Patty O’Callaghan, Technical Director, Head of AI for the Architecture & Engineering Group at Charles River Laboratories and a Google Developer Expert in AI & Cloud joins us on Tech Paired to unpack what software development looks like in an AI-first world.

This is a real-world conversation about how engineering teams are changing right now: AI writing code, developers evolving into architects, and why governance, guardrails, and AI literacy will define the companies that win in 2026.

Patty shares a mind-blowing example:

A project estimated at 3 developers for 3 months… delivered in 1 week using AI-assisted workflows.

But this isn’t hype. It’s a blueprint for what’s coming.

In this episode, we explore:

• Why developers must adapt now
• How AI is transforming the SDLC (planning → coding → testing → deployment)
• Why testing and validation are more critical than ever
• The risk of “shadow AI” inside organisations
• What good AI governance looks like at enterprise scale
• Why regulated industries are struggling to keep pace
• The shift from SEO to AI discovery and changing web traffic patterns
• How engineering roles are shifting from “coder” to “architect”
• Why Patty believes 2026 could be a “tsunami year” for unprepared teams

If you’re building software, leading engineering teams, hiring developers, or shaping AI strategy this is essential listening.

🎙️ Hosted by Michael Phair and Stuart Alexander, co-founders of Tech Pair a Tech & Change recruitment firm built on real relationships and hands-on expertise.

Tech Pair connects high-performing tech talent with scaling businesses through permanent, contract, RPO, and managed service models. Founder-led. No juniors. Just people who care about people.

Fraser Ferguson - Founder & CEO of KubeNet, serial entrepreneur, and former FTSE 250 board member joins Michael Phair and Stuart Alexander for a wide-ranging conversation on what it really takes to build technology businesses that survive multiple eras of change.

Fraser’s career spans nearly three decades of UK tech evolution: from early internet and the dotcom boom, through telecoms and recruitment, to today’s modern managed services, cloud, cyber, and digital infrastructure landscape. Few leaders have built, scaled, exited, failed, and reinvented themselves as many times and with as much honesty as Fraser.

In this episode, we go beyond surface-level leadership talk and into the realities founders and tech leaders face: timing versus hype, why hard work still matters more than narrative, and why “not getting carried away” might be the most important rule in business.

Fraser shares the story of founding one of Scotland’s earliest internet companies and seeing first-hand how infrastructure constraints, storage costs, and premature markets shaped the dotcom era lessons he draws direct parallels to today’s AI boom. We explore how he scaled a recruitment business to 110 people, why sales engines matter, and how relationships compound over decades. He also opens up about exiting that business for £4.9m, why every founder needs an exit lens (even early), and what happens when acquirers force culture change too fast.

We dig into failure too including a six-figure loss that taught Fraser a brutal lesson about focus, capital discipline, and why you can “run low on money, but you can’t run out of it.”

The conversation then turns to KubeNet and the evolution of a true modern MSP. Fraser explains how the business grew from WLR and ethernet foundations into a fully-fledged MSP and ISP delivering cloud, connectivity, voice, cyber, IoT, and digital transformation services nationwide. He breaks down what real managed service looks like, why many providers are just transactional IT, and how COVID accelerated a structural shift in the MSP market.

For CIOs, CTOs, and tech leaders, Fraser offers clear views on digital transformation: why it must be driven top-down, who should own it, and why fear not technology is the biggest blocker. We explore vendor pressure, subscription economics, accreditation costs, and the hidden financial realities MSPs face as Microsoft, Cisco, VMware, and others rewrite the rules.

AI and automation are a major theme too — not as hype, but as tools to augment engineers, reduce noise, and free teams to work on higher-value problems. Fraser explains why the future of MSP talent is multi-skilled, why rigid role definitions are dying, and how leaders must adapt to a workforce that values flexibility, purpose, and growth differently than previous generations.

Cybersecurity, compliance, and resilience round out the conversation, with Fraser making a strong case that MSPs not traditional cyber consultancies are best positioned to dominate the cyber market over the next 3–5 years. Not because they’re smarter technically, but because they already sit at the intersection of trust, sales, and long-term customer relationships.

We close with Fraser’s advice for anyone building or leading through change in tech today: work hard, don’t quit, don’t be rigid and don’t be afraid to change course when the ground shifts under your feet.

🎙️ Hosted by Michael Phair and Stuart Alexander, co-founders of Tech Pair, a tech & change recruitment firm built on real relationships and hands-on expertise.

Tech Pair is a founder-led video-first technology & change recruitment company partnering with companies across the UK on permanent, contract, RPO, and managed service models.

Andy Doyle, Chief Product & AI Leader, joins Michael Phair and Stuart Alexander to explore how the best tech leaders turn chaos into clarity. Andy shares lessons from scaling SaaS, IoT, and AI ventures, and why structure, empathy, and listening are the hidden forces behind high-performing teams.

We dig into why so many growing companies mistake their product teams for “feature factories,” how AI is misunderstood as a quick ROI machine, and why technology can never be truly neutral. Andy explains how great leaders build feedback loops that connect people, purpose, and progress, and why the best teams learn faster than they deliver.

- Section 1 | Leadership & Product Thinking 0-15min

- Section 2 | AI & Data Strategy | 15-38min

- Section 3 | Purpose, People & Learning | 38-49min

- Section 4 | Closing & Takeaways | 49min – 53min