In the fast-paced world of software development, every second counts. From compiling code to running tests, the tools developers use directly impact their efficiency and ability to stay in the coveted ‘flow’ state. But is investing in top-tier hardware truly worth it, or is it an unnecessary expense?
The Developer Hardware Dilemma
- Corporate Underinvestment: Many companies, even large tech giants, are often ‘penny-wise and pound-foolish’ when equipping their developers. This can lead to significant lost productivity.
Employers, even the rich FANG types, are quite penny-wise and pound-foolish when it comes to developer hardware.
- Proven ROI for Premium Hardware: Data suggests that the cost of high-spec machines is quickly recouped through increased developer output. One FAANG study showed ROI in weeks for senior developers.
The cost benefit showed a reasonable ROI that was realized in Weeks for Senior dev salaries (months for juniors).
- Evolving Performance Landscape: While older CPUs can still be functional for many tasks, modern desktop CPUs offer substantial generational improvements, particularly in multi-core performance. A 50% cumulative improvement often justifies an upgrade.
- Flow State Enhancement: Reducing waiting times, even by seconds, can prevent developers from getting distracted, keeping them focused and productive. Compile times, in particular, are critical here.
30s is long enough for a developer to get distracted and go off and check their email, look at social media, etc. Basically turning 30s into 3s can keep a developer in flow.
Unpacking the Productivity Bottlenecks
- Misguided Corporate Frugality: Companies fear hardware abuse, leading to strict approval processes for powerful machines, despite the cost being a small fraction of a developer’s salary.
To be fair, I know plenty of people that would order the highest spec MacBook just to do web development and open 500 chrome tabs. There is abuse.
- Software Bloat and Inefficient Code: Some argue that modern software is excessively bloated, and faster machines merely mask poor coding practices. This raises questions about whether hardware upgrades enable or discourage efficiency.
I wish developers, and I’m saying this as one myself, were forced to work on a much slower machine, to flush out those who can’t write efficient code.
- Identifying True Bottlenecks: A faster CPU isn’t always the silver bullet. Performance can be limited by I/O, memory, or other system components, meaning a CPU upgrade alone might not yield desired gains.
What if the compiler is IO bound? Or memory bound? Removing one bottleneck will get you to the next bottleneck, not necessarily get you all the performance gains you want
- Complex Upgrade Path: Upgrading a CPU often entails replacing the motherboard, cooler, and memory, essentially requiring a new computer, making it a more significant investment than just a chip.
Besides, usually it is not simply “a faster CPU”: sockets and chipsets keep changing, so that would also be a new motherboard, new CPU cooler, likely new memory, which is basically a new computer.
Smart Strategies for High-Performance Devs
- Justify with Data-Driven ROI: Presenting a clear cost-benefit analysis based on saved developer time can effectively advocate for better hardware. The investment often pays for itself rapidly.
I did the math on allocating developers machines with 16GB vs 64GB based on actual job tasks with estimates of how much thumb twiddling waiting time that this would save and then multiplied that out by the cost of the developer’s time.
- Strategic Upgrade Cycles: Instead of yearly upgrades, aim for a refresh every 3-4 years, or when a ‘massive change’ in architecture (like Apple’s M-series chips) offers significant cumulative performance gains (e.g., 50% improvement).
Everywhere I have worked has upgraded developers every 3-4 years, and it might make sense to upgrade if there is a massive change (like when Macbooks went to M-series).
- Prioritize Top-Spec for Productivity: For software engineers, investing in the highest-spec available (e.g., MacBook Pro) and upgrading regularly is often the most cost-effective approach. This is particularly true for performance-sensitive tasks like compilation.
I strongly believe that if you’re providing hardware for software engineers, it rarely if ever makes sense to buy anything but the top spec Macbook Pro available, and to upgrade every 2-3 years.
- Consider Thermal Solutions for Laptops: When choosing high-end laptops, prioritize models with robust thermal management to ensure sustained performance and prevent throttling. The CPU’s power efficiency is also key.
The limiting factor on high-end laptops is their thermal envelope. Get the better CPU as long as it is more power efficient. Then get brands that design proper thermal solutions.
