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Beyond efficiency: PayPal expands what's possible to build with AI
Summary
PayPal describes how it used Cursor to accelerate software development across an organization of 8,000 developers and a codebase spanning decades. It began with high-impact teams because the company moves money for more than 400 million customers and mistakes are costly; within two weeks, those teams were deploying daily rather than weekly or biweekly, and adoption spread organically. The company says a Java upgrade across 3,000 applications took two months instead of an estimated eight to twelve, while highly adopting teams saw more frequent deployments, shorter lead times, and lower change failure rates. PayPal continues to measure deployment frequency, lead time, and change failure rate rather than AI-generated code, and Michelle Chance believes the company could deliver 40% more capabilities in 2026 than in 2025.
Context
PayPal needed to adopt AI while moving carefully because it handles money for more than 400 million customers worldwide, making the cost of mistakes high. Its large scale includes 8,000 developers and a codebase spanning decades, while the company wanted to increase development speed and remain competitive with startup-level delivery.
Approach / What changed
PayPal rolled out Cursor first to high-impact teams building products where speed to market was essential. It measured deployment frequency, lead time from idea to production, and change failure rate, while avoiding AI-generated-code percentages as a productivity metric. Adoption then spread organically as engineers observed results from other teams.
Takeaways
Teams with high Cursor adoption, many exceeding 90%, moved from weekly or biweekly deployments to daily or multiple deployments per day, with shorter lead times and lower change failure rates.
PayPal’s software process shifted from a linear design-code-build-deploy lifecycle toward rapid prototypes and iteration, with product managers and engineers exchanging functioning prototypes and roles becoming less finite.
PayPal does not measure success by the percentage of AI-generated code because that could encourage verbose functions and distort developer behavior; it retains deployment and delivery metrics instead.
Source and freshness
- Source
- cursor.com
- Published
- Added to Yomu
- Last updated
Summaries are generated from the original by a language model. Check the original before relying on it.
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