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WorkThe story, in brief

How Datadog Used Claude and Cursor for Test-Driven Production Migration

Datadog didn't just use Claude and Cursor for prototypes. They shipped a full production migration on AI.

Reporting by InfoQ AI/ML 1 min brief
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The KeyNews take

Why it matters

Real-world case study of how enterprise teams are deploying AI coding tools (Claude, Cursor) to solve hard infrastructure problems at scale—moving beyond pilots to critical system overhauls. Shows practical adoption patterns and lessons learned that other engineering leaders need to understand.

The key facts

11 to know

  1. Datadog used Claude + Cursor for test-driven production migration

  2. Project involved overcoming storage backend hard limits

  3. Significant performance improvements achieved

  4. Production system (not pilot) involved in migration

  5. Engineer-authored lessons learned shared publicly

  6. Focus on what worked vs. what didn't

  7. Datadog production migration case study

  8. Tools: Claude + Cursor for test-driven development

  9. Use case: Storage backend optimization and performance improvement

  10. Focus: Practical lessons learned, not theoretical

  11. Source: Datadog engineer Arnold Wakim via InfoQ

Go to the source

InfoQ AI/MLinfoq.com

Publisher excerpt: In a recent article, Datadog engineer Arnold Wakim shared what worked, what didn't, and the lessons they learned while evolving a critical production system using AI to overcome hard limits in its storage backend and significantly improve performance. By Sergio De Simone
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