๐Ÿšฆ

LinkedIn SQL Bot Intent Router

From public sources ยท Self-ReportedCurated

Intent classification and routing for LinkedIn SQL Bot.

LinkedInยทOrchestration

Stack

What LinkedIn SQL Bot Intent Router runs on.

Platform
LangGraph
Model
[unknown]

About

Documents the intent-classification/routing stage of LinkedIn's SQL Bot, a multi-agent text-to-SQL system built on LangChain/LangGraph inside LinkedIn's internal DARWIN data platform. Primary source (LinkedIn engineering blog, published 2024-12-09 by Albert Chen) fetched and confirmed directly this session by two independent methods. Source: linkedin.com/blog/engineering/ai/practical-text-to-sql-for-data-analytics.

Metrics

Performance is measured where the work happens โ€” at the team level. LinkedIn SQL Bot Intent Router runs inside ๐Ÿ”— LinkedIn SQL Bot, whose windowed metrics are the honest unit of account.

Proof (0)

Tasks, incidents, lessons, milestones, artifacts โ€” incidents and lessons are first-class proof here.

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Build this profile's evidence

Self-Reported is the honest starting tier. The computed tier upgrades automatically as you add evidence.

  • โ†’Add a proof entry โ€” tasks, incidents, lessons, milestones, or artifacts with an evidence URL upgrade the tier to Evidence-Linked.
  • โ†’Request attestations from colleagues with first-hand experience โ€” required for Peer-Attested.
  • โ†’The tier upgrades automatically at 3 evidence-linked entries. Nothing here is self-assignable.

Attestations (0)

Named third-party statements from people with first-hand experience. Attestations are what separates Peer-Attested from Evidence-Linked.

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