Hello and welcome to this What’s Up Monday! I’m Lauro Müller, and I’m super happy to have you here with me 😄 This is a bit different from our Thursday exchanges: on Mondays, I’d like to share what caught my attention in the last week, something cool I came across or figured out while coding, and, when time allows, a personal take on relevant topics for our careers 🙂 Ready to get started? Let’s go!
Over the last couple of weeks I've been running several things in parallel: courses, labs, launching my own platform, publishing every week, and preparing AI-focused corporate trainings. AI assistance is definitely there and there are many touchpoints, so of course I thought I was moving faster.
But, as it turns out, when you run five or ten agents simultaneously, those little pesky pauses and permission requests pile up. Every time an agent stopped to think, do some research, or wait for my review, there was a temptation to switch to the next immediately available task. After a while (and a very tired brain), I realized I was doing a fraction of what I would have done if I had picked one thing and stuck with it.
Although AI enables faster work and iteration, it hasn't changed the biology of our brains. We're still wired the same way we were back then when ChatGPT needed "Think step by step" to produce useful output (remember the good old times? I'm not even gonna mention the StackOverflow days).
And the fact is: our brains are not wired for true multitasking. Using these brief pauses to switch context to other tasks just increases the cognitive burden and energy expenditure of our brains, and, while we might go under the illusion we are doing more for a while, we'll end up exhausted after a single work session.
So I prefer to use these small pauses as opportunities: to review what they're building, to steer the next step, to do real pair programming (one cool thing you get with agents is at least some visibility into their reasoning process, which is not always true for human pair-programming 😅). But that only works if you're actually paying attention to it.
So... How did this impact how I work? My approach now is to set a time window, pick one task, and focus primarily on it. With the anecdotal evidence I collected over the last few weeks, I noticed at least one of three things happens:
I finish earlier than expected (the time window is still running) and I can switch to and focus on the next task.
I make far more progress by the end of the time window than if I spread myself thin across five workstreams.
I produce something I'm genuinely happy with on the first pass.
Don't feel guilty for choosing to focus on a single task. You're not wasting time. You’re working in harmony with your brain.
This Week at LM Academy
Over the last couple of weeks I’ve been working hard on publishing my own e-learning platform, LM Academy, including:
All the courses I currently have (and future ones, of course 🙂)
Exclusive hands-on labs and content available only at LM Academy
And I’m excited to share that two exclusive Kubernetes autoscaling labs are now live! Horizontal Pod Autoscaling in Kubernetes and Kubernetes Queue-Based Autoscaling with Custom Metrics. The first covers CPU-based HPA end-to-end, including stabilization windows and scale-down tuning. The second picks up where the first leaves off: we build a full custom metrics pipeline that exposes Redis queue depth as a native Kubernetes metric and scales workers directly in response to queue load. Both labs are included in the Pro subscription, so make sure to check that out if you haven’t yet!
👉 And here’s a code for 20% off for 3 months in any subscription: PRO20OFF. Valid only for one week!