What happens when AI stops feeling free?

In this episode of The Next Thing Now, Rob and Kev unpack the growing reality behind token pricing, disappearing “all-you-can-eat” AI plans, and why the economics of AI are starting to shift dramatically.

From exploding enterprise AI bills to the sudden rise of local LLMs, they explore the next phase of the AI race: not just intelligence, but compute, infrastructure, and cost.

They cover:

• Why frontier AI companies are killing unlimited plans
• How token costs are becoming the new cloud bill
• Why Macs with huge amounts of RAM are suddenly selling out
• The rise of local LLMs and “bring your own model” architectures
• Why AI usage inside companies is growing faster than costs are falling
• The hidden operational cost of agentic AI workflows
• Why “vibe coding” breaks at enterprise scale
• The growing gap between AI experimentation and AI maturity
• Why organisations now need AI governance, policy and consultancy
• The rise of “flat is the new up” in AI-driven businesses
• Whether frontier models are becoming too expensive to democratise
• And the mystery surrounding Anthropic’s rumoured Mythos model

The future of AI may still be extraordinary.

But it is increasingly clear it will not be cheap.

What is actually changing inside engineering teams?

In this episode of The Next Thing Now, Rob Borley is joined by Gordon Lucas, Group Software Engineering Director at PureGym, to explore how AI is really impacting software engineering.

Away from the hype and headlines, this is a grounded conversation about what is happening inside real teams today.

While AI tools promise dramatic productivity gains, most engineering organisations are still working through a much messier reality. Backlogs still exist. Delivery pressure has not changed. And the day-to-day experience of engineers is evolving in ways that are as human as they are technical.

We explore:

• Why AI has not yet transformed engineering teams in the way people expected
• The growing tension between code as craft and code as output
• How the role of the software engineer is shifting towards orchestration and higher-level thinking
• The leadership challenge of taking teams through rapid, uncertain change
• Whether teams will get smaller, or simply produce more
• What happens to junior engineers in an AI-driven world
• Why decision-making, not coding, is becoming the real bottleneck

This is is a conversation about people, pressure, and the future shape of the profession.

If you are a CIO, CTO, Head of Engineering, or product leader trying to make sense of AI in your organisation, this episode will help you think more clearly about what actually matters next.

In this episode, we’re joined by Simon Ayley, Director of Strategic Growth Partnerships at WRC. Drawing on 30+ years of global industry experience, we explore what AI actually looks like inside critical national infrastructure.

From regulated industries to complex operational environments, AI is no longer theoretical. It is already being tested, challenged, and in some cases embedded into systems that millions of people rely on every day.

We discuss:

• Why innovation inside large, regulated organisations is fundamentally different
• The tension between speed, safety, and accountability
• What it really takes to move from experimentation to production
• How leaders should think about risk, regulation, and responsibility in an AI-driven world

If you are responsible for technology, operations, or strategy in a complex environment, this is a conversation you need to hear.

From freight fleets to finance teams, the data behind emissions reporting is often guesswork. Owen explains why this matters, how inaccurate data undermines trust, and what his team is doing to close the gap with AI-powered precision tools.

If you care about sustainability, data integrity, or how AI can be used for real-world impact, this conversation is for you.

In this episode:

• Why most carbon output reporting is wrong
• How inaccuracy erodes business credibility
• The role of AI in improving emissions measurement
• Why “good enough” data isn’t good enough anymore

Watch now to learn how accuracy can become your most valuable sustainability strategy.

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Hosted on Acast. See acast.com/privacy for more information.

They discuss the implications of these technologies for creativity, the challenges faced by organisations in adopting AI, and the evolving role of CIOs in navigating these changes.

The conversation highlights the tension between innovation and legacy systems, emphasising the importance of governance and the human element in technology adoption.

They discuss the implications of AI on various sectors, particularly focusing on the fear of technological disruption, the impact on employment, and the integration of AI within media companies.

They explore challenges faced by established companies like Apple in adapting to AI advancements, and the potential future of consumer technology as AI continues to evolve.

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For more than 30 years, Matt Barker has worked with leaders, teams, and individuals at moments of pressure, transition, and change, helping humans perform better as their environment shifts around them.

That experience matters now more than ever. As non-human entities enter the workplace, Matt brings a rare lens. Deep expertise in human performance, combined with a clear-eyed view of how machines are reshaping effort, value, and work itself.

This conversation isn’t about productivity or tools. It’s about what high performance means after humans stop being the limiting factor.

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They share personal experiences with various AI models, discussing their strengths and limitations, and explore the future of AI in creative fields.

Rob and Kevin discuss the evolution of AI writing models, focusing on their unique characteristics and capabilities. They explore the importance of memory in AI interactions, how it shapes user relationships, and the implications for data privacy. The concept of digital doppelgangers is introduced, highlighting the potential for AI to act on behalf of users. The discussion also touches on the economics of personal AI ownership and the definition of agents in AI, emphasising the need for clarity in understanding their roles in software development.

The implications of AI in web development, particularly focusing on the ability to clone websites using AI agents are discussed. They explore the ethical concerns surrounding AI-generated content and the potential for scams.

The discussion also touches on emerging AI tools, the evolution of AI in public, and the importance of establishing standards in AI development. They conclude by examining the competitive landscape of AI models and the future of AI integration into everyday applications.

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They explore how AI tools are transforming the workforce, the implications of quantum breakthroughs, and the emergence of new models like diffusion language models and AI agents.

The discussion highlights the convergence of various technologies and the challenges and opportunities they present for the future. In this conversation, Rob and Kev explore the fascinating world of autonomous agents and their implications for the future of work.

They discuss the rise of AI startups leveraging these technologies, the impact on knowledge workers, and the challenges posed by shadow IT and citizen developers.

The conversation also delves into the evolution of AI reasoning and the need for a balance between fast and slow thinking in AI systems.

And of course they teach AI to play Rock, Paper, Scissors

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In this episode of The Next Thing Now, Rob and Kev dive deep into the maturing world of agentic AI — and the quietly powerful new standard driving it: MCP.

We explore:

• Why Canva’s new Claude-powered integration might be the first real MCP breakthrough
• What MCP actually is (with a heating engineer analogy you won’t forget)
• Why the hype cycle has moved on, but the real impact is just beginning
• How OpenAI’s $3B Windsurf deal fell apart — and what Google’s surprise move means for the agentic ecosystem

Plus, a healthy dose of healthy cynicism on Apple’s AI intentions and why everyone’s talking “agentic” now.

Whether you're a product leader, a dev, or just trying to keep up, this is the episode to understand the infrastructure that might define the next decade of software.

🧠 No fluff. Just insight, laughs, and the odd Matrix reference.

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In this episode, we speak with Adrian Defta, founder and CEO of ProveIt, about how AI agents are revolutionising financial services—starting with underserved communities.

Adrian shares the journey behind ProveIt, a bootstrapped startup helping UK-based Romanians navigate financial complaints and reclaim lost money. What began as a TikTok experiment quickly turned into a hands-on support service, and now, with the help of Dootrix and the Agentic Incubator, it's evolving into an AI-powered system using intelligent agents to scale trust, compliance, and customer support.

🔍 Topics Covered:

• The origins of ProveIt and the problem it solves
• Why traditional automation hits a ceiling in financial services
• How agentic AI (like Personal Advisors and Sentinels) work in practice
• Using AI to empower users, not replace them
• What every financial services provider can learn from this model

🎧 Whether you're a fintech founder, product leader, or just AI-curious, this is a must-watch on the future of intelligent automation in regulated industries.

📌 Learn more:

ProveIt: https://proveitweb.co.uk

Adrian Defta: https://www.linkedin.com/in/adriandefta

Dootrix: https://dootrix.com

#AgenticAI #FinancialServices #Startups #ProveIt #AIForGood #DigitalTransformation #CustomerSupport #AIagents #Dootrix #AgenticIncubator #AIinFS

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Is this the moment everything quietly changed?

In this episode of The Next Thing Now, we unpack the restructure of OpenAI, the reworked AGI clause with Microsoft, and why the date 2030 suddenly matters far more than most people realise.

This is not about hype. It’s about incentives, contracts, infrastructure, and the uncomfortable signals buried in plain sight.

We explore:

• Why OpenAI and Microsoft have formally planned for an AGI endgame
• What the AGI clause really means and why independent verification changes everything
• Why AI is no longer just a product decision but an infrastructure race
• How agents, hardware, and energy reshape the future of work
• What leaders are missing while focusing on copilots and prompts

If you think AGI is a distant theoretical debate, this conversation may change your mind.

The shift is not coming loudly. It’s arriving through contracts, compute, and quiet decisions that lock in the next decade.

Pay attention.

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Rob and Kev explore the nature of AI as a predictive tool, drawing parallels between AI behaviour and human cognition. What does it mean as the AI enters the era of experience.

They discuss the potential for AI to learn and adapt like humans, the challenges of integrating AI into organisations, and the critical role of leadership in navigating these changes.

The conversation emphasises the importance of individual responsibility in adapting to the rapidly changing technological environment.

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This week, Rob and Kev unpack one of the strangest and most revealing signals in AI right now.

Anthropic has published a “constitution” for Claude. Not internal policy. Not developer guidelines. A document written for the AI itself, explaining the values it is expected to understand and reason from.

That raises an uncomfortable question.

Why would an AI need a constitution at all?

In this episode, we explore:

• What it means when AI companies talk about “non-human entities”
• The tension between AI constitutions and emerging EU regulation
• Why agentic systems are changing how we work, not just what we build
• The shift from asking AI questions to assigning it work
• Whether this is a technical decision, a cultural signal, or both

This is not a debate about consciousness or sci-fi futures.

It’s about how language, mental models, and responsibility are already changing as AI moves from tool to actor.

If you’re working with AI, building products, or making decisions about how these systems are used in the real world, this conversation matters.

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Hosted on Acast. See acast.com/privacy for more information.

In this episode of The Next Thing Now, Rob Borley, Kevin Smith and Simon Brookes explore the impact of AI on higher education and ask a deeper question: what is university actually for in an age of large language models?

The conversation looks at the future of degrees, the changing value of knowledge, the limits of traditional coursework, and why judgment, discernment and the application of knowledge may matter more than ever.

This is not a discussion about hype. It is a serious look at what happens when one of society’s most established institutions is forced to rethink its role.

In this episode:

• Will AI change university forever?
• Can essays still prove learning?
• What becomes valuable when knowledge is abundant?
• Why human judgment may matter more in an AI-shaped world
• What higher education may need to become next

Watch now and join the conversation.

#AI #HigherEducation #University #EdTech #FutureOfWork #TheNextThingNow #Dootrix #ArtificialIntelligence #Education

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They explore the complexities of traditional software engineering, the importance of maintaining quality and safety in software, and the balance between rapid prototyping and thorough development. 

Thinking fast, build slow. This is Vibe Coding for grown-ups. This is how professional should use the new wave of tools and techniques. And what to avoid.

The discussion also touches on the need for new training approaches for developers, the integration of AI in software development, and the rapid pace of technological change. 

The conversation also explores the dual nature of OpenAI, discussing its evolution from a research-focused organisation to a commercial entity. The speakers delve into the complexities of OpenAI's model naming conventions, the emergence of agentic models, and the impact of AI on creativity and development. 

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Ang emphasises the need for organisations to build trust, adapt to generational differences, and foster resilience among employees. The conversation also explores the challenges of remote work, the role of leadership in navigating change, and the future of work in a technology-driven environment.

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They emphasise the urgency for businesses to adopt AI technologies, likening it to the transformative impact of the internet and electricity.

The discussion also highlights the challenges organisations face in adapting to these changes and the importance of taking employees on the journey of AI integration.

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A year ago, AI was helping engineers write code.

Now, agents are building real enterprise software.

In this episode of The Next Thing Now, we unpack what has changed and why it matters. This is not another conversation about copilots or productivity boosts. This is about agentic platforms that can reason over requirements, generate architecture, write services, refactor systems, and ship meaningful functionality with minimal human intervention.

But there is a catch.

Agents can write code. They do not carry accountability.

We explore:

• The shift from AI coding assistant to agentic execution
• Why complex systems still require architectural judgement
• How senior engineers are moving from builders to orchestrators
• What this means for CIOs and technology leaders under pressure
• Why enterprise software delivery is about to be structurally redefined

If you are a CIO, CTO, Engineering Director, or product leader trying to understand what agentic development really means in production, this conversation is for you.

This is not theory. It is based on real experimentation inside live environments.

Agents are building software now.

The question is whether you are ready to orchestrate them.

Subscribe for more conversations at the intersection of emerging technology, disruptive business models, and the leaders shaping what comes next.

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They discuss the potential dystopian future of AI, the rise of wearable technology, and the evolving expectations surrounding AI development. The conversation highlights the challenges and adaptations users face as they navigate the rapidly changing landscape of AI tools and their applications.

In this conversation, Kevin and Rob explore the evolving landscape of AI adoption and its implications for the workforce. They discuss the challenges organisations face in integrating AI technologies, the potential transformation of job roles, and the importance of adapting interview techniques to identify candidates who can thrive in an AI-centric environment.

The discussion also touches on the quest for enhanced virtual presence in remote interactions, highlighting the need for innovative solutions to improve engagement and collaboration.

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