Tech Leaderism

Small Batches

In the book "The Lean Startup", Eric Ries presents a compelling argument for working in small batches, an idea that seems simple on the surface but has far-reaching implications for how we approach technology and operations.

The principle is straightforward: instead of building large, complex systems or features in one go, break the work into small, testable, and releasable chunks. Ship early. Learn fast. Repeat.

To illustrate this, Ries uses an example from a traditional office setting. Imagine you need to send out 100 newsletters. One approach is to fold all 100, then stuff all 100 into envelopes, then add stamps to all 100. The other approach is to fold, stuff, and stamp one newsletter at a time. The second method, despite seeming slower, is almost always faster overall. Why? Because problems are identified sooner (a misfit envelope, a missing component), and the process becomes more efficient with real-time learning and iteration.

This logic applies directly to IT. Working in small batches allows you to:

- Deliver software incrementally through Agile methods

- Test and deploy frequently via CI/CD

- Make controlled, reversible infrastructure changes

- Detect and resolve issues quickly due to a smaller change surface

Small batches create faster feedback loops, reduce risk, and encourage continuous improvement. They help teams stay aligned, deliver value sooner, and adapt to uncertainty with more confidence.

By contrast, big batch approaches delay learning, compound complexity, and increase the likelihood of failure.

Whether you're writing code, managing infrastructure, or launching new products, adopting a small batch mindset can lead to better outcomes across the board.