2026-06-06 –, Grand Hall 1
Every team runs on unwritten rules. Habits that shape how decisions get made, how failure is handled, and what is safe to say. This talk provides a framework for reading those rules, understanding the collective self-image that drives team behaviour, and influencing culture from any position. With a look at how AI adoption is forming new rules in real-time, you will leave knowing how to decode the system you are in and start shifting it.
Most talks on culture are aimed at managers, the people with formal authority to change things. But data scientists, engineers, and ML practitioners navigate team dynamics every day, often without that authority. This talk is for you: how to read the unwritten rules, understand what drives them, and shift them from any position.
The central idea is simple. Team culture isn't what is on the company wiki. It is a paradigm or a system of habits that shapes behaviour more powerfully than any stated policy. Beneath those habits sits the team's collective self-image: the shared belief about "who we are" and "what's possible." That self-image sets the upper limit of performance. A team that sees itself as "always firefighting" will keep firefighting, even when the fires are out.
The good news: you can influence this from any seat. Not through announcements, but through consistent action.
I will cover how to read the paradigm, the signals that reveal real culture. How failure is handled. Who speaks first. What gets celebrated versus quietly ignored. The stories that get repeated. These are data points that tell you what the team actually believes.
I will also share specific questions you can use in interviews to decode culture before you join. Questions about past failures, who thrives versus struggles, how disagreement is managed. The answers matter less than how people respond: the hesitation, the energy, the discomfort.
There is a trap worth knowing about. The longer you stay, the less you see. What felt strange in week one feels normal by month three. Your first weeks are a window of clarity. I will cover how to use it before it closes.
The core of the talk is about influence. Three ways are available to anyone: modelling the behaviour you want to see, naming what others leave unspoken, and holding a different picture of what's possible. This isn't positive thinking. It is praxis, which is integrating belief with behaviour through consistent action.
Finally, I will use AI adoption as an example. AI tools are shifting work toward individual tasks while new unwritten rules form around their use. Who is using AI openly? Who is hiding it? What is the unspoken agreement about quality and trust? This is a chance to watch a paradigm form in real-time and shape it before it solidifies.
This is a practical talk, not a tutorial. The target audience is data scientists, data engineers, and ML practitioners at any level and especially if you'] have recently joined a team, are navigating a tricky dynamic, or want more impact without moving into management.
You will leave with a framework for reading team culture, understanding what drives it, and influencing it through consistent behaviour starting the day you get back to work.
I am Chief Architect at Engineering is Easy, working in aerospace and defence consulting. I hold a PhD in environmental and geospatial modelling, and I have spent over 20 years across climate research, data science, AI, and developer advocacy.
I also run Living is Easy, where I work as a certified mindset consultant focused on how habits, self-image, and mental programming drive results. That work has given me a deep understanding of how paradigms shape behaviour for both individuals and teams.