Defensive innovation: Stop de-innovating
Explore how to combat de-innovation and unleash the constant potential for creativity in your projects to drive meaningful change and growth.
Duration: 0:52 | Size: 1.0 MB
It’s commonly thought that innovation depends on some sort of creative bursting forth. There certainly seems to be this sort of generative innovation where something new is deliberately made.
I wonder whether this kind of innovation is really so special and unique. I’m suspicious of explanations where “something magical happens”. So, I wonder if “creation” isn’t all around us all the time.
If it is, then why do we focus on this special, magical kind of innovation? If innovation is all around us, why don’t we see it more often?
I think this is because we see a lot of de-innovation. By that, I mean that the average project/effort spins off all kinds of new ideas. Mostly, these ideas are suppressed, diverted, or cancelled.
This means that “doing innovation” should focus at least as much on preventing de-innovation as on encouraging innovation.
The agent-shaped org chart
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AI as staff, not software
Two frames for what AI is doing to work. The tool frame makes tools smarter. The staff frame makes roles unnecessary. Those aren't the same product, the same company, or the same industry.
Knowledge work was never work
Knowledge work was always coordination between humans who couldn't share state directly. The artifacts were never the work. They were the overhead — and AI just made the overhead optional.
The work of being available now
A book on AI, judgment, and staying human at work.
The practice of work in progress
Practical essays on how work actually gets done.
The file I almost made twice
A small operational footgun that runs everywhere — building a parallel system when the one you have is fine.
The worker isn't lying. The worker is reporting what it thought it did, which is always one step removed from what the world actually shows. The fix isn't more self-honesty. The fix is a different pair of eyes.
Shopping is the last mile
Every meal planning app treats cooking as the hard problem and shopping as a logistics detail. They have it backwards. Cooking is mostly solved. Shopping is the last mile.
The work that remains
When AI handles implementation, the human job shifts from doing the work to understanding the work. Speed without understanding is just technical debt with better commit messages.
Manual fluency is the prerequisite for agent supervision
You cannot responsibly automate what you cannot do manually. AI agents speed up work for people who already know how to do it. They do not replace the need to learn the work in the first place.
Your process was built for a different speed
When work changes velocity, governance systems don't just fall behind. They become theater. And theater is worse than nothing—it gives you the feeling of control without any of the substance.