What if the real driver of digital disruption isn’t technology, but unit economics?

In this episode of Technovation, Peter High speaks with Dan Gill, Chief Product Officer of Carvana, about how disciplined unit economics power one of the most ambitious e-commerce models in retail. Rather than leading with engineering for its own sake, Carvana focuses relentlessly on eliminating friction, capturing profit pools, and reinvesting those economics back into customer value.

Key highlights from the episode:

• Vertical integration and competitive advantage

• Deterministic, self-service digital experiences

• Proprietary platforms vs. off-the-shelf tools

• AI-human collaboration at scale

How can early-stage investors deliver repeatable, outsized returns—without chasing hype?

In this episode of Techoventure, Mark Fernandes, Managing Director at Sierra Ventures, shares the disciplined model behind one of the industry’s most consistent early-stage venture firms. Sierra’s strategy is designed for repeatable 3–5x returns by focusing on founder-market fit, tight portfolio construction, and tech-savvy sectors like AI, cloud, and cybersecurity.

Key insights include:

• The four-part rubric Sierra uses to vet early-stage founders

• Why fund size discipline is critical to long-term VC performance

• How Sierra balances seed and Series A checks with portfolio theory

• The power of “AI enablers” in healthcare, legal, and vertical SaaS

• The 20-year evolution of Sierra’s CXO Board and its enterprise value

Is AI coming for your job—or just changing how you work?

In this episode, Wall Street Journal technology columnist Christopher Mims shares a grounded, deeply informed perspective on how AI is reshaping productivity, creativity, jobs, and knowledge work. From the pitfalls of overhyping generative AI to the rise of agentic systems and the enduring role of classic AI, Christopher unpacks what leaders need to know now. He also highlights how experts benefit most from AI, what happens when organizations anchor too heavily on AI tools, and why handwritten notes, walking meetings, and skepticism are critical in the AI age.

Key highlights from the episode:

• Why experts extract more value from generative AI
• How CEOs are freezing junior hiring while boosting senior productivity
• Mims’ concept of “work slop” and how to avoid it
• Why hallucinations are structural in AI and require human oversight
• Tips for AI adoption that preserve creativity and context

How does a 100-year-old manufacturing leader reinvent itself through autonomy and AI?

In this episode, Caterpillar CTO Jaime Mineart shares how her team is transforming industrial work sites using robotics, machine intelligence, and real-time data. From mining to construction, the company is applying decades of engineering expertise to modern digital challenges, partnering with customers to co-develop scalable automation solutions.

Key highlights from the episode:

• How autonomy is expanding beyond mining into quarries and construction
• What makes Caterpillar’s AI adoption strategy unique—and replicable
• Inside the Helios platform and NVIDIA partnership powering data-driven insights
• Why the company pledged $100M to upskill the workforce of the future
• Lessons from scaling R&D with real-world customer involvement

1048: What if the hiring process wasn’t broken—but reimagined?

Anthony Moisant, Chief Information Officer and Chief Security Officer at Indeed, details how his teams are building trusted systems, tackling AI bias, and leveraging background agents and AI sourcing to solve the “black hole” of hiring. He also reflects on the importance of early-career talent, skill-based hiring, and the balance of self-learning and leadership-led growth.

The conversation covers:

• Why trust is foundational to AI innovation at Indeed
• How “invite to apply” transforms the candidate experience
• The future of work through agentic systems and AI sourcing
• Balancing self-driven learning with leadership-created space

1047: What does it take to lead tech—and the enterprise—in 2026?

In this episode of Technovation, we feature a panel from our October 2025 Metis Strategy Summit where Steven Norton speaks with three top executive recruiters: Craig Stephenson (Korn Ferry), Jamey Cummings (JM Search), and Scott Robbin (Heidrick & Struggles). Throughout the conversation, each recruiter gives their perspective on the evolving mandate of the CIO.

The conversation covers:

• The convergence of data, security, digital, and operations under the CIO
• How talent strategy and succession planning are changing
• What makes a technology leader board-ready
• The rise (and ambiguity) of the Chief AI Officer
• Offshore workforce trends and leadership development

Enterprises aren’t failing at AI. They’re failing at data.

Daniel Docter, Managing Director at Dell Technologies Capital, shares why the biggest barrier to enterprise AI isn’t models or talent—it’s the fractured, unstructured, and context-free data that most companies still struggle to harness.

In this episode of Technovation, Daniel and Peter High explore:

• Why data context is critical to enabling enterprise reasoning

• How Redis and other startups are fixing the AI performance gap

• What Dell Technologies Capital looks for in early-stage enterprise AI

• How corporate VC has evolved into a founder-enabling force

• Why the next five years will reward enterprises that fix their data layer

Digitization was just the first step. True digital transformation in healthcare is only beginning.

Dr. Michael Pfeffer, Chief Information and Digital Officer at Stanford Health Care, shares how he and his team are moving beyond electronic health records to deliver real-time, AI-powered care. From building ChatEHR, a secure, embedded LLM interface, to developing Stanford’s FIRM framework for responsible AI, Pfeffer provides a behind-the-scenes look at one of the nation’s most advanced digital health systems.

In this episode, you’ll learn:

• Why “digitized” isn’t the same as “digital”

• How Stanford built the first integrated LLM in clinical workflows

• What makes healthcare AI safe, useful, and equitable

• Where AI adds real clinical value and where it doesn’t

• The vision behind precision health at scale