Technovation with Peter High (CIO, CTO, CDO, CXO Interviews)

AI-powered “agent hackers” work continuously, exploit known vulnerabilities at scale, and can move money or make purchases on a consumer’s behalf before anyone notices. Vincent Pilette, CEO of Gen Digital, explains how the company behind Norton, LifeLock, and Avast is responding: platformizing its stack, acquiring MoneyLion to extend from protection into financial wellness, and building Norton Genie as a security agent that filters what autonomous AI agents are allowed to do.

Pilette traces Gen’s evolution from point products to a membership model (Norton 360 reached 65% install-base adoption within 12–18 months) and addresses the engagement paradox at the heart of consumer security: the best outcome is silence, which makes the product nearly invisible by design.

Key Highlights:

Why 90-plus percent of consumer threats are now scams and phishing, layered on top of malware that never went away

How agentic AI changes attack economics by exploiting previously known but ignored vulnerabilities at scale

The customer-behavior logic behind acquiring MoneyLion: surveys showed consumers wanted Gen to move from protection to financial empowerment

How Norton 360’s membership model reached 65% install-base adoption in 12-18 months by collapsing point products into one offer

Why the ideal security outcome (you hear nothing) is structurally hostile to engagement, and how Gen is evolving toward an action loop that detects, verifies, and pays

How do CIOs prepare for a future where employees, service providers, and AI agents work side by side? In this episode of Technovation, Peter High speaks with Matt Ausman, Chief Information Officer of Zebra Technologies, about rethinking IT organizational structures, scaling AI responsibly, and preparing for the next evolution of software development.

Matt shares how Zebra is balancing AI experimentation with governance, strengthening its enterprise data foundation, and reimagining technology delivery as AI accelerates what teams can build.

Key Highlights:

Preparing for a Hybrid Workforce: How Zebra is rethinking IT organizational structures as employees, service providers, and digital workers increasingly work alongside one another.

Scaling AI Agents with Governance: Why Zebra initially restricts agent sharing, holds individual creators accountable for results, and is developing governance models for enterprise-wide adoption.

Reimagining Software Development: How AI could fundamentally reshape Agile teams, accelerate application development, and challenge traditional change management practices.

Building an AI-Ready Data Foundation: How Zebra's consolidated data platform and federated governance model help improve data integrity and support more reliable AI outputs.

The best venture bets are foundational: companies other companies build on top of, making them structurally irreplaceable no matter which end-user applications succeed.

In this episode of Technoventure, Peter High speaks with Aydin Senkut, Founder and Managing Partner at Felicis, about how the firm identifies technology waves before they reach consensus, why it backs founders outside Silicon Valley's orthodoxy, and how a contractual pledge to vote with founders rather than against them changed the nature of every board conversation.

Senkut spent four years angel investing his own capital before launching Felicis in 2006. He has since appeared on the Forbes Midas List for 13 consecutive years. Portfolio companies have delivered growth curves that, in his words, make Shopify's trajectory look like a flat line.

Key Highlights:

Why Felicis targets companies growing 500-1,000%+ and what "hyper demand" actually means in practice

How backing foundational infrastructure rather than end-user apps creates compounding, structurally durable positions

Why the AI wave is categorically different from Web 1.0, with contracts now measured in nine figures and instant global distribution

How a written pledge to vote with founders, not against them, makes honest early-warning conversations possible

Why 1% of every Felicis check funds founder coaching, and what that buys beyond goodwill

Semiconductor development cycles run a decade or longer, but markets shift faster than any company can predict. Ahmad Bahai, Senior Vice President and Chief Technology Officer at Texas Instruments, explains how TI navigates that gap by betting on directional technology vectors rather than specific end markets. TI’s high-voltage program, started over a decade ago with smart grid in mind, eventually served electric vehicles and then became core infrastructure for AI data centers. In this episode of Technovation, Peter High speaks with Ahmad Bahai, SVP and CTO at Texas Instruments, about long-horizon R&D, the power delivery bottleneck in AI infrastructure, and why transistor scaling is now one of several co-equal innovation vectors. Bahai also reflects on the Bell Labs model, TI’s $60B-plus US fab expansion, and the case for a “virtual Bell Labs” that bridges academic curiosity and commercial urgency.

Key Highlights:

Why TI embeds Kilby Labs researchers inside business units from the start, so innovations never expire on a shelf

How TI’s high-voltage program moved from smart grid to EV to AI data centers without changing the underlying technology platform

Why stepping voltage from 400V at the rack down to sub-1V at the processor is the overlooked bottleneck in AI infrastructure

Why transistor scaling is now one innovation vector among several, with materials and packaging becoming co-equal drivers

Why building fabs during a market trough is the only way to have capacity ready when the next peak arrives

A 70-year-old manufacturer’s proprietary test data may be a more defensible AI moat than software capability alone. In this episode of Technovation, Peter High speaks with Udit Mehta, Chief Technology Officer at Simpson Strong-Tie, about building an AI strategy on a foundation of structural engineering expertise. Mehta joined in 2024 from Carrier and Siemens, and has spent two years modernizing the company’s infrastructure, upskilling 1,200-plus employees on AI, and launching an integrated cloud-native software portfolio for component manufacturers. He describes how Simpson’s combination of hardware, software, services, and proprietary test data creates a position pure-play software entrants cannot match, and why AI must augment engineering judgment rather than replace it.

Key Highlights:

Why Simpson’s hardware-plus-software bundling creates an AI moat pure-play entrants structurally cannot replicate

How AI tools assist structural engineers without removing human judgment from high-stakes decisions

Why workflow embeddedness, not technical feasibility, is the real adoption gate in construction

How a three-pillar AI strategy spans individual productivity, enterprise value, and customer growth in parallel

Why business owners, not AI teams, must remain accountable for every AI-enabled workflow outcome

This podcast episode is sponsored by Blitzy. Autonomous software development at enterprise scale.