Table of Contents

Coming Soon — Early 2026

This in-depth technical series is currently in preparation. It will explore real-world performance gains with Mojo through progressive optimisation of Conway's Game of Life.

What to Expect

I'll take a detailed journey from pure Python through NumPy to multiple Mojo versions, including:

• Honest benchmarks on real hardware (not vendor cherry-picks)
• Performance attribution — what's Mojo-specific vs language-agnostic
• Documented failures — including optimisations that made things worse
• When Python+NumPy is already good enough (often!)
• Real ROI calculations for business decision-making
• Reproducible code you can run yourself

This series aims to answer: Can typical Python developers achieve 10–100× speedups on realistic problems? Where does Mojo truly shine, and where should you stick with existing tools?

In the Meantime

While you wait, explore:

• A Python-to-Mojo Sleigh Ride — gentle side-by-side introduction
• 10–100× Faster, Private AI for Mid-Sized Firms — business case and use cases
• Mojo 1.0 Roadmap — production-ready timeline
• Modular's Conway's Game of Life Tutorial — official hands-on guide

Check back soon, or comment below to be notified when this series launches.