Leading AI-Enabled Engineers: Skills, productivity and the next generation

As AI moves from experimentation to everyday tooling, engineering leaders are facing a new challenge:

What does a high-performing engineering team actually look like in an AI-enabled world?

At our latest London Engineering Leadership Roundtable, we brought together a group of CTOs, VPs and senior engineering leaders to share how they’re navigating this shift in practice.

This session, hosted by Simon Evans, focused on real experiences of implementing AI across engineering teams, and the impact it’s having on structure, skills, productivity and long-term strategy.

What we’ll cover

• Where AI is genuinely improving engineering workflows
  And where the reality still doesn’t match the hype
• The skills engineers need in an AI-assisted world
  Why judgement, architecture and systems thinking are becoming more important than ever
• Supporting the next generation of engineers
  How to help junior engineers build strong fundamentals while AI does more of the heavy lifting

Our moderator for the session was Rich Pearce, Engineering Director @ Iwoca.

Key themes from the discussion

1. AI is already changing hiring decisions

AI is no longer just augmenting work, it’s starting to replace it.

• Some businesses are making the decision not to rehire an engineer, opting to automate the role instead
• We're expecting this to become more common across the industry
• Teams are being forced to rethink what “essential headcount” looks like

2. Engineering roles are shifting towards technical leadership

The role of an engineering manager is evolving quickly:

• Moving towards 70% technical / 30% people leadership
• Greater emphasis on architecture, risk and system design
• Less demand for purely hands-off people managers

At the same time, engineers are expected to become more:

• Product-minded
• Cross-functional
• Outcome-focused rather than delivery-focused

3. Smaller teams, faster execution… but new risks

A consistent trend across the room:

• Teams shrinking to 1 PM, 1 designer, 2–3 engineers
• Founders favouring smaller, high-leverage teams
• Faster iteration and lower cost of experimentation

But this brings challenges:

• Single points of failure
• Production support gaps
• Increased pressure on senior engineers

4. Productivity is improving… but ROI is still unclear

AI is definitley speeding things up:

• Some businesses seeing ~20–30% efficiency gains
• Certain tasks now require “no cognitive load”

However:

• The challenge remains in how to clearly demonstrate commercial impact to the business
• Traditional metrics (e.g. DORA) are becoming less relevant
• Focus is shifting towards business metrics like customer lifetime value

5. The real bottleneck is no longer engineering

As build speed increases, a new constraint is emerging:

• Product teams defining the right problems
• Alignment across teams
• Decision-making and prioritisation

In short:
We can build faster than ever… but are we building the right things?

6. Skills that matter now

Across the discussion, a clear shift in “valuable skills” emerged:

• Strong fundamentals (for when AI breaks)
• System design and architecture thinking
• Writing high-quality specs and context
• Problem-solving and ownership
• Commercial awareness

The takeaway:
The best engineers are no longer just coders, they’re problem solvers.

About the series

These roundtables are run by Simon, who leads our Engineering Leadership practice. Across the year, he brings together engineering leaders from some of the UK and Europe’s most interesting tech-driven businesses to share real experiences, challenges and approaches.

Previous sessions have covered topics including product engineering, scaling teams, and the practical realities of AI adoption.

You can explore highlights and insights from past sessions here:
👉 content-hub/87/

Register your interest

If you’d like to join one of our upcoming sessions, drop us a message [email protected]