In our article “Building Faster Isn’t the Same as Building Trust Faster,” we discussed the pattern of an organization that rushes to build a first version without considering whether it provides a solid foundation for what comes next. That pattern deserves a more in-depth discussion.
AI and modern development tools make it tempting to quickly put something functional together. Within a few days, you have a dashboard, a data model, or a small AI application that does exactly what’s needed at that moment. The immediate problem is solved, and no one stops to consider whether this is also a solid foundation for the next step.
This isn’t about a solution that’s rigid or unchangeable. It’s about an initial choice—for example, how data is structured or which assumptions are implicitly built in—that becomes the foundation upon which everything else is built. If that foundation is just a little off, you won’t notice it right away. After all, the first version works just fine.
You only notice it during the next expansion. A new field, an additional data source, or a modification that seems logical turns out to be just a bit trickier than expected, because the existing structure isn’t designed for it. The same applies to the next expansion, and it all adds up. Each subsequent step takes a little more effort than the last, not because the solution is rigid, but because you constantly have to work around it instead of building on it.
This isn’t a problem with the technology; it’s a consequence of the order in which decisions are made. An initial version developed quickly under time pressure often locks in implicit choices that no one consciously made. Those choices are rarely wrong in the context of the initial use. They only become a burden as more is built on top of them, and by that time, the assumption has long since become the unspoken standard.
You can’t prevent this by building more slowly. A quick first version is often exactly what’s needed for the situation you’re in. What does help is to explicitly consider, during the initial design phase, which assumptions you’re locking in—and whether someone in the organization is capable of evaluating them before they become the new standard. AI can build that first version in an afternoon, but it won’t make that judgment call for you. That remains a human task.
Speed of development solves today’s problem. Whether that quick solution also serves as a solid foundation for tomorrow depends on how much attention was paid to the initial choices, not on how quickly they were made.
Wondering if your teams are sufficiently equipped to recognize these kinds of choices before they become the standard? We help organizations not only build a solid data platform but also recognize and establish a strong foundation themselves—whether that involves data engineering, analytics, or AI as part of that chain. Schedule a 30-minute no-obligation intake session, and we’ll work with you to find solutions.