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Almost Timely News: 🗞️ The Biggest Problem with AI Today (2026-07-05)
once something becomes rusty enough, it's cheaper and easier to replace it
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Almost Timely News: 🗞️ The Biggest Problem with AI Today (2026-07-05) :: View in Browser
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Content Authenticity Statement
99% of this week’s newsletter was made by me, the human. You’ll see a list that Claude made in the opening section. Learn why this kind of disclosure is a good idea and might be required for anyone doing business in any capacity with the EU in the near future.
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What’s On My Mind: The Biggest Problem with AI Today
What’s the biggest problem in AI today? Is it cost, with token budgets being blown out of the water by agentic AI? Is it sustainability, with AI consuming electricity and fresh water? Is it ethics, with tech companies cramming AI into everything?
I think it’s deeper than that. Those are all symptoms of a much deeper-rooted problem: nobody’s making decisions.
Or more correctly, we’ve abdicated far too much of our executive function to AI. We’ve surrendered our thinking.
Let’s dig in.
Part 1: Where This Issue Came From
On Friday afternoon, I was mulling over what I wanted to cover in this week’s issue. It’s a holiday weekend here in the USA, so not as many folks will be reading, and that’s okay. (I appreciate that YOU are) And I’ve covered a ton recently:
So on a whim, I set up a NotebookLM with the last 180 days of conversations from over 40 different subreddits, like r/marketing, r/chatgpt, etc. - everything around marketing, business, and AI. I connected it to Claude Code with the NotebookLM command line tool (the most token—efficient way for Claude to talk to NotebookLM), and then put all of my 2026 newsletters year to date into an input folder.
I asked Claude to compare what I’ve written about thus far this year with what folks are finding their hardest problems are with AI. Claude spit out a list of 10 major things derived from over 800,000 words of foaming at the mouth on Reddit that it thought might be good newsletter topics:
AI Visibility challenges
Agentic oversight is degrading
AI deployment is broken
40-60% of company budget is wasted on the wrong models
AI is a rental
AI sycophancy is screwing up synthetic focus groups
AI detectors don’t work
AI is hollowing out corporations and no one’s hiring junior staff
People measure AI by tokenmaxxing
Marketers are basically unpaid labor for AI companies training data
Claude was REALLY pushing for me to write about how measurement is broken in marketing and AI today, and I might do that at some point, but that’s not what I see when I look at this laundry list. Yes, there are measurement issues in many of them, data issues in many of them, but... measurement being broken is the symptom of what I said earlier - we’ve abdicated executive function.
For those who aren’t analytics nerds, you know that measurement is a trailing indicator. It’s not a leading indicator.
Part 2: Executive Function Recap
As a reminder, I bucket executive function into four categories that I call PODS:
Plan: you think about achieving something in the future and make a plan to get there from here
Organize: you take what you have and try to make sense of it
Dec