npx skills add ...
npx skills add waynesutton/convexskills --skill avoid-feature-creep
Prevent feature creep when building software, apps, and AI-powered products. Use this skill when planning features, reviewing scope, building MVPs, managing backlogs, or when a user says "just one more feature." Helps developers and AI agents stay focused, ship faster, and avoid bloated products.
npx skills add waynesutton/convexskills --skill avoid-feature-creep
Stop building features nobody needs. This skill helps you ship products that solve real problems without drowning in unnecessary complexity.
Feature creep kills products. It delays launches, burns budgets, exhausts teams, and creates software nobody wants to use. The most successful products do fewer things well.
Feature creep is the gradual accumulation of features beyond what your product needs to deliver value. It happens slowly, then all at once.
Warning signs you're in trouble:
What it costs:
Before adding ANY feature, run through this checklist:
If you can't answer YES to questions 1-3 with evidence, do not build the feature.
Rule 1: Define and Defend Your MVP
Write down exactly what "done" means before you start. Document what you're NOT building. Reference this constantly.
Rule 2: Use Version Control for Scope
Treat scope like code. Track changes. Require approval for additions.
Rule 3: The 48-Hour Rule
When someone requests a new feature, wait 48 hours before adding it to the backlog. Most "urgent" requests feel less urgent after reflection.
Rule 4: Budget-Based Scoping
Every feature has a cost. When something new comes in, something else must go out.
"Yes, we can add that. Which of these three features should we cut to make room?"
Saying no to features is a skill. Here are templates:
To stakeholders:
"That's an interesting idea. Based on our user research, it doesn't solve our core user's top three problems. Let's add it to the v2 consideration list and revisit after we validate the MVP."
To executives:
"I understand the value this could bring. If we add this, we'll delay launch by [X weeks] and deprioritize [Y feature]. Here are the trade-offs - which path should we take?"
To users:
"Thanks for the feedback. We're focused on [core problem] right now. I've logged this for future consideration. Can you tell me more about why this would be valuable?"
To yourself:
"Is this scratching my own itch or solving a real user problem? Would I bet the release date on this?"
To AI agents (Claude, Opus, Codex, Ralph, Cursor):
"Stop. Before we add this feature, answer: Does this solve the core user problem we defined at the start of this session? If not, add it to a DEFERRED.md file and stay focused on the current scope."
When working with AI coding agents:
When building AI-powered products, feature creep has extra risks:
AI Feature Creep Red Flags:
AI Feature Discipline:
Before adding any AI feature, answer:
A messy backlog enables feature creep. Clean it ruthlessly.
Monthly Backlog Audit:
Priority Framework (MoSCoW):
Be honest: Most "Should Haves" are actually "Could Haves" in disguise.
Session Start Check: Before coding with any AI assistant (Claude, Cursor, OpenCode), state:
Mid-Session Check: Every 30-60 minutes, ask your AI: "Are we building the right thing today, or are we adding scope?"
If the answer is "adding scope," stop. Commit what you have. Start fresh.
Session End Check: Before closing an AI coding session:
Daily AI Check: At the end of each day working with AI assistants:
Sprint Planning Guard Rails:
Stakeholder Management: Create a single source of truth for scope decisions:
Agents as Stakeholders: AI coding agents are now stakeholders in your project. They have opinions. They make suggestions. Treat them like any other stakeholder:
Common agent-driven scope creep patterns:
Each of these might be good ideas. None of them are your current scope unless you decide they are.
If feature creep has already happened:
Step 1: Audit Current Features
Step 2: Categorize
Step 3: Remove or Hide
Step 4: Prevent Recurrence
When reviewing any feature request, ask:
If you can't answer these clearly → Do not proceed.
Ship something small that works. Then iterate based on real usage data.
Users don't remember features. They remember whether your product solved their problem.
Every feature you don't build is:
The best products aren't the ones with the most features. They're the ones that do the right things exceptionally well.
"Perfection is achieved not when there is nothing more to add, but when there is nothing left to take away." - Antoine de Saint-Exupéry