For engineering and IT leaders taking a team through AIYour AI plan has a people problem nobody put on the roadmap.

Going deep in one codebase used to be the job. Now it’s orchestrating across teams, agents and decisions, and judging what to hand to AI and what to keep. It takes a different mindset, and skills your team was never trained for.

We start with one honest conversation about the hopes and fears, and turn it into the skills your team needs next.

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From Matej Strašek on LinkedIn (opens in a new tab), a senior engineering manager at a travel tech company who went through this with his own teams, and Irene Anggreeni, PhD on LinkedIn (opens in a new tab), a mental fitness coach, trainer and speaker who worked with him through it.

Fear: Will I still have work in IT?

Fear: We’re losing control over the code

Fear: I’m losing my skills. AI is the one who codes.

Hope: We can do at least 30% more

real notes from Matej’s engineers

When your team holds back on AI, it looks like resistance. What’s really underneath it?

MatejEngineering manager

The pressure from above was clear: use AI in every project, scale without adding people, 30% more output this year, at the same quality. Underneath, people were asking questions nobody had put on the roadmap:

Are we losing the craft we built our careers on?

Is my job replaceable by an AI agent?

What becomes of us then?

William Bridges’ transition model, drawn as a productivity curve: output dips through the ending and the neutral zone, then recovers in the new beginning, often above where it started. Ending Neutral zone New beginning what am I losing? what now? productivity dips productivity time
William Bridges’ transition model. A new tool can land in a day; learning the new job it brings takes months. The red line is productivity: it often dips through the ending and the neutral zone, then recovers, often above where it started. A concept, not to scale.

IreneMental fitness coach, trainer, speaker

From the outside it all looks the same: pushback in meetings, tools nobody opens, a polite “it’s not ready yet”. Underneath, it can be many things. Fear for the job. Missing work they were proud of. Not knowing what’s expected of them now. Or a real risk they’ve spotted: tech debt that can explode, control over the code that can slip.

You can’t tell which from the outside, and pushing harder won’t tell you either. When people can say it out loud, you find out what’s really there, and which fears to act on. And if you’re the one leading people through it, you’re probably carrying some of it too.

The blueprint shows you how to ask

Four short emails, one a week. Free.

From the two of us, starting with the blueprint. The first three each give you one thing to use with your team. The last one helps you pick your next step. That’s all.

Inboxone a week
Matej & IreneEmail 1: the blueprint — the signals, the setup, the session itself, and keeping it aliveWeek 1
Irene & MatejEmail 2: make sense of the fears — a one-page guide for after the session: the four pathways, the strength and saboteur in each, and what you do as their leaderWeek 2
Irene & MatejEmail 3: you, and the part you play in all this — your own fears and saboteurs, like the Judge and the Hyper-Achiever, and a short quiz to find yoursWeek 3
Matej & IreneEmail 4: turn the fears into action — find where you are, one step for this week, and how we can helpWeek 4
Get it by email

so this becomes something you do, not just a page you read.

Who we are

MatejSenior engineering manager

Matej Strašek leads the engineering teams behind operations at Exoticca, a travel tech company: everything after a customer books a trip, until they’re back home. This year he took about 12 engineers through AI adoption, and worked out what it meant for his own role along the way.

Matej on LinkedIn (opens in a new tab)

IreneMental fitness coach, trainer, speaker

Irene Anggreeni, PhD, is a mental fitness coach, trainer and TEDx speaker, and a former software engineer. She works with engineering leaders and their teams to build burnout-proof, high-performing cultures. As Matej’s mentor on this AI adoption journey, she brings a deeper understanding of the human side of that change, and hands-on tools to work with it.

Irene on LinkedIn (opens in a new tab)

Invite us to speak

Why do good teams hold back on AI? An engineering manager and a mental fitness coach answer from both sides, and your audience leaves with one thing to try on Monday. Tell us what you have in mind, and let’s check if we’re a fit to work together.

Invite us to speak