Chris Greeno, CTO at Fresha, joins Andy Davis to discuss how Fresha approaches real-time data streaming, engineering productivity, AI adoption, Claude in practice, and what it takes to build technology at serious scale.

Chris shares a practical view of what it takes to scale technology inside a high-growth product business, covering Fresha’s approach to near real-time data streaming, architecture decisions, cost trade-offs, and the move from traditional reporting infrastructure towards more responsive data products.

The conversation also explores how AI is changing software engineering. Chris discusses Fresha’s adoption of tools like Claude, Cursor and other AI coding assistants, why developer adoption is often harder than expected, and how engineering leaders need to rethink productivity, safety, observability and platform tooling in an AI-enabled environment.

A particularly strong theme is mindset. Rather than seeing AI as a threat to engineering craft, Chris argues that engineers need to learn how to express their craft differently moving from writing every line of code themselves to guiding, reviewing and orchestrating AI-enabled systems.

In this episode, Andy Davis is joined by Liam Morris-Ellis, Dan Prideaux and Ankit Rawat to discuss where organisations are actually seeing value from AI today.

The conversation moves beyond hype and explores why the biggest opportunity is not just automating individual tasks, but rethinking workflows, scaling productivity and building the right data foundations. The group also discusses AI adoption, trust, governance, data quality, human-in-the-lead thinking, and why successful AI programmes need to bring business, risk, compliance and technology teams together.

A practical discussion for data, analytics, AI and transformation leaders who want to move from experimentation to measurable business value.

In this episode of Databricks Diaries, Daniel Thornton sits down with Andreea Moldovan, Associate Director of Data Science at Sage Publishing, for a candid and wide-ranging conversation about what it actually takes to lead data science and AI in the real world.

Andreea's journey is anything but conventional — starting as a social scientist in Romania, she went on to complete a PhD funded by the Wellcome Trust, before moving through the Financial Conduct Authority, a specialist insurance company, and a price reporting agency, to ultimately find her home in academic publishing.

In this episode, they explore:

• Why a background in social science is one of the most underrated assets in data science and AI
• How to quantify and communicate uncertainty to non-technical stakeholders without losing their trust
• The mindset shift from individual contributor to data science leader — and why it's harder than it looks
• What "outcome-first" thinking really means in practice when building AI solutions
• How generative AI is changing the shape of data science roles — and why the fundamentals haven't changed as much as people think
• The one constant in a decade of working in data science: change

Whether you're an aspiring data leader, a seasoned practitioner, or simply curious about the human side of AI, this is a conversation packed with honest reflections, hard-won lessons, and a refreshing dose of realism about what the next few years hold.