BreakpointThe post appears to address stability in Jetpack Compose. The body was unavailable, so no technical details or concrete takeaways could be verified.
Booking.com engineering blog
How Booking.com scales a shared DWH across multiple teams without turning governance into a delivery bottleneck.
How Booking.com scales a shared DWH across multiple teams without turning governance into a delivery bottleneck.
This post explains why standard A/B testing can mismeasure opt-in product features in digital marketplaces, especially when voluntary adoption and user heterogeneity create dilution and selection bias. It proposes combining Randomized Encouragement Design with Double Machine Learning to estimate both the causal lift for adopters and the overall rollout impact, helping teams distinguish product quality problems from adoption-funnel problems.
How a seemingly simple AWS API call can silently slow down your CI/CD pipelines.
Scaling Experimentation Quality at Booking.com Authors: Edgar Cano, Daisy Duursma, Nils Skotara, Melanie Mueller. The post appears to discuss how Booking.com improves the quality and reliability of experimentation at scale.
Our experience using Backstage at Engineering Portal. This talk explores Booking.com's journey toward a unified developer experience and how Backstage supports that effort.
This post describes how Booking.com migrated its backup catalog for more than 250 MySQL clusters to AWS. It highlights the engineering approach used to modernize the system and improve reliability.
This post is an internship announcement for a GenAI and machine learning PhD research role. It invites candidates to help shape travel experiences using AI and ML.
The necessity of imperfection: Designing for distributed ownership in Backstage. The article discusses how to design internal platforms that support distributed ownership and scale across many developers.
This post explains how Booking.com applied supervised fine-tuning to improve travel recommendations beyond prompt engineering. It shares practical learnings from using model training techniques to make recommendations more useful.
A talk from Tech Leads Summit 2025 that explores cognitive and organizational biases that can derail engineering decisions, from hiring to product trade-offs. It highlights common traps such as confirmation bias and sunk cost fallacy and discusses approaches to mitigate them in team and product contexts.
AI Agent Evaluation: practical tips at Booking.com. The post shares lessons and practical advice for evaluating AI agents and judging model behavior.
This roundup highlights Booking.com’s publications from 2025. It summarizes notable work across research and applied machine learning.
Constrained Best Arm Identification To be presented in NeurIPS 2025. The post discusses a research contribution related to experimentation and decision-making under constraints.
This post describes Booking.com’s work on building a GenAI agent for partner-guest messaging. It likely covers how generative AI can support communication workflows between partners and guests.
A talk describing a system for automatically detecting dormant AWS accounts (inactive for 60 days) and safely cleaning them up using multi-step notifications and deletion workflows. The presentation details design decisions and automation strategies used to optimize cloud costs at scale.
A talk that examines how optimizing for specific metrics can produce perverse or misleading outcomes and offers a practical two-step framework for building metrics that encourage real progress rather than box-ticking. It provides guidance for product and analytics teams to create more robust measurement practices.
This post explains how to estimate correlations between metrics using historical A/B tests. It focuses on experimentation analysis and practical statistical methods.
This recap summarizes the 2025 Experimentation Conference at Booking.com. It highlights key themes and takeaways from the event.