Continuous Improvement Automation

AI-Powered Feedback Loops

Note that agent loops don't work very well yet

graph LR
    A[Codebase] --> B(GPTDiff Analysis)
    B --> C{Identify Improvement}
    C --> D[Generate Patch]
    D --> E[Apply Changes]
    E --> F[Verify]
    F --> A

Core While Loop Pattern

while true; do
  gptdiff "<improvement-prompt>" --apply
done

Test Enhancement Recipes

Missing Test Case Detection

# Continuously analyze test coverage gaps
while :
do
  gptdiff "Identify and add missing test cases for edge conditions" \
    --apply \
    --temperature 0.3
done

Improvements Per Cycle:

1. Null input handling tests
2. Boundary value validations
3. Error state simulations
4. Concurrent execution checks

Flaky Test Remediation

while true; do
  gptdiff "Find and fix intermittent test failures by adding retries/cleanup" \
    --model deepseek-reasoner \
    --apply
done

Code Quality Automation

Tech Debt Reduction Loop

while true
do
  # Prioritize worst code first
  gptdiff "Refactor functions with high complexity scores" \
    --apply \
    --temperature 0.1
done

Security Hardening Daemon

while :; do
  gptdiff "Find and fix OWASP Top 10 vulnerabilities" \
    --apply \
    --model deepseek-reasoner
done

Documentation Syncing

Code-Docs Alignment

while true;
do
  gptdiff "Update documentation to match current implementation" \
    --apply \
    --temperature 0.5
done

Performance Optimization

while true; do
  gptdiff "Identify and optimize slow database queries" --apply
done