Smaller teams first

When AI coding tools arrived, most of the conversation was about which tools to buy. In my experience the constraint was the team leads.

The gap

Most team leads are excellent engineers who got promoted. By the time AI became part of daily work, many were managing 8, 10, or 12 people. Their days were full of reviews, planning, and people work, with very little room left to learn a new way of building software: prompting, working with agents, and changing how code gets written and reviewed.

A team rarely adopts a new way of working faster than its lead does.

What I changed

I made two moves at the same time.

1. A bootcamp, so everyone started from the same baseline on AI-assisted engineering.
2. Teams cut to 4 or 5 engineers, with every team lead spending 60 to 70% of their time hands-on.

Smaller teams gave the leads time back. Hands-on time meant they learned the new tools by shipping with them.

After a year

After almost a year the team leads were proficient. They knew how to work with agents, how to prompt well, and how to review that kind of work. That is when the teams grew again, because a lead who understands the new way of working can support more people doing it.

Then I went one step further and removed layers of hierarchy. Fewer handoffs between levels meant the business moved faster, and decisions were made closer to the people who understood the work.

Velocity went up by more than 45%, and AI adoption peaked at 98% across the department.

How the org changed, in four stages

1. Stage 1 AI arrives, and leads have no time to learn

   Team size

   8, 10, or 12 people per lead

   Team lead's time

   Days full of reviews, planning, and people work. Very little room left to learn.

   Hierarchy

   Existing layers

   What changed

   A team rarely adopts a new way of working faster than its lead does.

2. Stage 2 Bootcamp and smaller teams

   Team size

   4 or 5 engineers per lead

   Team lead's time

   60 to 70% hands-on. Leads learn the new tools by shipping with them.

   Hierarchy

   Existing layers

   What changed

   A bootcamp put everyone on the same baseline for AI-assisted engineering.

3. Stage 3 After almost a year, teams grow again

   Team size

   Teams grow again. The copy gives no figure.

   Team lead's time

   No split given. Leads are proficient with agents, prompting, and reviewing that work.

   Hierarchy

   Existing layers

   What changed

   A lead who understands the new way of working can support more people doing it.

4. Stage 4 Layers of hierarchy removed

   Team size

   Not stated

   Team lead's time

   Not stated

   Hierarchy

   Layers removed. Fewer handoffs, and decisions closer to the people who understand the work.

   What changed

   Velocity went up by more than 45%. AI adoption peaked at 98% across the department.

What I'd tell other leaders

• Team size isn't fixed. Shrink it on purpose while people learn, and grow it again once they can lead the new way.
• Your team leads set the ceiling for adoption, so invest in them first.
• Hands-on time for leads is the training program.
• Once the skills are there, look at your hierarchy. With AI, extra layers cost more than they used to.

Learn first, then grow, then flatten.