# AI Feature Creep Guillotine

> AI identifies the 20% of features consuming 80% of your time so you can cut them and actually ship

**Category:** Dev
**Keywords:** ai, feature creep, shipping, pareto, mvp, project planning, scope, prioritization, product, AI-powered
**URL:** https://complete.tools/ai-feature-creep-guillotine

## Why projects don't ship

Feature creep kills more software projects than technical debt, bad architecture, or team conflict combined. The pattern is consistent:

1. You plan a reasonable set of features
2. Each feature looks simple on the surface
3. Implementation reveals nested complexity: auth edge cases, API rate limits, mobile compatibility, error states, admin interfaces
4. Timeline doubles, motivation drops, the project dies

**Common time-sink features disguised as "simple":**
- User role management (looks simple, involves complex permission trees)
- File uploads (storage, processing, CDN, previews, virus scanning)
- Real-time features (WebSockets, fallbacks, reconnection logic)
- Search functionality (indexing, ranking, filters, pagination)
- Email notifications (templates, deliverability, unsubscribe flows)
- Mobile responsiveness for complex interactions
- Third-party integrations (OAuth, webhooks, versioning)

## How to use

1. Write a brief description of what you're building
2. List your planned features — one per line or as a bullet list
3. Select your project type and team size
4. Click "Run the Guillotine" and let the AI analyze your list
5. Review the three categories: Must Ship, Cut These, and Defer to V2
6. Read the hidden complexity warnings carefully
7. Commit to the lean MVP summary before you start building

## Understanding the verdict

**Must Ship** — These features are genuinely core to the product. Without them, you don't have a product worth shipping. These are non-negotiable.

**Cut These** — These features have hidden complexity that will consume disproportionate time. They may seem simple but involve authentication edge cases, third-party dependencies, mobile compatibility issues, or infinite polish rabbit holes. Cut them entirely from v1.

**Defer to V2** — These are good ideas that don't belong in the initial launch. They're not time-sinks per se, but they dilute focus and slow the critical path. Ship v1 first, add these later when you have real user feedback to validate them.

**Hidden Complexity Warnings** — Specific landmines in your feature list that aren't immediately obvious. Read these carefully — they often reveal that a feature you thought was trivial is actually a multi-week project.

## FAQs

**Q:** Should I always follow the AI's recommendations?


**A:** Use them as a starting point for discussion, not a final verdict. The AI applies general software development heuristics. Your specific context — team expertise, existing infrastructure, customer commitments — may justify keeping some "cut" features.


**Q:** What if the AI cuts a feature my users specifically asked for?


**A:** That's important signal. If a feature was specifically requested by paying customers or is in a signed contract, override the AI's recommendation. The tool is most useful for features that came from internal "wouldn't it be cool if..." discussions.


**Q:** How specific should my feature list be?


**A:** More specific gives better results. "User management" is vague. "Users can invite team members via email, set roles (admin/viewer/editor), and see an activity log" gives the AI enough detail to identify the real complexity.


**Q:** What is the 80/20 rule in software development?


**A:** The Pareto principle applied to development suggests that approximately 80% of your development time will be consumed by roughly 20% of your features — typically those with hidden complexity, edge cases, or infrastructure requirements. Identifying and cutting those features early is the most leveraged thing you can do to ensure a project ships.

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*Generated from [complete.tools/ai-feature-creep-guillotine](https://complete.tools/ai-feature-creep-guillotine)*