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“however good your inputs are will dictate how good your output is”
What It Means
AI output quality is directly proportional to input quality - garbage in, garbage out
Why It Matters
Establishes fundamental principle that most AI development problems stem from poor inputs, not model limitations
When It's True
Always, but especially with modern high-capability AI models
When It's Risky
When used to excuse genuinely poor AI model performance or capabilities
How to Apply
Audit your prompts and requirements when getting poor AI outputs
Invest time in detailed planning before development
Focus on improving input clarity before trying different tools
Example Scenario
“Developer gets poor results from AI coding tool, realizes their requirements were vague, rewrites with specific technical details and gets excellent results”
Related Knowledge
Input Quality Determines Output Quality
The fundamental rule that AI agent outputs are directly proportional to the quality, precision, and completeness of inpu
if something is working, then probably you can copy it and put your own spin on it
Success patterns can be replicated and improved rather than starting from scratch