I’ve spent the past six months working at a startup, and it’s been a completely different experience from working at larger, more established companies. The pace is faster, the decisions are more frequent, and the impact of your work is immediately visible. Here are some of the most important lessons I’ve learned.

Ship User Value Every Week

The single most important thing I’ve learned is that you need to deliver value to users consistently and frequently. At a startup, you don’t have the luxury of working on features for months before releasing them. Users need to see progress, and that progress needs to be tangible.

This doesn’t mean shipping half-baked features. It means breaking down big ideas into smaller, valuable increments. Can you ship 20% of a feature that solves a real problem? Do that first. Then iterate.

The weekly cadence keeps you honest. It forces you to think about what actually matters and what’s just nice to have. If you can’t ship something useful in a week, you’re probably working on the wrong thing or thinking too big.

Most Doors Are Reversible

One of the biggest traps I see engineers fall into (myself included) is over-engineering solutions because we’re worried about making the wrong choice. We spend days or weeks debating architecture decisions, trying to predict every possible future requirement.

Here’s what I’ve learned: most decisions you make are reversible. You chose the wrong database? You can migrate. You structured your API poorly? You can refactor it. You picked the wrong state management library? You can swap it out.

Obviously, some doors are one-way. Choosing your core tech stack, deciding on your data model, or making commitments to customers: these are harder to reverse. But they’re rarer than you think.

For everything else, make the decision that lets you ship faster. You can always change it later, and you’ll make a better decision then anyway because you’ll have real data instead of hypothetical scenarios.

You Don’t Need to Scale for a Million Users

This is probably the hardest lesson for engineers to internalize, especially if you’ve worked at companies that operate at scale. We love to think about distributed systems, caching strategies, and database sharding. It’s interesting and intellectually satisfying.

But you know what? You don’t need any of that right now.

A simple setup works fine. One server. One database. A monolith instead of microservices. It’s boring, but it works. And more importantly, it’s fast to build and easy to reason about.

Will it scale to a million users? No. But here’s the thing: if you get to the point where you have scaling problems, that’s a great problem to have. It means you’ve built something people want. It means you have product-market fit. It means you’re going to succeed.

And when you get there, you’ll have the resources and the knowledge to solve those problems. You’ll know where the actual bottlenecks are instead of guessing. You’ll have monitoring and metrics. You’ll have revenue to hire people who specialize in solving these problems.

Premature optimization isn’t just the root of all evil. It’s a startup killer. Every hour you spend building for scale you don’t need is an hour you’re not spending on features that could win you customers.

Ship Simple, Iterate Fast

These lessons all point to the same underlying principle: value speed over perfection. Not because quality doesn’t matter, but because at a startup, learning fast matters more.

You need to figure out what users actually want, and the only way to do that is to put things in front of them. You can’t learn from a feature that’s still in development. You can only learn from something that’s shipped.

So ship simple things. Ship things that aren’t perfectly architected. Ship things that don’t scale. Then iterate based on what you learn.

And if you encounter something that’s an easy fix? Just fix it. You don’t need a ticket in Jira for everything. Saw a typo? Fix it. Found a small bug? Fix it. Notice an inefficient query? Fix it. The overhead of creating a ticket, discussing it, estimating it, and tracking it is often more expensive than just fixing the problem.

The code you write today is probably going to be rewritten anyway. Not because you did a bad job, but because you’ll learn things that change what you’re building. That’s not failure, that’s progress.

Final Thoughts

Working at a startup has taught me to be more pragmatic about software engineering. Perfect architecture doesn’t matter if you run out of money before finding product-market fit. Scalability doesn’t matter if you never get users.

What matters is shipping value to users, learning from their feedback, and iterating quickly. Everything else is secondary.

That’s not to say architecture and scale don’t matter. They do, eventually. But they matter later. First, build something people want. The rest will follow.