What happens when AI stops talking and starts working, and who really owns the value it creates?

In this episode of Tech Talks Daily, I'm joined by Sina Yamani, founder and CEO of Action Model, for a conversation that cuts straight to one of the biggest questions hanging over the future of artificial intelligence.

As AI systems learn to see screens, click buttons, and complete tasks the way humans do, power and wealth are concentrating fast. Sina argues that this shift is happening far quicker than most people realize, and that the current ownership model leaves everyday users with little say and even less upside.

Sina shares the thinking behind Action Model, a community-owned approach to autonomous AI that challenges the idea that automation must sit in the hands of a few giant firms. We unpack the concept of

Large Action Models, AI systems trained to perform real online workflows rather than generate text, and why this next phase of AI demands a very different kind of training data. Instead of scraping the internet in the background, Action Model invites users to contribute actively, rewarding them for helping train systems that can navigate software, dashboards, and tools just as a human worker would.

We also explore ActionFi, the platform's outcome-based reward layer, and why Sina believes attention-based incentives have quietly broken trust across Web3. Rather than paying for likes or impressions, ActionFi focuses on verifying real actions across the open web, even when no APIs or integrations exist. That raises obvious questions around security and privacy.

This conversation does not shy away from the uncomfortable parts. We talk openly about job displacement, the economic reality facing businesses, and why automation is unlikely to slow down. Sina argues that resisting change is futile, but shaping who benefits from it remains possible. He also reflects on lessons from his earlier fintech exit and how movements grow when people feel they are pushing back against an unfair system.

By the end of the episode, we look ahead to a future where much of today's computer-based work disappears and ask what success and failure might look like for a community-owned AI model operating at scale.

If AI is going to run more of the internet on our behalf, should the people training it have a stake in what it becomes, and would you trust an AI ecosystem owned by its users rather than a handful of billionaires?

Useful Links

• Connect with Sina Yamani on LinkedIn or X
• Learn more about the Action Model
• Follow on X
• Learn more about the Action Model browser extension
• Check out the whitelabel integration docs
• Join their Waitlist
• Join their Discord community

Thanks to our sponsors, Alcor, for supporting the show.

What does it really take to remove decades of technical debt without breaking the systems that still keep the business running?

In this episode of Tech Talks Daily, I sit down with Pegasystems leaders Dan Kasun, Head of Global Partner Ecosystem, and John Higgins, Chief of Client and Partner Success, to unpack why legacy modernization has reached a breaking point, and why AI is forcing enterprises to rethink how software is designed, sold, and delivered.

Our conversation goes beyond surface-level AI promises and gets into the practical reality of transformation, partner economics, and what actually delivers measurable outcomes.

We explore how Pega's AI-powered Blueprint is changing the entry point to enterprise-grade workflows, turning what used to be long, expensive discovery phases into fast, collaborative design moments that business and technology teams can engage with together.

Dan and John explain why the old "wrap and renew" approach to legacy systems is quietly compounding technical debt, and why reimagining workflows from the ground up is becoming essential for organizations that want to move toward agentic automation with confidence.

The discussion also dives into Pega's deep collaboration with Amazon Web Services, including how tools like AWS Transform and Blueprint work together to accelerate modernization at scale.

We talk candidly about the evolving role of partners, why the idea of partners as an extension of a sales force is outdated, and how marketplaces are reshaping buying, building, and operating enterprise software. Along the way, we tackle some uncomfortable truths about AI hype, technical debt, and why adding another layer of technology rarely fixes the real problem.

This is an episode for anyone grappling with legacy systems, skeptical of quick-fix AI strategies, or rethinking how partner ecosystems need to operate in a world where speed, clarity, and accountability matter more than ever.

As enterprises move toward multi-vendor, agent-driven environments, are we finally ready to retire legacy thinking along with legacy systems, or are we still finding new ways to delay the inevitable?

Useful Links

• Connect with Dan Kasun
• Connect with John Higgins
• Learn more about Pega Blueprint

Thanks to our sponsors, Alcor, for supporting the show.

What does it really take to move AI from proof-of-concept to something that delivers value at scale?

In this episode of Tech Talks Daily, I'm joined by Simon Pettit, Area Vice President for the UK and Ireland at UiPath, for a grounded conversation about what is actually happening inside enterprises as AI and automation move beyond experimentation.

Simon brings a refreshingly practical perspective shaped by an unconventional career path that spans the Royal Navy, nearly two decades at NetApp, and more than seven years at UiPath. We talk about why the UK and Ireland remain a strategic region for global technology adoption, how London continues to play a central role for companies expanding into Europe, and why AI momentum in the region is very real despite the broader economic noise.

A big part of our discussion focuses on why so many organizations are stuck in pilot mode. Simon explains how hype, fragmented experimentation, and poor qualification of use cases often slow progress, while successful teams take a very different approach. He shares real examples of automation already delivering measurable outcomes, from long-running public sector programs to newer agent-driven workflows that are now moving into production after clear ROI validation.

We also explore where the next wave of challenges is emerging. As agentic AI becomes easier for anyone to create, Simon draws a direct parallel to the early days of cloud computing and VM sprawl. Visibility, orchestration, and cost control are becoming just as important as innovation itself. Without them, organizations risk losing control of workflows, spend, and accountability as agents multiply across the business.

Looking ahead, Simon outlines why AI success will depend on ecosystems rather than single platforms. Partnerships, vertical solutions, and the ability to swap technologies as the market evolves will shape how enterprises scale responsibly. From automation in software testing to cross-functional demand coming from HR, finance, and operations, this conversation captures where AI is delivering today and where the real work still lies.

If you're trying to separate AI momentum from AI noise, this episode offers a clear, experience-led view of what it takes to turn potential into progress. What would need to change inside your organization to move from pilots to production with confidence?

Useful Links

• Learn more about Simon Pettit
• Connect with UiPath
• Follow on LinkedIn

Thanks to our sponsors, Alcor, for supporting the show.