Is AI quietly pushing us to work alone when creativity has always thrived on collaboration? In this Fast Tracked conversation, I'm joined by Joseph "Coop" Cooper, co-founder of Nullshot, to unpack a different vision for how AI should support creators, builders, and teams. And before any Interstellar fans get too excited, this is not the cinematic space explorer navigating wormholes; this is a serial entrepreneur building something very real on Earth, where conversations turn into working applications in real time.

Coop shares how his journey from modding video games as a child to launching multiple ventures across crypto and developer tools shaped his belief that current AI tools lean too heavily towards individual productivity. He explains the thinking behind Nullshot's jam rooms, where multiple people can co-create with AI in a shared space, instead of building in isolation. We explore how this model encourages quieter voices to contribute, removes the pressure of pitching ideas, and replaces it with live prototypes that speak for themselves.

Alongside the enthusiasm for this collaborative future, Coop also addresses the tougher questions around ownership, fair credit, and how contributions should be recognised without being gamed. There is an honest discussion about whether AI-powered creation lowers barriers for everyone or risks shifting too much power towards the platforms that control it. The balance between opportunity and risk feels central to what Nullshot is attempting to achieve.

As teams, founders, and creators look for better ways to bring ideas to life together, this conversation offers a grounded look at what shared AI creation could mean in practice. Are we ready to move from solo prompts to collective building, and what might that shift say about how we define creativity in the next phase of digital work?

What do you think, could collaborative AI change the way your team builds, and how would you feel about sharing ownership in a live creative space?

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Is the UK quietly slipping into the role of a cautious observer while other nations shape the future of AI with greater confidence and intent?

In this episode of Tech Talks Daily, I sit down with Rav Hayer, Managing Director at ThoughtWorks and Head of BFSI, to explore why our approach to AI regulation may be slowing progress at a time when momentum matters.

We move beyond the headlines of multi-billion pound investment announcements and look at what is really happening on the ground for business leaders trying to innovate in an environment shaped by uncertainty, shifting guidance, and risk aversion.

Throughout our conversation, Rav shares his perspective on how this climate is affecting founders, scaleups, and established enterprises alike. We examine why so much British innovation still finds its way overseas, and what that says about ownership, long-term competitiveness, and the confidence gap holding many organisations back.

I also ask Rav to compare the UK's position with regions such as Singapore, Brazil, and Saudi Arabia, where proactive regulation is being used to encourage innovation rather than create friction. Together, we unpack the hidden costs of ambiguity, from time lost in legal interpretation to talent being drawn away from building meaningful progress at home.

We close the episode on a more human note as Rav reflects on his personal journey, the role his parents played in shaping his work ethic, and the values that continue to guide his leadership today.

As the UK weighs protection against progress, should we continue to step carefully, or is it time to show greater conviction and direction in our AI strategy? I would love to hear your thoughts on where that balance should sit. What do you think, and how should the UK move forward from here?

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What happens when a seasoned finance leader steps into the world of enterprise software and decides to rebuild the financial close with AI at its core?

In my conversation with Darren Heffernan, CEO of Trintech, we look at the shifts taking place inside the office of the CFO and how automation is reshaping a discipline that has relied on spreadsheets and manual routines for generations. Darren's story spans public practice, GE Capital, and twenty years inside Trintech, which gives him a rare view of both the pressure inside finance teams and the opportunities created when workflow, data, and intelligence finally come together.

Across our discussion, Darren explains how Trintech has spent decades refining the financial close by embedding intelligence directly inside the workflow rather than bolting it on. He talks through real examples of AI identifying exceptions, writing rules, scanning volumes of transactions, and reaching back to a human for review so the outcome remains transparent and traceable. His point is that trust and clarity matter as much as speed, especially in a profession where regulators, auditors, and boards expect every action to be explainable. It is a reality check for anyone comparing providers claiming to deliver AI without the decades of grounding needed to understand how finance actually works.

We also talk about the human side of transformation. Darren believes the people who learn to work with AI will thrive, and he pushes back against the idea that automation threatens finance roles. Instead, he sees a future where agents and humans collaborate while accountants focus on judgment, interpretation, and value.

His reflections on leadership, mentorship, humility, and the maturity that comes from doing almost every role inside a company add a personal texture to the story. It is clear that his philosophy of making time count is not a slogan, it is a way of working that shapes how Trintech designs its products and how teams support customers.

As we look toward 2026, Darren shares his view on the next frontier in finance. He describes a future where AI powered workflows not only detect issues but take action, improve continuously, and still respect the need for control. His message is simple.

Finance runs on trust, and AI must strengthen that trust, never weaken it. So how should leaders approach this moment, and what might the financial close look like once AI becomes a reliable partner rather than a confusing buzzword? I would love to hear what you think.