Tech Talks Daily

Is AI quietly pushing us to work alone when creativity has always thrived on collaboration? 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?

Useful Links

Learn More About Nullshot

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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.

What happens when a leader realises that the success of every major initiative, from AI projects to return to office plans, rests on something far deeper than strategy or tools? In my conversation with Phil Gilbert of Irresistible Change, we look at why culture is the deciding factor behind whether transformation takes root or quietly falls apart. Phil has spent a career inside some of the most complex organisations on the planet, and his work at IBM showed that change only becomes real when people want it, when they feel part of it, and when they see its value in their daily work.

Across our conversation, Phil explains how he approached transformation inside a company with nearly four hundred thousand employees without forcing anyone into compliance. Instead of relying on memos or mandates, he treated change like a young startup that needed to earn believers. He focused on proof rather than persuasion, clarity rather than slogans, and an understanding that people respond to meaning, autonomy, and trust. It is a refreshing contrast to the typical corporate playbook that often leans on pressure rather than participation.

We talk through the mindset shifts that helped him rebuild a culture at scale, including treating change like a product with a clear value proposition. Phil shares stories from inside IBM and reflects on why the same lessons now apply across industries. Today's workforce is more informed, more selective, and less willing to accept top down directives that lack substance. His view is that leaders who miss this reality are the ones left wondering why their carefully crafted strategies never quite land the way they expected.

Phil's new book, Irresistible Change, digs into these ideas in detail. Our conversation gives a taste of that thinking and offers practical insight for anyone wrestling with transformation in their own organisation. Culture shapes the outcome of every big shift, whether leaders acknowledge it or not. So how can organisations build change that people choose to be part of, and what might be possible if more leaders approached transformation this way? I would love to hear your thoughts.

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What happens when your entire market disappears overnight? That was the reality facing LoopUp when the pandemic transformed the way the world communicates.

In this episode of Tech Talks Daily, I sit down with Steve Flavell, co-CEO of LoopUp, to talk about how his company turned disruption into a defining moment of reinvention.

LoopUp began in 2003 with a mission to make conference calls less painful. For over a decade, the company grew steadily, even going public on the London Stock Exchange in 2016. But when Teams and Zoom became household names during the pandemic, LoopUp's core business all but vanished.

Faced with that challenge, Steve and his team made a bold pivot, moving into global cloud telephony for Microsoft Teams. That shift didn't just save the company, it transformed it into what Steve now calls the world's most multinational telco, providing enterprise voice services in 136 countries.

Steve shares what it took to steer through that transformation, from managing fivefold surges in traffic to building a scalable global service model. He also reflects on the leadership lessons learned along the way, including the power of persistence, transparent communication, and the strength of his 22-year co-founder partnership with Michael Hughes.

This is a story of resilience, clarity, and strategic courage. For any founder or business leader who's ever faced a market shock or wondered how to evolve when everything changes, Steve's journey offers an honest and inspiring roadmap for rebuilding stronger than before.

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What happens inside a transformation program when every decision must withstand scrutiny, every dependency carries weight, and every undocumented rule inside a legacy system can change the outcome of an entire initiative? That was the starting point for my conversation with Adebimpe Ibosiola, a specialist who has spent her career working in regulated industries where nothing is ever as simple as it looks on paper.

In a space where leaders often feel pressure to modernize at speed, she argues that the real progress comes from slowing down long enough to understand the truth of the systems, people, and cultures already in place.

During the discussion, Adebimpe shared how many organisations walk straight into failure because they begin with visions instead of diagnosis. She explained how hidden logic in old systems, variations in compliance interpretation, and the invisible labour teams carry out daily can derail the best-intentioned roadmap.

Her view is that transformation only becomes possible when leaders commit to technical truth-finding and accept that legacy platforms often contain valuable intelligence worth translating rather than discarding.

It was eye-opening to hear how she decodes behavioural quirks in systems, aligns teams around shared language, and builds processes where correct behaviour becomes the easiest path.

We also spoke about the human journey that accompanies digital change. Adebimpe sees emotional resilience, micro wins, and psychological safety as core components of sustainable progress in any regulated environment.

Her approach blends structure with empathy, especially when teams feel pressure from audit requirements or fear of missteps. She also offered powerful reflections on why collaboration is the real competitive advantage for future professionals and how diversity strengthens decision-making in high-stakes environments.

This conversation stays with you because it reframes transformation through honesty, clarity, and human understanding rather than slogans or promises of fast fixes. It also highlights an emerging truth. Regulated industries are moving toward a future shaped by people who can translate across technology, regulation, and culture rather than those who see transformation as a tooling exercise.

What stood out to you in Adebimpe's perspective? And where do you think regulated organisations should begin if they hope to create change that actually lasts? I would love to hear your thoughts.

Connect with Adebimpe Ibosiola on LinkedIn

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Why do entire organisations invest millions building resilient data centres yet leave their endpoints exposed to outages that can last days? That question kept coming back to me during my conversation with James Millington of IGEL at the Now and Next event, because it highlights a gap that most IT leaders still underestimate.

James walked me through the reality he sees every day. Companies have high availability strategies for their servers, cloud platforms, and networks, yet the devices workers rely on remain the weakest point. When ransomware or system failure hits, the response often involves scrambling for spare laptops, calling suppliers, and hoping inventory exists. As James pointed out in our chat, many firms quietly rely on a handful of unused machines sitting in a cupboard. That approach might have worked a decade ago, but today's threat landscape exposes every delay.

Our discussion centred on IGEL's dual boot approach, a fresh way to recover access within minutes by placing IGEL OS alongside Windows on the same device. Instead of waiting hours or even weeks to rebuild machines, organisations can simply switch to a secure environment that restores access to cloud apps, collaboration tools, and virtual desktops. James shared stories of analysts admitting no comparable solution exists, and of customers having light bulb moments as they calculated the true cost of endpoint recovery. The theme running underneath it all was simple. You cannot coordinate your crisis response unless your people have a working device in their hands. Everything else depends on that.

This episode also reflects a wider shift in how organisations think about resilience. Leaders are beginning to question old assumptions about failover, preparation, and what it takes to keep people productive when attacks or outages strike. The conversations I heard throughout Now and Next showed that businesses are realising the endpoint is no longer a peripheral concern. It is the gateway to every service that keeps a company running. When that gateway fails, everything slows.

James also shared lighter moments from his journey. His career began as a DJ, something he has circled back to at IGEL events, and it was fascinating hearing how skills from that era still show up in his approach to communication and timing. It reminded me how varied experiences shape the leaders driving today's conversations around security, SaaS evolution, Zero Trust, and the growing overlap between IT and operational technology.

So here is my question for you. As cyber risks rise and downtime becomes harder to tolerate, how ready do you feel for the disruption that begins at the endpoint? I would love to hear your thoughts.

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What happens when a founder who built a billion dollar company during a global crisis steps into the centre of industrial AI and begins reshaping how entire organisations think and work? That question sat at the heart of my conversation with Somya Kapoor, CEO of IFS Loops, recorded live on the show floor at IFS Industrial X Unleashed.

Somya's journey carries a level of grit and perspective that shines through every answer. She shared how surviving the Gulf War as a child shaped her instinct to take on the hardest problems in technology. That mindset not only guided her early career at SAP, ServiceNow, and other enterprise giants, it also laid the foundation for Loops, the agentic platform she co-founded in 2020 with a simple scribble on a notepad that eventually grew into one of the most significant acquisitions in the IFS ecosystem.

Her stories about early rejections, the wave of scepticism around AI in the early days, and the first customer conversations held on Zoom during lockdown reveal the human side behind a platform many now take seriously across the industrial world.

Across the episode, Somya explained in plain terms what makes IFS Loops so different. The platform connects data across systems using natural language, helps redesign processes that used to be locked inside individual applications, and introduces digital workers that remove the grunt work from everyday operations. She brought the technology to life with examples that landed with real clarity. From supplier order handling to complex field service tasks, and the now famous Kodiak Gas case where thousands of hours were saved each year, she showed how agentic workflows change what is possible for industrial companies who have spent decades wrestling with fragmented data and rigid processes.

We also talked about the importance of keeping people at the centre of AI driven change. Somya was clear that amplification, not replacement, is the story that matters. The shift requires new skills, new supervision models, and a thoughtful approach to adoption. Her reflections on change management, the energy she felt from customers at the event, and the speed at which leaders now want to move painted a picture of an industry that feels very different from the early days of AI excitement. The hesitation has faded. Curiosity has taken over. Action is starting to follow.

Somya closed with a message aimed at every leader who might still be watching from the sidelines. The technology is real, adoption is accelerating, and the window to learn, experiment, and adapt is narrowing. She believes this is the moment for teams to decide whether they want to lead or be led by others who are moving faster.

As you listen to this conversation, I'd love to hear what stood out for you. Do you feel the same shift in confidence and urgency around industrial AI that Somya described? Let me know your thoughts.

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Have you ever wondered what happens when the browser stops being a simple window to the web and starts becoming the control point for how AI touches every part of enterprise life? That was the starting point for my conversation with Michael Shieh, founder and CEO of Mammoth Cyber.

What followed was a detailed look at why the browser is turning into the foundation of enterprise AI and why the shift is arriving faster than many expect.

Michael shared why employees already spend most of their working lives inside a browser and how this makes it the natural place for AI to support decisions, speed up routine work, and act as the interface between people, applications, and data. But we also spoke about the uncomfortable reality behind that convenience.

When consumer AI browsers rush ahead with features that harvest data or request wide-reaching permissions, the trade off between speed and governance becomes harder to ignore. Michael explained how this gap leaves security teams unable to see where sensitive data is being sent or how shadow AI creeps into daily workflows without oversight.

During our conversation he broke down what makes an enterprise AI browser different. We talked about policy controlled access, device trust, identity federation, and the safeguards that protect AI from hazards like indirect prompt injection. Michael also described how the Mammoth team built a multi layer security model that monitors what the AI can view, what it cannot view, and how data moves across applications in real time. His examples of DLP at the point of use, low friction controls for workers, and granular visibility for security teams showed how the browser is becoming the new enforcement boundary for zero trust.

We also covered the growing tension between traditional access models like VPNs or VDI and the faster, lightweight deployment Mammoth is offering to large enterprises. Hearing Michael explain how some customers replaced heavy remote access stacks in weeks made it clear that this is more than a new product category. It hints at an early move toward AI shaped workflows running directly at the endpoint rather than through centralised infrastructure. As he looked ahead to the next few years, Michael shared why he expects the browser to operate as a kind of operating system for enterprise AI, blending native AI agents, web apps, and policy controls into a single environment.

This episode raises an important question. If the browser becomes the place where AI reads, writes, and interprets information, how should enterprises think about identity, trust, and control when the pace of AI adoption accelerates again next year? I would love to hear your thoughts.

What happens when a former NHL player who once faced Wayne Gretzky ends up running a global data company that sits at the center of the AI boom? That question kept coming back to me as I reconnected with Mike McKee, the CEO of Ataccama, seven years after our last conversation. So much has shifted in the world since then, yet the theme that shaped this discussion felt surprisingly grounded. None of the big promises of AI can take hold unless leaders can rely on the data sitting underneath every system they run.

Mike brings a rare mix of stories and experience to this theme. His journey from the ice to the C suite feels like its own lesson in discipline, teamwork, and patience, and he openly reflects on the way those early years influence how he leads today. But the heart of this conversation sits in the reality he sees inside global enterprises. Everyone is racing to build AI powered services, yet the biggest blockers are messy records, inconsistent metadata, long forgotten databases, and years of quality issues that were never addressed. It is a blunt problem, and Mike explains why the companies winning with AI right now are the ones treating data trust as a foundation rather than an afterthought.

Across the discussion, he shares stories from organisations like T Mobile and Prudential, where millions of records, thousands of systems, and vast volumes of structured and unstructured data must be monitored, understood, and governed in real time. Mike walks through how teams build confidence in their data again, why quality scores matter, and how automation now shapes everything from compliance to customer retention. What stood out most is how quickly the expectations have shifted. Boards and CEOs now treat data as a strategic asset rather than an operational chore, and entire roles have emerged above the chief data officer to steer these programmes.

This episode is also a reminder that AI progress is never only about models or GPUs. Mike pulls back the curtain on why organisations struggle to measure AI readiness, how they can avoid bottlenecks, and what it takes to prioritise the work that actually moves the needle. His point is simple. Without trustworthy data, AI remains a promise rather than a practical tool. With it, businesses can act with confidence, respond faster, and make decisions that genuinely improve outcomes for customers and employees.

So as AI reaches deeper into systems everywhere, how should leaders rethink their approach to data trust, governance, and quality? And if you have been on your own journey with data challenges, where have you seen progress and where are you still stuck? I would love to hear your thoughts.

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