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Most startups don't fail because of bad code.
They fail because they build too much before talking to users.
After working on production systems and startup products, I've noticed the same mistake again and again.
Everyone wants to build the "perfect" product.
More features.
More screens.
More integrations.
But your first version only has one job:
Validate the idea.
When I think about an MVP, I ask three simple questions:
✅ Does this feature solve the user's main problem?
✅ Can we launch without it?
✅ Will users actually notice if it's missing?
If the answer to the last two questions is "No", it doesn't belong in version one.
A successful MVP isn't the one with the most features.
It's the one that gets into users' hands the fastest.
Perfect products don't win.
Products that get real feedback do.
What's one feature you removed from a project that turned out nobody missed?
The network for creativity
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Stop overengineering your MVP.
Devs pick microservices, Kubernetes, and a 12-tool CI/CD pipeline
for an app with zero users.
Most things I've shipped ran on Next.js, PostgreSQL, and one VPS.
One deploy script. Complexity got added only when something
actually broke.
Write the least code that solves today's problem. You can refactor
when scale demands it. You can't get back the six months you spent
building infrastructure nobody needed.
Your architecture should be embarrassing until it can't be.
#WebDevelopment #SoftwareEngineering #NextJS #Freelance
"I can't start until I find a technical co-founder" is how good ideas die in someone's Notes app for 18 months.
You don't need a co-founder to get a working prototype. You need 3-7 days and someone who'll build it without asking for equity.
Validate first. Recruit later.
I was hired to engineer a founder's product.
Then something unexpected happened.
We started having weekly sessions where I wasn't just building the product for him, I was teaching him how to build with AI himself.
We work through the things that actually matter:
→ Turning ideas into buildable features
→ Using modern AI development tools
→ Connecting APIs, MCPs, and automations
→ Debugging AI-generated solutions
→ Making better technical decisions
And when something requires deeper engineering, architecture, or implementation, I take ownership of it.
I think this is where AI-native product development is heading:
Founders don't need to become developers.
They need to become better at building with AI.
That's the kind of technical partnership I want to build with founders.
🎥 Sharing a short clip from one of our sessions.