Matthew Sinclair talks about how AI can help programmers scrap the code they—or rather, the AI—has written and start over when they realise the approach won’t work, may lead to technical debt, or for any of thousands of other reasons, because new code can be generated fairly quickly.
Working with Claude Code has fundamentally shifted how I think about the economics of programming time. Traditionally, coding involves three distinct “time buckets”:
- Why am I doing this? Understanding the business problem and value
- What do I need to do? Designing the solution conceptually
- How am I going to do it? Actually writing the code
For decades, that last bucket consumed enormous amounts of our time. We’d spend hours, days or weeks writing, debugging, and refining. With Claude, that time cost has plummeted to nearly zero. I can generate thousands of lines of functional code in a sitting—something that is, frankly, mind-blowing.
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And there’s a new skill that emerges: wielding the knife. With code generation being essentially free, we need to become much more comfortable with throwing away entire solutions. The sunk cost fallacy hits programmers hard—we hate discarding code we’ve invested in, fearing we might break something important or never get back to a working state.
But when your assistant can rewrite everything in minutes, that calculus changes completely. Three times during my backend project, I looked at substantial amounts of code—thousands of lines that technically worked—and decided to scrap it entirely because the approach wasn’t right. This wasn’t easy. My instinct was still to try to salvage and refactor. But the right move was to step back, rethink the approach, and direct the AI down a different path.
This willingness to cut ruthlessly is a muscle most developers haven’t developed yet. It requires confidence in your architectural judgment and a radical shift in how you value implementation time.