Smell #3: Context Flood
Context Flood: Providing massive amounts of unstructured code or documentation to an AI in a single prompt. This "big dump" overwhelms the model's reasoning capacity and leads to generic or buggy output.
Symptoms
How to recognize this smell in your workflow:
- [ ] You are pasting 1,000+ lines of code into a single chat turn.
- [ ] The AI response says "I've updated your code" but ignores half of your constraints.
- [ ] The AI "hallucinates" variables or functions that don't exist in your project.
- [ ] Your AI API bill is exploding due to massive token usage per prompt.
Self-Assessment
If you checked 2+ items, you are flooding your AI context.
Example
Bad Pattern (The Context Dump)
❌ "Here is my entire App.jsx (1,347 lines) and my server.js (583 lines).
Add real-time notifications using WebSockets."
Why it's bad: The AI's "attention" is split across 2,000 lines of noise. It might propose a WebSocket solution that ignores your existing Redux state or security middleware because those details were "lost in the middle" of the flood.
Clean Alternative (Curated Context)
✅ "I have a React app using Redux. I want to add real-time notifications.
Here is the relevant Redux slice (50 lines): [code]
Here is the existing API structure: [docs/api.md]
Implement the WebSocket handler following our existing auth pattern."
Why it's better: High signal-to-noise ratio. The AI can focus its reasoning on the specific task at hand.
Debt Impact
This smell contributes to:
| Debt Category | Impact | |---------------|--------| | 🏗️ ARCH | AI makes assumptions about global state that lead to tight coupling. | | 💸 FIN | Token waste leads to escalating API costs. |
How to Fix
- Audit Dependencies: Look for "Implicit Coupling" created during flooded sessions.
- Modularize Context: Break your documentation into small, high-signal files.
- Refactor for Decoupling: Fix the "Magic Threads" that the AI created between distant modules.
How to Prevent
- The 500-Line Limit: Try to keep the provided code context under 500 lines per turn.
- Reference, Don't Paste: Use tools like
@filein Cursor or specialized context-loading rules. - Standardized Instruction Files: Use
.cursorrulesto provide high-level context without re-pasting it.
Related Smells
- Smell #7: Hidden Dependencies — A direct result of context flooding.
- Smell #6: Magic Black Box — Flooded AI often produces opaque logic.
Book Reference
- Chapter 3: Context is King — how more information ≠ better understanding.
- Chapter 13: Clean Prompts — the "Curated Context" methodology.