment—and even risk failure—as they integrate AI into daily workflows. Avoiding Over-Reliance on AI: While AI enhances productivity, it can’t replace human judgment. Insightful, context-driven use of AI yields the biggest returns. Building Core Competency: Don’t outsource the heart of your digital transformation; instead, build internal expertise and maturity to stay ahead in a rapidly evolving landscape. Insightful Quote from Rudy Abitbol: "All the insight within the phrasing, within the way that it’s done...still needs to come from you. You still need to have someone that is a product owner with a great vision, because that's the sole person that is able to infuse [the business]." Tune in to learn how AI is fundamentally reshaping B2B commerce and how leaders can stay ahead of the digital curve. Links LinkedIn : https://www.linkedin.com/in/rudyabitbol/ Website : https://www.trustinsights.ai Thanks to our sponsors: VKTR Earley Information Science AI Powered Enterprise Book…

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[Earley AI Podcast] Episode 73: Mark Anderson - Unlocking Hidden Patterns: A New Approach to Enterprise AI 32:35

il y a 8 weeks32:35

32:35

In this episode of Earley AI Podcasts, host Seth Earley welcomes Mark Anderson, co-founder and CEO of Pattern Computer, for a fascinating exploration of what lies beyond the current AI mainstream. With a career grounded in technology, strategy, and scientific innovation—including receiving the Alexandra J. Nobel Award for his contributions to computing and medicine—Mark brings nearly a decade of experience in developing proprietary pattern recognition technologies that move far beyond traditional machine learning models. Together, Seth and Mark dive deep into the journey of Pattern Computer, unveiling its revolutionary Pattern Discovery Engine—a platform with the unique ability to make discoveries in data that have eluded conventional approaches. Mark explains how his passion for science and the shortcomings of the classic scientific method sparked the creation of new mathematical and architectural foundations in AI, leading to major breakthroughs not only in medicine but also across enterprise applications. Key Takeaways: Origins of Pattern Computer: The story behind the formation of Pattern Computer and its foundational mission to turn pattern discovery from an art into a science. A New Approach to AI: How the Pattern Discovery Engine goes beyond finding incremental improvements, enabling true discovery by flipping the traditional scientific method. Breakthroughs in Medicine: The real-world impact of Pattern Computer’s approach, including the discovery of gene patterns and the development of new drugs for triple negative breast cancer. Pattern Discovery vs. Large Language Models: The critical differences between pattern discovery engines and LLMs, and how these technologies can work together to combine human-friendly communication with genuine scientific discovery. Explainable AI and Ethics: Why true explainability, interpretability, and ethical data are at the heart of next-generation AI—and how Pattern Computer is leading the way with interpretable outputs and transparency. Enterprise & Science Applications: Use cases in aerospace, mining, healthcare, and more, where Pattern Computer’s approach has led to major discoveries in seconds—successes that eluded brute-force methods for years. Advice for Organizations: How businesses and innovators can access and test the Pattern Discovery Engine for their own complex data challenges. Insightful Quote from Mark Anderson: “Instead of having a hypothesis and then you run, you want to go again, it’s the opposite. You’re not allowed to have any hypothesis. You can’t bring your bias to the game. And instead of that, you have good data. You run the data and you generate the hypothesis. That’s the right way to solve problems.” Links LinkedIn : https://www.linkedin.com/in/markandersonpredicts/ Website : https://www.patterncomputer.com Thanks to our sponsors: VKTR Earley Information Science AI Powered Enterprise Book…

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[Earley AI Podcast] Episode 72: AI in the Enterprise: What Really Matters 46:55

il y a 8 weeks46:55

46:55

In this episode of the Earley AI Podcast, host Seth Earley sits down with Christopher Penn, co-founder and Chief Data Strategist at Trust Insights. Widely known as an authority on analytics, data science, and AI, Chris brings a wealth of practical experience, thought leadership, and cutting-edge perspective to the conversation. With a proven track record as an author, keynote speaker, and trusted advisor in digital transformation, Chris delves deep into the realities of AI for today’s enterprises. Join Seth and Chris as they cut through the hype surrounding generative AI and focus on what truly matters for organizations: effective AI adoption, data strategy, and delivering measurable value. Key Takeaways: AI Content Detection is Overrated: Most people don’t care if content is AI-generated; what matters is whether it solves their problem or meets their needs. Effective AI Use Is About Differentiation: Real business value comes from leveraging your unique voice, expertise, and data—not simply automating generic processes. Enterprise AI Adoption Challenges: Organizational inertia, politics, and risk-averse cultures are frequently the biggest barriers to successful AI projects, not technology itself. Failure is Essential for Innovation: Enterprises with zero tolerance for failure will struggle with AI: experimentation and learning from failure are critical. AI’s Impact on Jobs: Entry-level roles are rapidly changing or disappearing with automation, especially for routine and repetitive tasks. Data Quality Still Reigns: The success of tools like Microsoft Copilot depends on having clean, well-organized foundational data—bad data in, bad results out. Agentic AI and Model Context Protocols: The future of AI involves building robust agentic infrastructure, understanding APIs for AI, and navigating security/privacy in enterprise integrations. Transform, Don’t Just Optimize: Leaders must ask if they’re truly transforming or just making old processes faster; meaningful change starts with people and process—not tech-first thinking. Insightful Quote from Christopher Penn: "In the enterprise, it is actually more important to navigate the people and the politics than it is the technology. The technology is easy. It is the humans that are the hard part." Links LinkedIn : https://www.linkedin.com/in/cspenn/ Website : https://www.trustinsights.ai MAICON 2025 Code: PENN200 Thanks to our sponsors: VKTR Earley Information Science AI Powered Enterprise Book…

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Earley AI Podcast Episode 71: The Real Work of Operationalizing AI 51:12

il y a 13 weeks51:12

51:12

In this episode of the Earley AI Podcast, host Seth Earley welcomes Charlie Betz, Principal Analyst at Forrester Research. With an extensive background in digital operating models, enterprise architecture, and the future of work, Charlie brings a systems thinking approach to how digital initiatives are planned, governed, and scaled. As a leading expert covering a $250 billion segment of the global IT market—including vendors like ServiceNow, Atlassian, and Dynatrace—Charlie provides invaluable perspective for technology and business leaders facing the complexities of AI enablement and digital operations in large organizations. Together, Seth and Charlie dive deep past buzzwords to uncover practical, actionable insights about harnessing AI, operationalizing feedback loops, and navigating legacy technical debt. Charlie shares his real-world experiences wrangling with generative AI tools—including building systems with Anthropic's Claude as a "junior developer"—and distills lessons for executives on aligning business needs with technological advancements. Key Takeaways: How AI, particularly generative models like Claude, has moved from simple code autocompletion to accelerating the development of full-fledged applications—and the challenges and opportunities this creates for non-developers and professionals alike. The architecture of the $250 billion IT control plane market, including IT Service Management (ITSM), AIOps, and the massive influence these domains have on enterprise performance and boardroom-level decision-making. Why the ultimate business value of AI lies in accelerating feedback loops and continuous learning, not just automation or chatbot deployments. Lessons from continuous improvement (lean, Deming cycles, etc.) and why previous attempts struggled at scale—plus how modern AI may finally make the learning organization a reality. The importance of architectural governance, data stewardship, and feedback loop closure in successful AI integration—plus concrete calls to action for executives and enterprise architects. A nuanced discussion of legacy systems and technical debt: why simply layering new technology on top of old can lead to "technical bankruptcy," and practical strategies for managing (and paying down) technical debt before it becomes existential. Cutting through the hype around AI agents and swarms: separating realistic enterprise use cases from risk-laden hype, and the current limitations and essential guardrails needed for safe, effective agentic operations. Insightful Quote from the Episode: "If you held my feet to the fire and you told me, 'Charlie, there’s only one point,' I would say look for the feedback loop... What AI is enabling is essentially a faster feedback loop than we've ever had before in industry. And this is where the old becomes new." – Charlie Betz Tune in for an unvarnished, deeply practical conversation on making AI real in complex enterprise environments—packed with tangible guidance no matter where you are on your digital transformation journey. Links: LinkedIn : https://www.linkedin.com/in/charlestbetz/ Website : https://www.forrester.com Thanks to our sponsors: VKTR Earley Information Science AI Powered Enterprise Book…

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Earley AI Podcast Episode 70 - AI at Scale: Why Infrastructure Matters More Than Ever 30:57

il y a 17 weeks30:57

30:57

This episode features a fascinating conversation with Sid Sheth, CEO and Co-Founder of d-Matrix. With a deep background in building advanced systems for high-performance workloads, Sid and his team are at the forefront of AI compute innovation—specifically focused on making AI inference more efficient, cost-effective, and scalable for enterprise use. Host Seth Earley dives into Sid’s journey, the architectural shifts in AI infrastructure, and what it means for organizations seeking to maximize their AI investments. Key Takeaways: The Evolution of AI Infrastructure: Sid breaks down how the traditional tech stack is being rebuilt to support the unique demands of AI, particularly shifting from general-purpose CPUs to specialized accelerators for inference. Training vs. Inference: Using a human analogy, Sid explains the fundamental difference between model training (learning) and inference (applying knowledge), emphasizing why most enterprise value comes from efficient inference. Purpose-built Accelerators: d-Matrix’s approach to creating inference-only accelerators means dramatically reducing overhead, latency, energy consumption, and cost compared to traditional GPU solutions. Scalability & Efficiency: Learn how in-memory compute, chiplets, and innovative memory architectures enable d-Matrix to deliver up to 10x lower latency, and significant gains in energy and dollar efficiency for AI applications. Market Trends: Sid reveals how, although today’s focus is largely on training compute, the next five to ten years will see inference dominate as organizations seek ROI from deployed AI. Enterprise Strategy Advice: Sid urges tech leaders not to be conservative, but to embrace a heterogeneous and flexible infrastructure strategy to future-proof their AI investments. Real-World Use Cases: Hear about d-Matrix’s work enabling low-latency agentic/reasoning models, which are critical for real-time and interactive AI workloads. Insightful Quote from Sid Sheth: “Now is not the time to be conservative and get comfortable with choice. In the world of inference there isn’t going to be one size fits all... The world of the future is heterogeneous, where you’re going to have a compute fleet that is augmented with different types of compute to serve different needs.” Tune in to discover how to rethink your AI infrastructure strategy and stay ahead in the rapidly evolving world of enterprise AI! Thanks to our sponsors: VKTR Earley Information Science AI Powered Enterprise Book…

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Earley AI Podcast Episode 69: Empowering Creatives with Generative AI with Charles Migos 45:00

il y a 18 weeks45:00

45:00

In this episode of the Earley AI Podcast, host Seth Earley sits down with Charles Migos, a veteran toolmaker whose career has spanned animation, post-production, visual effects, and large-scale media systems. Charles is recognized for his innovative approach to making emerging technologies—particularly generative AI—intuitive and accessible for creatives at every level, not just technical experts. Drawing on decades of experience, Charles shares what it means to design tools that empower storytellers and production teams, accelerate creativity, and address industry-specific needs. Key Takeaways: The media and entertainment industry has been under stress due to macroeconomic changes and the disruptive impact of generative AI. Creative jobs and processes are being transformed as AI tools dramatically speed up and democratize production workflows, bridging the gap between concept and execution. Traditional creative roles are shifting: Directors, producers, and even clients can now participate directly in visual storytelling without years of technical training. Instead of relying solely on prompt-based AI systems, innovation lies in giving creatives precise, fine-grained control for rapid exploration and content iteration. Asset repurposability, modularity, and the ability to build on prior creative work are becoming crucial for agencies and studios to scale, reduce costs, and increase creative output. Protecting intellectual property and ensuring ethical AI use—particularly around deepfakes and content control—is fundamental as generative tools become more powerful. The foundation of successful creative AI lies in deeply understanding and honoring existing workflows, enabling faster collaboration, clearer communication, and greater creative trust. Insightful Quote from Charles Migos: "Your ability to create faster and better than you ever have before, your ability to collaborate with your team and your stakeholders in ways you never have before, and the ability to communicate around what you create as that team effort is what matters most." Tune in to explore how AI is reshaping the creative landscape and to gain actionable insight on building truly human-centered design into emerging tech. Thanks to our sponsors: VKTR Earley Information Science AI Powered Enterprise Book…

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Earley AI Podcast - Episode 68 - Composable Intelligence: Rethinking Customer Data with Seth Earley and Abhi Yadav 44:27

il y a 21 weeks44:27

44:27

In this episode of the Earley AI Podcast , host Seth Earley sits down with Abhi Yadav, founder of iCustomer AI—a cutting-edge composable decision intelligence company. With a deep background in enterprise technology, Abhi pioneered the Customer Data Platform (CDP) category and is now leading innovation in advanced multigraph frameworks and customer intelligence. He is also an advisor to leading data management organizations and is passionate about helping brands reshape how they connect with customers by making data truly "AI-ready." Together, Seth and Abhi explore the evolving landscape at the intersection of AI, data, and enterprise maturity. They dive deep into the challenges and opportunities organizations face as they strive for higher levels of decision intelligence, highlighting both the technical and strategic shifts driving the industry forward. Key Takeaways: The evolution from traditional MDM (Master Data Management) and CDP platforms toward a “knowledge engineering era” powered by AI and multi-graph architectures. Why a single source of truth is more about a unified, reconcilable semantic layer than a single data repository. The importance of developing robust taxonomies, ontologies, and knowledge graphs to contextualize customer data and orchestrate intelligent decisioning at scale. Clear definitions and distinctions between zero-party, first-party, second-party, and third-party data—and why they matter for privacy, compliance, and effective marketing. Challenges enterprise leaders face in scaling decision intelligence, especially in determining the right balance of human and machine-led decisions. The emerging need for "decision lineage": tracking not only what data was used, but how and why decisions were made, for compliance and transparency. Advice for founders, technologists, and enterprise leaders: avoid the hype and focus on solving real, specific problems before building platforms or dreaming of category creation. Insightful Quote from Abhi Yadav: "Don't follow the hype, follow the real problem. There are still so many real problems—and the more specific that problem is, the more impact you can make. Platforms and categories come later; start with solving measurable problems today." Tune in for a thoughtful, actionable conversation on unlocking the true potential of enterprise AI and creating data architectures that drive meaningful impact. Thanks to our sponsors: VKTR Earley Information Science AI Powered Enterprise Book…

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Earley AI Podcast Episode 67: How AI Is Transforming Software Engineering With Yang Li of Cosine 36:09

il y a 24 weeks36:09

36:09

In this episode of the Earley AI Podcast, host Seth Earley sits down with Yang Li, a leading figure in AI and software innovation. Yang is the Chief Operating Officer of Cosine, an advanced AI development firm, with deep experience driving startups, scaling organizations, and pioneering advancements in engineering and software development. Yang’s work focuses on leveraging AI to empower the next generation of developers, especially in navigating the increasingly complex landscape of modern and legacy codebases. Yang and Seth dive into how AI is reshaping the role of software engineers, the evolving challenges of handling massive backlogs and legacy systems, and what creativity and efficiency really look like in an age of AI-powered software development. Key Takeaways: AI’s Impact on Software Engineering: AI is shifting the developer’s role from hands-on coding to more creative, iterative, and strategic work. Tackling Legacy Code: Cosine is pioneering new ways for AI to handle outdated and complex codebases (like COBOL and Fortran) that most engineers—and AI models—struggle with. Augmenting, Not Replacing, Engineers: AI tools like Cosine’s Genie reduce ramp-up time for engineers, help address daunting backlogs, and act as creative partners rather than outright replacements. The Challenge of Benchmarks: Yang explains why public coding benchmarks can be misleading when bringing products to real-world enterprise environments, especially with diverse codebases. The Emergence of ‘Vibe Coding’: Idea-to-prototype time is shrinking, allowing non-technical team members to quickly bring their ideas to life using AI assistants. Risks & Limits: Over-reliance on AI, standardization versus differentiation, and the need for new evaluation criteria in engineering organizations. Future Skills: The importance of risk-taking, adaptability, and prompt engineering as software development evolves, plus insights into how organizations are rethinking career ladders and promotions in an AI-powered world. Insightful Quote from Yang Li: "Previously you had to use words and language to describe your idea, you can now show people your idea... The time between you having thought of an idea to actually be able to show people that idea has now reduced almost to zero because of vibe coding." Tune in to discover what’s next for software engineering in the age of AI, and how to stay ahead in this rapidly changing landscape. Thanks to our sponsors: VKTR Earley Information Science AI Powered Enterprise Book…

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Earley AI Podcast Episode 66: Reengineering Knowledge for the AI Era 29:49

il y a 26 weeks29:49

29:49

In this episode of the Earley AI Podcast , host Seth Earley sits down with industry analyst and advisor Tony Baer, a seasoned expert in data, cloud, and analytics. With decades of experience guiding global tech leaders like AWS and Oracle, Tony brings a nuanced perspective on how knowledge engineering is evolving—and why context is the missing link in many enterprise AI initiatives. Together, Seth and Tony explore the shift from static data models to dynamic knowledge frameworks, the renewed importance of governance, and how graph databases and generative AI are reshaping enterprise intelligence. This is a conversation packed with hard-earned lessons and actionable insight for data, IT, and transformation leaders aiming to make AI work in the real world. Key Takeaways: Knowledge engineering today is about dynamic, adaptive structures—not static ontologies or rigid models. The role of the knowledge engineer is shifting: it’s less about technical mastery and more about bridging data, business, and domain expertise. Context is foundational. The five W’s—Who, What, When, Where, Why (and How)—unlock meaningful, actionable intelligence. Graph databases and AI are enabling real-time connections across data, turning static information into living knowledge. Generative AI delivers the most value when rooted in organizational context. RAG strategies demand clean data and strong information architecture. Successful AI initiatives are focused. Start with well-bounded, high-impact processes—avoid boiling the ocean. Core principles from previous data waves still apply. It’s about evolving governance, stewardship, and architecture for the AI era. Sustainable value comes from feedback loops, iteration, and alignment—not silver bullets. Tune in to discover how to make AI practical, actionable, and intelligent for your organization. Quote of the Show: "Just because something is old does not make it wrong. There are a lot of disciplines we've built up over the years—governance, data stewardship—that still matter. The principle was right. We just adapt it and use our learnings from each cycle to become more knowledgeable and proficient." Tony Baer Links LinkedIn : https://www.linkedin.com/in/dbinsight/ Website : https://www.dbinsight.io Thanks to our sponsors: VKTR Earley Information Science AI Powered Enterprise Book…

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Earley AI Podcast Episode 65: David Hartley and Dave Blatt - Turning AI Hesitancy into Opportunity 26:23

il y a 32 weeks26:23

26:23

In this episode of the Earley AI Podcast, host Seth Earley welcomes two insightful guests from Anders, a top 100 CPA firm: David Hartley and Dave Blatt. David Hartley is a seasoned CPA with a profound understanding of the synergy between finance and technology. He advocates for how AI can enhance traditional accounting roles rather than replace them. Dave Blatt brings a wealth of knowledge in AI automation and analytics, focusing on empowering mid-sized companies to harness AI for competing with larger players. Join us as we dive into the world of AI applications in the finance, accounting, and mid-market operations sectors. Our guests dispel common myths and fears surrounding AI, exploring how small and medium-sized enterprises can practically and effectively adopt AI technologies to drive transformation and growth. Key Takeaways: Demystifying AI: Understanding AI in the context of mid-market companies and addressing misconceptions around AI replacing human jobs. AI for Mid-Sized Enterprises:** How AI is accessible and beneficial for mid-sized businesses, allowing them to compete with larger organizations. Impact on Accounting: Enhancing traditional accounting roles through AI and freeing up time for more value-added activities. Implementation Strategies: Best practices for implementing AI in mid-sized companies, focusing on education, small projects, and quick wins. Real-World Applications: Case studies in industries like construction and manufacturing, where AI has improved efficiency and productivity. Communication and Trust: The importance of communication and building trust among team members to ensure successful AI adoption. Quote of the Show: "Start small and not make it so daunting... get some quick wins that will be a catalyst to doing more projects and bigger efforts." - Dave Blatt Links: LinkedIn : https://www.linkedin.com/in/davehartley/ LinkedIn : https://www.linkedin.com/in/daveblatt/ Website : https://anderscpa.com Article : AI Adoption Is Not as Hard as You Think – Start Now or Fall Behind Thanks to our sponsors: VKTR Earley Information Science AI Powered Enterprise Book…

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Earley AI Podcast Episode 64: Understanding AI: From Misconceptions to Effective Product Mindset 36:07

il y a 35 weeks36:07

36:07

In this episode of the Earley AI Podcast, we welcome guest, Jack Lampka, an accomplished advisor and speaker with over 27 years of experience in corporate roles within the tech and pharma sectors. Now based in Munich, Germany, Jack specializes in enhancing data storytelling and cultivating a product mindset among technical employees. His extensive career journey includes living and working in countries like Poland and the United States. Key Takeaways from this Episode: The importance of a product mindset for technical teams when developing AI solutions. Understanding the misconceptions and realistic expectations for AI and generative AI in businesses. How to successfully sell AI solutions internally by focusing on business needs and creating a comprehensive product marketing plan. The role of data storytelling in bridging the gap between technical and non-technical users. Insights into the hype surrounding Agentic AI and its relevance to current business applications. Thanks to our sponsors: VKTR Earley Information Science AI Powered Enterprise Book…

Earley AI Podcast

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[Earley AI Podcast] Episode 63: Revolutionizing CRM with AI: Insights from Adam Honig 31:57

il y a 37 weeks31:57