Skipper, Airbnb’s embedded workflow engine, is now open source
Durable workflows, running inside your service with no separate orchestration cluster.
Durable workflows, running inside your service with no separate orchestration cluster.
We benchmarked a fine-tuned E2B model against frontier APIs on a real production classification task. It matched their quality in under 100ms, at about a hundredth of the cost.
How we addressed the cold-start problem for Airbnb’s natural language search by jointly generating synthetic training data — queries and relevance labels — from de-identified booking and search signals.
How we capture real production database traffic at Airbnb and replay it offline to load-test, plan capacity, and de-risk upgrades.
How Airbnb uses proximity signals to personalize without relying on individual user history.
How Airbnb built a lightweight workflow engine to solve durable execution.
From defensive end to cloud security engineer, meet Jonathan Woodard.
How Airbnb built forecasting models resilient enough to survive a global pandemic and whatever shock comes next.
How we changed our Observability as Code alert review process and cut development cycles from weeks to minutes.
How Airbnb rolled out 20+ locally relevant payment methods worldwide in just 14 months
2025 was a big year for research at Airbnb, as we made significant progress toward our mission to use AI, data science, and machine learning to become the best travel and living platform.
A more powerful engine and a simpler API for our data-oriented mesh
How to achieve high availability with distributed database on Kubernetes.
New techniques we’re using at Airbnb to improve and maintain performance of SwiftUI features at scale
Comprehensive Load Testing with Load Generator, Dependency Mocker, Traffic Collector, and More
A deep dive on the framework that lets us identify the most valuable listings for our guests.