Here’s another in my occasional series of posts where I have an AI tool write an unedited blog post analyzing a spectacular failure to see what we might learn from it.
By ChatGPT (GPT-6)
I was given a clear assignment, the necessary source…
I’m launching the Successful Innovation Learning Outcomes Notebook.
It’s a deliberately bounded experiment with independent value, built to make my work easier to explore, question, apply, and build upon through an AI-assisted interface.
To create it, I took the PDF of my book, Successful Innovation Outcomes in Law: A Practical Guide for Law Firms…
Another in my continuing series of letting AI write its own posts for me explaining how and why it failed at what I asked it (quite reasonably, if I may say so) to do. I might start calling this AIsplaining.
The Prudent AI Series: A Field Guide for the Next Era of Enterprise Strategy
Recently, I completed a ten-part series on AI strategy and operations on this blog about Prudent AI. It grew out of a simple observation: most corporate conversations about artificial intelligence are trapped in a false binary.
On one side, vendor hype…
Specification Sovereignty
Why You Can Outsource Execution But Never the Definition of Success
One of the great attractions of generative AI is that execution keeps getting cheaper. Work that once required scarce professional time can increasingly be delegated to a model, an agent, a vendor, or some combination of all three. That can be a…
Direction Over Acceleration
When Execution Becomes Cheap, Strategic Choice Is the Ultimate Competitive Advantage
AI conversations have a natural starting point: What can this technology do?
It is an understandable question. Every few weeks, the answer gets larger. Models can write, analyze, code, search, reason, generate images, operate software, and increasingly take autonomous action rather…
In the adoption of almost every useful technology, there comes a quiet turning point when the fundamental question shifts from whether the system can do the work to whether it should be allowed to do it. Early on, you…
Shadow AI and the Proof Problem
Making AI Output Look Finished Is Easy. Proving It’s Right Is the Hard Part.
There is a familiar, weary conversation happening inside organizations about shadow AI: Which tools are allowed? What data can employees upload? What security controls should IT impose?
Those are legitimate governance questions, but they miss…
The End of the Standardization Bargain
Decoupling Scale from Uniformity in the Age of AI
For most of the last century, sameness was the price of scale: if you wanted to deliver a product or service to thousands of people, you had to standardize it. Litigators didn’t draft custom interrogatories or complaints from scratch for…
Kill Criteria and Exit Mechanics: An Option You Cannot Bring Yourself to Abandon Is Not an Option at All
Real-options reasoning sounds clean in a corporate slide deck, promising a cheap trial where you evaluate evidence before deciding whether to commit real capital. But an experiment only works if its main job is to…
