Find out more about Marian Kamenistak and his work with engineering leaders:https://www.marian.coach/Explore the Engineering Leaders Community:https://www.engineeringleaders.io/What happens when your best engineer becomes a leader but can’t let go of the keyboard?We often promote our strongest technical people into leadership roles. But being a brilliant engineer doesn’t necessarily make someone a brilliant leader, and moving into management isn’t always the right next step for them.In this episode of The Common Sense CTO Podcast, I’m joined by Marian Kamenistak, fractional CTO, mentor and founder of the Engineering Leaders Community. Marian has mentored more than 300 technology leaders across 17 countries and brings his experience of scaling engineering teams to a conversation about the transition from technical expert to leader.We discuss why that transition can be so difficult, how businesses can give talented engineers room to progress without pushing them into management, and what leaders can do to prepare the next generation before they hand over the job.We also explore the challenge of being accountable for work you’re no longer doing yourself, the importance of developing your own replacement, and how AI might change the skills technology leaders need in the future.In this conversation:00:00 Introduction01:08 Meet Marian03:18 The challenges of promoting technical leaders07:31 Do engineers have to become managers to progress?10:16 How hands-on should a CTO be?13:57 Why letting go of the keyboard is so difficult17:20 Finding the right leadership role for your strengths20:52 Supporting newly promoted leaders21:57 Succession planning and developing future leaders24:14 Rethinking performance appraisals28:51 How to prepare a brilliant engineer for leadership33:32 Giving people responsibility and support35:36 Accountability without direct control37:55 Individual performance and team success40:23 The future of engineering leadership and AI46:09 Closing thoughtsFind out more about The Common Sense CTOhttps://commonsensecto.com/If you enjoyed the conversation, please subscribe and share it with someone who is developing their technology leadership career.#TechnologyLeadership #CTO #EngineeringLeadership

AI is changing how we discover, design and deliver products. But if we can build software faster, how do we make sure we’re building the right things?In this episode of The Common Sense CTO podcast, I’m joined by Anna Dick, who leads product and technology at Capsule, to explore how her team is using AI across the product lifecycle.Anna shares practical experience of bringing customer insight together, creating richer prototypes and involving engineers earlier in product discovery. We discuss how those changes affect decisions, expectations and the people doing the work.We also explore• Why faster development makes good product judgement more important • How realistic prototypes can create unrealistic expectations • Using a shared “product brain” to make business knowledge more accessible • Why AI guardrails are as much about people as technology • How roles are changing while specialist expertise remains valuable • Giving people time back without assuming everyone enjoys the same work • Whether customers want change as quickly as we can deliver it It’s a conversation grounded in what Anna and her team are doing, what they’re learning and where they want to go next.Connect with Anna on LinkedIn https://www.linkedin.com/in/anna-dick-b4bb434Find more from The Common Sense CTO https://www.commonsensecto.comTry the free Technology Confidence Checkerhttps://www.commonsensecto.com/confidence-checkerIf you enjoyed the conversation, subscribe for more practical perspectives on technology, leadership and the businesses they support.

Have we reached the point where AI can genuinely build software without developers writing code?

In this episode of The Common Sense CTO Podcast, Matt Stephenson sits down with digital transformation and AI specialist Mark Strefford to explore a question that is rapidly moving from theory to practice: what happens when software development becomes an exercise in specification, validation and orchestration rather than programming?

Matt has been openly sceptical about claims that AI will replace experienced engineers. Mark, meanwhile, has spent the last two years building products almost entirely through AI-driven workflows. Their conversation reveals just how quickly the landscape is changing.

Together they discuss:

• Why AI coding has progressed dramatically in the last six months
• Whether developers are becoming designers, reviewers and orchestrators rather than coders
• The emergence of AI agents acting as members of a software delivery team
• Building AI-native software delivery lifecycles with automated governance and review processes
• Accountability, quality assurance and human oversight in AI-generated systems
• Why acceptance criteria and engineering discipline may matter more than ever
• The economics of AI-assisted development and the reality of token-based pricing
• Local models, edge AI and whether organisations will eventually run their own AI infrastructure
• The uncomfortable question of who is accountable when AI-generated software fails

Mark shares practical examples from his own workflow, including autonomous coding agents, AI-driven testing, multi-agent review processes and the surprising extent to which he now judges software by outcomes rather than source code.

For Matt, the conversation represents a shift in perspective. While many of the concerns around quality, governance and accountability remain, it is becoming increasingly difficult to dismiss the possibility that AI-assisted engineering is evolving into something much bigger.

If you're a CTO, engineering leader, architect, product professional or experienced developer trying to separate hype from reality, this episode offers an honest and nuanced discussion about where software engineering may be heading next.

Perhaps the biggest question isn't whether AI can write code.

It's whether our delivery processes, governance models and organisational structures are ready for what comes after that.