Why Software Projects Fail

In traditional software development, 70% of projects fail.

Most of them don't fail because of incompetent developers or bad technology choices. They fail because of something you couldn't have known at the start.

You scope a project. You plan it carefully. You start building. 60 hours in, maybe 120, someone realises a core assumption was wrong. The data model doesn't fit. The user flow needs to work differently. The integration you planned for doesn't actually behave the way the docs said it would.

Now you're in a meeting explaining to a client that the $80,000 they've spent so far needs to be, essentially, thrown away. And that fixing it will cost another $40,000 to $80,000.

Maybe they stomach it this one time. Maybe.

But here's the thing about software projects: it almost never happens just once. The second time that conversation happens, the project is effectively dead. The client has lost confidence, the budget has ballooned past anything that makes business sense, and everyone quietly starts looking for an exit ramp, or simply never speaks of it again.

The problem isn't that you don't know what to do, it's that it's too costly to do it.

Every project has a landmine. Every single one.

If you've shipped software professionally, you know this is true. 100% of projects surface something that wasn't in the original requirements. Something nobody thought of. Something that seemed obvious in retrospect but was invisible at the start.

Sometimes the landmine is small. A minor scope adjustment, a few extra days of work. You absorb it and move on.

Sometimes the landmine blows up the entire project.

And you never know which one you're going to get. In every project, you're essentially just hoping that whatever you missed isn't big enough to kill you. That's a terrible position to be in when you're spending $150,000 or more on a custom build.

Proper scoping can de-risk this to some degree, but never entirely.

A real example: ChemistLink

We ran into exactly this with one of our clients, ChemistLink. The original architecture had a marketplace model where clinics purchased from pharmacies via the ChemistLink platform which acted as the intermediary. Orders would flow through to the pharmacy directly, just facilitated by the platform.

Turns out that was wrong.

ChemistLink was actually supposed to be the merchant. Orders needed to come through to ChemistLink first, get paid for in full, and then get manually assigned to a pharmacy by a human on their team based on a number of factors. Completely different commercial model, completely different data flow, completely different architecture.

This wasn't caught in requirements. Should it have been? Yes. But that's the point: there's always something that should have been caught and wasn't. That's just the nature of building complex systems.

This is a full re-architecture. Traditionally, we're talking dozens, maybe hundreds of hours of work. At that point, the project economics collapse. You've already spent the budget building the wrong thing, and now you need to spend nearly that much again building the right thing. This single misunderstanding could have killed the entire project.

What actually happened

We fixed it in less than an hour. The client wasn't billed for any additional time.

Because we're experienced engineers who lean heavily into AI coding tools, rearchitecting the system wasn't a months-long rebuild. It was a series of thoughtfully crafted prompts from engineers who understood the system's architecture. The code got rewritten. The data model got restructured. The order flow got rewired.

A few prompts. Not a few sprints.

This is what AI-driven development actually changes about software. It's not about writing code 10x faster (though that happens). It's about making mistakes survivable.

The math that matters

At LaunchAssembly, we build software at roughly 10 to 20x the speed of a traditional agency, at a fraction of the cost. But the speed isn't the important part.

The important part is what that speed does to risk.

When course corrections cost $100,000 and take 12 weeks, projects are fragile. One bad assumption and the whole thing cracks. When course corrections cost virtually nothing, projects are resilient. You can hit three landmines and still ship on time and on budget.

Every software project is going to surprise you. The question is whether those surprises are fatal or fixable.

With AI-driven development, they're fixable.