🥵 You don’t need long hours to be a TOP software engineer. Make technology your ally, not your enemy

Struggling with long hours? Discover how top software engineers use deep work and AI to boost productivity and accelerate career growth.

Feb 09, 2025

I produce quality work faster by using my time well, and so do you.

I rely on deep work and smart tools to deliver results. My day is structured around high-impact tasks and scheduled recovery. I have learned that output matters more than clocking hours.

The 40-hour workweek was designed at the time of the Industrial Revolution, one that no longer fits the needs of software engineering. Multiple countries in Europe are leading the charge, reducing work hours.

⭐ In this post you'll learn

The origins of the 40-hour workweek and why it's obsolete for software engineers.
How to apply the science of deep work to maximize your productivity.
Practical strategies for leveraging AI to automate tasks and free up time.
How to achieve a better work-life balance through focused work.

🏭 #1 The History of the 40-Hour Workweek (And Why It’s Becoming Obsolete)

The 40-hour workweek has its roots in the Industrial Revolution, when 10-16 hour shifts were common. Labor movements fought for an 8-hour workday, and Ford’s adoption of the 40-hour workweek in 1926 became a standard, later codified by the 1940 Fair Labor Standards Act in the U.S.

However, this model was designed for factory labor, not knowledge work like software engineering. Europe is moving away from the 40 hours. Countries like France and Denmark have already implemented shorter workweeks, and Spain is proposing a 37.5-hour week by 2025. These changes show that a shorter workweek can support better work-life balance and efficient output.

Software engineers don’t need 40 hours to be productive—we need focused work. As I like to say, “What I’m measured for is the output I produce, not the hours I’m around.”

🧪 #2 The Science of Working Less but Achieving More

Deep Work, as defined by Cal Newport, suggests you can only sustain 4-5 hours of focused, high-impact work per day.

Most people waste too much time on shallow work. To maximize deep work, start with 60-90 minute sessions, reduce distractions, and balance intensity with recovery. Sessions over 90 minutes often yield diminishing returns. I've seen that beyond 90 minutes, my mind tends to slow down, and productivity falls off.

AI and automation can free your time for high-impact work. Many engineers still waste time on low-value tasks. AI can automate administrative work, letting you focus on critical thinking. I am super productive since AI became part of my workflow.

Before, I would have been the human in charge of googling the docs of a framework, using an online conversion tool for JSON formatting, or writing all my code for the machine to execute. Now I'm one step back, telling a machine to write code for another machine to execute.

Most engineers aren’t limited by time; they’re limited by how they use their time. With AI, you can ensure you block time for walks, naps, or hobbies to recharge.

⚡ #3 How to 10x Your Productivity (and Career) Using AI Today

My routine has changed significantly since I began using AI tools. I now automate tasks like documentation, scheduling, and drafting meeting notes. When I feed my technical design into an LLM, it produces the answers I need for other documents and tasks, so I can focus on higher impact work.

I use LLMs to speed up reviews and test creation. With AI assistance, I quickly gather a list of concerns and test cases. This helps me create my own artifacts and review the artifacts from others. My feedback is more precise and delivered faster, as I can check the primary sources faster.

One example is that on the first task I took on a project was already an implementation task to create infrastructure with AWS CDK (infrastructure as code). Rather than re-reading the design document I had read a month ago, I asked an LLM for all the configurations the document mentioned for the AWS resources that I had to implement. Then I asked the LLM to compare all the possible configurations and provide me with guidance on what the defaults are, so I could decide if I wanted to update any. This may have taken me 5-10 minutes instead of 1-2 hours from reading and googling around.

🎯 Conclusion

Companies should value results over the number of hours worked. The quality of output is what truly matters. I have redefined my workflow by focusing on what I produce rather than how long I work.

Experience matters for sure, but the tools do too. What I was doing in one week, I'm doing in one day. By combining deep work with AI-driven automation, I keep my workload within a 40-hour week without compromising on quality. My process lets me finish work faster, allowing extra time for learning and personal projects. I believe that smart work leads to faster career growth.

I'm planning on writing about my framework for productivity with AI, one that you can apply to work, personal projects, or even your life.

Identify and automate one repetitive task today.