Why did retry loops with error feedback outperform carefully engineered prompts?
A single perfect prompt has to anticipate every failure mode in advance, which is nearly impossible across thousands of unique files. A retry loop instead feeds the model its own concrete failure — the exact validation error from the last attempt — so each retry corrects a specific, known problem instead of guessing blind. Most files needed only one or two retries to pass.
Answered in
How to Migrate Thousands of Legacy Test Files With LLMs, Not RewritesA step-based pipeline, retry loops instead of perfect prompts, and rich context injection turn a year-long manual migration into a six-week automated one.
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More development best practices questions
- Why is a large-scale test framework migration usually so slow to do by hand?
- When does a migration pipeline need rich prompt context instead of just retries?
- How do you migrate the last 3% of files that automation can't fully finish?
- Does this approach only work for test framework migrations?
- What is Project Polaris and how does it relate to GitHub Copilot?
- What architecture does Project Polaris use?
- How does Project Polaris perform compared to GPT-4 Turbo on coding benchmarks?
- Can teams still use GPT-4 Turbo in Copilot after the Polaris rollout?
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