Too Easy to Start - AI Tools Shifted My Bottleneck from Building to Shipping
Getting started used to be the hardest part.
Like with running... sometimes the biggest hurdle is just putting your shoes on. Once you're out the door, momentum kicks in. That’s how building software used to feel: bootstrapping an idea took effort, so only the ideas worth chasing made it off the ground.
Then came AI tools like ChatGPT, Copilot, and others. They made starting projects frictionless. I could describe an idea and get a working prototype in minutes. It was exhilarating.
But now I’m drowning in half-finished projects. I’ve got 50 things in various states of completion, and I can’t seem to finish any of them. The problem isn’t starting anymore; it’s finishing.
Now, starting is frictionless. I can describe an idea and get scaffolding, functions, and even UI components in seconds. It's amazing.
But now I’ve got 50 half-finished projects instead of 5 and 45 ideas.
The problem isn’t starting anymore. It’s finishing.
The Bottleneck Has Moved
Before AI coding tools, every new project required a real investment:
- Setting up boilerplate
- Digging through API docs
- Writing from scratch
The friction was real. And it was good—it filtered out weak ideas and forced clarity.
Now the bottleneck has shifted. The technical hurdle is gone. The new hurdle is discipline. Choosing which projects to finish. Saying no to the others.
Productivity Theater, AI Edition
It’s easy to confuse activity with progress.
With these tools, I’m productive every day. I generate code, spin up ideas, explore new approaches. But most of it goes nowhere. It runs—but it doesn’t ship. There’s no documentation, no feedback loop, no users.
It’s productivity theater. All build, no release.
Code ≠ Product
Here’s what most of my AI-assisted projects lack:
- A clear user story
- Polish and testing
- Any plan for distribution
I’ve gotten good at building, but building isn’t the same as delivering. AI makes it feel like you're almost done, but most of the work is still ahead—product design, feedback, iteration, support.
From Infinite Starts to Focused Finishes
The shift I’m working on now is this:
Use AI to accelerate the middle, but slow down the start—and finish what I begin.
Some strategies that help:
- Shipping backlog: I keep a list of active projects, max 3 at a time
- Kill or commit: Each week I archive or move forward every stalled project
- One-in, one-out: I don’t start a new idea until I finish something
And I treat AI like a junior teammate: helpful for execution, but not in charge of strategy.
Less Building, More Finishing
The power of these tools is real. They give us superhuman velocity. But that velocity needs direction.
The goal isn’t to generate more code. It’s to deliver more value.
Less building. More finishing.