Clarity first, code second.
I used to think complexity was a sign of seriousness.
If a feature needed a long explanation, I assumed it was sophisticated. If a workflow required caveats, I assumed users would adapt. If the architecture diagram got denser, I assumed the product was maturing.
I was wrong.
Most of the time, if I can't explain something clearly, one of two things is true: either I don't understand it well enough yet, or it shouldn't exist in the product in that form.
That became a hard rule for me: if I can't explain it, I don't build it.
This isn't about dumbing things down. It's about forcing precision before code hardens ambiguity. Software has a way of turning fuzzy thinking into expensive maintenance. You can hide confusion in implementation details for a while, but eventually it surfaces in support tickets, user hesitation, brittle integrations, and features nobody trusts under pressure.
As a solo founder, I feel this faster than most teams. Every unclear decision comes back to me later as operational drag. Every poorly defined behavior becomes documentation debt. Every "we'll clarify this later" turns into a branch of complexity that never really gets pruned.
The explainability test is simple.
Before I build something, I try to answer in plain language:
What is this?
Who is it for?
What decision does it improve?
What happens when it fails?
If those answers are vague, the implementation is not the next step. The next step is sharper thinking.
I've learned that technical depth and clear language are not opposites. In good systems, they reinforce each other. When a behavior is clearly explainable, architecture usually improves. State boundaries get cleaner. Failure modes become more explicit. Naming gets better. Testing becomes more direct because the intent is legible.
When it isn't explainable, code tends to grow around exceptions. You start adding one-off flags, special branches, hidden assumptions, and fallback paths that feel necessary only because the core model was never clean.
That's how products become hard to reason about.
I also use this rule in user-facing decisions. If a feature needs a paragraph of warnings before someone can safely use it, that's a design failure, not a user failure. Users should not need to reverse-engineer intent from a settings panel.
Clear behavior is a trust feature.
There's a founder-level benefit too: speed.
When I can explain a change in a few direct sentences, prioritization is faster. Tradeoffs are clearer. Release notes are easier to write. Feedback is easier to interpret because users are reacting to concrete behavior, not fuzzy abstractions.
It also makes saying no easier. A lot of "good ideas" collapse when you try to explain exactly what they do and why they matter. That's useful. It prevents me from spending weeks building something that looked valuable only at a distance.
I still build complex systems. I just don't allow unexplained complexity.
If I can't explain it clearly, I keep working the model until I can, or I drop it.
That rule has saved me from shipping features that were technically impressive but operationally weak.
And over time, I've come to trust it more than almost any planning framework: clarity first, code second.