Much of business software organizes familiar things: people, documents, inventory, time, and the work connecting them. Those jobs remain important. Our belief is that the growing ability to reuse their foundations should make the application layer more affordable.
That is a direction we want to build toward, rather than a claim that software has become free to produce. A dependable product still needs engineering, infrastructure, testing, security decisions, support, and maintenance. Better tools change that work; they do not make responsibility disappear.
Carry the recurring work forward
A new product needs accounts, permissions, useful forms, clear navigation, documents, and a way to run longer tasks. Rebuilding every one of those capabilities independently consumes attention before a team reaches the problem that makes the product worth using.
Our response is to develop a shared platform and design system. Common services and interaction patterns give new work a starting point. Each product can then focus on its domain: the records people need, the decisions they make, and the exceptions that appear in a real working day.
We expect AI-assisted development and these shared foundations to keep changing the economics. That expectation is our operating thesis. It needs to be tested through the quality, usefulness, and ongoing cost of the products we actually build.
An application creates a place to work
An inventory record gives a team a common account of what is on hand. A timesheet records where hours went. A versioned document makes it possible to identify the revision behind a decision. There is substantial value in a dependable system of record, even before intelligence enters the workflow.
We want access to that foundation to be straightforward for the company. People need to collaborate across responsibilities, and we do not want the addition of another participant to become another seat-pricing decision.
Intelligence needs a useful job
The next opportunity is to help someone use the information to get work done. An answer that points to a passage in the right document can save a search. A prepared draft can give a person something concrete to review. The result should be relevant to the task and inspectable by someone responsible for it.
As our construction work moves toward presales, we want to explore assistance with estimating and takeoffs. A quantity still needs review. An estimate still needs industry judgment. The goal is to reduce useful effort while preserving a clear place for that judgment. Those workflows are product development ahead of us, rather than a completed capability inferred from having an AI model.
The application gives the team a place to work. Intelligence has to earn its place by helping the team finish something useful.
Let the commercial model reflect the belief
Our planned model separates company access from variable usage: a company base fee with unlimited users, an included allowance for hosting and intelligence, and additional usage credits when needed. Unlimited users means no charge for each additional seat; it does not mean unlimited processing.
That structure gives us a reason to make the foundation broadly useful and the intelligence worth choosing. We describe the intended base fee and credit allowance in our software economics field note. This is the model we are building toward, rather than a claim that every future product will have identical requirements.
Industry knowledge remains the deciding input
The ability to build more efficiently does not tell us which problem deserves a product. People in an industry know which workarounds are unavoidable, which exceptions matter, and where a proposed shortcut would create another problem.
Our design partners bring that knowledge directly to the engineers. We fund development and bring the product to market; partners help shape priorities and use working versions early enough to influence the result. Construction is our first focus, starting with inventory and time tracking, with presales next.
The thesis becomes credible through that work: a foundation people can rely on, an interface they can use, and intelligence whose contribution they can judge.