Tech Talks Daily

What if the biggest barrier to successful AI isn't the model itself, but the lack of context behind every decision your teams make? As AI agents become more capable, how do organisations ensure they understand the people, projects, documentation, and history that shape real work?
In this episode of Tech Talks Daily, recorded at Team '26, I'm joined by Taroon Mandhana, CTO of AI and Teamwork at Atlassian. His responsibilities span engineering for products including Jira, Confluence, Loom, and Trello, alongside the company's AI strategy and the development of Rovo. Our conversation explores why Atlassian believes AI should become a teammate rather than simply another chatbot.
Taroon explains why enterprise context has become one of the most valuable assets in the AI era. While today's foundation models continue to improve at an incredible pace, they still lack the organisational knowledge that human teams naturally accumulate over time. Atlassian's Teamwork Graph aims to bridge that gap by connecting people, projects, documentation, code, goals, and conversations into a living knowledge network that AI agents can use to produce more accurate, relevant outcomes.
We also discuss why Atlassian has chosen an open approach, making its Teamwork Graph available through technologies such as MCP rather than limiting it to its own AI products. Taroon shares why interoperability will become increasingly important as businesses adopt multiple AI platforms and why organisations should be free to use the agents that best suit their needs without losing access to valuable business context.
Another fascinating part of our conversation focuses on how Atlassian's own engineering teams are changing the way they build software. Smaller teams, tighter collaboration, AI-assisted development, and faster iteration cycles are allowing products to move from concept to release in weeks rather than months. Taroon explains how AI is changing both software development and the structure of engineering teams themselves.
We also examine where AI should take ownership of work inside platforms like Jira, where human judgement remains essential, and why successful organisations are treating AI adoption as an ongoing product journey rather than a one-time technology deployment.
If your business is looking beyond isolated AI experiments and wondering how to build AI into everyday work, this conversation offers valuable insight into the role context, openness, and organisational change will play in the next generation of enterprise software.
As AI becomes part of every workflow, what do you think will become the real competitive advantage: better models, or better organisational knowledge?

What happens when customer service moves beyond answering questions and starts anticipating needs, coordinating actions, and resolving problems with AI? And what does that mean for the future of the contact center?
In this episode of Tech Talks Daily, I'm joined by Jonathan Barouch, Vice President and General Manager of Contact Center at Zendesk, to discuss the company's vision for the next generation of customer experience following the integration of Local Measure into the Zendesk platform.
Jonathan explains why the contact center is entering a new chapter, where AI is becoming part of every interaction rather than existing as a standalone feature. We discuss the announcements from Relate 2026 and how Zendesk is bringing together customer service, voice, automation, and AI to create a more connected experience for both customers and agents.
A major part of our conversation focuses on the acquisition and integration of Local Measure. Jonathan shares why bringing enterprise voice capabilities into the Zendesk platform creates new opportunities for organisations looking to modernise their contact centres without adding unnecessary complexity. Rather than treating voice as a separate channel, Zendesk is building an experience where every customer interaction contributes to a complete understanding of the customer journey.
We also discuss how AI is changing the day-to-day reality for contact center teams. Instead of replacing people, Jonathan explains how AI can remove repetitive work, surface the right information at the right time, and allow agents to spend more time solving problems that require empathy, judgement, and human conversation.
Looking further ahead, we examine what the future of Contact Center as a Service could look like as AI agents become increasingly capable. Jonathan shares his perspective on how businesses should prepare for this shift, where automation fits alongside human expertise, and why success will depend on creating experiences that customers genuinely value rather than simply reducing costs.
If your organisation is rethinking customer service, investing in AI, or planning the next stage of its contact center strategy, this conversation offers practical insight into where the industry is heading and what business leaders should be thinking about today.
What role do you think AI should play in customer service? Where should businesses draw the line between automation and the human touch?

What happens when a company best known for garage door openers decides to compete with the biggest names in smart home technology? Can a business built on hardware reinvent itself as an AI-powered software company without losing the trust that made it successful in the first place?
In this episode of Tech Talks Daily, I welcome Jeff Meredith, CEO of Chamberlain Group, to discuss one of the more fascinating business transformations happening in the technology sector. Chamberlain Group has spent more than 70 years building products that millions of homeowners rely on every day. Under Jeff's leadership, the company has expanded that heritage into intelligent access, creating a connected ecosystem through the myQ platform that now serves more than 15 million users worldwide.
Jeff shares why leaving a successful career at Lenovo to join what many dismissed as "a garage door company" became the biggest leadership challenge of his career. Rather than following the comfortable route, he chose what he describes as the hardest path, helping reshape an established manufacturer into a technology business built around software, data, AI, and recurring customer relationships.
Our conversation looks at what it really takes to attract software engineers, AI specialists, and data scientists into a company with an industrial heritage. Jeff explains why interesting problems often matter more than fashionable brands, and how Chamberlain Group's combination of trusted hardware, millions of existing customers, and ambitious software projects created an environment that appealed to top technical talent.
We also spend time discussing leadership. Jeff believes the best leaders teach rather than direct, preferring to stand at the whiteboard alongside colleagues instead of issuing instructions from the corner office. He speaks openly about mistakes he made when joining the business, why vulnerability has strengthened trust across the organisation, and why admitting when you're wrong can become a strength rather than a weakness.
Looking ahead, Jeff explains how AI could reshape intelligent access, moving beyond notifications to systems that understand patterns, recognise context, and help people secure their homes and businesses in smarter ways. Instead of viewing AI as technology searching for a purpose, he believes access control offers one of its most practical everyday applications.
From leadership philosophy and organisational change to connected homes, AI, and the future of intelligent access, this conversation offers valuable lessons for anyone leading transformation inside an established business.
What part of Jeff's story resonated most with you? Is the biggest challenge in business transformation changing the technology, or changing the mindset of the people building it?

What happens when the biggest AI security risk isn't the technology itself, but the people using it?
In this episode, I sit down with Cormac Whelan, CEO of Nitro Software, to discuss why organizations need to rethink their approach to AI adoption. With research showing that 68% of C-suite executives are bypassing approved AI tools in favor of their own, we explore how an "ask forgiveness, not permission" culture is creating new security and compliance challenges for businesses around the world.
Cormac shares why successful AI adoption begins with business outcomes rather than the latest model or headline-grabbing announcement. Drawing on his experience leading Nitro and previously building an AI company acquired by Apple, he explains why AI should be an enabler rather than the destination, and why organizations that focus on trust, transparency, and practical business value will ultimately pull ahead.
Our conversation also looks at why documents, contracts, PDFs, and e-signatures have become some of the most overlooked parts of the enterprise AI conversation. As AI systems increasingly interact with sensitive business information, protecting document workflows is becoming just as important as securing networks and endpoints.
We also discuss how European privacy standards are becoming a competitive advantage rather than simply another compliance requirement, how to separate genuine AI innovation from expensive security theater, and why AI should quietly improve the way people work instead of becoming the center of attention.
If you're trying to balance AI innovation with security, governance, and business value, this conversation offers practical advice without getting lost in the hype. After listening, I'd love to hear your thoughts. Is your organization focusing on outcomes first, or is it still chasing the latest AI headline?

What if the biggest weakness in cybersecurity isn't the technology, but the way defenders communicate with each other?
Cybercriminals openly exchange techniques, vulnerabilities, and attack methods, constantly learning from one another. Meanwhile, many organizations remain reluctant to share details of breaches, investigations, or lessons learned. In this episode, I sit down with Lee Sult, Chief Investigator at Binalyze, to discuss why that imbalance is creating an advantage for attackers and what the industry can do to change it.
Drawing on almost two decades in digital forensics and incident response, including work with Palantir, law enforcement agencies, and government organizations, Lee explains why cybersecurity should learn from industries such as aviation and emergency services, where every major incident becomes an opportunity for everyone to improve. We discuss why incident response needs to move beyond reacting to alerts, how proactive threat hunting can reduce attacker dwell time, and why repeatable investigation processes are becoming just as important as the security tools themselves.
We also explore the growing influence of AI, not because it is making attackers dramatically smarter, but because it is lowering the barrier to entry and increasing the volume of attacks security teams must handle. Lee shares why automation is becoming essential for investigators, how organizations can move from hours to minutes when responding to threats, and why cybersecurity is steadily becoming a boardroom issue rather than simply an IT concern.
If cybersecurity is truly an information war, what would happen if defenders became just as collaborative as the attackers they face every day? After listening, I'd love to hear your thoughts. Should organizations be more open about cyber incidents if it helps strengthen security for everyone?