Leading AI-Enabled Product Teams

You’re accountable for how well your team delivers with AI.

Your process and leadership practices were not built for that.

You’re an engineering manager, product manager, design lead, TPM, or team lead. AI now does a real share of your team’s work, and that has changed the conditions your process was built around: where the time goes, what breaks and why, the value of collaboration, how people build skill and stay engaged.

By now you’ve heard that this calls for rethinking your team’s way of working rather than bolting AI onto what you had. That’s right, and over the past year it’s become the consensus. What’s rarely supplied is the next part: what rethinking it actually consists of, where to start, and what it asks of you as a leader.

So, most leaders proceed a patch at a time: a practice here, a policy there, some task acceleration. Team members improvise too. These local moves don’t add up to an effective and efficient way of working, and they produce friction that lands on you.

Our flagship course, “Leading AI-Enabled Product Teams,” provides a coherent picture of how to upgrade your team’s way of working, and your own leadership practices, so that both are safe, sustainable, and impactful.

What you’ll learn

1. How to design and evolve your team’s AI-enabled workflow: Sizing up AI’s strengths, weaknesses, opportunities, and threats in your context — an analysis you can also bring into conversations with executives who are pushing on you; seeing your entire system of value delivery, with its bottlenecks, its feedback loops, and the constraint that’s actually limiting it; and determining what the system should optimize for and why, so you can change practices effectively rather than graft AI tools onto your existing process.

2. Planning and managing AI-speed product development: Framing initiatives for maximum alignment, buy-in, and effective prioritization; planning large-scale work around outcomes rather than outputs, and evolving toward them in a way that controls the cost of change; proceeding in short cycles that produce something worth having; and achieving flow — through visual management, WIP limits, and pull systems — which works whichever process you run and becomes critical once AI is in the mix.

3. Leading people and teams when AI changes their work: Identifying what people need in order to engage and to keep performing well over time; supporting both performance and growth in the context of today’s pressures; setting teams up to succeed rather than just staffing them; and planning your team’s AI journey so the changes stick, people come along, and the gains are real.

About the instructor, Gil Broza

I specialize in guiding product development leaders to reliably deliver meaningful impact. Over 22 years I’ve served more than 100 clients across Canada, the US, and Europe — both tech companies and enterprise IT — usually helping them work and lead more collaboratively, adaptively, and with an eye on value, rather than by installing a framework. I’ve recently used agentic engineering to build a games portal from the ground up, and before all this I wrote enterprise software professionally for 17 years. I’ve written four books on effective value delivery, and my newsletter, The 3P Vantage Point, has been running since 2009.

“The course was very relevant to the work I do every day. The content was realistic, practical and applicable. Everything was thoughtfully designed to set the participants up to succeed.”
— T. D., senior manager of four product development teams

This course is for you if:

You’ve adapted some of your process for AI and you’re ready to take on the way of working as a whole
Team adoption is patchy, and the resulting friction lands on you
You have to work within your current roadmap, decision rights, and structure; changing the org isn’t on the table
You want practical guidance that will serve you for years — not theory, hype, or tips that expire with the next model release

What this course is not about

This course doesn’t prescribe a framework or a set of best practices. Those depend on context, and yours isn’t the same as anyone else’s. Instead, you’ll learn how to determine the practices that fit your situation.

It isn’t about AI models, prompting, or how to configure agents.

It’s also not about the business, HR, data, security, or privacy aspects of AI adoption.

It’s about what you can do, from your organizational position, to bring AI into product development in an effective, sustainable, and safe way.

Logistics

To fit your busy schedule, this course is structured as 5 sessions of 2.5 hours each (including a break) spread out over two weeks. In total, that’s equivalent to a two-day course.

Sessions will not be recorded. Even though there will be group discussions, you will not need to share anything confidential.

Dates: November 3, 5, 6, 12, and 13, 2026

Time: 1:00-3:30pm Eastern Standard Time

Space is limited to 12 people (and max 4 from the same company) to ensure interactive, diverse, high-quality sessions. Registration closes one week before the course starts.

Fee:

By Sep 13 (super early bird): US $1050 (about Cdn $1465 / €910 / £780)
Sep 14 – Oct 4 (early bird): US $1275 (about Cdn $1775 / €1100 / £945)
Oct 5 – Oct 27 (regular): US $1500 (about Cdn $2090 / €1300 / £1110)

The registration fee includes a course booklet full of relevant content (not slides, which we don’t use anyway).

Optional add-on: 2 x 30-min private coaching sessions after the course to help you work through implementation challenges.