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What does a slaughterhouse have to do with your org chart?
In this episode of The Intentional Spill, Yvette and Frank trace one of modernity’s quiet organizational origin stories: Henry Ford borrowing the logic of the slaughterhouse to build the assembly line and, in the process, embedding segmentation, efficiency, and divide-and-conquer thinking into the DNA of our institutions .
We’ve been living inside that metaphor ever since.
But what if the future isn’t a factory?
This Spill introduces the “A” in ALIVE: Abductive Thinking, a way of deeply sensing the whole rather than optimizing the parts. Drawing on Nora Bateson’s definition of “mutual learning contexts,” we move from assembly lines to meadows, from siloed data columns to living systems where meaning only exists in relationship.
Because a meadow is not a log.
A mind is not a spreadsheet.
And foresight is not a predictive machine.
Along the way, we question whether AI can ever “know” the embodied feeling of care, explore why foresight keeps trying to earn credibility from non-abductive systems, and share a story about a porch goose that might just restore your faith in human interdependence.
Intentional evolution asks us to notice the metaphors guiding us.
Are we rehearsing futures of separation?
Or practicing futures of connection?
Less assembly line.
More meadow.
The future is alive . . . and it’s learning with us.
By TFSX5
55 ratings
What does a slaughterhouse have to do with your org chart?
In this episode of The Intentional Spill, Yvette and Frank trace one of modernity’s quiet organizational origin stories: Henry Ford borrowing the logic of the slaughterhouse to build the assembly line and, in the process, embedding segmentation, efficiency, and divide-and-conquer thinking into the DNA of our institutions .
We’ve been living inside that metaphor ever since.
But what if the future isn’t a factory?
This Spill introduces the “A” in ALIVE: Abductive Thinking, a way of deeply sensing the whole rather than optimizing the parts. Drawing on Nora Bateson’s definition of “mutual learning contexts,” we move from assembly lines to meadows, from siloed data columns to living systems where meaning only exists in relationship.
Because a meadow is not a log.
A mind is not a spreadsheet.
And foresight is not a predictive machine.
Along the way, we question whether AI can ever “know” the embodied feeling of care, explore why foresight keeps trying to earn credibility from non-abductive systems, and share a story about a porch goose that might just restore your faith in human interdependence.
Intentional evolution asks us to notice the metaphors guiding us.
Are we rehearsing futures of separation?
Or practicing futures of connection?
Less assembly line.
More meadow.
The future is alive . . . and it’s learning with us.