
When Your Vibe Coded App Goes Viral—And Then Goes Down
Lessons learned when vibe code meets high load
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At 4 a.m. on the day after we launched our agent-native document editor, Proof, I watched yet another Codex agent try to revive our server.
Over 4,000 documents had been created since launch, but the app had been mysteriously crashing all day. This left users with crucial documents that they couldn’t access, and me with egg on my face.
I hadn’t slept for almost 24 hours, and all I could do was nervously munch trail mix as Codex investigated yet another bug buried deep in a codebase that I didn’t understand. It felt less like programming and more like being the dumbest participant at a math Olympiad. Needless to say, I was reconsidering my life choices.
Today, almost a week later, Proof is more or less stable. And I’ve learned a lot about both building and launching a purely vibe coded app. Perhaps more importantly, I’ve also learned what happens once that app goes live—and then goes down.
My current opinion is this: If you can vibe code it, you can vibe fix it. You just might not be able to fix it quickly.
Software engineering is changing rapidly as a discipline. The days of typing code into a computer manually seem to be over, and the current conversation on X is around “zero-human startups.” My experience with Proof, though, is a good reality check.
It demonstrates both what is truly possible with vibe coded apps, and where human engineers will continue to be critical now and in the future.
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What’s possible at the edge
I’ve been writing about how AI is changing programming for a few years now, and my experience with Proof confirms a lot of my thoughts...
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- What it took to bring a crashing, vibe coded app back from the brink
- The specific failure modes coding models keep hitting
- Why allocation is the new key skill for human engineers
Thanks to our Sponsor: MongoDB
Auto-scale AI workloads with ease
Traditional databases struggle with unstructured data, slowing AI workflows. MongoDB natively handles JSON-like, unstructured data, giving you freedom to store, query, and scale diverse datasets—whether text, images, or sensor data—easily and flexibly, without rigid schemas.
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