Khan Academy went from vibes-based prompt testing to running A/B experiments on their AI tutor, Khanmigo, in production. Kelli Hill shares the journey, including a fascinating iterative case study on latency vs. math accuracy.
GrowthBook 4.3 Release: Run experiments 20% faster using post-stratification, metric drilldowns for deeper insights, and feature evaluation diagnostics. Plus Rust & Roku SDKs.
Stop guessing what works and start knowing: A/B testing transforms hunches into data-driven decisions, turning every change on your website from a risky bet into a calculated experiment that can boost conversions without spending more on traffic.
Khan Academy went from vibes-based prompt testing to running A/B experiments on their AI tutor, Khanmigo, in production. Kelli Hill shares the journey, including a fascinating iterative case study on latency vs. math accuracy.
Tired of high-stakes deployments and 3 AM rollbacks? Learn how feature flags let you decouple deployment from release so you can ship with confidence.
Type-safe feature flags in React catch silent bugs before production. Learn to auto-generate TypeScript types with GrowthBook and stop shipping broken flags.
A feature flag platform ends up in critical paths: request handlers, render paths, mobile startup flows, and incident response. Most
Prolog: Is A/B Testing Here to Stay? In the age of AI, there is a growing debate about how
GrowthBook 4.3 Release: Run experiments 20% faster using post-stratification, metric drilldowns for deeper insights, and feature evaluation diagnostics. Plus Rust & Roku SDKs.
Real data from The Social Hub shows just how much you can save with GrowthBook.
Stop relying on "vibe checks" to ship GenAI. While AI Evals answer "can the model do the job?", only A/B testing answers "do users care?" Discover how to combine offline evaluation with online experimentation to build a reliable pipeline for shipping LLM features.
Why optimizing for short-term A/B test wins can degrade user trust and product quality. A look at common dark
Only 10–30% of experiments produce a clear winner — and that’s not a problem, it’s reality. This article shows how high-performing teams design experiments to learn faster and make better decisions, even when results are neutral.
GrowthBook 4.2 introduces Product Analytics (beta), a Statsig migration kit, and enterprise-scale enhancements. One platform for features, experiments, and analytics.
In under two minutes, GrowthBook can be set up and ready for feature flagging and A/B testing, whether you use our cloud or self-host.
