Resilience is a Mindset
When the trains stop running, or your car breaks down, or your flight is cancelled, you experience how resilient you are. If you are in an unexpected situation with other people—as I was yesterday when the trains here in Copenhagen stopped—you get to watch resilience in action.
Some people calmly make other plans. Others are overwhelmed and whining. The situation is the same, but the mindset is different.
Tell yourself now that next time you are in an unexpected and challenging situation, you will notice how you react. Setting up this behavior in advance makes it more likely that you are able to reflect on the situation while you are in it. Once you have the awareness, you can also change your reaction if it is not helpful.
The Rest of the World is Different
I just received my settlement cheque from the FTC. Apparently, as an ex-Amazon Prime member, I have been injured by their deceptive practices and am entitled to 29 dollars and 98 cents. And I receive a paper cheque. No bank in Denmark will cash that – cheques were discontinued in Denmark a decade ago. To get my $29.98, I would have to travel to the U.S., which for obvious reasons won’t happen.
We assume that the rest of the world operates like we do. It doesn’t. Germany still has fax machines. I don’t know how things are done in South Korea or China, but it is a safe bet that I cannot imagine it.
If you want to address the world, you need someone who knows each part. Distance is not dead.
Overconfidence
40 years ago, when I started dating my wife, I was the confident one. She was the one with the best sense of place and direction. We did get lost quite a few times before she realized I was over-confident in my own abilities, and I learned that her wayfinding skills were superior to mine.
It is a common human trait to defer to (possibly misplaced) confidence. IT already suffers from this, as anyone subjected to the latest fad in IT development or architecture can attest.
But with AI, this problem is magnified a hundredfold. Total nonsense and sharp analysis are both presented with utter confidence. For any important decision, take some time to think it through yourself. Or at least ask another AI to criticize the decision of the first one.
One Thing at a Time
Do you have a dozen changes you want to make in your life? When I start coaching and mentoring someone, they often come to me with a long laundry list of changes they want to implement in their lives. Bad habits reinforce one another – if you’re not getting any exercise, you also don’t eat well, and waste time on streaming services, and get too little sleep, and don’t get things done, etc., etc.
But changing one thing for the better doesn’t magically affect the rest. That’s why it’s easy to drift into an unsatisfactory life, but hard to get out.
Start with one thing, but make a plan for the others. I advise people to get a habit-tracking app and set a start date for one thing they want to change. But also register the start date for the next thing you want to change, two weeks out. And the third thing, four weeks out. In that way, your app will start reminding you to do the one thing you committed to and ramp up reminders for the others over the next few months. Most people cannot make another change until they have spent at least two weeks anchoring the previous one.
Change one thing at a time.
Spreadsheet Optimizing
The train drivers here in Denmark are getting sicker and sicker, and it’s the computer’s fault. Specifically, it is the fault of the new fancy train driver schedule optimization software that our blundering national railway company has ineptly implemented.
It optimizes away people’s breaks, violates union-agreed rules, and fragments a train driver’s working day into running four different trains in a day instead of one or two.
It is a classic case of Spreadsheet Optimizing. Someone who doesn’t know the real world or cares about the people doing the work will twiddle with a spreadsheet or other software to gain a theoretical 1-2% benefit, but will realize a 10-20% loss.
In theory, there is no difference between theory and practice. In practice, the difference is huge.
Change Happens IRL
I just met some enthusiastic young people at the train station on my way to work. They were handing out flyers for one of the political parties here in Denmark in advance of our upcoming election. It doesn’t matter if I agree with them – it makes me happy that they are there and making a difference.
Liking a post on Facebook or Instagram does not make a difference.
If you are unhappy with the way things are going in your country, you need to get off the couch. Volunteer IRL for a cause or political organization you believe in.
Do You Test Your AI?
How do you test the AI you use? All the major providers are constantly leapfrogging each other, and if you don’t investigate their improving capabilities, you are at risk of missing out.
My personal test suite for LLM chatbots includes playing chess against them. Two years ago, they could manage 5-7 moves before they made an illegal or stupid move. The best LLMs are now up to 20-25 moves.
In a professional coding setting, you should create a test suite of relevant coding tasks on your codebase. For example, giving each AI a block of code and asking for a security and performance review. You’ll find a big difference between engines, and all of them are rapidly improving.
Have someone on your team test the current crop of AI tools regularly. Rotate the task between team members – they will each test different aspects.
Forcing AI
Tech companies like Amazon, Meta, and Google have begun forcing AI tools down the throats of unwilling engineers. Managers are presented with dashboards showing how their underlings use AI. In some places, insufficient enthusiasm for AI tools will count against you in your next performance review.
That is an amazingly stupid idea. You should reward the outcome, not the way it was achieved. It reminds me of other poorly led organizations that reward those who put in many hours over those who get the same job done faster.
If your AI tools are so great, people will use them of their own volition. Forcing them on people demonstrates that they don’t work as well as advertised.
Remote or Relationships?
Most people are not cut out for fully remote working. It sounds alluring to be the master of your time and to run errands or go to the gym during the day when you have the shop or the gym to yourself. But even if you can land one of these coveted jobs, it probably won’t make you happier.
The problem is that if you don’t go to the office, you will have to work harder to establish and maintain relationships. The office provides you with a ready-made social circle. We are social animals, but most people are not good at building new relationships.
So instead of bemoaning being forced to go to the office, appreciate the relationships you have there.
A Place Where AI Can Help
IBM stock dropped 13% on the news that Claude Code can now refactor COBOL. That might be bad for IBM, but it is good for the wider IT world.
Using an LLM inductively—writing a lot of code from a short prompt—allows it to confabulate over-complex and buggy code. But using an LLM deductively—distilling knowledge from a larger data set—is a place where the AI can do something well that humans are not very good at.
Since the beginning of programming, we have struggled with documentation. Everybody who has been in the industry for a while has experienced being thrown into a swamp of inconsistent, badly documented code with the instruction to fix it.
I’m not afraid that AI will put us all out of a job. We have a gazillion lines of legacy code that need refactoring. That has been prohibitively expensive until now. With modern AI tools, we have a chance to make a dent in the problem.