The Capacity Lever: How Emily Petroff turned founder judgement into business infrastructure

When I spoke with Emily Petroff, founder and CEO of Switch Society, the obvious AI story was that she had built technology her business could not afford to commission.

That is impressive, but it is not the most important part of what she did.

The deeper story is about capacity: how a founder took knowledge, decisions and processes that depended too heavily on her and began turning them into infrastructure the business could use without constantly pulling her back in.

That distinction matters. Efficiency asks: How can we complete this task faster? Capacity asks: What becomes possible when the business no longer needs the same person to keep carrying the same work?

The problem was bigger than a difficult tech stack

Switch Society is a membership-based circular wardrobe, processing more than 10,000 garments into circulation every month while preparing to expand through franchising. Its operating model has moving parts at both ends: inventory arriving and being processed behind the scenes, and members tracking points and interacting with the service at the front.

But the systems underneath it had evolved in fragments.

“Our tech stack was just a nightmare.”

Emily knew the business was losing money, but the systems could not show her precisely where. Her team was being asked to carry work that technology should have handled. The infrastructure was also unsuitable for the franchise growth she was pursuing.

This was not one operational inconvenience. It was affecting delivery, revenue, team performance and the founder's ability to concentrate on growth.

Without the budget for a custom development team—and after several attempts to find outside support had fallen flat—Emily used AI to build the operating system herself.

The result connected the back-end processes used when members bring in garments with the front-end member experience. Within months, Emily said the new system had found thousands of dollars per month that had previously been leaking from the business.

But the financial recovery was only one effect.

“[My team members] need technology to do this for them so that they can be doing the thing that they're really, really good at.”

That is the Capacity Lever in practice: removing work from people that does not make good use of their capability, so they can apply their judgement where it creates more value.

Founder dependency is a commercial constraint

Emily was unusually direct about the problem beneath the problem:

“Founder dependency is the biggest freaking problem that we have.”

In many founder-led businesses, the founder's knowledge is both an advantage and a constraint. It helps the business stand apart, but if the decisions, standards and methods remain locked inside one person's head, the business cannot use that knowledge without repeatedly drawing on that person's time.

Emily did not solve this by asking AI to imitate her from a short prompt. She spent hours in conversation with it—explaining how she serves members, how she responds in difficult situations, what the business should protect and what its processes need to achieve.

She describes the principle as conversation before creation.

Those conversations helped her identify patterns she had not formally named and turn them into documentation, standard operating procedures and systems her team could use. What had been instinctive founder knowledge began to become repeatable business infrastructure.

The point was not to remove Emily from the character of the company. It was to stop the company requiring her physical involvement every time it needed to benefit from her thinking.

That is a materially different use of AI from generating a document more quickly.

The human remains the decision-maker

Emily also built a group of specialised custom GPTs that operate like a small advisory team. One of them, Atlas, runs a weekly CEO reset that challenges distractions and brings her back to the priorities connected to her goals.

She can also bring several of these AI advisers into a virtual “war room” to examine a decision from different perspectives. But she is clear about where judgement sits:

“I get multiple points of view to put through my own filter.”

That sentence captures the human role precisely. AI expands the inputs. Emily evaluates them.

Used this way, AI does not take thinking away from the founder. It creates the conditions for better thinking: surfacing patterns, challenging assumptions, retaining context and applying pressure to a decision before anything is created.

The human remains at the centre—the star of the show—but no longer has to perform every supporting role as well.

One founder story, five business effects

Capacity is the primary lever in Emily's story, but its commercial value becomes clearer when we trace how it affects the other four levers in the AI Power Women Five Business Levers framework.

The sequence is important:

Better insight directs capacity. Released capacity strengthens delivery. Better delivery protects revenue. Together, they make growth more achievable.

This is why AI should not be assessed only by the number of hours it saves. The more useful question is what the business can now do with the capacity it has released.

From Emily's practice to a Power Asset

Every AI Power Women conversation leaves something practical behind.

Inspired by Emily's weekly AI boardroom practice, we created the Weekly AI Co-Founder Session: a private, repeatable session designed to challenge the decision a founder is avoiding, test competing priorities and turn the conversation into clear next steps.

It is not a replica of Emily's Atlas setup. It translates the principle behind her practice into something another founder can use: the AI asks, the founder thinks and creation begins with a deliberate decision.

The commercial purpose is simple:

Protect the founder's limited capacity by directing it towards the work that matters most.

My Lever Lens takeaway

What I learned from Emily is that capacity is not simply the ability to produce more.

It is the ability to reduce unnecessary dependence on the founder, stop skilled people carrying work that technology can support, and make valuable judgement available to the business in a more repeatable form.

AI created leverage for Emily because it sat underneath her experience. It helped her extract what she knew, examine how she thought and build systems around the standards she wanted the business to preserve.

That is the opportunity for experienced founders: not to hand their judgement over to AI, but to stop leaving so much of its value trapped inside them.

The Lever Lens is where Michelle Jones-Walker examines each AI Power Women conversation through five commercial levers: Insight, Growth, Revenue, Capacity and Delivery. Business acumen provides the lens; applied AI is the lane.