You know that sinking feeling when you read about yet another ‘revolutionary’ AI-built project, only to realize it’s a hollow shell with borrowed words? That’s not innovation. That’s a costume.
Take this recent scheme: A pure Scheme web server inspired by Erlang’s fault tolerance — hot code swapping, remote retry rings, continuations on the web, sexpr RPCs. The ambition? Stunning. The execution? Embarrassing.
A top comment cuts through the noise: “Another 2 day old vibe coded project. The premise is great, but it’s pretty apparent that no thought was put into it. They couldn’t even be bothered to write their own text for the web site.”
Let that sink in. Someone dreamed of merging two of the most profound programming paradigms — Erlang’s let-it-crash resilience and Scheme’s call-with-current-continuation — and then used ChatGPT to write the landing page copy.
The tragedy of modern tech isn’t failure — it’s the illusion of success built on a foundation of AI-generated sand.
This isn’t an edge case. It’s the new normal. Every day, developers flood Hacker News and GitHub with ‘innovative’ projects that are actually just prompt-engineered wish fulfillment. The code compiles. The demo runs. But ask the creator why they chose a particular abstraction or how their continuation-passing style handles a critical failure, and you get silence. Because the AI wrote it. The human didn’t understand it.
We’ve convinced ourselves that if it compiles and runs, it’s good enough. But it isn’t. You haven’t built something just because you can generate it in an afternoon. You’ve built a facade.
The original insight behind this project — merging Erlang’s fault-tolerant actor model with Scheme’s first-class continuations — is genuinely brilliant. It’s the kind of deep, cross-paradigm thinking that pushes computer science forward. But it requires a developer who has wrestled with both worlds. Who has debugged a process crash at 3 AM. Who understands that a continuation is not just a ‘time-travel’ trick, but a fundamentally different control flow model.
That depth can’t be vibed into existence.
AI doesn’t make you a better engineer. It makes you a faster typist. And right now, the entire industry is confusing typing speed with architectural insight.
We need to stop celebrating the shallow and start demanding the deep. The next time you see a project that claims to fuse two esoteric paradigms, ask: Did the author write their own readme? Did they explain the design tradeoffs? Or did they just paste a prompt and hit deploy?
Because real engineering isn’t about what you can generate. It’s about what you can defend. What you can explain to a skeptical colleague. What you can debug when the AI’s hallucinated logic unravels at 2:00 AM.
That’s the difference between a vibe and a system. Choose wisely.
FAQ
Q: Isn't this just a prototype? People start somewhere.
A: Prototypes are fine, but calling a 2-day AI-generated hack 'a pure Scheme webserver inspired by Erlang' is misleading. The ambition sets expectations of deep architectural understanding. When that understanding is absent — and the site copy is AI-written — it's not a prototype; it's a marketing gimmick that dilutes real engineering.
Q: What should developers do instead of 'vibe coding'?
A: Use AI as a tool, not a crutch. Generate a skeleton, but then spend time <em>understanding</em> every line. Write your own documentation. Explain your design decisions. If you can't defend a piece of code in a code review, you don't own it. Real engineering means being able to rebuild the system from scratch, not just prompt it.
Q: Isn't AI coding actually good for prototyping and exploration?
A: Yes, for low-stakes exploration and boilerplate. But when you're claiming to combine Erlang's fault tolerance with Scheme's continuations — that's high-stakes architecture. AI excels at regurgitating patterns, not at deep integration. If you can't articulate the tradeoffs yourself, you're building a house of cards that will collapse under production load.