The Vibe Coding Graveyard
Aug 21, 2025
Vibe coding is the feeling you get when the machine meets you halfway.
You describe what you want in plain language. You gesture at an interface. You paste a spreadsheet. You say: “Make it like Airbnb but only for telescopes,” or “Turn these Zoom calls into meeting notes with action items and a Zap to Slack.” And the thing, this modern, eager, silicon apprentice, builds you a first draft. You correct it. It revises. You nudge. It snaps into place. You press “Run,” and for a few shining minutes, it all works. You ship a prototype in a weekend. You ship an MVP in a week. If you’re charming, stubborn, and lucky, you ship an MLP,a minimum lovable product, before your latte cools.
That first act, the high of it, is real. It feels like a cheat code: software without the software engineer, code without the coding. It’s intoxicating, and the world has never seen a better on-ramp. This is the moment people use words like “superpowers,” and they aren’t wrong.
But if you keep going, if you add users, data, rules, permissioning, payment flows, versioning, analytics, mobile, localization, compliance,the ground tilts. You hear creaks in the rafters. Yesterday’s prompt unravels today’s feature. The magic turns moody. You discover the place I call the Vibe Coding Graveyard: a quiet valley filled with abandoned apps that were amazing for twelve days and impossible on day thirteen.
This essay is about that valley, why so many projects end up there, and how the 2%,the true vibe coders, make it out, ship real products, and prove that technical expertise isn’t a barrier to launching. The difference isn’t access to an LLM or a no-code builder. Everyone has those now. The difference is patience, process, and perseverance when the vibes get messy.
What Vibe Coding Is
Vibe coding isn’t a tool. It’s a posture.
It’s the decision to substitute classical accuracy with conversational iteration. It biases toward “describe and refine” over “design and implement.” You trade up-front precision for speed and a human feedback loop. You let the model produce the first wrong answer faster than you could have written the first right spec.
Practically, vibe coding looks like this:
You write natural-language instructions instead of APIs.
You ask for concrete examples instead of drawing schemas.
You correct with screenshots and scribbles instead of diffs.
You accept an imperfect draft because you can fix it in five more turns.
And it works brilliantly at small scale. Most applications are 80% scaffolding: UI, CRUD, routing, auth, a few webhooks. Vibe coding devours scaffolding. It knows what a signup form looks like, how a Kanban board behaves, what “upload a CSV and show a chart” means. You get a ton “for free.”
Prototypes, MVPs, MLPs
The best version of vibe coding feels like storyboarding with a responsive crew:
“Give me a landing page that promises ‘Tax deductions in 5 minutes.’ Top nav: Pricing, Docs, Login. CTA: ‘Start Free.’”
“Upload a PDF and extract vendor names and amounts. If confidence < 0.8, ask the user to confirm. Store in a table.”
“Create a ‘Plans’ page: Free (100 docs), Pro (10,000 docs), Business (unlimited). Stripe checkout. Monthly and annual toggle.”
You type. It builds. You click. It works. You iterate three times and it’s presentable.
At this stage, the most common wins are:
Shape discovery. You can make the idea “visible,” compare variations, and throw most of them away cheaply.
Narrative truthing. Showing a working thing forces precise thinking about onboarding, pricing, and value.
Momentum. You stop pitching your friends on a vision and start sending links.
If the product is narrow enough and the audience forgiving, you can live in this phase for a long time. Many small utilities never need to graduate. That’s not failure; it’s an efficient match between ambition and complexity.
When Apps Get Big
The trouble starts when your app becomes a system.
Systems have invariants, facts that must always be true. “No user can see another company’s data.” “An order can’t be ‘shipped’ unless it’s ‘paid.’” “A refund cannot exceed the original amount.” In code, those invariants live in types, validation, transactions, and tests. In vibe coding, they live in your head and your prompts, until they don’t.
Here are the friction points that create the cliff:
State explosion. As features multiply, the states and transitions between them grow combinatorially. A chatty back-and-forth is poor at encoding deep state machines.
Cross-cutting concerns. Logging, auth, i18n, caching, retries, rate limits, things that slice across every feature, are invisible until they’re on fire.
Ambiguity drift. Natural language is squishy. The model that understood “customer” yesterday may confuse it with “account” tomorrow if your examples shift.
Backwards breakage. A prompt that improves page A unintentionally breaks page B because both relied on a shared but unstated rule.
Observability gaps. You get a broken behavior but no stack trace, no error class, no reproducible failing test. Only vibes.
This is the path to the graveyard: a series of small regressions that make you fear touching the thing you built, followed by one final push that breaks signups on a Friday night. You promise to fix it in the morning. You don’t.
The Graveyard: Why Projects Die
Projects die for boring reasons:
Nobody writes down the invariants.
Nobody versions the prompts.
Nobody saves the working examples.
Nobody separates “public contract” from “internal implementation.”
Nobody knows which change broke it.
Everyone is scared to roll back.
Vibe coding encourages improvisation, which is its power. It also encourages forgetting, which is its cost. The graveyard is full of apps that were one checklist away from surviving.
The 98% vs the 2%
Here is the blunt difference.
The 98% want the magic trick to keep working at the same speed forever. When it doesn’t, they assume they’ve hit the ceiling of the tool. They get frustrated by regressions, by “why did it do that?” They stop at the first nasty tangle of logic. The project drifts into the graveyard.
The 2% accept that the trick changes after the honeymoon. They change with it. They still use plain English and try-error iteration, but they add patience and ritual. They will restate the same rule ten different ways. They will isolate a failing behavior into a tiny reproducible case and rehearse it with the model until it cannot fail. They will let the model break yesterday’s page, then calmly shepherd it back. They are gardeners, not magicians.
The 2% aren’t necessarily technical, but they learn to think like an engineer about process while staying non-technical about syntax. That’s the future founder advantage: you don’t need to read every stack trace, but you do need a method.
The Vibe Coder’s Method: Practices of the 2%
Here’s a field-tested, plain-English method that keeps you out of the graveyard without turning you into a compiler.
1) Write Acceptance Criteria in English, then Fix to Them
Before you “just build it,” write a tight paragraph of what “done” means.
Who is acting?
What are the inputs and outputs?
What must never happen?
What happens on error?
How will we know it works?
Example:
“When a user uploads a bank statement CSV, we map columns: Date, Description, Amount. We detect duplicates by (Date + Description + Amount). If any row is missing Amount, the import pauses and shows a review screen. No more than 10,000 rows per upload. On success, we show a summary: total rows, duplicates skipped, net new.”
Paste that paragraph into every iteration. It becomes your guardrail.
2) Capture Golden Examples
For each feature, maintain a tiny set of “golden” inputs and the exact outputs you expect. Think of them as flashcards. Use them to retrain the model every time something slips.
Five ideal CSVs.
Five tricky CSVs (weird separators, negative amounts, missing headers).
The correct summaries for each.
Inline those examples in your prompts. Examples beat philosophy.
3) Version Everything, Even Prompts
Name things. Save drafts. Tag the good ones.
“ImportSpec v1.1 – introduces duplicate detection”
“OnboardingFlow v2.3 – adds 2FA, preserves guest checkout”
“EmailTemplates v0.9 – transactional only”
When a regression appears, roll back to a known-good prompt. This is not fancy. It is a folder of text files with dates. But it’s the difference between a small detour and a lost weekend.
4) Freeze Contracts, Flex Internals
A public contract is the behavior you promise to users (and to yourself). Internals can morph. Make that separation explicit in English:
“The shape of the ‘Transaction’ record is: id, date, description, amount, currency, account_id. That shape cannot change without a migration. The way we parse it can change.”
Remind the model of your contracts often. Paste them in. Don’t apologize.
5) Put Tests in Plain Language
You don’t need Jest to test a vibe-coded flow. You need a checklist.
“Upload sample A → expect 1,000 rows, 42 duplicates, total amount $12,345.67.”
“Try to import sample B with missing Amount → expect error message ‘Amount required’ and a review screen.”
“Turn on annual billing → expect Stripe link with price_id ‘price_annual_01’.”
Run the checklist before and after you change anything. If you can’t run it manually every time, you’re building too much at once.
6) Shrink the Problem
When something breaks, make it smaller until it obeys you. If the model keeps generating the wrong SQL for a complex query, isolate the query. Cut out the app. Give it only the schema and three rows of data. Get the query perfect. Then paste it back into the app.
Models get jumpy in busy rooms. Give them a quiet desk.
7) Maintain a Glossary
Confusion kills. Create a living glossary of the terms in your product.
Account vs. Workspace vs. Company
Customer vs. User vs. Admin
Project vs. Job vs. Task
Write one-sentence definitions with examples. Paste the glossary into your longer prompts. The more your words stay still, the more your app stays put.
8) Log Like a Journalist
You won’t get stack traces, so write logs for humans:
“User 183 uploaded ‘jan.csv’: 1,037 rows, 32 errors (missing Amount).”
“Mapped columns: Date→col2, Description→col3, Amount→col4 (inferred).”
“Duplicates removed: 19 (hash = date+desc+amount).”
If a behavior surprises you, add a log line that would have made it obvious. Future-you will thank you.
9) Separate “What” From “How”
Structure prompts with two sections:
What must be true: the acceptance criteria, the invariants, the glossary terms.
How to approach it: the preferred data structure, helper functions, performance hints, or “first try a simpler method.”
The “what” should outlive any single implementation. The “how” can change every day.
10) Practice Prompt Minimalism
Overlong prompts are mud. Keep them tight. Use numbered steps. Prefer examples over adjectives. Replace “optimize” with a specific goal: “fewer than 50ms,” “no more than 10 API calls,” “don’t regenerate HTML, only update text content.”
Shorter prompts are easier to maintain and reuse.
11) Expect and Budget for Regressions
Regressions aren’t evidence that vibe coding “doesn’t work.” They’re evidence that you’re building something real. Budget time each week to re-run golden examples, harvest surprises, and update your contracts.
The 2% treat regressions as tuition.
Who Need Engineers? Or do you..
You can ship more than you think without deep technical skills. You can also waste a year pretending you don’t need any.
Here are honest markers that you should bring in an engineer or raise your own ceiling:
Performance matters. You have >100k records, heavy joins, or knotted front-end state. Models can rewrite a slow query; they cannot invent an indexing strategy tuned to your dataset without feedback you probably can’t supply.
Security matters. AuthZ is tricky. Token leakage is common. PII and compliance (HIPAA, SOC2, GDPR) are not vibe-friendly.
Concurrency matters. Background jobs, idempotency, retries, race conditions, these bite. You can describe the invariants, but somebody has to wire up guarantees beneath them.
Interfaces harden. You now integrate with banks, ERPs, or payment gateways. They will yank your chain. You need durable, testable adapters.
You’re building a platform, not an app. Extensibility, plugin systems, SDKs, versioning, deprecation policy, these require architectural choices that deserve deep care.
This is not a concession. It’s a strategy. Vibe coding is a multipler even when you have engineers. It accelerates specs, mocks, tests, and scaffolding. It keeps the team in human language longer and makes the code better.
The Founder’s Guide for Vibe Coding
If you want a repeatable loop, use this operating system:
Narrative
Write a one-page story of the user flow. Screens, buttons, outcomes. No technical words.Acceptance Criteria
Turn the story into a checklist. Capture risks and “never” statements.Glossary & Contracts
Define terms; declare shapes (fields, required/optional).Examples
Create golden inputs/outputs that demonstrate happy paths and edge cases.Scaffold
Use the model to generate the first UI and data storage with minimal logic, wired to logs.Pin What Works
Save the prompts and outputs that feel right. Tag them. Version them.Iterate Feature by Feature
One invariant at a time. One edge case at a time. Keep tests nearby.Telemetry
Add human-readable logs for every surprise. Add a simple “health page” that summarizes counts, recent errors, and suspicious patterns.Release Notes
In plain English, write what changed and what you tested. Future-you is an important stakeholder.Weekly Regression Ritual
Re-run golden examples. Fix drift. Update contracts. Only then add something new.
This loop is boring, which is why it works.
Prompts Are Product
The biggest mental shift: prompts and examples are not ephemeral. They are the product.
Treat them like code:
Store them in a real repo (even if you never run a build).
Name them. Tag them. Archive them when retired.
Write short READMEs for each feature’s prompt pack: “Inputs, outputs, invariants, known weaknesses.”
When a teammate or collaborator arrives (designer, marketer, contractor), they should understand the product by reading these documents. No IDE required.
Teams, Roles, and the “LLM Wrangler”
Vibe coding doesn’t eliminate roles. It changes them.
Founder/Product: Owns the story, acceptance criteria, glossary, and contracts. Decides “what must be true.”
LLM Wrangler: Crafts prompts, curates examples, performs the weekly regression ritual, and keeps a tidy library of golden cases.
Engineer: Hardens the system, security, data modeling, migrations, performance, observability, release automation.
Designer/Researcher: Keeps the user truth close. Translates usability tears into acceptance criteria you can actually test.
One person can wear multiple hats. The point is not titles. The point is honoring each kind of work as distinct and necessary.
Ethics and Safety, Even for Vibes
Plain language doesn’t absolve you from responsibility.
Privacy: If you touch PII, declare it in your contracts. Mask it in logs. Don’t ship “temporary” hacks that email spreadsheets around.
Attribution: If you generate content, label it. Give users a way to review and override.
Bias & Fairness: Your golden examples are your values. Include edge cases that represent real diversity of inputs and users.
Security: “We’ll fix auth later” is a famous last prompt.
You don’t need a 50-page policy. You do need five sentences you actually follow.
The Future: Why Perseverance Still Wins
Models will keep getting better. Tools will keep getting friendlier. The honeymoon lasts longer each year. Some of today’s cliffs will be tomorrow’s flat roads.
But perseverance remains non-negotiable for two reasons:
Ambiguity never goes away. Users contradict themselves. Markets shift. “What must be true” changes. You will still need to re-articulate your product in words and examples again and again.
Systems still have invariants. Even perfect code generation can’t guess the rules you never wrote down. Someone has to point at reality and say, “That is the rule.” That someone can be you.
This is why the 2%, the ones who keep trying, calmly, will extract the most value. They aren’t better at prompts. They are better at process in plain English. They can sit with a stubborn behavior without flinching. They can keep fixing “yesterday broke” without losing faith. They can hold the product still while the implementation wiggles.
A Short Field Guide (Pin This)
Say what must be true. One paragraph. Paste it everywhere.
Keep five golden examples. Happy and tricky. Update them as you learn.
Version your prompts. Names, dates, notes. Rollbacks are life.
Freeze shapes, flex internals. Contracts are sacred; implementations are cheap.
Log for humans. What happened, why, how many.
Shrink to solve. Isolate the smallest case that fails and win there first.
Glossary beats genius. Shared words, shared world.
Regression is ritual. Not a surprise - a schedule.
Invite help with intention. Engineers for hardness; keep the language human.
Ethics is a feature. If it’s not in your checklist, it’s not in your product.
Walking Past the Graveyard
If you’ve already buried a vibe-coded project, you aren’t alone. The graveyard is big. Some of those tombstones are beautiful. They remind us that making something new is messy and that the line between “toy” and “tool” is crossed in inches, not leaps.
The promise of vibe coding is not that nobody will ever need technical expertise. The promise is that technical expertise is no longer the barrier to starting and, with a method, not a barrier to shipping. The 2% who carry projects across the valley do not trade vibes for rigidity. They trade vibes for discipline at the right moments. They keep the warmth of conversation and add the coolness of contracts. They make the machine meet them more than halfway.
If you want a label, call them founders. If you want a picture, it’s someone at midnight with a cup of tea, rewriting the same acceptance criteria for the fifth time, smiling, because they know that tomorrow the app will behave. It will behave because they made the rules explicit and the examples undeniable. They will paste the paragraph, run the golden files, and ask the model once more, without drama.
And that’s how you leave the graveyard behind: not by avoiding regressions but by outlasting them; not by wishing for perfect tools but by building humane processes; not by “being technical,” but by being relentlessly clear about what must be true.
The rest is vibes. And vibes, with perseverance, ship.