The hardest part of building a project isn’t always dealing with failure.
It’s dealing with a project that is doing just well enough to keep going. There is a common situation in software where a project isn’t a total disaster, but it isn’t a hit either.
It has some users and some traction, but not enough to be a clear success. This is the "middle ground," and as Dropbox founder Drew Houston once noted, it can be the most difficult place to be. If a project fails, the choice to stop is easy. If it’s a success, the choice to grow is easy. But when it’s just "okay," it stays alive and uses up energy without a certain future.
In the AI era, the timing of this decision feels different because the industry moves so fast. A few years ago, it was common to let a project sit for a long time to see if it would eventually grow. Today, a project that is only "okay" now might be outdated in a very short time because tools and markets change every month. The "wait and see" approach carries a new kind of risk. The speed of the field makes the gap between a slow-growing project and a fast-moving market much more obvious.
Deciding what to do next usually involves a mix of data and intuition.
Some look at retention data to see if users are actually staying. It is a choice between waiting for more growth or deciding that the current traction isn't enough to justify more time. In a world that moves this fast, the middle point remains a challenging spot to navigate, with no clear data-driven/rational solution.
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