Pick a Smaller Mountain

Property management companies — the businesses responsible for running apartment communities, commercial buildings, HOA neighborhoods, and more — were piecing together their financial operations from disconnected software, manual processes, and bank relationships that hadn't modernized in decades. They needed integrated banking and accounting. They needed ACH, remote deposit capture, lockbox, credit cards. They needed AR and AP systems that actually talked to each other and connected to their treasury operations.

We thought we could build all of it. A full online ERP, purpose-built for real estate management.

It was an ambitious idea. It felt like the right size of ambition for the opportunity we saw.

It wasn't.

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The market that wasn't one market

Real estate management looks like a single vertical from the outside. It isn't.

Multi-family housing had one set of workflows and compliance requirements. Commercial real estate had another. HOA management — the associations governing planned communities, condo buildings, and neighborhoods — had its own. Each segment collected payments differently, managed expenses differently, and maintained relationships with different bank partners who had different capabilities and integration requirements.

We were building one platform for all of them. Every design decision had to account for the full range of use cases. Every feature had to be explained to customers who didn't always share the same vocabulary. Every integration had to survive contact with bank partners whose capabilities varied significantly by geography and segment.

We worked hard. The team was capable. The technology was real.

But we couldn't find product-market fit. We were too broad to be anyone's obvious choice, and too committed to breadth to make the depth decisions that would have made us genuinely compelling to any specific buyer.

We were trying to climb a mountain that was too large for the team and resources we had.

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The pivot we didn't plan

As I described in my last post, we found our way into the HOA management space serendipitously. It wasn't a strategic decision mapped out on a whiteboard. It was a conversation, a connection, a recognition that a specific corner of the market had a distinct and tractable problem.

HOA management companies had clear, repeatable workflows. Their payment needs were specific and bounded. Their accounting requirements, while still meaningful, were more uniform than the broader market. Their buyers had similar characteristics and similar pain points.

When we focused there, things changed.

We could go deep on the actual workflow instead of the generalized version. We could make product decisions with conviction because we knew exactly who we were making them for. We stopped trying to hedge every tradeoff across an abstracted customer and started building for a real one.

The company started to move.

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What we learned

The lesson I've carried from this experience: a large, heterogeneous market is often a harder starting point than a smaller, more uniform one.

This seems counterintuitive. Big markets mean more opportunity, more potential customers, more room to grow. That's true — but only if you can actually sell to them. And selling requires that your product fits the buyer's specific reality, not just the general shape of their industry.

"We serve property management companies" sounds like a big market. "We serve HOA management companies specifically" sounds like a limitation. But the second one is what drove sales, retention, and referrals — because buyers in that segment knew we understood them. We weren't a general solution they had to configure into something useful. We were the obvious fit.

When you try to build for everyone in a large, varied market, you tend to build for no one in particular. A product that broadly fits a large market often narrowly fits every individual buyer within it.

Pick a smaller mountain. Get to the summit. Then look at what's next.

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Does this lesson still hold in the AI era?

In the spirit of this series, I want to run this lesson against what AI actually changes for founders today.

The short answer: mostly yes.

Building faster doesn't change what product-market fit requires. Fit comes from understanding a specific customer in a specific context well enough to make decisions with conviction — about what to build, what to cut, what to prioritize. That depth doesn't accumulate from broad exposure to a fragmented market. It comes from focused attention on a bounded problem.

When we were trying to build for all of real estate management, we were collecting wide signal from a fragmented market. Lots of inputs, lots of variation, no clear pattern. When we focused on HOA management specifically, the signal became legible. We knew what to do. That's not a function of build speed — it's a function of focus.

What I do think changes with AI is the speed of the feedback loop itself.

In the past, moving from one segment to the next took years — not primarily because the software took years to build, but because the customer learning took years to accumulate. You had to live in a segment long enough to understand it, get it right, build a reference base, and earn the credibility to expand.

If AI enables founders to consume and synthesize customer feedback at a pace that keeps up with development, that changes the calculus meaningfully. The sequence still applies — start focused, build conviction, expand with intention, and have a vision for where you're ultimately headed — but you can move through it faster. You're no longer locked into a segment for years while the learning catches up to the building.