From Outsider to Security Founder with Ankita Dhakar

For a long time I was proud of how I lead: give people the vision, give them trust, get out of the way. Then I handed a big new area to someone brilliant, did exactly that, and watched them slowly fall apart. This episode is about situational leadership: the four stages every person moves through on every task that matters, the four styles that match them, the two ways leaders get it wrong, and the one insight that changed how I see my team. It ends with a challenge you can do in under a minute while you're still listening. The sponsor of this episode is Wires Uncrossed.

Andrea Magnorsky started out writing Delphi and C#, went off to build video games, fell for functional programming and F#, and somewhere along the way accidentally invented a practice for helping teams understand their own systems. In this episode, we pick up the decision-making thread from our conversation with Ammar and pull it somewhere new. Andrea and I get into why teams quietly mean different things by the same word, how "rework is just the modelling you didn't do," and the difference between hat, haircut and tattoo decisions. We dig into the advice process, how anyone can make a decision as long as they seek advice, not permission, why ivory-tower architects make worse calls than the people building the system, and how to move a team from consensus-by-default toward transparent, decentralised decisions without losing control. This episode is sponsored by Wires Uncrossed.

We call almost any group of people "a team." But is it? Ammar Sagban has spent his master's research chasing that exact question, and his answer starts with a small shift that changes everything: teaming isn't a noun; it's a verb. Something you do, on purpose. In this episode, Ammar is just weeks away from defending his thesis, having done something I once did and then ran away from — gone back to academia mid-career. We talk about what that journey gave him, why teaming is a verb, and the question most of us skip in the rush to be efficient: does this decision even need to be made by the team? In this episode: - Why going back to study mid-career is worth doing every ten years or so - Teaming as a verb and the test of whether your "team" is really a team - The fishbowl: are our coaches, facilitators and buffer roles helping the team, or getting in the way? - Team decision-making and why "how are we deciding this?" matters more than the technique - The tool Ammar built from his research, and the conversation he's hoping to start

Looking for an executive role in New Zealand is nothing like looking for a senior one. The market is smaller, the rules are unwritten, and most of what decides outcomes happens in rooms you're not in. In this solo episode, Jakub shares three big ideas that reframed how he thought about the exec search, the small things that quietly make or break processes, and what to remember when it doesn't go your way.

After three years, Joekub is back, and this time they brought a startup, an AI agent that writes project updates in five minutes, and some very uncomfortable questions about your career trajectory. Jakub and Joe (collectively: Joekub) reunite on Tech Waka for a wide-ranging conversation about what's actually happening at the coalface of AI-powered delivery. Joe left agile coaching to join an AI startup and hasn't looked back. Jakub is steering product and technology through the same wave from the C-suite. Between them, they've got enough delivery scar tissue to know when something is new and different. They cover why extreme programming turned out to be a prophecy rather than a methodology. Why the spec is more important than the code now. Why your AI agent might be sandbagging its own performance to protect team morale. And the question that no one in a sprint planning meeting wants to answer out loud: if the agent is outperforming the humans, who gets the bonus? Funny, honest, and grounded in real experience, this is what it sounds like when two people who've been around long enough to have opinions stop being polite about AI and just say what they think.