I wonder if anyone else recognizes this as an ode to the neurodivergent strategist - there’s so many kickass strategists, especially women, who’ve realized over the last several years that their strategic superpowers (and! some of the things they spent too long apologizing for) were connected to one diagnosis or another that flew under the radar because (shocker) none of that was designed for them either.
Anyway, I see my audhd self in this and many others that fit the bill above and I applaud the shit out of it — obviously it goes way beyond that, but I wanted to call it out because I think it’s likely to be particularly resonant and so I wanted to say I see you too. The patterns! The deep diving! The willingness to go rogue! The intuition!
It's a beautiful manifesto, and I largely applaud this synthesised multidisciplinarian intuitionist strategist vision.
I just don't think AI connects to it in this way. You assume that GenAI can empower us to do the pattern recognition you describe, with butterfly wings on TikTok and consequential storms in crypto communities, but GenAI is mostly good at identifying the most obvious patterns and not those nuanced connections.
Ironically, I believe you describe precisely what will set the strategist of the future from those who over-rely on AI.
Depends on which AI tools you’re using. I also don’t think she’s talking about over-relying on AI, she’s pointing out the ways it can be an advantage and I think she’s nailed it.
Comfort with the old methods is entirely dead. But I found it odd that everything itemized in your strategist's manifesto was passive and receptive, which is a major oversight.
Even tinkering with "new tools", such as AI, and extracting signals is still playing with old data. Old data is useful when the future is very much like the present. But guess what? That way of working is dying along with everything else. The more strategy remains observational and aloof, the more it will be a victim of the future. That's just driving a car looking through your rear-view mirror.
What's missing is the active piece. In complex adaptive systems, no one can simply surmise all the complexities and interactions of the system's mechanics by modeling it on old patterns and past data. The only way to truly understand how a system is working, and how it can be changed, is to intervene.
And by intervention, I don't mean "applying" observed patterns by strategically committing to leverage them in related domains. Fire and forget has no place in our future. This is much more "start with evolving hypotheses and learn as you go", committing to iterating on your hypotheses as you seek windows where you should commit more. This is analogous to what BCG Henderson Institute highlighted as "competing on the rate of learning" a few years ago.
Lots of experiments with tight, data-fed feedback loops to iterate and discover the adjacent possible. And a continuous process of reconciling the adjacent possible with desired direction. Note that I used direction and definitely NOT destination - because that kind of myopia closes perceptive minds off from novelty that will ultimately emerge during the process.
It's insufficient to leverage old data. You must create new data as part of the act.
Get out of the ivory tower and get your hands dirty. Strategy that isn't actively participating in the learning process, with tight learning loops, is dead strategy for a past that no longer exists.
As always, full of amazing ideas I can't wait to try and apply to my own work!
The idea that AI is replacing or even conflicting with real human insight is a funny one - for me, the ability AI has given me to both collect and synthesize (or as you say, spot patterns in) more real human data in a more meaningful way is the most ground-breaking change it's made to my working practice.
AI isn't replacing human insight, it's supercharging it.
I wonder if anyone else recognizes this as an ode to the neurodivergent strategist - there’s so many kickass strategists, especially women, who’ve realized over the last several years that their strategic superpowers (and! some of the things they spent too long apologizing for) were connected to one diagnosis or another that flew under the radar because (shocker) none of that was designed for them either.
Anyway, I see my audhd self in this and many others that fit the bill above and I applaud the shit out of it — obviously it goes way beyond that, but I wanted to call it out because I think it’s likely to be particularly resonant and so I wanted to say I see you too. The patterns! The deep diving! The willingness to go rogue! The intuition!
💛🌻✨
Love this angle!
It's a beautiful manifesto, and I largely applaud this synthesised multidisciplinarian intuitionist strategist vision.
I just don't think AI connects to it in this way. You assume that GenAI can empower us to do the pattern recognition you describe, with butterfly wings on TikTok and consequential storms in crypto communities, but GenAI is mostly good at identifying the most obvious patterns and not those nuanced connections.
Ironically, I believe you describe precisely what will set the strategist of the future from those who over-rely on AI.
I don't think you're using it right :)
Depends on which AI tools you’re using. I also don’t think she’s talking about over-relying on AI, she’s pointing out the ways it can be an advantage and I think she’s nailed it.
Comfort with the old methods is entirely dead. But I found it odd that everything itemized in your strategist's manifesto was passive and receptive, which is a major oversight.
Even tinkering with "new tools", such as AI, and extracting signals is still playing with old data. Old data is useful when the future is very much like the present. But guess what? That way of working is dying along with everything else. The more strategy remains observational and aloof, the more it will be a victim of the future. That's just driving a car looking through your rear-view mirror.
What's missing is the active piece. In complex adaptive systems, no one can simply surmise all the complexities and interactions of the system's mechanics by modeling it on old patterns and past data. The only way to truly understand how a system is working, and how it can be changed, is to intervene.
And by intervention, I don't mean "applying" observed patterns by strategically committing to leverage them in related domains. Fire and forget has no place in our future. This is much more "start with evolving hypotheses and learn as you go", committing to iterating on your hypotheses as you seek windows where you should commit more. This is analogous to what BCG Henderson Institute highlighted as "competing on the rate of learning" a few years ago.
Lots of experiments with tight, data-fed feedback loops to iterate and discover the adjacent possible. And a continuous process of reconciling the adjacent possible with desired direction. Note that I used direction and definitely NOT destination - because that kind of myopia closes perceptive minds off from novelty that will ultimately emerge during the process.
It's insufficient to leverage old data. You must create new data as part of the act.
Get out of the ivory tower and get your hands dirty. Strategy that isn't actively participating in the learning process, with tight learning loops, is dead strategy for a past that no longer exists.
Completely agree.
Boom
As always, full of amazing ideas I can't wait to try and apply to my own work!
The idea that AI is replacing or even conflicting with real human insight is a funny one - for me, the ability AI has given me to both collect and synthesize (or as you say, spot patterns in) more real human data in a more meaningful way is the most ground-breaking change it's made to my working practice.
AI isn't replacing human insight, it's supercharging it.