As you mention in your post its more about keeping up with the moving bleeding edge rather than keeping what you have. The most important point/habit is to be invested in lifelong learning.

The moment you stop learning, only doing rote work, is when you stagnate. Thankfully I don't know almost anyone in software who can do even a days worth of work without something unexpected happening. As we all know, execution of a plan is never as simple as the plan. Each unexpected moment is an opportunity to learn, make sure to squeeze those moments for learning and knowledge as much as you (and your employer) will allow.

If your job doesn't present many opportunities for learning then the answer would be to look for another job or hobby-projects if you have the time and energy available.

I believe this is a good time for going from Engineer -> Architect mindset. You don’t need to wait for a formal career progression.

When I got into tech, as an engineer, I enjoyed learning as much as I could about building systems.

Systems are comprised of technology, people, and business needs.

How can we help our customers in the best way possible given some constraints (usually $$).

For example, perhaps at the current scale, the customer needs search but the company cannot afford deploying ElasticSearch. You are already using postgres, and you have 80 million candidate records. How can you make this system work until you have a billion records and need ES?

Honestly, I have no idea what the future holds but this is how I view things.

Realistically you can't. People trying to compete with AIs at processing or manipulating data are going to fall short both in capability and in speed.

We've seen a lot of these posts in recent years:

- "Sure, AI can create a basic prototype, but you need real engineers to build something production ready"

- "Maybe we don't need to write code by hand anymore, but the real skill is in good prompt engineering"

- "AI is good at grunt work, but it can't replace the creativity of humans to solve novel coding and math problems"

All of it is cope, or comes from people with bad mental models for AI.

For some time there will be niches where people will find areas that AI can't compete well with human labour for various reasons. The obvious examples for now are where human communication is valued, or where the AI needs to interface physically with the world – especially in complex environments.

So I'd argue the question you are asking is wrong. It should be – "given we humans can't keep our edge to AI, what do we do?"

There are near-term and long-term ways to approach answering this.

Near-term you find the best work you can't which requires minimal reskilling (because whatever you reskill into will likely start to be disrupted in 1-10 years too). People who think jobs which involve physical labour are safe are vastly underestimating how much intelligence is a bottleneck to robotics currently.

Then longer term you should be asking how you prepare for what's coming to the best of your ability - specifially in a world where human labour is worthless and cyber weapons are disrupting basic infrastructure, will you be okay?

I've been saying for years now that people should be prepping for their current job in tech to be their last. This sounded unreasonably doomer and unhinged a couple of years back, but I thought it was the right message to be sending. Similarly now in good faith I cannot tell you to look into some niche that I believe probably won't exist in a few years.

Don't position yourself for the world today, but look 10 years out and ask how the world will be and how you can position yourself well for that. People who make bad career and lifestyle choices tend to be too concerned with optimising for the immediate problems and choices they face.