Fatbobman's Swift Weekly #146

Photo by Wouter De Praetere on Unsplash

It’s Not That the Models Are Slower—The Tasks Have Become Bigger

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Lately, even tasks that I consider relatively simple often take AI several minutes—or sometimes even tens of minutes—to complete. It gave me the impression that as models become more capable, they somehow have to become slower.

In reality, the main reason lies with me. Although today’s AI agents let us choose different models and reasoning levels, it’s much easier—and often more reliable—to simply hand even straightforward tasks to the most capable models. At the same time, modern agents no longer limit themselves to the small change you explicitly requested. They proactively expand their search, analyze whether the modification could affect other parts of the project, and try to identify potential issues before they happen. The models may be more powerful than ever, but they’re also taking on substantially more work for every task.

There’s another factor as well. As my trust in these models has grown, so has the scope of the tasks I assign to them. What used to be “refactor a function” or “improve a screen” has gradually become “implement a feature,” “build a module,” or even “create an entire product.” Without realizing it, I’ve started treating AI agents as genuine collaborators. The pace at which model performance improves simply hasn’t kept up with the way we now use them.

In other words, developers are no longer pursuing only “writing code faster.” Increasingly, we’re using AI to write better code, even if it takes longer.

The shift from question-answering to task delivery has happened in just a single year. As we grow accustomed to waking up and reviewing completed work, the real bottleneck is quietly moving elsewhere. We used to ask whether a model was capable of completing a task. Today, the more important questions are how to define a clear, verifiable objective, and how to reduce the cost of achieving it. AI is becoming more like a teammate,…