Software Development Used to Be Slow

There was a time, not long ago, when the ultimate bottleneck in tech was engineering hours. We had to meticulously plan, write, test, and deploy our code. By far the most resource-intensive phases were the planning and the actual typing of code. This reality birthed a well-known industry maxim: "An hour of a developer’s time is worth more than a missed millisecond of a user’s time."

For a long time, this was completely justified. We had to ship features to survive. It was infinitely more important to get code working and bugs squashed than it was to make every function mathematically perfect. After all, who would notice a tenth of a second?

Well, for one, I do.

While the average user might not be able to articulate why a platform feels snappy, they can instantly tell you when it feels sluggish. On paper, the difference between 0.1 seconds and 0.5 seconds sounds pedantic. In practice, when it comes to user experience and perceived responsiveness, it is the chasm between a seamless flow and a frustrating stutter. Yet, the old adage persisted, treating performance as a luxury we simply couldn’t afford.

Was It Ever Actually True?

When planning sprints, we have historically treated performance optimisation as a "nice-to-have". There was always a higher-priority feature or a more critical bug competing for our attention. But the math behind dismissing "just 0.1 seconds" has always been fundamentally flawed.

Consider the compounding effect of scale. If a single request is delayed by 0.1 seconds:

100 requests add up to an extra 10 seconds.
1,000 requests cost 100 seconds.
10,000 requests waste 16.7 minutes.
1,000,000 requests swallow 27.8 hours of aggregate time.

If you are running a serverless architecture, like AWS Lambda or Azure Functions, you aren't just wasting your users' time; you are actively draining your company's bank account. Because these services bill by the millisecond, inefficient code is a direct, measurable tax on your infrastructure budget. Suddenly, the argument that developer time is too expensive to spend on optimisation falls apart. Inefficient code is a recurring drain on your budget.

Beyond the balance sheet, there is the psychological impact. A button click that reacts instantly builds user confidence. It makes the application feel robust, reliable, and premium. A laggy UI does the exact opposite. We have all used Jira and if you haven't I am jealous.

Enter the AI Era: No More Excuses

Even if you bought into the old argument that performance tuning was a nicety, the rise of generative AI completely obliterates that excuse.

AI has radically accelerated the standard development lifecycle. We are generating boilerplate, writing initial drafts, and scaffolding applications faster than ever before. This newfound efficiency has handed us an incredible gift: time. The hours we used to spend wrestling with syntax or hunting down missing semicolons have been refunded to us.

We no longer have an excuse to ship bloated, unoptimised code under the guise of "budget constraints."

Take that database query that has been taking 3 seconds to run. Instead of putting it off for another sprint, you can now throw it into Claude, Composer, GPT, or Gemini (if you hate yourself) and ask it to write a more performant version.

The risk-to-reward ratio has shifted entirely. If the AI-generated query doesn't yield a speed boost, you’ve lost about thirty seconds of your day. But if it works, you've just shaved seconds off your runtime, lowered your cloud bill, and salvaged your user experience: all for the cost of a single prompt.

AI has commoditised the creation of code. As developers, our value is shifting from how fast we can type to how deeply we can refine. It’s time to stop hiding behind old adages, embrace the extra time we've been given, and start making software fast again.