How to Think About AI
Why trying to predict the future is pointless and what do to instead
There’s a lot of hype around AI these days. A lot of fear mongering. A lot of bold statements about the future.
I bet many of you follow each new model release with a tinge of anxiety, worrying if your job will be replaced by it soon. I felt the same way at first.
I started using coding agents extensively at work since the beginning of year and since then I’ve kept searching for a sensible way to make sense of what’s going on. Something devoid of hype. Something based on fundamental truths.
That’s the main reason I’ve been so quiet with this newsletter.
I wrote almost 3000 words on the idea that you can use logic to predict the future. Then I scrapped it. Why? Because I had a much better idea!
Alan Kay once said: “The best way to predict the future is to invent it” And so my main message in this post is one of hope:
AI is what you make of it!
When a new wave of innovation comes, there are those who sit on the sidelines fearing the worst and those who hope for the best.
Who wins? It’s always those who tinkered with the innovation, built something, learned from it and made it useful for themselves. Everyone else is brought along by the few brave souls who actually did something.
Even the language we use these days when talking about AI (prompt engineering, context engineering, vibe coding, agent orchestration, etc.) was literally invented by someone who dared to mess around with the technology in order to learn.
This post is literally 1 year old!!
How I almost took the wrong turn
If there’s anything you should know about me, I’m never early on new technologies. I’ve successfully avoided most of the fads of the last decade (crypto, blockchain, NFTs, etc).
And so for a long time I stayed on the sidelines when it came to AI. I decided I was skeptical and chose to ignore all the hype. That was until last month.
So what changed?
In January we decided to switch our software engineering to agentic, AI driven at work. Meaning whenever we’re developing a new feature, we first write the spec, develop a plan, develop the test cases for it, review the plan and then let an agent do all the coding.
Another thing you should know about me, I can be impatient. Code has always been too low level for me. I think that’s what drew me to SQL and data. I can operate at a slightly higher level of abstraction.
Hence why AI assisted software development has been a godsend for me.
With AI handling the coding, I can focus on what I do best: figuring out what the problem is, what needs to be built, gathering requirements and writing specs. This by the way coming from someone who used to hate writing specs; (read the code bro)
Worried that AI is a better analyst than you?
Figure out how to use AI to get accurate answers to most analytics questions quickly so you can focus on more interesting pursuits.
Worried that AI can build data pipelines in minutes?
That kind of work was low leverage anyways. Automate it with AI so you can get to the good parts.
Don’t let AI happen to you. Make AI work for you. Be agentic. Do things. Tinker with it, try things out, build something and then showcase it. Most AI projects are failing, but at least people are trying things.
Some things are bound to work. Some people are bound to reap the rewards of this new age. Why can’t it be you?
Until next time.