Story · arXiv
Self-evolving Agentic Customer Support System at LinkedIn (arXiv)
paper · Story page
LinkedIn's support agent improves without model retraining, running retrieval, evolutionary prompt optimization, and evaluation as one versioned, guarded loop. A two-week production A/B test lifted QA self-serve 9.0 percentage points, cancellation self-serve 4.8, and routing accuracy 30.6.
In plain words
- LinkedIn built a customer support system that improves without retraining the artificial intelligence behind it.
- It updates the instructions, searches company information for answers, and checks each version against tests.
- Safety rules and saved versions let LinkedIn control changes and compare them with earlier versions.
- In a two-week production test, self-service improved by 9.0 percentage points for questions and 4.8 points for cancellations.
- The reported gains matter to customers seeking answers and support teams trying to direct requests correctly.
Appeared in
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Aug 13, 2026 · in the sections
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