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The Problem
Most senior engineers eventually hit a wall where AI feels like it’s making more work than it’s saving.
The Cause
This happens because “vibe coding”—writing a prompt and hoping for the best—does not scale to enterprise codebases filled with “invisible constraints” like:
- Unwritten architectural patterns
- Complex dependency chains
- Legacy system integrations
- Team-specific conventions
The Reality Check
AI isn’t a “magic black box” but a system with predictable failure modes:
- Confident hallucinations: AI generates plausible-looking but incorrect code
- “Helpful” refactors: Changes that seem good but break unrelated code
- Context blindness: Missing critical constraints outside the immediate scope
The solution isn’t to abandon AI—it’s to evolve how we work with it. 
