The New Shape of High-Performing Teams in the AI Era

3 Feb

BY MARCIO SETE

Welcome to the age of small giants.

Something interesting is happening inside modern organisations.
Tiny teams. Big outcomes. Slightly uncomfortable questions for traditional org charts.

We’re seeing 2–4 person pods outperform teams ten times their size. Not because they’re burning the midnight oil. Not because they’ve magically hired superheroes. But because AI has completely rewired the economics of what a small team can do.

Agentic workflows aren’t just changing how software gets built. They’re changing how teams should be designed in the first place.

And once you see it, you can’t unsee it.

The Old Economics of Teams (aka: why hierarchies made sense… once)

For decades, team design followed a pretty logical formula:

Complex work needed coordination

Coordination needed people

More complexity = more people

So we added layers. Project managers to track progress. Architects to protect standards. Reviewers to catch mistakes. Leads to make decisions. Managers to manage the managers.

Handoffs were everywhere, because no single person could hold the whole picture. And the org chart? That was basically a map of dependencies.

All of this made perfect sense in a slower world.

When lead times were measured in weeks.
When mistakes were expensive.
When reviews, approvals, and coordination meetings were a necessary tax on progress.

But here’s the uncomfortable question:

What happens when lead time drops from weeks… to minutes?

The New Economics (this is where it gets spicy)

We’ve been measuring what happens when AI isn’t just a side tool, but baked directly into how teams build software.

Not “AI helps sometimes.”
More like “AI is part of the workflow.”

The numbers are… hard to ignore:

Median lead time from intent to shipped code: 26 minutes

Code output multiplier: 22.5x

AI co-authored code: 98%

Quality gates: maintained or improved

Sit with that for a second.

If a small team can ship over 20x more code at the same quality, what happens to the logic that justified large teams?
If handoffs take minutes instead of weeks, what happens to all the roles designed to manage slow handoffs?

The economics flip.

Suddenly, size isn’t strength. It’s drag.

Communication paths explode. Decisions slow down. The structure that once enabled complex work starts actively getting in the way.

Enter the Small Giants

What’s emerging instead are small, empowered pods that can do what used to require an entire department.

These aren’t scrappy teams cutting corners. They’re deeply skilled groups with strong product thinking, sharp design instincts, and AI systems that massively amplify their output.

A well-set-up 2–4 person pod can now:

Move from idea to production in hours, not quarters

Hit quality standards that many large teams struggle to reach

Iterate on real user feedback instead of guessing and waiting

Make decisions without running an escalation obstacle course

Small in headcount.
Giant in capability.

Hence: small giants.

What This Changes for Leaders (hint: quite a lot)

If this is the direction of travel, it has real implications for how organisations are designed.

Fewer layers, more autonomy.
Middle layers that existed to coordinate and approve start to feel like friction. Flatter structures, with decisions pushed closer to the work, just… work better.

Different skills matter now.
When AI handles the predictable execution, humans add value through judgment, creativity, and navigating ambiguity. Speed still matters but thinking quality matters more.

Team boundaries need a rethink.
Most team structures were designed for slower cycle times. If your cycles are now 10x faster, your boundaries are probably in the wrong places.

Coordination costs compound.
Every extra person adds communication overhead. In a world where small teams can move incredibly fast, that overhead gets expensive quickly. The default should be “smaller,” not “larger.”

A Concrete Example: Pull Requests

Let’s make this real.

Pull requests have been a cornerstone of software development forever. One person writes code. Another reviews it. Feedback ping-pongs back and forth. Eventually, it gets merged.

That ritual made sense when human code review was the primary quality gate.

But AI has exposed something important: pull requests are really a coordination mechanism for a world with slow cycle times and limited automation.

When you have continuous quality gates, automated security scanning, enforced test coverage, and AI-assisted review, pull requests often become a bottlenecK, not a safeguard.

Teams that rethink these rituals move faster.
Teams that cling to them because “that’s how we’ve always done it” get outpaced.

Usually by… small giants.

This Isn’t Future Speculation (it’s already happening)

Some organisations are already redesigning their teams around these principles. Flattening hierarchies. Removing layers that only existed to manage coordination. Pushing decision rights closer to the work.

Others are waiting. Watching. Assuming there’s time.

But look at the pace of change around us.

Anthropic went from observer to major player in days.
OpenAI makes multiple strategic moves in a single week.
The frontier isn’t operating on enterprise timelines.

The organisations that wait for certainty will find themselves competing against teams that moved while they were still deliberating.

Questions Worth Asking in the Boardroom

If this is landing uncomfortably (good sign), here are the questions to explore:

What would our team structure look like if lead time was minutes, not weeks?
Overlay faster cycle times onto your org chart. Where do layers stop making sense?

Where are we adding people to solve coordination problems?
Every coordination hire is a signal. What if the structure, not the headcount, is the issue?

Which rituals exist because of old constraints?
Pull requests. Sprint planning. Architecture review boards. Which ones now add friction instead of value?

How would a 4-person team approach this?
Before scaling up, ask whether a small, empowered pod could move faster than a large, coordinated group.

The Leadership Opportunity

Organisations that get this right won’t just be more efficient. They’ll be fundamentally more capable.

Imagine competing against teams that move from idea to production in hours.
That run experiments while you’re still planning sprints.
That respond to customer feedback in real time while you’re scheduling review meetings.

That’s the gap opening up right now.

The good news? This isn’t about having more resources or shinier tools. It’s about being willing to rethink how work actually flows. Letting go of structures that made sense in a slower world. Trusting small, empowered teams with real autonomy.

The age of small giants is here.

The only question is: will you build one or compete against them?

At Neu21, we help organisations redesign how work flows in the AI era. Not just adopting tools, but rethinking team structures, decision rights, and operating models from the ground up.

If you’re curious what small giants could look like in your world let’s talk.

Guest User