Series · 1 parts
Experimentation for Business
A practical guide to making better decisions with data — from statistical foundations to experimentation culture
Most teams ship changes based on intuition, seniority, or loudest voice.
Some add metrics dashboards. A few run A/B tests. But very few build a rigorous experimentation practice that connects engineering decisions to business outcomes.
This series is about bridging that gap — giving engineers and engineering leaders the statistical foundations, practical techniques, and organisational patterns to make better decisions with data.
The central question:
How do you move from "we think this is better" to "we know this is better" — and build a culture that demands the difference?
Inspired by David Sweet's Experimentation for Engineers, this series translates rigorous experimentation methods into practical guidance for teams building software products.
We'll cover:
- Why experimentation matters — and what goes wrong without it
- The statistical foundations you actually need
- Designing and running A/B tests that produce trustworthy results
- Adaptive methods like multi-armed bandits
- Bayesian optimisation for complex parameter tuning
- Building an experimentation culture that scales
The goal is not to turn every engineer into a statistician. It's to make experimentation a natural part of how your team builds.