The challenge of diminishing returns when using AI to complete software projects
Core Idea: AI coding tools enable rapid initial progress (about 70%) on software projects, but completing the remaining 30% becomes increasingly difficult due to complexity and knowledge gaps.
Key Elements
The Challenge
- Non-engineers using AI for coding hit a wall after achieving 70% completion
- Initial progress feels magical and creates false expectations
- The final 30% becomes an exercise in diminishing returns
- Completing production-ready software requires engineering knowledge beyond what AI provides
The Two Steps Back Pattern
- Attempting to fix a small bug leads to a cascade of problems:
- AI suggests a seemingly reasonable fix
- The fix breaks something else
- Fixing the new issue creates two more problems
- A cycle of regression begins
- Particularly painful for non-engineers lacking mental models to understand root causes
- Creates a whack-a-mole situation with code they don't fully understand
Root Causes
- Knowledge Gap: Users lack understanding of underlying systems and principles
- Debugging Deficit: Without established debugging skills, fixing issues becomes increasingly difficult
- Architecture Limitations: AI-generated code often lacks robust architecture needed for maintenance
- Edge Case Handling: The "happy path" works, but edge cases remain unhandled
- Technical Debt: Quick initial progress often comes at the cost of accumulated technical debt
Strategies to Overcome
- Use AI as a learning tool, not just a code generator
- Take time to understand how generated code works
- Learn basic programming concepts alongside AI usage
- Build a foundation of knowledge gradually
- Accept that production software still requires real engineering knowledge
Additional Connections
- Broader Context: Learning Curve Paradoxes (similar patterns in other domains)
- Applications: AI for Prototyping (where the 70% can be valuable)
- See Also: Refactoring AI-Generated Code (techniques for improving the final 30%)
References
- Field observations of non-engineers using AI coding tools
- Tweet by Peter Yang highlighting the 70% problem
#ai-coding #software-development #learning-curves #technical-debt
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