The one simple habit of “starting thinner” will help you build faster & with way less frustration
There’s a concept from software engineering that almost nobody talks about in vibe coding and product builder circles. It’s been “discovered” over and over through decades of software engineering and yet goes there’s little alignment on what it’s called (see end note). But what’s important is that it might be the single most useful mental model for anyone building software using AI in 2026.
It’s called a steel thread.
Think about how a bridge gets built. You can’t just start from both sides and hope they meet in the middle — you need foundations, supports, careful sequencing. It’s inherently methodical and sequential. Real-world construction forces you to build piece by piece before you can test if the whole thing works.
Software can be different. You can string a steel thread across the entire river on day one. A thin wire from one bank to the other. It’s not a bridge yet. You can’t drive trucks across it. But you’ve just proven the most important thing: that you can get from one side to the other, in the right place. From there, you build it out progressively. First, someone can pull a bucket across. Then walk across. Then ride a bike. Eventually, you’ve got a full bridge with lanes for cars, bikes, and pedestrians.
That’s the steel threads approach. You build the thinnest possible working end-to-end version first, then expand from there.
The piece-by-piece approach — and why it stalls
Most builders start by building each piece, then connecting them. It’s an intuitive approach. You’ve got a slick frontend. You’ve got the data and maybe a database schema. Maybe you’ve got an API. They’re all well thought out in isolation. Then comes the connection phase… and you discover the data shape your frontend assumes doesn’t match what your database has, and your API is entirely different again. The auth layer you built first has no idea about the user model you built directly in the data schema. Everything needs to be retrofitted. A few months ago, you’d be back to the drawing board, but today you’re still left wasting time and tokens putting your square peg into a round hole.
There’s a reason most AI builders end up here. It’s the intuitive way to think about building things. Finish each component, then assemble. It’s how you’d build furniture, or a house, or a car… If you’ve been here, that probably means you’re a logical thinker. But software is different from the physical world, and this approach consistently creates the same headache: your first real test of whether everything works together comes right at the end, when you have the least amount of time and flexibility to fix it.
Why steel threads especially matter when you’re building with AI
When you’re prompting an AI to build something, it will happily do whatever you ask… including building things that don’t connect to each other. AI doesn’t feel integration pain. It doesn’t get that low-grade anxiety of “wait, how do these two things actually talk?” the way an experienced engineer does. Sure, you can prompt it to make sure it’s integrated along the way, but then you’re halfway to adopting the full steel threads approach anyway. Might as well go all in.
But there’s another risk: if you haven’t defined a thin enough steel thread before you start building, you’re asking the AI to hold too much in its head at once. It’ll misinterpret your requirements. It’ll make reasonable-sounding decisions that conflict with decisions it made five prompts ago, and it’ll rewrite all your code for no good reason. You’ll burn through time and tokens watching it work on something impressive that turns out to be subtly wrong or only slightly better than what you had 15 minutes ago. The more you try to specify all at once, the more likely things are to drift from what you actually wanted.
A well-defined steel thread fixes this. You’re giving the AI a narrow, concrete goal with a clear definition of done. One input, one output, working end-to-end. That’s how you work systematically through your checklist of features and requirements. Once that thread exists, every subsequent prompt has something real and functional to build on.
What this looks like in practice
Say you’re building an AI-powered reporting tool. The intuitive approach: build the data pipeline, build the analysis layer, build the UI, then try to connect everything. The steel threads approach: get one report — the simplest possible one — to run all the way through. Hardcode whatever you need to. Skip edge cases. Make it ugly. Ship that first.
It’ll feel slow. It won’t feel impressive. But from that moment forward, you have a working system you’re expanding — not a collection of parts waiting to be assembled.
Before you write your next big prompt, ask yourself: what’s the thinnest path through this system that actually does something real? Build that first. Then build the bridge.
Note: The concept of steel threading isn’t remotely new. I was originally exposed to the concept by my engineering counterpart many years ago. More recently, I’ve shared the link to this article by Jade Rubick many, many times. But I found myself sharing a growing chunk of additional context each time. So here we are, with a new article. Like most engineering principles, it goes by many names including: vertical slices, walking skeleton, spike solution, and even “tracer bullets” (The Pragmatic Programmer, 1999).