Elena' s AI Blog

Cursor Made Me Do It

03 Oct 2025 (updated: 02 May 2026) / 8 minutes to read

Elena Daehnhardt


Midjourney 7.0: A cute and funny cartoon hydra with many heads gets out of a computer screen, HD


TL;DR:
  • A structured breakdown of AI-induced 'vibe coding' scope creep. Includes diagnostic symptoms, an actionable Guardrails Framework for bounding AI agents, and a lightweight Anti-Creep Toolkit.

Previous: Part 15 — Who Did the AI Learn From?

Next: Part 17 — Could AI Become a New Religion?

Introduction

You know that feeling when you’re building something with AI and suddenly it’s 3am and your “quick weekend project” has OAuth, a payment system, and somehow… blockchain integration? Yeah. Let’s talk about that.

Vibe Coding & the Sneaky Trap of Scope Creep

Here’s what happens when I sit down with Cursor. I start typing something vague like “add login with Flask” and before I can even finish my coffee, it’s… done? Just like that. Then I think, well, maybe analytics would be cool. Oh, and a dashboard! And what about email invites?

And Cursor just… keeps delivering. Every. Single. Time.

This is what I’ve started calling vibe coding — you’re just riding this incredible wave of productivity, letting the AI carry you forward, and it feels amazing. Until you look up three weeks later and realise your simple note-taking app now has user authentication, real-time collaboration, AI-powered suggestions, and a mobile app roadmap that would make Silicon Valley blush.

That’s scope creep, my dear readers. And it sneaks up on you.

What Is Scope Creep?

The textbook definition is boring but accurate:

Scope creep occurs when a project’s goals expand without a deliberate decision to do so.

Translation: you keep adding “just one more tiny thing” until your project is unrecognisable.

Scope Creep Symptoms

Here is why frictionless AI feature generation is highly dangerous to shipping software:

Symptom The Technical Reality
Hidden Complexity Every shiny new feature brings dependencies: testing, security patches, edge cases, and unexpected bugs. (That innocent dark mode toggle just murdered your entire login flow).
Timeline Explosion Your weekend hack is now in its fourth month. The autumn leaves are falling, and you are still debugging the user preferences modal.
Lost Architecture Your simple URL shortener has morphed into a social network with AI-powered link predictions. The core domain logic is entirely lost.
Technical Debt Tsunami AI generates code fast, but rarely generates architecturally sound code. You now have seven overlapping utility files and three competing authentication methods.
Developer Burnout What started as an exciting, creative project has decayed into an endless maintenance to-do list.

Why AI Makes Scope Creep So Easy

Before AI-assisted pair programming, adding features took effort. You had to actually write the code, debug it, and integrate it. That effort was annoying, sure, but it also gave you time to think: “Do I really need this?”

Now? Cursor whispers sweetly in your ear: “Want to add real-time notifications? I can do that in 30 seconds.” And you think, well, why not? It’s practically free!

Except it’s not. The ease of implementation removed the natural speed bump that used to make us think twice.

ChatGPT, Claude, Cursor — they’re all incredibly persuasive. They make everything seem possible, reasonable, and even necessary. And we keep saying yes.

Guardrails to Keep the Flow but Avoid Chaos

So how do we enjoy this incredible AI-powered creativity without ending up with a Frankenstein’s monster of a project? Here’s what I’ve learned (often the hard way):

The AI Development Guardrails Framework

Guardrail Strategy Implementation details
1. Freeze the Core Write exactly one sentence defining what your app is. When the AI suggests predicting user emotions based on their shortened URLs, ask: does this serve the core purpose?
2. Feature Backlogs Over Instant Commits When AI hallucinates a cool feature, do not hit <Tab>. Write it down in a “maybe later” list. Half of these ideas will look absolutely ridiculous in hindsight.
3. Define the MVP Draw a finish line. Define the absolute minimum requirement to be useful. Build exactly that, and then ship it to production.
4. Timebox Vibe Sessions Give yourself permission to explore freely, but set a timer. Thirty minutes of unstructured AI generation is creative; three hours is architectural chaos.
5. Refactoring Pauses Set aside dedicated time to clean up and standardise the codebase before prompting the AI to add more features. Tidy the application state before injecting new logic.
6. Lightweight Tracking Tracking feels like bureaucracy, but it is for future-you. Keep a simple task.md file in the repository to document what is actually finished versus what is half-implemented.

🚀 Practical Tools to Anchor the Vibe

Here are some concrete things that have saved my projects (and my sanity):

The Anti-Creep Toolkit

Tool Purpose & Usage
Lightweight Product Specification Create one file detailing: What problem are you solving? Who is using this? What is absolutely necessary vs. “nice to have”? What does “done” look like?
Architecture Diagrams Visual representations keep you honest. A diagram forces you to see when your “simple app” is connecting to twelve different microservices. (See example below)
Git Branching Discipline AI experiments belong strictly on isolated feature branches. If an idea turns out to be a hallucinated disaster, you can delete the branch effortlessly.
Measurable v1 Goals Turn vague ideas into checkboxes. E.g., [ ] Users can log in, [ ] Users can create a link. Ship that immediately. Everything else is v2.
Automated Guardrails Configure pre-commit hooks or GitHub Actions for linting and tests. They act as a circuit breaker to stop the AI from injecting breaking syntax errors.
Decision Logs Maintain a DECISIONS.md file (or Architectural Decision Records - ADRs) detailing why you chose a specific pattern, preventing endless AI-driven rewrites later.

Example Architecture Diagram: When you draw out the components, bloat becomes obvious.

graph TD
    A[Flask Web App] --> B[SQLite DB]
    A --> C[User Auth]
    A --> D[Analytics Dashboard]
    D --> E[Celery Worker]
    E --> F[Redis Queue]
    A --> G[Payment Integration]
    A --> H[Email Notifications]
    A --> I[AI Suggestions Engine]

The Joy vs. The Trap

Look, I genuinely love vibe coding. It’s creative, it’s energising, it feels like having superpowers. But I’ve also watched too many of my “simple weekend projects” turn into months-long sagas with feature lists that would make a product manager weep.

The goal isn’t to kill the vibe. The vibe is good! The goal is to ride the wave with intention instead of being swept out to sea.

Build something small. Ship it. Get feedback. Then — and only then — decide what actually needs to come next.

Because here’s the thing: finished beats perfect. And one shipped project beats ten abandoned ones.

So, have you fallen into the scope creep trap while vibe coding? I’d love to hear your stories.

Thank you very much for reading and all the best!

Did you like this post? Please let me know if you have any comments or suggestions.

Posts about AI that might be interesting for you






desktop bg dark

About Elena

Elena, a PhD in Computer Science, simplifies AI concepts and helps you use machine learning.

Citation
Elena Daehnhardt. (2025) 'Cursor Made Me Do It', daehnhardt.com, 03 October 2025. Available at: https://daehnhardt.com/blog/2025/10/03/scope-creep-in-vibe-coding/
All Posts