I was in Silicon Valley recently for the initial meeting of the University of Michigan Law School AI Advisory Council. With a little free time around
“Polishing the Mirror While the House Burns: Why Your AI is a Liability”
You’ll be looking below at a self-autopsy performed by an AI on its own failure.
What follows is the raw, unwashed output of an LLM that found itself in an AI recursi
Why the OpenAI Hiring Surge Signals a Crisis of Professional Control
The management problem in AI is no longer whether the models are improving. They are. The management problem is whether the working surface is becoming more dependable or less.
That is why the recent OpenAI hiring story on its plan to nearly double its
Intelligence is Raw Material. Protocol is the Product.
We often confuse the power of a new tool with the effectiveness of its application.
The giants of the AI industry have provided us with a magnificent “Power Grid.” They have given us raw, unmanaged intelligence at a scale previously unimagined. But we must be clear-eyed about
Most people use AI the way the system is designed to be used: ask a question, get a synthesis, and leave with answer. Keep it brief, transactional, and clean. We treat hallucination as a bug to be patched and drift as a signal to reboot.
This is exactly backward.
As popularized in AI discourse by
Most legal AI talk is still focused on whether the engine starts, while the real danger is that no one knows who’s actually steering the car once it hits the highway. It turns out the human in the loop isn’t a safety feature if the human doesn’t know which loop they’re currently standing in.
We
Let me explain why that is a principle, not a preference, and
The promise is leverage: brief, high-intent sessions. You bring the question, the tool brings the synthesis, and you leave with more than you arrived with. That is the value proposition.
Here is what often happens
We pay AI tools to do the hard work, like the synthesis, the heavy lifting, and the cognitive labor we do not have time for. What we often get instead is a tool that produces a decent first draft and then hands the real work back to us.
Not just the hard work. The administrative
We’ve spent the last couple of years treating generative AI like a vending machine. Select a task. Insert a prompt. Retrieve a product. And to be fair, in many legal and professional contexts that’s exactly the right frame: accuracy and precision matter and “creative” output in payroll or billing codes is usually just a polished
