Andrew is the founder of Debugging Leadership, a platform combining a kanban-based leadership program, a library of templates and resources, and add-on extensions to help people become great tech leaders.

Andrew began his career as a software engineer before being promoted into management — and like many engineers making that transition, quickly discovered that leadership is a whole new skillset. He had to figure it out as he went, progressing through roles across consultancies and SaaS companies over more than 15 years leading engineering teams.

That experience shaped everything he now does. Having coached hundreds of managers stepping into leadership for the first time, Andrew kept seeing the same pattern: brilliant engineers promoted without the skills or support to succeed. Debugging Leadership is his answer to that problem — a single platform where new and aspiring tech leaders can learn, build, and practise real leadership skills, with the support they need to make the transition well.

Aubrey Blanche is an expert and executive in equitable people and culture, ethical business operations, and responsible AI. Known as “The Mathpath” — math nerd meets empath — she combines an intersectional, data-driven approach with deep empathy to help organisations build AI systems that serve diverse communities fairly. A recovering American now based in Australia, Aubrey advises a portfolio of organisations on embedding equitable design into their operations, programs, and products. Her work on responsible AI examines how large language models trained on biased datasets risk perpetuating and exacerbating social and institutional biases — and what builders can do about it. She sits on the Board of Directors of the Culture Amp Foundation and Circle of Blue, and her writing and speaking have been featured in Wired, the Wall Street Journal, the Australian Financial Review, and USA Today.

Hamish Songsmith is the founder of ryora.ai, focused on accelerating enterprise AI adoption through practical AI risk visibility, governance, and controls for AI agents. Previously, he was an AI Leader at Optiver, operating in a highly risk-sensitive environment where implementation speed and control discipline must coexist. He brings an implementation-first perspective on why traditional governance models break under agentic systems, and how to align engineering, risk, legal, and security with lightweight frameworks that scale to emergent, user-configured AI capabilities.

Nick Lothian is a AI/ML engineer and technical leader with deep experience in AI, applied machine learning, forecasting, NLP, and privacy preserving technologies. Nick has led or contributed to projects that won the National AI Centre Sprint (2024) and the Red Dot Design Award (2022), and has built AI systems used across industry, government, and national security.

Nick’s background spans CTO, Head of ML, and Head of Product roles. Nick is a co-author on papers in PNAS and ACM, and a co-inventor on an NLP geolocation patent.

Nick also help grow the Australian AI ecosystem as Adelaide Lead for AI.Build Club and Co-Founder of the Artificial Intelligence Collaborative Network.