For more on building AI products and careers, along with early course announcement and special pricing, subscribe to the AI Career Boost mailing list at https://aicareerboost.com/interested

THE GUEST

Nico Posner, VP of Product Management at Q3D Sensing and a veteran product leader whose career spans some of the world’s most innovative companies, including LinkedIn, eBay, Clover, and Xero.

Nico has spent years leading technology and AI-driven product innovation across industries, helping scale products from early-stage concepts to global adoption. At Q3D Sensing, he’s now focused on the next frontier of AI: capturing and digitizing the real world through advanced LiDAR and spatial sensing technology.

With deep experience in AI, predictive analytics, product strategy, and emerging technology, Nico brings a unique perspective on how real-world data is becoming the foundation for the next generation of AI systems, robotics, construction tech, digital twins, and spatial computing.

THE SUMMARY

What happens when AI moves beyond text and begins interacting with the physical world?

Nico Posner breaks down why the future of AI depends on accurate, real-world spatial data — and how LiDAR technology is unlocking entirely new possibilities across industries.

The conversation explores the launch of Q3D Sensing’s new OraGo 3D reality capture LiDAR sensor and why accessible, affordable spatial sensing could become a foundational layer for AI-powered workflows. Nico explains how modern LiDAR systems work, why current enterprise solutions are often too expensive or impractical, and how new tools are democratizing access to high-quality 3D data capture.

Polly and Nico also dive into:

• The growing role of real-world data in AI systems
• How LiDAR enables digital twins, robotics, construction intelligence, and spatial computing
• The difference between consumer-grade scanning and professional LiDAR systems
• Why edge processing and on-device rendering matter for enterprise workflows
• How AI is accelerating innovation, product strategy, research, and operations
• The future of AI-powered infrastructure, warehouses, and physical environments
• Lessons from building products at both startups and global technology companies
• The importance of solving real customer pain points when developing AI products

This is a fascinating look at the intersection of AI, hardware, spatial computing, and product innovation — and why the next wave of AI breakthroughs may depend less on prompts and more on understanding the physical world around us.

THE SHOW

Weekly conversations with the AI’s top product leaders. Join Polly Allen as she discovers the paths to success in the world of AI.

THE LINKS

Have a question you want us to answer? Send it through to support@aicareerboost.com

Nico Posner
LinkedIn: https://www.linkedin.com/in/nicoposner/

Q3D Sensing Website: https://www.q3dsensing.com/

Q3D Sensing LinkedIn: https://www.linkedin.com/company/q3d-sensing/

My links
LinkedIn: ⁠https://www.linkedin.com/in/pollymallen/⁠

AI Career Boost: ⁠https://www.aicareerboost.com/⁠

For more on building AI products and careers, along with early course announcement and special pricing, subscribe to the AI Career Boost mailing list at https://aicareerboost.com/interested

THE GUEST

Bill Takacs is a veteran product executive with over two decades of experience building and scaling platforms across SaaS, security, analytics, AI, and enterprise infrastructure. He’s currently VP of Product at MTrain, where he leads product and engineering—growing the business past $10M+ ARR, cutting platform costs by 50%, and doubling team velocity. A proven zero-to-one operator and turnaround leader, Bill’s background includes roles at Salesforce, AOL Instant Messenger, O’Reilly Media, HP, and multiple venture-backed companies. He’s also a former U.S. Army Ranger and Captain, bringing a unique blend of disciplined execution and bold innovation. In this episode, we’ll dive into operationalizing AI in enterprise products, scaling efficiently, and leading high-impact product teams.

THE SUMMARY

If you’re not adopting AI, you’re already behind: This isn’t incremental tech — it’s a step-change. Companies that treat AI as a “nice-to-have” efficiency tool will lose to AI-native competitors with lower costs, faster execution, and fundamentally different products. Survival depends on embracing it now.

Most companies are using AI wrong and too safely: Simply making existing processes faster is the least imaginative use of AI. The real opportunity is redesigning workflows and products entirely — not just layering AI on top of old systems.

Start with workflows, not hype: The smartest entry point isn’t “build something cool with AI” — it’s identifying repetitive, structured tasks and automating them. Map the process step-by-step, then apply AI where it actually removes friction.

Agents are coming faster than most people think: We’re moving toward a world where teams manage AI agents that do the work — writing code, running workflows, even transacting. The shift from “tools” to “autonomous workers” is already underway.

Roles are collapsing — not just evolving: AI is blurring boundaries between product, design, and engineering. Tasks that once required multiple roles can now be done by one person with AI support. This will fundamentally reshape team structures.

No one actually knows the playbook yet: There is no “best practice” right now. Waiting for clarity is a losing strategy — the only way forward is experimentation, failure, and iteration.

AI-first companies will outpace incumbents: Startups built natively with AI will have massive advantages: smaller teams, faster builds, and radically lower costs. Incumbents must actively disrupt themselves or risk irrelevance.

The simplest advice: just start: Don’t overthink it. Pick a painful, repetitive task, try to automate it, and learn by doing. Momentum beats strategy at this stage.

THE SHOW

Weekly conversations with the AI’s top product leaders. Join Polly Allen as she discovers the paths to success in the world of AI.

THE LINKS

Have a question you want us to answer? Send it through to support@aicareerboost.com

Bill Takacs

LinkedIn: https://www.linkedin.com/in/btakacs/

My links

LinkedIn: ⁠https://www.linkedin.com/in/pollymallen/⁠

AI Career Boost: ⁠https://www.aicareerboost.com/⁠

For more on building AI products and careers, along with early course announcement and special pricing, subscribe to the AI Career Boost mailing list at https://aicareerboost.com/interested

THE GUEST

Shampa Banerjee, PhD, is a powerhouse product leader who has scaled global digital platforms from scrappy startups into billion-dollar growth engines. As EVP and Chief Product Officer of Pluto TV at Paramount, she helped drive the platform from 20 million to over 50 million monthly active users while accelerating revenue to $1 billion ahead of schedule, expanding the service across Latin America and Europe. Prior to that, Shampa led the growth of Eros Now to 150 million users across 135 countries, delivering an extraordinary 240% year-over-year subscription growth. Over the course of her career, she’s served as both CPO and CTO across venture-backed startups and Fortune 500 companies, building world-class product, engineering, and data teams from the ground up. Trained as a physicist, Shampa brings a rare ability to recognize patterns in complex systems—pairing bold product vision with disciplined experimentation. Today, she advises growth-stage startups and global enterprises on scaling impact through AI, product strategy, and global go-to-market leadership. And in this episode, we’re diving into what it takes to scale digital platforms globally, the leadership behind building billion-dollar product ecosystems, and how AI and data are shaping the future of product strategy.

THE SUMMARY

AI adoption is failing in many companies — and nobody wants to talk about it: Many organisations are blindly adding AI because leadership mandates it, not because it solves a real problem. The smarter approach is to first ask whether AI is even the right solution. If it doesn’t improve growth, retention, or economics, it’s just expensive hype layered on top of existing systems.

Understanding how AI works matters more than just using it: Treating AI like a magical tool leads to frustration when it produces imperfect results. Modern AI systems are probabilistic by nature — meaning uncertainty is built into how they work. Leaders who understand this design guardrails, human-in-the-loop processes, and better prompts instead of dismissing the technology as “wrong.”

AI should drive growth — not just cost cutting: Too many companies frame AI purely as a way to reduce headcount or operational costs. The real opportunity is using it to expand capabilities, unlock new products, and scale output. Businesses that only focus on savings risk shrinking themselves instead of multiplying their impact.

The AI transformation requires three shifts: People, Product, and Process: The biggest challenge isn’t the technology — it’s organisational change. Teams must get comfortable with uncertainty, rethink what products they should build, and redesign processes that were inherited from the manufacturing era. Companies that only upgrade tools without updating culture and workflows will stall.

The AI revolution mirrors the early internet — but at a much faster speed: Just like the dot-com era, many experiments will fail, but the underlying ideas will eventually reshape industries. Concepts like Webvan looked wrong in the early 2000s, yet later became the foundation for companies like Instacart. Today’s AI experiments may look messy, but they are laying the groundwork for tomorrow’s dominant platforms.

Technical credibility still matters for leaders: Leaders who understand the mechanics behind technology gain trust with engineering teams and make better strategic decisions. Getting hands-on — even building a small prototype — helps leaders translate between executives and technical teams and prevents unrealistic expectations about what technology can actually do.

Hands-on experimentation is the fastest way to understand AI