Knowing Thy Enemy

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My career will be defined by a few handfuls of code that ultimately decide where I’m taking my talents next. It happened when I worked in AdTech – a bit of an update from Google’s ad platform rendered me obsolete. Alas! And today I’m staring down the barrel of a diminished business model thanks to the output from Large Language Models.

Frankly, I’m not sure I have enough runway for an “I told you so.” The return to the low-tech will happen, it always does, and people will once again be scouring the wastelands for someone to help them put together their message.

This isn’t so much about “if you can’t beat em, join em,” so much as it is: know your enemy, and know it well.

Consider the artist Nam Jun Paik:

“I use technology in order to hate it properly.”

And Paik was working in the 70s and 80s. His gripe was with TV. His solution was to find ways to get the machines to act against itself.

TV Buddha by Nam Jun Paik

I mean, even Rick Rubin (who I love to roll my eyes at) published tome of autofellatio he’s calling “The Way of Code.”

I’m waiting for the day that all of this AI garbage is ruined and it all takes a back seat (well, more ruined, I suppose). Until then, it is a matter of finding out how the tools work and how I can use them to my advantage while still holding on to my ethics.

I will not create or publish AI slop. I will not subject my audience to the outputs of Large Language Models that were trained on stolen data.

Where possible, the processes I create will be made available for free.

The aim is to create tools that either effectively save time, or show how much time and energy is wasted applying digital tools to analog tasks.