Why I Wrote Hyperadaptive
For years, I saw organizations hit walls with transformations. Hyperadaptive learns from those lessons.
For several years at Scaled Agile, I hosted the SAFe Business Agility podcast. I spent week after week talking with people in the middle of changing how their organizations worked. The thing about podcasts is you get to hear the stories that don’t make it onto websites and stages.
A lot of it was wonderful. Teams shipping faster, seeing their own work clearly, making decisions where the information actually lived instead of sending it up a ladder that lost the signal at every rung. I loved those conversations.
But there were other conversations I kept having. Organizations would be a year or two into a serious transformation, doing everything the frameworks asked, and they would hit walls that had nothing to do with technology. Generally, people and organizational walls:
Job descriptions and career paths that no longer matched how people were now being asked to work.
Incentives pointed one way while strategy pointed another.
Leaders were making calls without a real feel for the operational reality underneath them.
Teams that clung to the canon so tightly they lost the point of it
Others that ran so loosey-goosey there was nothing left to hold onto.
I heard versions of that story so many times that it stopped sounding like a pile of unrelated problems and started sounding like lessons to be learned. When I left Scaled Agile and co-founded the Agile Marketing Alliance, we ran straight into the same walls. Different function, same lessons.
This goes beyond Agile
Agile and other transformations generally work beautifully inside the teams they reach. But these efforts stop headlong when they hit the annual budget cycle, the performance review, the procurement process. Even the org chart itself, humming along on its industrial-age logic. Meanwhile, a hundred-person engineering team learns to work in a completely different way. Agile could change how those teams worked. It couldn’t change the company around it.
When you zoom out, you see that this is the story of nearly every serious attempt to fix how organizations run. The Toyota Production System, which I first studied at Waseda, reshaped Toyota…and very few others. Business process reengineering became famous for a roughly 70% failure rate. Six Sigma, TQM, Lean out beyond the factory floor, value-stream thinking. Serious people, real methods, genuine improvement, and the same walls every single time.
What caused all of these to fail, in my view, is that the operating system underneath was always strong enough to absorb the method and keep going. You could adopt new practices and route around the parts that would have required the structure to actually change. So the structure stayed exactly as it was, and the improvement lived inside its box.
Why I believe AI is different
I wrote Hyperadaptive because I think AI is the first force I’ve come across that the operating system can’t quietly absorb.
Every previous method could be quarantined. You could let Agile happen inside engineering and leave everything else intact. Let Lean run the manufacturing floor, while the rest of the organization stayed siloed. Contain BPR to the functions it touched. AI doesn’t sit still like that. It isn’t a practice you install in one function. The work is changing under everyone’s hands at the same time. Like a recently titled movie, it is touching everything, everywhere, all at once.
When AI handles a million support tickets, what happens to the L1 role? When AI drafts the first version of the contract, what happens to the junior associate’s whole apprenticeship? When AI does the analysis, what happens to the analyst’s climb to senior analyst? Can an operating model really stay intact while the work it was built to organize dissolves underneath it? I don’t think it can.
Which means we finally have an opening to change the entire system. It’s changing already, in every organization, mostly without anyone deciding what it should become. So the question becomes, does it change by accident, in whatever direction the next model release happens to shove it? Or does it change on purpose, leveraging the lessons we learned from transformations past? That opening is what the book was written to name.
The opportunity is ours to take
The systems we have been working in have been broken for a long time. And I don’t just mean enterprises. I mean schools. Government. Higher education. They were built for another era. One where information moved slowly. Where change moved slowly. Where bureaucracy made some semblance of sense.
And..we’ve been trying to fix these systems for years. With one caveat, there was never a forcing function quite like AI. Both in terms of speed and scale, but also in terms of the value it unlocks. Not only can good ideas come from anywhere, AI enables good execution to follow from more places than ever before.
But in order for these changes to take hold, we have to realize two things. The first is that if we limit AI to a pocket of the organization, we will hit the same walls we’ve always hit. The second is, we’ve been at this for years. We know where a lot of the failure patterns exist. I heard them week after week on the podcast, and incorporated them into the book. AI is providing an opening. The question becomes, what will we do with it?
One voice in the choir
I know what I would like to see. More human institutions where people aren’t burned out all the time. Enterprises that focus on profit, people and the planet (the triple bottom line). Where individuals aren’t just pushing paper, but fulfilling their purpose. I’m just one voice in the choir, but it mattered to me to join the choir.
If you’re the person at your company who keeps seeing the broken system and wondering if you’re the only one who does, I want you to hear that you are not alone. Others have been seeing the cracks in the systems for years. Entire industries support the change of the system. But we need more people to join the movement, who see the cracks and see that AI is an opportunity to fix the cracks at a scale never before possible. You have far more company than it feels like from where you sit.
At the end of the day, I wrote Hyperadaptive for that reason. In the hope we can use AI to fix broken systems. To incorporate the lessons learned and shine a light on a way forward. It isn’t a book about AI, and it isn’t a book about rewiring the organization just for the sake of rewiring it. It’s a book about using AI to finally amplify the better way of working that serious people have been trying to build since Toyota. To finally break through the walls that were described to me over and over.
Are You In?
If any of this is landing for you, let’s build the movement.
Right here, on Substack. This is where we connect. Where we can talk about what becoming AI-native actually takes, the patterns playing out inside real companies. Subscribe so the conversations land in your inbox, and if you want the deeper, proprietary pieces, the paid tier is where the serious conversations happen.
On LinkedIn. This is where the day-to-day conversation happens, and where I honestly learn as much from the comments as anyone learns from me. Come follow along.
And in the class. Running Hyperadaptive Organizations is where we stop talking about the wiring and start building it. It’s two working sessions where you leave with a leadership-ready map for spreading AI adoption across your organization without having to push every single piece yourself.
None of this happens overnight. But it happens if enough of us look up from the latest feature and the latest fear story, get clear on what we actually want to build for the people who work with us and the people who come after us, and start wiring it in where we sit. I’d love for you to be in the choir.
Be well,
Melissa