Why Side Projects Should Study Failure First

On August 3, a personal content system I had spent more than a year building was finally taken offline.

It was not broken. The frontend, backend, job queue, search, and draft generation all still worked. The fatal condition was much simpler: nobody was using it anymore. Capture had moved to a lighter tool, and writing had moved to a scheduled workflow. Keeping the old system alive would only mean another server and another maintenance bill.

That outcome clarified something for me. When building an independent product or a side business, success stories may not be the most valuable material.

Success stories are easy to read. They tell you which features were built, which technologies were used, and how many users eventually arrived.

But a product survives through a mixture of timing, distribution, early customers, and luck. Some founders cannot separate those conditions clearly. Others never notice them. What an outsider can copy is usually just the interface and the feature list.

Following that list may reproduce the winner's appearance, but not the conditions that kept it alive.

The bigger problem is that success stories easily turn chronology into causality. A team ships a feature, then user numbers rise, and readers automatically fill in the gap: the feature caused the growth. The missing event may have been a recommendation, one large customer, or a competitor leaving the market at exactly the right time.

For someone who only has evenings and weekends, spending dozens of hours reproducing an unproven causal story is not a small cost.

A success story shows you the finish line, but often hides the holes the winner never fell into.

Failure stories are less polished. No users arrived. Acquisition cost too much. Delivery required too much labor. Payments came too slowly. Each one reveals a concrete way a project can die.

When Google's Site Reliability Engineering teams investigate system incidents, they write postmortems. They do more than celebrate that service was restored. They document the incident, understand every contributing cause, and put preventive actions in place.

Failure also forces a distinction between "fixable" and "time to stop." A button that does not respond is a fixable defect. A product whose features all work but whose users never return cannot be explained by "one more fix." The first case needs a code change. The second needs a fresh judgment about whether the product still has a reason to exist.

The same logic works for side businesses. A failure cannot guarantee that my next attempt will succeed, but it can keep me from falling into the same hole twice.

For someone with limited spare time, avoiding one known failure is more useful than learning one more success formula.

Before I start now, I would rather write a short "stop-work list": where users are supposed to come from, which signal would prove that they want to return, and which condition means I should stop adding features.

That page does not make a project look impressive. It can feel discouraging. Its value is that it replaces "one more feature will fix this" with a condition that can actually be checked.

When my old system was retired, its code and data were archived rather than dismissed as wasted work. The most useful thing it left behind was not a feature, but a death condition: when the capture path is too heavy, a working system can still be replaced by a lighter route.

The next time I see a successful product, I will first look for the projects that fell beside it.

What deserves copying may be where the losers died rather than what the winner did. If the project in your hands stopped tomorrow, which line would break first?