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• Tackling Legacy Code: Cosine is pioneering new ways for AI to handle outdated and complex codebases (like COBOL and Fortran) that most engineers—and AI models—struggle with.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.

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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

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• VKTR
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• AI Powered Enterprise Book

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

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