It’s Friday at 4pm. I’ve just closed my 12th bug of the week. My brain is completely fried. And I’m staring at the bug leaderboard, genuinely sad that Monday means going back to regular work. Which is weird because I love regular work. But fixit weeks have a special place in my heart.

What’s a fixit, you ask?

Once a quarter, my org with ~45 software engineers stops all regular work for a week. That means no roadmap work, no design work, no meetings or standups.

Instead, we fix the small things that have been annoying us and our users:

• an error message that’s been unclear for two years
• a weird glitch when the user scrolls and zooms at the same time
• a test which runs slower than it should, slowing down CI for everyone

The rules are simple: 1) no bug should take over 2 days and 2) all work should focus on either small end-user bugs/features or developer productivity.

One of my biggest weaknesses as a software engineer is procrastination when facing a new project. When the scope is unclear, I have a tendency to wait until I feel I’ve “felt out” the problem to start doing anything. I know I’ll feel better and work much faster when I get “stuck in” but I still struggle with that first step, overcoming the “activation energy” required to engage with the details.

LLMs have been a game-changer for me in this respect: I can just throw a couple of sentences at them with the shape of the problem. This leads to one of two outcomes:

1. The LLM comes up with a good solution, usually in a slightly different way than what I was thinking. I realize “oh wow the solution is much simpler than I thought”. Straight away I start thinking about the consequences of implementing and improving what the LLM suggested.
2. The LLM comes up with a solution that I intuitively recognize as “wrong”. My immediate reaction is frustration (“How could it get it so wrong”) which leads me to go back and forth with the model, explaining to it why its solution could not possibly work. But in the process of arguing with the model, my brain is churning away and generating variations or different approaches that could work. After a while, even if the AI is still on the wrong track, the debate will trigger a moment of inspiration where suddenly the solution will come to me. I’ll excitedly start up a new conversation and start working through it with the model.

The key is the emotional reaction I have immediately to the LLM’s response, either excitement or frustration. By harnessing this immediate feedback loop, I get my brain out of its passive, procrastination mode. It’s almost like a jolt: either I’m thrilled because it’s simpler than I thought, or I’m spurred to action by the urge to correct a perceived ‘wrong’ answer. This forces me to engage with the problem in a meaningful way.