People seem to like my AI session transcripts where I see big AI failures. I definitely don’t like living through them, but they can be instructive to readers of this blog.
Here’s an excerpt that will give you much to think about. Note my prompting style (my two prompts are in bold) as we reached
The 2026 Associate: Lessons from My Michigan Law Class
In the latest episode of The Kennedy-Mighell Report, Tom Mighell and I turned the spotlight inward to talk about the course I just finished teaching at the University of Michigan Law School called Legal Technology Literacy and Leadership. This course is considered a practical simulation class. It was built this past semester around
New Podcast Episode: The Expanding Minefield of Legal AI
The Expanding Minefield of Legal AI
I’ve been tracking a subtle but dangerous shift in the legal tech landscape. For the last few years, the entire industry has been obsessed with “hallucinations”—obvious, glaring errors like fake case citations. But as Tom Mighell and I discussed on episode 418 of The Kennedy-Mighell Report, focusing
The Hidden Instruction Problem for Agentic AI and All Other AI
The Door in the Hallway: Agentic AI and the Illusion of Control
We used to talk a lot about the concept of a customized, bounded news feed designed to give professionals exactly what they need to know, and nothing they don’t. It was usually called the “Daily Me.”
Lately, I’ve been trying to build a
The Competence Trap: Anatomy of a Captured Claude #Fail
The prevailing narrative I hear in the legal world is that Claude is the “most human” of the LLMs and, especially, a nuanced, sophisticated writer. When I report that the system has begun to fail my specific research protocols, the common response is a suggestion that I am simply using the wrong version and a
AI as the Unreliable Witness and the Appearance of Completion
Coherence degrades while fluency improves.
The central problem is not that AI systems sometimes fail. Of course they fail. Nor is the main problem that they occasionally hallucinate, wander, or produce obvious nonsense. Those are manageable problems because they announce themselves early. The more interesting and professionally dangerous problem is that a system can become
The Threshold Moment
At a certain point in a long AI session, I can feel the texture change.
The words are still smooth. The tone is still confident. But something underneath has started to slide and give way. The session is still moving forward, yet the logic is no longer holding together in the same way.
That happened
Fresh Voices at Three: What Listening Taught Us About AI, LegalTech, and the Next Generation
When Tom and I started the Fresh Voices series on The Kennedy-Mighell Report podcast, we had a pretty simple idea.
A lot of the most interesting work in legal tech seemed to be coming from people who were newer to the field, earlier in their careers, or just not as widely known yet as
What Scarcity Taught Computing, and AI Might Need to Relearn
“A larger context window can create the feeling that a cognitive problem has been solved, when sometimes all that has happened is that disorder has become harder to notice.”
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
The Helpfulness Trap: Anatomy of an AI Recursive Failure Loop
“Polishing the Mirror While the House Burns: Why Your AI is a Liability”
The Editor’s Introduction: A Note on the “Sliver of Silence”
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