Vertical software in the age of GenAI.
Our current point of view on what Generative AI is changing, and what it isn't, for mission-critical software companies. We're excited about where GenAI is taking us, and we're excited to work through this generational change to the software world with our partner companies.
We spend a lot of our time debating this, with each other and with the teams we work with. Here's where that thinking has landed, for now.
GenAI is moving faster than any platform shift we've worked through, and the picture keeps shifting under us. So we hold these views firmly but loosely: firmly enough to back them, loosely enough to update them when the ground moves.
GenAI is clearly the biggest change to how software gets built, tested, deployed, and used since the move to the cloud began fifteen years ago. It will cause the biggest change to how people interact with software since the graphical interface replaced the command line. One consequence of note (and there are many): a new kind of user. Agents, your customers' and increasingly your own software's, operating software on behalf of the humans who used to click every button. We can no longer build software assuming that a person is on the other end.
Another, and one we're especially excited about: how much a focused team's work can now be amplified. The most ambitious version of the roadmap is increasingly within reach of the team already in the room.
What are consequential building blocks for success in the GenAI era?
Every software company is grappling with the question right now of whether GenAI will disrupt or compound its value proposition. We don't think the answer is random, and we don't think the answer will be strictly binary for many companies. Three characteristics, in our view, put an incumbent software company in a structurally better starting position, most powerfully when it has all three at once.
Deep vertical focus.
Software built around the specific workflows, edge cases, and unwritten rules of an industry sits on knowledge that took years to accumulate. It is through deep and trusted connectivity to customers that this software evolves over time to meet how this vertical is evolving. Incidentally, much of the knowledge that makes a product 'world class' at serving customers in a given vertical, rather than 'good enough,' doesn't exist anywhere a model could have been trained on it, at least as of now.
The rules are hard.
Where a workflow touches compliance and regulation considerations, especially when rules are ambiguous, change often, or contradict each other, someone has to interpret, document, and stand behind the call. That judgment doesn't reduce cleanly to a prompt.
The system of record.
The companies that own the important data, the trusted store of what's true, are the ones other systems plug into. In a world of agents, we expect this to be a key driver of what makes a system something an agent reaches for, rather than a system it routes around or tries to replace on its own. None of this is new to GenAI: owning the record mattered through every earlier wave of machine learning too. But GenAI clearly raises the importance to another level.
Put all three together, deep in a regulated vertical and owning the customer's data of record, and you have the profile we get most excited about.
But Andy Grove is still correct that only the paranoid survive.
None of this is permission to sit still. Every software company, well-positioned or not, large or small, has to take this moment seriously: investing in how the product gets built, upskilling the team to use these tools every day, and often rethinking what the product even is, from its interface to its core capabilities. We remember how desktop-to-cloud went. The companies that kept their heads in the sand for the first few years spent the next ten paying for it. What encourages us is that the industry as a whole seems to be taking GenAI far more seriously, far earlier, than some of the industry took SaaS.
This is the work we like best: partnering with mission-critical software companies that fit this profile, and rolling up our sleeves side-by-side with great teams. We've spent most of this page on product and software strategy, but we don't think the opportunity stops there. We see just as much of it in how you sell, how you work with customers, and how you run the company day to day, from finance to HR. Where this gets specific (which companies, which workflows, where the real leverage is) is a conversation, not a webpage. If any of this resonates, we'd genuinely like to compare notes.
What our team is thinking about.
Investors who operate, or investors who are 'operationally inclined'?
Nearly every firm below $100M of ARR brands itself "operationally focused" — gray-haired advisors and an ops team a phone call away. It works, but it's imperfect. Everyone on our team has been both an investor and a CEO, which is why we send Functional Operating Executives into every company we back.
Saying 'no' is hard. When is it the right answer?
Our largest customer offered us over a million dollars a year to build a new module. We ran the diligence, found the category had defeated everyone who tried it, and said no while keeping them as our biggest advocate.
Restoring sanity to your customer contracts
Our largest customer refused to renegotiate a contract tilted entirely in their favor, so we called their bluff and terminated before auto-renewal. Four months later, every bad term was gone, with a 50%+ price increase and a multi-year renewal.
Want to learn more? Start a conversation.
We'd love to meet, trade notes on what we're seeing as the software world goes through a generational evolution, and share more about our philosophy for building great software companies.