Philosopher Barbara Herman points out that the goal and purpose are two separate things. For instance, professional baseball might seem like a sport where the goal and purpose is to win. But that isn’t true. To be clear, the goal is win the game. But the purpose is to entertain. And as fans, we can watch our favorite teams’ strategies in a way that follows the metrics, to the point where the game is optimized (which, in most ways, it is now), but that isn’t entertaining to watch. It turns out that, in an age of analytics, we think we want everything optimized to create more convenience. But the reality is, this isn’t a world we want to occupy if it becomes so.
How people think LLMs are used:
And what happens when we take a break:
The reality is, there is still a learning curve to these tools. And if you’re not going to put the time and effort into it, it’s going to go haywire quickly.
However, the bar to learning has never been lower, and it has dropped significantly in just two years. Now is the time to get fluent with these tools.
If coding is solved, which anyone who has played with an LLM knows it has, then what’s next?
It seems to me, at least in this moment, what matters now is imagination, great taste, great products that solve interesting problems…not autocomplete tasks. Not bullshit jobs. Not middle managers or TPS reports.
I have talked to many nonprofit leaders over the last year who have it all wrong and are thinking about how they’re going to use AI.
The mindset at the top is: how do I replace my poor performers by implementing AI as quickly as possible?
The problem is the technology, which, while good, isn’t quite good at implementing what you have going just yet. Obviously, there are exceptions, like in the software tech industry.
The better mindset is, how do I use these tools to 10x my top performers? How do I give them the right tools and the time to learn so they can do their job better than they ever could imagine? And when they learn how to do this, the profits follow. Not by cutting costs and employees. But by investing in your best people to do their best work.
If you give a milkshake in a big cup to an eight-year-old that’s half full, someone with a fixed mindset would say, “It’s only halfway full.”
Give them the same amount of milkshake in a smaller cup, and all of a sudden, you have sparked joy.
It’s easy to chalk everything up to growth or to fixed mindsets and to assume everyone needs to adopt a growth mindset. But life is hard. And what I keep getting pulled into is the choice architecture used to deliver the information to change the interaction we are having.
Problems are everywhere.
They are endless. And we need people to solve them.
That didn’t change when humans invented the printing press, electricity, the internet, or AI.
There is always a cost to quitting something.
But the price isn’t so high that you can’t pay it.
The internet makes us think global.
Social media makes us think about status.
The job makes us think in bottom lines.
All these systems floating around to optimize one thing or another.
We don’t think enough about why optimization is the goal for more GDP, more clicks, more money.
Optimizing isn’t where we need to land. It isn’t the destination. And it probably isn’t part of the journey either. At least not as important as we make it out to be.
In the age of AI, it can feel like humans are becoming obsolete. I don’t see it that way. People are miserable with the work that code and LLMs can now handle for us so that we can be free to exercise good judgment, craft a better story, show we have good taste, connect people, change the emotion in the room, be creative, and so on.
What I think this tech does is allow us to have an honest conversation about what work we do matters and what is just bullshit. Unfortunately, for many of us, it’s more than we like to admit.
But not everyone is productive.
The way we use our time is a signal of what we value.
Josh Allred's Blog 