The Art of Scheduling: Lessons from Algorithms to Live By

Time is our most valuable resource. It’s an age-old mantra, repeated time and again because it holds a fundamental truth about our existence. Managing time effectively isn’t just about productivity — it’s about creating the mental space to focus, make progress, and maintain balance across different areas of life.

In my pursuit of continuous improvement, I’ve explored countless time management methods, both professionally and personally. Juggling multiple responsibilities — between work, entrepreneurship, and personal commitments — often leaves me wondering: What should I focus on? What deserves the highest priority? How do I juggle the different demands of my work and personal life without feeling overwhelmed?

Reading the chapter on scheduling in Algorithms to Live By by Brian Christian and Tom Griffiths helped me rethink these questions. It introduced strategies grounded in mathematics and computer science that provide a structured way to approach scheduling and prioritisation. One quote that perfectly captures this mindset is:

“We are what we repeatedly do. Excellence, then, is not an act but a habit.”

In this post, I’ll explore key takeaways from that chapter and how I’m applying them to improve both my workflow and my daily life.

1. The Importance of Explicit Goals

One of the first key insights from the book is that you can’t optimise your schedule if you don’t know what you’re optimising for. In scheduling theory, this means defining a clear metric — whether it’s minimising deadlines missed, completing tasks as quickly as possible, or maximising overall impact.

How I Apply This

I realised that simply “staying busy” isn’t the same as being productive. So, I’ve made goal-setting an explicit part of my routine. Instead of blindly working through a to-do list, I schedule time regularly to define and review my goals. This allows me to adjust my priorities when needed, ensuring I’m always optimising for the right outcomes.

2. Scheduling Strategies: From Theory to Practice

Reading about these time management strategies in detail has been fascinating. They are intuitive enough that most people apply them in some form without formal study. However, understanding the theory behind them brings a new level of awareness to the choices we make every day. It’s easy to get lost in a sea of tasks, and while no scheduling method is perfect, these algorithms offer a structured way to approach prioritisation — helping to reduce stress and improve efficiency.

Earliest Due Date (EDD): Deadlines First

If you want to minimise how far behind schedule you fall, the best approach is simple: always tackle the task with the earliest due date first. Interestingly, the actual duration of a task doesn’t matter — just the due date.

How I Apply This

In software engineering, we often mix and match different scheduling strategies intuitively. When planning at a high level — such as creating a roadmap for the year or a quarter — we naturally apply the Earliest Due Date strategy. By prioritising major initiatives based on when they need to be delivered, we create a structured plan that ensures we’re focusing on what needs to happen first.

This same principle is reflected in how we prioritise a backlog. While factors like business value and effort estimation come into play, the most pressing deadlines often dictate which tasks rise to the top. However, once we enter a sprint, all tasks effectively share the same deadline — the end of the sprint. At that point, other strategies, like Weighted Shortest Processing Time and Moore’s Algorithm, become more relevant for deciding the order of execution within the sprint.

Moore’s Algorithm: Cutting Losses

EDD works well, but what if you simply don’t have enough time to complete everything? Moore’s Algorithm takes this into account: if a task threatens to push others past their deadlines, you drop the longest task to ensure you complete as much as possible on time.

How I Apply This

Sprint planning is essentially a combination of scheduling strategies. While we prioritise based on business impact and due dates, Moore’s Algorithm comes into play when we need to make trade-offs. If a sprint is overloaded, we don’t just pick tasks at random to cut — we remove those that are either too time-consuming or that would jeopardise the completion of more critical work. This ensures that we maximise task completion rather than overloading the sprint with unrealistic expectations.

Shortest Processing Time: Quick Wins First

Another simple yet effective strategy is completing the shortest tasks first to reduce the overall time spent waiting for things to be finished.

How I Apply This

In the context of day-to-day software development work during a sprint, Weighted Shortest Processing Time makes a lot of sense to handle tasks efficiently. By focusing on high-impact, low-effort tasks first, we maximise output while keeping the workflow smooth. This approach helps build momentum, prevents bottlenecks, and gives everyone a sense of completion — which is crucial for maintaining team morale. Additionally, clearing out smaller but important tasks early can create space to tackle more complex issues without distractions.

A key takeaway here is that if it ever feels overwhelming to manage your calendar efficiently, maybe that’s because it actually is. The complexity of scheduling is a well-documented challenge, but these strategies provide a solid starting point — even if they can’t deliver a perfect solution.

3. The Hidden Costs of Context Switching

One of the biggest challenges in scheduling — especially for developers — is context switching. Every time we jump between tasks, there’s a cognitive cost. In computing, excessive switching between processes leads to thrashing, where a system spends more time switching than actually doing work. The same happens to us when we’re constantly interrupted.

How I Apply This

This is one of the main reasons I advocate for remote work for software developers. In an office, I often found myself surrounded by distractions, to the point where the first thing everyone did was put on headphones to block out the noise. So why be in the office at all?

To combat context switching, I:

• Batch emails and check them only once per day.
• Batch Teams/Slack messages a few times per day instead of responding instantly.
• Time-box deep work sessions where I focus solely on development without distractions.

4. Interrupt Coalescing: Balancing Responsiveness and Throughput

Real-time scheduling is a delicate balance between responsiveness (reacting quickly to tasks) and throughput (getting as much done as possible). If you’re too responsive, you constantly switch gears and lose productivity. If you’re too focused on throughput, you risk missing important updates.

In computing, interrupt coalescing is a technique used to group interruptions together instead of handling each one individually. Humans can apply the same principle.

How I Apply This

I now structure my workday to balance these competing demands:

• I batch low-priority interruptions into designated time slots instead of letting them disrupt my focus.
• I set clear “office hours” for responsiveness — times when I’m available for questions and quick back-and-forth discussions.
• I prioritise deep work outside of those hours, ensuring I’m not constantly shifting contexts.

A great analogy here is how a software team handles bugs. There’s always a trade-off between responding instantly and keeping development on track. In my team, we balance this by designating a point-of-contact for urgent issues while the rest of the team focuses on development. This approach keeps responsiveness high without sacrificing deep work.

Final Thoughts: Applying Scheduling Lessons to Real Life

Reading about scheduling in Algorithms to Live By gave me a fresh perspective on time management. It helped me recognise that scheduling is not just about getting things done — it’s about choosing the right things to do, in the right order, while minimising unnecessary friction.

Some of the biggest takeaways I’ve applied so far:

• Explicit goal-setting — defining what I’m optimising for before I start planning.
• Using the right scheduling strategies — mixing EDD, Moore’s Algorithm, and Shortest Processing Time where applicable.
• Minimising context switching — batching communication and prioritising deep work.
• Interrupt coalescing — finding the right balance between responsiveness and throughput.

At the end of the day, scheduling will never be perfect, and most scheduling problems are, in fact, mathematically intractable. But by applying these principles, I’ve at least gained a structured approach that helps me stay focused and productive without feeling overwhelmed. As Jason Fried puts it:

“Feel like you can’t proceed until you have a bulletproof plan in place? Replace ‘plan’ with ‘guess’ and take it easy.”

Have you experimented with different scheduling strategies? Let me know your thoughts!

If you found these strategies interesting and want to explore the science behind them in more depth, I highly recommend Algorithms to Live By. It’s an insightful read that bridges the gap between computer science and real-life decision-making.

?? Get the book on Amazon