There’s a paradox in modern computing: computers today are faster, more powerful, and sleeker than ever before, yet they often feel slower when doing everyday tasks. How can this be true? The answer lies in a growing mismatch between hardware advancements and software development practices.
The Promise of Moore’s Law
You’ve probably heard of Moore’s Law, the observation made by Gordon Moore in 1965 that the number of transistors in an integrated circuit doubles approximately every two years. This doubling translates to exponential growth in computing power. For decades, this trend held true, allowing computers to become faster and more capable at an astonishing rate.
But while hardware performance has skyrocketed, the way we write software has changed dramatically, and not always for the better.
The Reality of Modern Software
In the early days of computing, resources were scarce. Developers had to be highly efficient, squeezing every ounce of performance out of limited hardware. Programs were carefully written to minimize memory use and maximize speed. But today, those constraints are less pressing. Why? Because hardware is “fast enough” to accommodate less efficient software. Or at least, that’s the assumption.
Take modern applications: instead of being optimized for speed and efficiency, they’re often bloated with unnecessary features, redundant processes, and layers of abstraction. Think of a simple text editor. In the past, it might have been a few kilobytes in size, designed to launch instantly and use minimal system resources. Today’s equivalent might consume hundreds of megabytes, taking seconds to load, even though it fundamentally performs the same function.
The Bandwidth vs. Processing Paradox
While internet bandwidth and storage capacities have dramatically increased, the responsiveness of software hasn’t kept pace. Consider web applications. Are they twice as fast as they were two years ago? Probably not. The complexity of modern web technologies—frameworks, plugins, and bloated libraries—often offsets the benefits of faster internet and improved hardware.
An Embarrassing Anecdote
Here’s a real-life example of the inefficiency problem. A developer needed to
number the lines of a text file. Instead of using a built-in Unix utility like
nl, which does this instantly, they wrote a Python script that looped through
the file line by line. The script was not only redundant but far slower than the
existing tool.
Why did this happen? Likely because the developer wasn’t familiar with the utilities already available on their system. This lack of awareness is increasingly common. Instead of learning to use efficient, purpose-built tools, many programmers default to reinventing the wheel, often less effectively.
The Layers of Abstraction
Another culprit is the growing reliance on layers of abstraction. Modern software often sits atop frameworks, libraries, and APIs that insulate developers from the underlying hardware. While abstraction makes development faster and more accessible, it can also lead to inefficiencies. For example, a web application might load dozens of unnecessary libraries to perform a single task, consuming memory and processing power needlessly.
The Snowball Effect of Inefficiency
When everyone writes inefficient code, the inefficiencies accumulate. The result? Computers that are orders of magnitude more powerful than their predecessors often feel just as slow—or slower—because they’re bogged down by bloated software.
This trend is particularly noticeable in areas like:
- Web browsers, which consume gigabytes of RAM to load basic websites.
- Operating systems, which include countless background processes and telemetry features.
- Games, which rely on technologies like DLSS or FSR to compensate for inefficient rendering pipelines.
The Path Forward
The solution isn’t to stop using modern tools or frameworks—they’ve made incredible advancements possible. But we do need to strike a balance. Developers should:
- Learn the Basics: Familiarize themselves with existing tools and utilities. Why write a script when a built-in command will do?
- Focus on Efficiency: Write code that’s not just functional but also optimized for performance.
- Avoid Unnecessary Complexity: Use only the features and libraries truly needed for the task at hand.
- Adopt a Minimalist Mindset: Sometimes, less is more.
Conclusion
As computers continue to grow more powerful, it’s crucial that we don’t take this progress for granted. Moore’s Law may keep advancing hardware capabilities, but it’s up to us to ensure that software development keeps pace. Otherwise, we’ll be stuck in a world where faster computers only mean slower programs.