All Episodes
Displaying 1 - 20 of 128 in total
Episode 128: [Value Boost] The Three Types of Memory Every AI Agent Needs
One of the most frustrating things about working with AI is when it seems to suddenly forget everything it knew about you and your work. This is annoying when using AI...
Episode 127: From Algorithms to Agents and What It Means for Data Science
The agentic AI era hasn't made algorithms irrelevant. It has just changed where data scientists need to focus their attention. And the data scientists who understand t...
Episode 126: Why AI Excels at Some Things and Sucks at Others
Large language models excel at some tasks while struggling badly with other. At a time where it seems everyone is currently trying to make sense of AI, understanding a...
Episode 125: The AI Chicken Nugget Problem
Building something valuable with AI doesn't automatically make you valuable. If the value sits in your creation and your employer owns your creation, you're the one wh...
Episode 124: [Value Boost] 8 Disciplines Every Decision System Needs
Machine learning is what most data scientists know best. But when it comes to building systems that enable better decision-making, machine learning is just one piece o...
Episode 123: How to Build a Decision Factory Inside Your Organisation
Data scientists are trained to build better models. But stakeholders don't wake up hoping for a better model. They wake up hoping to make better decisions. And the gap...
Episode 122: [Value Boost] 4 Questions Every Data Scientist Should Ask About AI Strategy
Choosing which AI tools to buy is the easy part of an AI strategy. The hard part - and the part most organisations are ignoring - is everything that sits beneath the t...
Episode 121: What Hybrid Agentic AI Organisations Mean for Data Science
The debate about whether AI will replace human workers has already been settled - not by academics or futurists, but by the organisations that fired their humans, disc...
Episode 120: [Value Boost] The AI Silent Correctness Problem
AI hallucinations get all the attention. But hallucinations are relatively easy to catch because the output is obviously wrong. The failure mode that should worry data...
Episode 119: Rewiring Your Data Science Thinking for the Agentic AI Era
The shift to agentic AI doesn't make data science skills obsolete. But it does require data scientists to rewire how they think about familiar concepts, such as uncert...
Episode 118: [Value Boost] Compounding Your Data Science Authority Beyond Blog Posts
A well-written blog post gets you noticed. But for data scientists who want to build authority that compounds over time, it's just the beginning. Every piece of writin...
Episode 117: Writing Your Way to Authority as a Data Scientist
For data scientists who want to build authority beyond their organisation, writing is one of the most powerful tools available. But in a world flooded with AI-generate...
Episode 116: [Value Boost] What Data Scientists Need to Know Before the AI Free Ride Ends
Right now, AI is cheap. But the companies providing it are losing billions of dollars a year and are expected to go public within the next 12 months. When they do, the...
Episode 115: Evolving Your Data Career for the AI Era
The AI era presents a choice for data professionals: wait to see what happens to your role, or get ahead of it and decide what it becomes. Nicholas Kelly made that cho...
Episode 114: [Value Boost] The Four Conversations Every Data Scientist Needs to Master
For data scientists, getting a project approved is a sale. It might not feel like one and money might not change hands, but the dynamics are exactly the same. And like...
Episode 113: The Experts' AI Manifesto
Building genuine expertise takes years. And in the age of AI, losing it can happen gradually and almost invisibly, through small delegations that each seem reasonable ...
Episode 112: [Value Boost] Lies, Damned Lies and Stakeholders
AI misinformation is a new problem. Misleading data is not. Long before anyone had heard of a hallucination, organisations were making bad decisions based on cherry-pi...
Episode 111: Building Your Defences Against AI Misinformation
AI doesn't lie - at least, not intentionally. It just sounds completely confident while filling in the gaps with whatever seems most plausible. And in a world where AI...
Episode 110: [Value Boost] Why You Need Less Data Than You Think
In high-stakes decision-making, waiting for more data is often not an option. Yet many data scientists assume that without a large dataset, meaningful analysis is impo...
Episode 109: How to Measure Anything and Make Better Decisions
Data scientists are trained to work with large datasets. But the decisions that truly make or break an organisation are rarely the ones with large datasets behind them...