AI is triggering a "big bang" in how organizations operate—and those that adapt fastest will win.
In this episode, Stephen Wunker and Jonathan Brill explore the concept of the Octopus Organization, where intelligence is distributed, decisions happen at the edge, and workflows—not jobs—are automated. Drawing on biology, they explain how autonomy, governance, and visibility can coexist to unlock speed, resilience, and innovation.
The discussion dives into overcoming organizational debt, avoiding groupthink and analysis paralysis, and shifting from rigid hierarchies to adaptive "kill web" structures. Real-world examples—from L'Oréal's rapid product cycles to AI-powered patent creation at Deep Invent—highlight how companies are already transforming.
This episode is essential listening for leaders looking to redesign their organizations for the AI era.
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(00:00):
we need to start treating our peoplewith that autonomy because if we don't,
and if we don't put the governancemechanisms in place for them to do that
safely for the organization, we won'tget the speed we need to move forward.
And what AI does is it gives you, forthe first time that ability to superpower
(00:20):
the individual, to give them context,to give them tools, to improve executive
judgment, to think through scenariosat scale, and at the same time as a
leader, have that visibility into theorganization about what's going on.
Before we start, I want to thankour sponsor Kyndryl, who runs
and reimagines the technologysystems that drive advantage for
the world's leading businesses.
(00:41):
With a unique blend of AI poweredconsulting, built on unmatched managed
service capability, Kyndryl helpsleaders harness the power of technology
for smarter decisions, faster innovation,and a lasting competitive edge.
You can find out more aboutKyndryl at KYNDRYL Kydryl.com.
Bang and everything changed 66 millionyears ago, an asteroid the size of
(01:04):
Manhattan struck the Yucatan Peninsula.
With the energy of 10 billion Hiroshimabombs, massive clouds of toxic dust,
blotted out the sun, cooled the planet,and generated torrent of acid rain.
Within weeks, 75% of Earth's specieswere on the road to distinction.
One of those was the ammonite,and it was the exact opposite
(01:29):
to our friend the octopus.
A little teaser for today's episode todaybecause why did the octopus survive and
thrive and continues to keep on thriving?
Our guests today aregonna tell us about that.
They are the authors of a brand newbook, aI and the Octopus organization.
We're joined by both authors,Steven Wunker and Jonathan Brill.
(01:50):
Welcome to the show.
thanks
us.
Good to be here.
Great to have you both on the show.
I don't always get to coverbooks that are just out.
And the only reason I cover this wasbecause I was supposed to cover one of
these guys older books, and then theypop out this brand new one as well.
So thank you for that.
Adding new books to my list as well.
(02:11):
I set us up there about theammonite versus the octopus.
Maybe one of you'll tell us whatthe hell I was talking about.
300 million years ago, the worldwas obviously a different place
and that's when the octopus startedto evolve into way it is today.
It doesn't have anystrong natural defenses.
(02:31):
It doesn't have a shell,it doesn't have big teeth.
It doesn't have any of thethings you, would kind of think
about, , as a way to defend itself.
And yet, for the last 300 millionyears after species, after species,
after species has gone extinct, ithasn't even had to evolve to thrive.
In fact, in our age of climatechange, it is thriving more than ever.
(02:53):
And so the question we started toask ourselves is, what can we learn
from the strategies of nature?
What can we learn from the strategiesof the octopus to change the way we
think about resilience, innovation,performance, agility in our organizations?
one of the things thatcomes to mind then is.
When you're reading this intro,you're thinking to yourself, well,
(03:16):
digital was probably a big bang.
The internet was a big bang, buttoday we're seeing an exponential big
bang with ai, and that's the contextinto which you entered the book.
Absolutely.
We're seeing a, a nuclear chain reactionof innovation starting to occur.
And it's hard to even imagine what thislooks like 10 years from now, which means
(03:39):
that it's hard to do long-term planningunless you plan in a really different way.
we see analogies in whatpeople are doing today.
You would not have highfrequency trading firms.
Without ai, you would not have,, digital advertising marketplaces
without ai you wouldn't have analysesof patients telematics, , as they're
(04:02):
outside of the hospital without ai.
So they might well need tobe kept as an inpatient.
This is not futurism.
This is right now.
So we have to think not just aboutthis very narrow vision of replacement
of humans, but what is now possible.
There are plenty of examples outthere in the real world today where
(04:23):
companies have shown what they can do.
I, I think the difference, right?
The big thing to think about isthat AI isn't about automating jobs.
It is about automating tasks sothat we can automate workflows.
And it's about that shift, right?
How do we replace entire workflowswith things that are better so that
(04:44):
our people are freed to do the workthat creates value as opposed to
checking the boxes and conveyinginformation and trying to remember
what the heck they did nine months ago.
I think that point is the biggest thingthat we've all experienced, the digital
revolution when digital came along andpeople just basically put websites up.
(05:07):
They just digitizedtheir existing processes.
Steven, I know you worked withthe Great Clay Christensen.
He called it cramming.
, But AI is being used the same way.
We're, we're not changingthe underlying architecture.
And this has to happen.
You talk about where mostorganizations sink before they even
start, which is organizational debt.
(05:28):
People are very concernedabout technology debt, right?
We have 23-year-old.
Machines.
We're running our ERP on Fortranfrom the Vietnam War, you know,
whatever the issue is, right?
But what I think we miss moredeeply is the organizational
(05:49):
debt that we face, right?
That, that to gain fromartificial intelligence.
To get the real benefits.
What we need to do is profoundly changethe way that we enable our people to work.
And it's in that culture shift.
It's in that process shift.
(06:12):
It's in the incentive shiftthat you will see the difference
between failure and success.
In two years, everybody will havemade many of these transitions.
That's not gonna be the differentiator.
It's whether you have made the humantransitions, not the technology
transitions that define the differencebetween being mediocre maybe worse
(06:38):
with all these new technologiesand supercharging your potential.
You know, there's this disconnect.
That was already present between howwe formally organized our companies
and how we actually behaved.
If you look at an org chart, thatis a relic of the 1850s when those
things were created, and that isnot actually how work gets done.
(07:00):
It occurs across these differentpyramids in the organization.
Rarely is that charted out.
AI is a great opportunity to chartit, but to rethink it and to look at
the bottlenecks and the constraintswhere things are suboptimal.
It might be timing, it mightbe people's attention, it
(07:22):
could be suboptimal decisions.
Where can AI alleviateall of those pain points?
One of the.
Best capabilities of ai, but theone the least talked about is the
ability to get the right data tothe right people at the right time.
Now, that can empower the front line.
It can revolutionize a middlemanagement job, it can transform
(07:45):
senior management meetings.
we have to proactively think about thatrather than starting with the technology.
Let's start with the problemswe have and how we organize.
Then so much is possibleas we rethink things.
in the book you chapters two throughfive, you showed the four pillars
of the octopus organization based onthe biological traits of the octopus.
(08:09):
I love the eight arms part and how eachof the arms actually has a brain and
then there's a central brain, and howit's just beautiful for decision making
and how decision making gets distributedin an age of ai because the people
at the edges are the people closestto the information, and up until now
there's been an asymmetry between powerand knowledge inside an organization.
(08:33):
Let's share that because if there'snothing anybody else gets outta
today's show, it's that, particularlyif you're a leader because you've
worked in Bain, for example.
Jonathan, you've worked as aconsultant as well, that so much of
the knowledge is in the organization,but it's just stuck and it's doesn't
have a way of getting to the top.
Jonathan pioneered, the, idea of theOctopus Organization back in 2022
(08:56):
at South by Southwest, and he wastalking about, mainly the RNA and
how you have radical adaptability.
And then we started looking as westarted conceptualizing the book at
what else Makes an Octopus weird?
And there's actually a lot, , ishow , you frame it in the different
elements of, those chapters.
So the fact that it has ninebrains makes it a great analogy for
(09:18):
distributed intelligence, but italso is a secret to how an octopus
can thrive without any real naturaldefenses in this hyper competitive,
dangerous environment that it's in.
you have eight arms and they couldbe doing eight independent things.
They're all sensing and thinkingand acting on their own.
(09:38):
And yet with complete contextualawareness about what's going on now,
this is what an organization needs toact like if it is going to be hyper
adaptable and hyperresponsive to thechanges with the meteor strike of ai.
So.
What does it make possible when youhave a brain, if you will, in each
(09:58):
of the arms of the organization,all the way down to the front line?
Now we can suspend all the pastassumptions about what can and
can't be devolved to the front line.
I mean, look, Aidan, we've been talkingfor 40 years about the need to devolve
and Desilo organizations back since.
Tom Peters in the 1980s, and it hasn'treally happened because you haven't had
(10:23):
the right information at the front line,nor the right amount of visibility by the
central brain senior leadership to what'sgoing on in the arms of the organization.
Now, AI changes all of that.
It makes possible.
It changes the cost of doing right.
I spend more of my time looking at thepsychology of management and less on , the
(10:48):
operational transformation, tactics.
And what strikes me the most aboutorganizations is we've talked about
psychological safety, we've talkedabout becoming more innovative.
We've talked about being more agile.
and there are two reasonsthat hasn't happened.
One, has this been too energyintensive for managers to put two
(11:10):
hours a week into their 40 employeesand then do their 40 hour a week job.
AI allows software to do80% of that work for you.
But the second thing that we don'ttalk about maybe it wasn't a good
idea for you as a leader to convinceyour secretary that they could
(11:33):
be a corporate vice president.
And what we're seeing in this world ofacceleration in this world where agents
superpower your people that it is notonly in your interests to accelerate
their careers, it is the only thing thatwill enable you to accelerate yours.
(11:53):
I think that's why, out of all thosethings you talk about, the gates
that you have to go through, edgecomputing, all these kind of things.
AI software maturity, thatthat's where people put their
efforts, not on the human parts.
And there's the human parts that blockthe technological parts from actually
distributing it in the organization.
Absolutely.
I mean, I've worked with, a major holdingcompany that basically said we're gonna.
(12:19):
We aren't gonna focus on the AI trans,the digital transformation side.
We're gonna focus on thehuman transformation side.
and they are successful acrossa whole range of industries.
You know, running multi-billiondollar portfolios with Excel, right?
The technology helps,but it's that human side.
(12:40):
It's the culture side that superpowers thetechnology and not the other way around.
The other beautiful biological traitthat you talk about is the a neural
necklace, and you say insight radiatesfrom the center, but discovery is
coordinated at the edges and thearms and heads are working as one.
(13:00):
Maybe we'll explain what thismetaphor means for the organization.
So when you talk about, an octopusis a really interesting thing about
the intelligence and the octopus . ifa shark bites off a tentacle from
the octopus, that, that tentaclewill go and attack the shark.
It has enough intelligencein it to make decisions to go
(13:22):
after that shark on its own.
When we talk about distributingintelligence, when we talk about pushing
decision making down into the firm,when we talk about creating autonomy
in the firm, we're talking about isthat how can the tentacles operate
on their own and yet coordinate todo something bigger than themselves?
(13:44):
I love that the idea of the armencountering a shark and going, wait a
second, I just need to check with the bossif this is okay to escape and not get my
arm ripped off, because that's actuallywhat happens inside organizations, Steven.
Yeah.
Jonathan and I have an article out thisweek in Top Sales Magazine, which is a
lean publication for, sales profession.
(14:07):
And we talk about AI makes possible.
Close to segments of one atleast, you know, going from three
to five segments to 50 plus.
And in fact, it already has done thisin industries like mobile gaming.
You can do that because you start to desithings like marketing and sales, and you
(14:29):
develop very detailed profiles on thecustomer, on their context, on the queues.
You can get a very clear picture aboutwhat is going to be important to them.
And then you can create marketingmaterials that are very bespoke to their
needs, is what mobile gaming companies do.
'cause they have all this data and theyoperate in this real time environment.
(14:53):
Now you can bring this to hypercomplicated B2B sales environments even.
So you've desiloed these operations.
Now look, this opens up a lot of questionsaround who's gonna do what and where
are the decision rights lying how doyou create the necessary competencies?
So it opens up a whole other series ofquestions, but it creates this remarkable
(15:17):
capability if you can start addressingthose human obstacles to change.
super turbocharge your salesand marketing organizations.
That's just one exampleof that neural necklace.
Creating this fluidity of informationthat you just didn't have before.
AI could bring structureto unstructured data.
I love that you call out again, thehuman aspects that block the change.
(15:42):
So two gremlins that areliable to gum up The works are
groupthink and analysis paralysis.
When you do get the organizationacting as one brain, not one voice.
You know, people can freakout when you have a lot of
information being presented to you.
And so either you gravitate to oneeasy, commonly understood framing
(16:07):
of the marketplace, is wrong.
In a VUCA world, that is a very dangerousthing to do, you freeze because you
have so much information, and that isincredibly wrong when you have this
hyper speed of transformation in anindustry, in an in, in a broader economy.
So we have to name the dangersto be able to defeat them.
(16:31):
And I think there are certainly two.
It means that we have to changehow we make decisions, who gets
brought into conversations.
We need to change our comfortlevel with uncertainty.
We need to insist as managers thatwe're presented with multiple options.
And we often take multiple options,probably different levels of investment.
but you have to think about your portfolioof options and not your one big bet,
(16:56):
is a hyper dangerous thing to do today
Jonathan, you worked as futuristin residence in a company I admire.
I know lately people are starting tonot admire so much, but for different
reasons, for political reasons, but whata company Amazon is and what a company.
If you were lucky enough to havestock in that company in the early
(17:17):
days, how you've absolutely killed it.
But I love the principles regardlessof people, what people think are not
of the company, of how they operateand how they're inventive of how when
they run into, oh, that doesn't exist.
Well, let's build it ourselflike Amazon Web Services.
But one of the things Iabsolutely love is how.
(17:38):
The company used APIs and there's a commonlaw called Conway's Law, which is where
the organizational technology mirrorshow the organization actually works.
And Amazon were huge pioneers ofAPI mandate and API using APIs,
Mm.
but equally they.
Mirrored that with small, close-knitteams and these service interfaces.
(18:02):
I'd love you to share firsthand yourexperience of that and how this ties
exactly into the octopus organization.
It was a deep insight for me.
I worked, on data centers, in thenineties and two thousands quite a bit.
And what was interesting was how Amazonkind of got this idea of virtualization
(18:22):
together and that you don't have oneapplication on one server that starts
to spread these things across devices.
there was an insight in there.
I think that defined how Amazon operated,which was that you could have these
independent clusters, right, theseneural clusters in the organization
(18:43):
that could operate very differently,operate on whatever software stack
operate within, with whatever way ofworking that the leader thought was
appropriate, as long as everybodyelse's code, as long as everybody else's
processes could jack into that team.
so I think there's a lot of wisdom inhere about how the octopus works, right?
(19:05):
That the octopus has these neuralnodes that operate independently.
And just to clarify what it was sayingbefore, it's not that the octopus
asks if it can get its arm bit off.
If the octopus gets its arm bitoff that tentacle, the tentacle on
its own no longer attached to theoctopus will attack that shark.
(19:27):
And so what I'm suggesting is the levelof autonomy, the level of independence
that you give your people, them theinability to innovate when you look
at special forces operators in themilitary versus, versus infantry, right?
Especially in, in, in the uk mil military,the British military, what you'll find is
that the enlisted men in the general, theydon't have a sense of seniority and the
(19:52):
way that you might a CEO and an intern.
They operate at the same place.
They eat at the same mess.
And the reason behind that, and I hada special forces planter who, rent
used to run my strategy capability.
And, you know, he'd neverquite say what he did, what he
would do was say where he was.
(20:13):
Now imagine if you're operating 250people, 2 24 hours a day, seven days
a week the border of North Korea.
Just imagine what you'redoing every night.
Now imagine for a second what happens ifyou get caught or anything goes wrong.
the general said youshould do is irrelevant.
(20:33):
To the international disasterthat's about to occur.
My point is we need to start treating ourpeople with that autonomy because if we
don't, and if we don't put the governancemechanisms in place for them to do that
safely for the organization, we won'tget the speed we need to move forward.
(20:54):
And what AI does is it gives you, forthe first time that ability to superpower
the individual, to give them context,to give them tools, to improve executive
judgment, to think through scenariosat scale, and at the same time as a
leader, have that visibility into theorganization about what's going on.
In the Navy, it's the shift fromwhat we call kill chains, where you
(21:17):
know, the president says something,therefore the admiral says something,
blah, blah, blah, blah, blah.
Down to the swabby.
Right?
To the swabby, sees something, takesan action and It impacts strategy.
Right.
In the world that we're moving into,we're moving from what the Navy calls
kill chains into what the Navy callskill webs, where the person closest
(21:40):
to the action who has the informationand the capability to make a decision.
Or in the case of the Navy,increasingly I believe the software
they need to have the decision right.
take the action.
How are you gonna do thatin your organization?
That's the big questionof the next five years.
There's great counter examplethat comes from the Navy too.
(22:03):
, Around 1900 Navy captains had atremendous amount of authority.
To go out there and basically enact theadmiral's orders, go out on the high
seas and execute commander's intent.
And by 1930 that autonomy had almostentirely vanished, and it was due to
one form of technological progress,which was the radio, because
(22:28):
the admirals could give orders.
They did.
And that's human nature, right?
We all think that we know best.
And we're gonna give the orders.
You could use AI for that to gettremendous visibility into what's
happening at the front line, andthen be barking orders all day long.
And that is not the spirit of theoctopus organization that is gonna lead
(22:53):
you to be an ammonite, to be this, veryslow moving fossilized relic, fighting
yesterday's battles and not beingresponsive to what's happening today.
let's just be aware of ourhuman natures and realize we
have to act in a contrary way.
There's a meditation I do, andit's called Heart Brain Coherence.
(23:14):
The whole idea is that you sync yourheart and brain, and I thought of it
when I was reading the book because.
First you talk about the importanceof the nine brains, each limb having
its own brain and the central brain.
But then you talk about the beautifulconcept that I didn't know about the
octopus, that it has three hearts,and I thought about how the brain
(23:35):
and heart working together createsthis ultimate adaptable organization,
Or
an organism that if that'sadapted by the organization,
it can at least thrive for awhile in these rogue waves, in
these treacherous waters thatare in the business world Today.
Let's share this beautiful concept ofthe three hearts and what each of them
(23:55):
do and how it reflects the organization.
so an octopus has different heartsfor different purposes, it has a
heart to pump its blood, it hashearts to power its skills, and it
can direct energy to the differenthearts, depending upon the needs.
It can even give itself a heartattack, which is just astonishing.
(24:17):
so that it can just have maximal energyto do what is necessary in the moment.
Organization's, heartsare their processes.
Sometimes they're articulated,sometimes they're invisible, and
therefore we call culture, but theyoperate or should operate at different
speeds and for different purposes.
(24:38):
So we define three of them.
There's the analytic heart.
Most organizations, particularlythe larger ones, are pretty good
at being the analytic heart.
There's the agile heart of beingentrepreneurial and flexible, and
usually the bigger the organization,the worse they are at that.
(24:59):
And then critically, particularlyfor ai, there's the aligned
heart to make sure that people.
Have a common purpose.
They have a clear visionabout where things are going.
They feel that the organization is notout there to cross them, but they're sort
of, both, functionally and emotionallyaligned on what needs to get done.
(25:19):
And with all that dislocation,that AI plus everything else is
creating in organizations, youneed to have that aligned heart.
So think about what are the differenthearts you need for different purposes,
and then really take stock about how goodyou are at each, and whether people know
the rules of engagement for the differentpurposes in a particular meeting.
(25:43):
Is this more about analysis?
Is it about agility?
Is it about alignment?
Sometimes it's all three, but you needto have a sense about what the waiting
is in order to hit the right notes tomake sure that people interact in the
right way, but also that they listento the messages in the right way, too.
One of the examples, becauseyou called it out there.
the difficulty for a large organizationto have an agile heart, but an example
(26:07):
you give in the book is L'Oreal,which is a massive organization.
Maybe we'll share how theyengage the agile heart.
I could not believe this when Iinterviewed a, a friend of mine who works
as a executive at L'Oreal, so this isthe world's largest cosmetics company.
It's enormous, tens ofbillions of dollars.
(26:28):
They can go from concept in a conferenceroom to product on shelf in six
weeks, which is just breathtaking.
The reason they can do thatis because they have to.
In the cosmetics world, trends govery, very quickly, and so you have
(26:50):
to be responsive at that rate inorder to thrive, and so then they've
developed all the muscles aroundthat in order to be able to do so.
The world is picking up for all ofus in terms of its rate of change.
Maybe we don't need to go from conceptto product in six weeks, but it's
definitely gonna be a faster timeframethan it has been historically.
(27:12):
So we need to think alittle bit like L'Oreal.
How do we optimize our systems to operateat that rate rather than hope the world
optimizes to our internal clock speed.
I thought this is important.
I'd love you to give some examplesof companies either you've worked
with or you've seen that start small.
(27:32):
Like the example you give isWalmart's syntilla platform.
This, AI platform that, thatcan just really sense what's
happening in the marketplace.
But maybe some other examples ofwhat you're seeing out there would
be great, just so people can see.
You don't have to be massive.
You don't have to have hugepockets to get started.
You can get started in a smaller way.
(27:53):
You know, the, the realities hereare these right companies like
Lovable, which does vibe coding.
You can explain in English what you wanta website to do, what you want a piece
of software to do, and then AI will writethat code for you, to give a sense of
speed of scale, You can explain, I wantthis website to do so on and so forth.
(28:16):
Maybe in 15 minutes andit will write the code.
It will give you a webpageand so on and so forth.
It'll take another couple of hoursto jack in all of the APIs, get
everything tested, so on and so forth.
But when you think about whathad to happen before, right?
You had to explain what you wanted Clientmanager would listen to what you said,
(28:40):
write it down wrong, give it to an artist,a designer who would make the wrong thing,
give it to a coder who would then makethe wrong thing, and then you would get to
pay to do it over again, and six or eightweeks later or six months later, you might
have a product that kind of did what youneeded and the market would've changed.
(29:01):
Now for, call it a hundred bucksa month as a product manager,
you can do that yourself.
Now, will it get there a hundred percent?
No.
Will it give everybody on theteam everything they need to do it
right the first time in three days?
Yes.
What we're talking about is that shiftin mindset, that shift in workflow.
(29:26):
Like we said before, I don't thinkthat makes all the jobs go away.
I think everybody's gonna dothis approximately at the same
time, and therefore everybodyneeds to do 10 times as much work
with the same number of hours.
So the question that we needto ask is how are we going to
do higher quality work faster?
How are we going to innovate harder?
(29:47):
How are we going to push thatcapability, those rights, to make
decisions down into the firm?
Because unless we allow our tentaclesto explore and take action faster
than we can tell them what todo, like the Navies of the early
second World War, we will be sunk.
(30:09):
Lemme give you an example
from, uh,
from,
uh,
my work, uh, new marketsadvisors, consulting firm I
run, we're about 15 people.
So we have not changed our headcount.
We do a lot more now andwe do it a lot faster.
We have a consumer healthcare client.
Previously we might have createdconcepts with them based on
some in-depth market research.
(30:31):
Now we can.
Sketch out what these concepts willphysically look like if they're, devices.
For instance, we can get anengineering schematic for different
ways that this might work, whetherit's mechanical or electronic.
We can get a rough bill ofmaterials on the costing.
We can get a rough regulatoryanalysis around where it might
(30:51):
be easier to bring to market,at least in a test market sense.
Now, is that gonna replace an industrialdesigner or a lawyer in the end?
No, but it's gonna allow usto winnow down concepts a lot
faster than we could before.
So there's gonna be a lot fewer,dead ends that we run into.
And when we finally do the turnover, thenthey're gonna be able to devote their
(31:15):
energy and their very high cost labor tothe things that are the most promising.
we can do this all so muchfaster than we did before.
So, you know, you typically think ofcheaper, faster, and better, and so
much of the world is focused on cheaper.
I mean, in some instances, sure.
Cheaper, but there's a whole lot offaster and better that people are just
(31:37):
starting to broach the possibilities of.
To me, I think that the interesting.
about so much of AI and workflowsis you're suddenly getting all
three, faster, better, and cheaper.
that's what people are kind ofmissing, is that it's no longer
(31:57):
an A plus B equals C equation.
You can put all three on the same side.
Let's share Jonathan as well, what you'reworking on, because you're working on
a product that actually can do whatSteve is doing, but for the individual.
So if you have an idea, you can reallymove fast to market and actually see,
do you have a patent on your hands?
(32:17):
I am the head of invention at acompany called Deep Invent, and
one of the things we're doing isreinventing the patent workflow.
And it's stunning when you thinkabout how patents are created
and why they're created today.
So we create patents to create amonopoly around an area of invention.
(32:39):
The, when we do it today, right,we do it typically after we have an
idea that we think has market value.
So you're six or nine monthsoften into an invention process
before you file a patent.
And the reason is that it oftencosts about half a million dollars.
You've gotta get, an applied inventor orengineer, maybe some scientists involved.
(33:00):
You have a product manager who's figuringout what the product opportunity is.
You have, patent lawyers.
And, you know, so, so you're six or ninemonths into this thing and you haven't
protected your, your area of invention.
What would happen if your momcould have an idea on Tuesday?
Say, I have a problem inmy quilting circle, then.
(33:24):
AI could say, okay,well that's interesting.
Here are all of the companies that kindof deal with stuff around this space.
Here is everything that'sever been written about this.
Here's all of the scientificliterature that's ever been developed.
Here are some areas of inventionthat might be interesting to you.
Which of these.
Are interesting.
And then let's come up with 10 inventions.
(33:45):
It'll come up with 10 ideas for howyou might solve this problem, and you
spend maybe 20, 30, 45 minutes with it.
Say, Hey, yeah, all right, I got it.
This is really, I think, the right thing.
And you press a button andit files the patent for you.
Now what's interesting about whatwe've done at Deep Invent is our
last rev of the software, we actuallyhad the AI tools write the software.
(34:11):
Figure out what was useful.
the patent themselves in this casethrough our attorney because it had
to, you had to do that because thegovernment's not caught up to this
idea yet and file its own patents oninventions it had created, created.
(34:31):
for products we are selling.
That is the shift thatwe're talking about.
We're creating tools that are faster.
That are better and that arecheaper all at the same time.
It is incredible opportunity.
I, I want to share one thing.
I can't let you guys go without sharingbecause I want to show you have the
(34:53):
scar tissue of what it's like to havean organization block your ideas.
That's why I wanted to tee you up withthe idea of Deep Invent, because back in
2009, you both have experiences of this,and it's probably why you do the work
you do today to try and prevent peopleexperiencing the frustration you had.
So.
Another great company you worked in wasHP Jonathan, and then I'm gonna come
(35:17):
to you, Steven, and talk about Scion.
But back in 2009, you saw an opportunityjust like our friend Chuck House by
the way, a predecessor of yours in HPsaw with the screen for the computer
and he was blocked, and he wrote abook called Permission Denied, but
you saw this when you were like,how the hell are we not pursuing a
(35:38):
marketplace for touchscreen devices?
And you were told to be a fast followerand it was terrible advice, but I wanted
to share this because it's what theai, octopus Organization can solve.
It can solve bottom up information,getting blocked, get to the top of
the people, making decisions fromthe people who see it on the field.
(35:59):
Maybe you'll share your story andthen it'll come and share Stevens.
well, I think there aretwo challenges here, right?
The thing that I learned, at HP theway tops down organizations work
and most organizations today aretops down , is shareholders have
a set of shareholder objectives.
They hire a board.
The board enforces thoseshareholder objectives.
(36:20):
They hire the executive teams.
They incentivize all the way down.
If you are not aligned withthe shareholder objectives.
You are not gonna have a thing happen.
what happened at HP was it was reallyoriented toward reliable performance,
especially after Mark heard the CEO in.
(36:41):
There was a moment.
Where there was an opportunity to geta couple of years ahead, potentially on
the capacitive touchscreen technology.
I was a consultant atthat point that came in.
They said, Hey, here's the opportunity.
Here's what it looks like.
Here's what other competitors are doing.
Here's where I think the market is.
I got brought in, the president ofthe PC group came in, CTO came in.
(37:03):
We had a big.
Chat about and the said, Well, here'sthe thing is that our strategy is
we are going to fast follow Apple.
We're just gonna let them buildthe market and then take it.
That didn't.
Work.
What happened was they gotcaught with their pants down.
They tried to buy something calledWeb os, which was palm computing, if
(37:26):
you remember that, their operatingsystem, which was not set up for
the next generation of devices.
So they went there, they fastfollowed, they tried to buy the
assets they needed, they didn'twork, and then they got their pants.
Taken off of them.
They got their shirt eaten orwhatever mixed metaphors we can come
up with here, and it was entirelyknowable that was going to happen.
(37:51):
The issue was that the peopleat the bottom knew this.
in the middle weren't listening tothem or asking them to actually vet
the technology, and the leadershipwas disincentivized to think about the
world beyond their revenue windows,their personal revenue windows.
And so you ended up with an almostinevitability here of the investor
(38:13):
objectives, which are growth, butconservative, reliable growth were in
conflict with the reality that therewas a sea change in the market that
the people on the ground could see,but that investors could not yet.
it's always the case, and I get stuck inthe middle, a decade previous, Steven,
(38:36):
you had a similar experience withanother product that Apple went on and
not so successfully developed, whichwas A PDA, but this was in 99 at Psion.
Maybe you'll share yourscar tissue as well.
So I left Bain and Company in 99, becauseI wanted to do something exciting.
I was working on a private equityproject in plastics, and I thought
(38:59):
the whole world was passing me by.
So I joined up with a, another, ex baney.
he was the CEO of Scion, which isthe British company that had actually
invented the PDA back in the eighties.
And they were competing againstPalm Pilot, a different sort
of,, machine, different formfactor, and doing pretty well.
The CEO had this idea of going into,what do you called a smartphone?
(39:20):
This was very novel term at the time.
So basically, connecting a, youknow, A-A-P-D-A into being a phone.
And that was about all thatwe had, , as a concept.
And we were gonna do this on awhite label basis for Motorola and a
participant for Eric Erickson as well.
So we were the guts behind their initialentries into the smartphone, business.
(39:41):
Now, I quickly got intoxicatedby what a smartphone could do.
You could play games and you could domaps, and you can even have short videos.
It was really beguiling and so we starteddeveloping a pretty high spec device
that could do all these things based oncomponents from elsewhere, but integrating
(40:02):
them together for the very first time.
All the while there was this loneindustrial designer on the team who
said, Hey, how about we just havea basic phone, but with a keyboard
rather than just a numeric keypad?
And I said, oh, you,you, you simpleton you.
Uh, no, no.
We can do far more glamorous things here.
(40:25):
And so he broadly was ignoredbecause we were, entranced by this
high-end device and the demandsof our big demanding customers.
and we wanted the prestige.
So it was the culture, it was theclassic innovators dilemma track of
being, uh, trapped by, by what ourbig, demanding customers wanted.
(40:47):
And, sure enough, we developed allsorts of dependencies on components.
There was a critical software supplierthat led us down, in terms of the data
connectivity with early mobile networks.
And that was a big, big problem.
And it turned out that theindustrial designer was describing
what became the blackberry.
Because those guys were working onthe same problem at the same time,
(41:09):
and they came out with the blackberryand they cleaned up and they dominated
the smartphone business for sevenyears until the iPhone came out.
So I took away some lessonsfrom that, for one, listen.
Secondly, for heaven'ssake, read Clay Christensen.
I didn't read his stuff untilthe weekend before I interviewed.
(41:30):
You know, with the great man, and thenI just, I smacked my forehead and I
thought, oh, I was such an idiot for notreading this stuff beforehand, because
that's exactly the trap that I fell into.
And then, yes, have a vision aboutwhere the market is gonna go.
And this definitely applies for ai, right?
Have that futuristic vision,have your priorities and your
(41:52):
step-by-step route to get there.
Way too many companies are ateither end of the spectrum.
They've got this.
This g whiz Jetsons version of the future.
And then they have their very boringhere and now let's put a chatbot in for
something and try to replace a human.
And they're not thinking aboutall the steps in between.
(42:13):
Had we done that, we shouldhave been Blackberry.
We had every right to be Blackberry, butlargely 'cause I just, I was 30 years old,
I didn't know the trap I had fallen into.
And I learned from that experience.
I think that's why we do the work we do,because that knowledge that you can learn
from just reading an article or a bookcan change the lens through which you see
(42:37):
and you see something totally different.
You see opportunity where otherssee threat or see nothing at all.
It's why I love sharingbrilliant work like this.
We haven't even gotten near.
The amount that's in the book,there's a chapter on how do you
create strategic serendipity.
There's a chapter at the end, chaptereight, where the guys bring you
as an organization, as a leader.
Through a load of questions toask yourself and exercises to
(42:59):
implant into the organization.
Doesn't cost you money, cost youa bit of time, cost you a bit of
reorganization of the organization aswell, to become an octopus organization.
Guys, let's share each of youwhere people can find you.
I know you do keynotes.
I know you do consulting.
I know Steven, you do a lotof jobs to be done work.
And of course, the patent work that youdo now, deep invent jonathan as well.
(43:23):
Really valuable stuff.
Let's share maybe Jonathan first
My name's Jonathan Brill.
I'm a business futurist.
You can find me at jonathanbrill.com.
I do keynotes andworkshops around the world.
I'm in about 80 cities a year,so I might be near you today.
and Steven.
Best way to find me is on LinkedIn.
(43:43):
Please write, I do respond toall my emails, so I would love
to, just correspond and hear whatyou're thinking about all of this.
The company is new markets advisors andyou can find us in many places online.
Authors of AI and the OctopusOrganization, Jonathan
Brill and Steven Wunker.
Thank you for joining us.
Thank you.
(44:04):
Thank you so much.
Thanks again to our sponsor,Kyndryl and the Kyndryl Institute.
With a unique blend of AI poweredconsulting, built on unmatched
managed service capability.
Kyndryl helps leaders harness thepower of technology for smarter
decisions, faster innovation,and a lasting competitive edge.
You can find out more aboutKyndryl and the Kyndryl Institute
(44:25):
at K-Y-N-D-R-Y-L Kyndryl.com.
we need to start treating our peoplewith that autonomy because if we don't,
and if we don't put the governancemechanisms in place for them to do that
safely for the organization, we won'tget the speed we need to move forward.
And what AI does is it gives you, forthe first time that ability to superpower
(00:20):
the individual, to give them context,to give them tools, to improve executive
judgment, to think through scenariosat scale, and at the same time as a
leader, have that visibility into theorganization about what's going on.
Before we start, I want to thankour sponsor Kyndryl, who runs
and reimagines the technologysystems that drive advantage for
the world's leading businesses.
(00:41):
With a unique blend of AI poweredconsulting, built on unmatched managed
service capability, Kyndryl helpsleaders harness the power of technology
for smarter decisions, faster innovation,and a lasting competitive edge.
You can find out more aboutKyndryl at KYNDRYL Kydryl.com.
Bang and everything changed 66 millionyears ago, an asteroid the size of
(01:04):
Manhattan struck the Yucatan Peninsula.
With the energy of 10 billion Hiroshimabombs, massive clouds of toxic dust,
blotted out the sun, cooled the planet,and generated torrent of acid rain.
Within weeks, 75% of Earth's specieswere on the road to distinction.
One of those was the ammonite,and it was the exact opposite
(01:29):
to our friend the octopus.
A little teaser for today's episode todaybecause why did the octopus survive and
thrive and continues to keep on thriving?
Our guests today aregonna tell us about that.
They are the authors of a brand newbook, aI and the Octopus organization.
We're joined by both authors,Steven Wunker and Jonathan Brill.
(01:50):
Welcome to the show.
thanks
us.
Good to be here.
Great to have you both on the show.
I don't always get to coverbooks that are just out.
And the only reason I cover this wasbecause I was supposed to cover one of
these guys older books, and then theypop out this brand new one as well.
So thank you for that.
Adding new books to my list as well.
(02:11):
I set us up there about theammonite versus the octopus.
Maybe one of you'll tell us whatthe hell I was talking about.
300 million years ago, the worldwas obviously a different place
and that's when the octopus startedto evolve into way it is today.
It doesn't have anystrong natural defenses.
(02:31):
It doesn't have a shell,it doesn't have big teeth.
It doesn't have any of thethings you, would kind of think
about, , as a way to defend itself.
And yet, for the last 300 millionyears after species, after species,
after species has gone extinct, ithasn't even had to evolve to thrive.
In fact, in our age of climatechange, it is thriving more than ever.
(02:53):
And so the question we started toask ourselves is, what can we learn
from the strategies of nature?
What can we learn from the strategiesof the octopus to change the way we
think about resilience, innovation,performance, agility in our organizations?
one of the things thatcomes to mind then is.
When you're reading this intro,you're thinking to yourself, well,
(03:16):
digital was probably a big bang.
The internet was a big bang, buttoday we're seeing an exponential big
bang with ai, and that's the contextinto which you entered the book.
Absolutely.
We're seeing a, a nuclear chain reactionof innovation starting to occur.
And it's hard to even imagine what thislooks like 10 years from now, which means
(03:39):
that it's hard to do long-term planningunless you plan in a really different way.
we see analogies in whatpeople are doing today.
You would not have highfrequency trading firms.
Without ai, you would not have,, digital advertising marketplaces
without ai you wouldn't have analysesof patients telematics, , as they're
(04:02):
outside of the hospital without ai.
So they might well need tobe kept as an inpatient.
This is not futurism.
This is right now.
So we have to think not just aboutthis very narrow vision of replacement
of humans, but what is now possible.
There are plenty of examples outthere in the real world today where
(04:23):
companies have shown what they can do.
I, I think the difference, right?
The big thing to think about isthat AI isn't about automating jobs.
It is about automating tasks sothat we can automate workflows.
And it's about that shift, right?
How do we replace entire workflowswith things that are better so that
(04:44):
our people are freed to do the workthat creates value as opposed to
checking the boxes and conveyinginformation and trying to remember
what the heck they did nine months ago.
I think that point is the biggest thingthat we've all experienced, the digital
revolution when digital came along andpeople just basically put websites up.
(05:07):
They just digitizedtheir existing processes.
Steven, I know you worked withthe Great Clay Christensen.
He called it cramming.
, But AI is being used the same way.
We're, we're not changingthe underlying architecture.
And this has to happen.
You talk about where mostorganizations sink before they even
start, which is organizational debt.
(05:28):
People are very concernedabout technology debt, right?
We have 23-year-old.
Machines.
We're running our ERP on Fortranfrom the Vietnam War, you know,
whatever the issue is, right?
But what I think we miss moredeeply is the organizational
(05:49):
debt that we face, right?
That, that to gain fromartificial intelligence.
To get the real benefits.
What we need to do is profoundly changethe way that we enable our people to work.
And it's in that culture shift.
It's in that process shift.
(06:12):
It's in the incentive shiftthat you will see the difference
between failure and success.
In two years, everybody will havemade many of these transitions.
That's not gonna be the differentiator.
It's whether you have made the humantransitions, not the technology
transitions that define the differencebetween being mediocre maybe worse
(06:38):
with all these new technologiesand supercharging your potential.
You know, there's this disconnect.
That was already present between howwe formally organized our companies
and how we actually behaved.
If you look at an org chart, thatis a relic of the 1850s when those
things were created, and that isnot actually how work gets done.
(07:00):
It occurs across these differentpyramids in the organization.
Rarely is that charted out.
AI is a great opportunity to chartit, but to rethink it and to look at
the bottlenecks and the constraintswhere things are suboptimal.
It might be timing, it mightbe people's attention, it
(07:22):
could be suboptimal decisions.
Where can AI alleviateall of those pain points?
One of the.
Best capabilities of ai, but theone the least talked about is the
ability to get the right data tothe right people at the right time.
Now, that can empower the front line.
It can revolutionize a middlemanagement job, it can transform
(07:45):
senior management meetings.
we have to proactively think about thatrather than starting with the technology.
Let's start with the problemswe have and how we organize.
Then so much is possibleas we rethink things.
in the book you chapters two throughfive, you showed the four pillars
of the octopus organization based onthe biological traits of the octopus.
(08:09):
I love the eight arms part and how eachof the arms actually has a brain and
then there's a central brain, and howit's just beautiful for decision making
and how decision making gets distributedin an age of ai because the people
at the edges are the people closestto the information, and up until now
there's been an asymmetry between powerand knowledge inside an organization.
(08:33):
Let's share that because if there'snothing anybody else gets outta
today's show, it's that, particularlyif you're a leader because you've
worked in Bain, for example.
Jonathan, you've worked as aconsultant as well, that so much of
the knowledge is in the organization,but it's just stuck and it's doesn't
have a way of getting to the top.
Jonathan pioneered, the, idea of theOctopus Organization back in 2022
(08:56):
at South by Southwest, and he wastalking about, mainly the RNA and
how you have radical adaptability.
And then we started looking as westarted conceptualizing the book at
what else Makes an Octopus weird?
And there's actually a lot, , ishow , you frame it in the different
elements of, those chapters.
So the fact that it has ninebrains makes it a great analogy for
(09:18):
distributed intelligence, but italso is a secret to how an octopus
can thrive without any real naturaldefenses in this hyper competitive,
dangerous environment that it's in.
you have eight arms and they couldbe doing eight independent things.
They're all sensing and thinkingand acting on their own.
(09:38):
And yet with complete contextualawareness about what's going on now,
this is what an organization needs toact like if it is going to be hyper
adaptable and hyperresponsive to thechanges with the meteor strike of ai.
So.
What does it make possible when youhave a brain, if you will, in each
(09:58):
of the arms of the organization,all the way down to the front line?
Now we can suspend all the pastassumptions about what can and
can't be devolved to the front line.
I mean, look, Aidan, we've been talkingfor 40 years about the need to devolve
and Desilo organizations back since.
Tom Peters in the 1980s, and it hasn'treally happened because you haven't had
(10:23):
the right information at the front line,nor the right amount of visibility by the
central brain senior leadership to what'sgoing on in the arms of the organization.
Now, AI changes all of that.
It makes possible.
It changes the cost of doing right.
I spend more of my time looking at thepsychology of management and less on , the
(10:48):
operational transformation, tactics.
And what strikes me the most aboutorganizations is we've talked about
psychological safety, we've talkedabout becoming more innovative.
We've talked about being more agile.
and there are two reasonsthat hasn't happened.
One, has this been too energyintensive for managers to put two
(11:10):
hours a week into their 40 employeesand then do their 40 hour a week job.
AI allows software to do80% of that work for you.
But the second thing that we don'ttalk about maybe it wasn't a good
idea for you as a leader to convinceyour secretary that they could
(11:33):
be a corporate vice president.
And what we're seeing in this world ofacceleration in this world where agents
superpower your people that it is notonly in your interests to accelerate
their careers, it is the only thing thatwill enable you to accelerate yours.
(11:53):
I think that's why, out of all thosethings you talk about, the gates
that you have to go through, edgecomputing, all these kind of things.
AI software maturity, thatthat's where people put their
efforts, not on the human parts.
And there's the human parts that blockthe technological parts from actually
distributing it in the organization.
Absolutely.
I mean, I've worked with, a major holdingcompany that basically said we're gonna.
(12:19):
We aren't gonna focus on the AI trans,the digital transformation side.
We're gonna focus on thehuman transformation side.
and they are successful acrossa whole range of industries.
You know, running multi-billiondollar portfolios with Excel, right?
The technology helps,but it's that human side.
(12:40):
It's the culture side that superpowers thetechnology and not the other way around.
The other beautiful biological traitthat you talk about is the a neural
necklace, and you say insight radiatesfrom the center, but discovery is
coordinated at the edges and thearms and heads are working as one.
(13:00):
Maybe we'll explain what thismetaphor means for the organization.
So when you talk about, an octopusis a really interesting thing about
the intelligence and the octopus . ifa shark bites off a tentacle from
the octopus, that, that tentaclewill go and attack the shark.
It has enough intelligencein it to make decisions to go
(13:22):
after that shark on its own.
When we talk about distributingintelligence, when we talk about pushing
decision making down into the firm,when we talk about creating autonomy
in the firm, we're talking about isthat how can the tentacles operate
on their own and yet coordinate todo something bigger than themselves?
(13:44):
I love that the idea of the armencountering a shark and going, wait a
second, I just need to check with the bossif this is okay to escape and not get my
arm ripped off, because that's actuallywhat happens inside organizations, Steven.
Yeah.
Jonathan and I have an article out thisweek in Top Sales Magazine, which is a
lean publication for, sales profession.
(14:07):
And we talk about AI makes possible.
Close to segments of one atleast, you know, going from three
to five segments to 50 plus.
And in fact, it already has done thisin industries like mobile gaming.
You can do that because you start to desithings like marketing and sales, and you
(14:29):
develop very detailed profiles on thecustomer, on their context, on the queues.
You can get a very clear picture aboutwhat is going to be important to them.
And then you can create marketingmaterials that are very bespoke to their
needs, is what mobile gaming companies do.
'cause they have all this data and theyoperate in this real time environment.
(14:53):
Now you can bring this to hypercomplicated B2B sales environments even.
So you've desiloed these operations.
Now look, this opens up a lot of questionsaround who's gonna do what and where
are the decision rights lying how doyou create the necessary competencies?
So it opens up a whole other series ofquestions, but it creates this remarkable
(15:17):
capability if you can start addressingthose human obstacles to change.
super turbocharge your salesand marketing organizations.
That's just one exampleof that neural necklace.
Creating this fluidity of informationthat you just didn't have before.
AI could bring structureto unstructured data.
I love that you call out again, thehuman aspects that block the change.
(15:42):
So two gremlins that areliable to gum up The works are
groupthink and analysis paralysis.
When you do get the organizationacting as one brain, not one voice.
You know, people can freakout when you have a lot of
information being presented to you.
And so either you gravitate to oneeasy, commonly understood framing
(16:07):
of the marketplace, is wrong.
In a VUCA world, that is a very dangerousthing to do, you freeze because you
have so much information, and that isincredibly wrong when you have this
hyper speed of transformation in anindustry, in an in, in a broader economy.
So we have to name the dangersto be able to defeat them.
(16:31):
And I think there are certainly two.
It means that we have to changehow we make decisions, who gets
brought into conversations.
We need to change our comfortlevel with uncertainty.
We need to insist as managers thatwe're presented with multiple options.
And we often take multiple options,probably different levels of investment.
but you have to think about your portfolioof options and not your one big bet,
(16:56):
is a hyper dangerous thing to do today
Jonathan, you worked as futuristin residence in a company I admire.
I know lately people are starting tonot admire so much, but for different
reasons, for political reasons, but whata company Amazon is and what a company.
If you were lucky enough to havestock in that company in the early
(17:17):
days, how you've absolutely killed it.
But I love the principles regardlessof people, what people think are not
of the company, of how they operateand how they're inventive of how when
they run into, oh, that doesn't exist.
Well, let's build it ourselflike Amazon Web Services.
But one of the things Iabsolutely love is how.
(17:38):
The company used APIs and there's a commonlaw called Conway's Law, which is where
the organizational technology mirrorshow the organization actually works.
And Amazon were huge pioneers ofAPI mandate and API using APIs,
Mm.
but equally they.
Mirrored that with small, close-knitteams and these service interfaces.
(18:02):
I'd love you to share firsthand yourexperience of that and how this ties
exactly into the octopus organization.
It was a deep insight for me.
I worked, on data centers, in thenineties and two thousands quite a bit.
And what was interesting was how Amazonkind of got this idea of virtualization
(18:22):
together and that you don't have oneapplication on one server that starts
to spread these things across devices.
there was an insight in there.
I think that defined how Amazon operated,which was that you could have these
independent clusters, right, theseneural clusters in the organization
(18:43):
that could operate very differently,operate on whatever software stack
operate within, with whatever way ofworking that the leader thought was
appropriate, as long as everybodyelse's code, as long as everybody else's
processes could jack into that team.
so I think there's a lot of wisdom inhere about how the octopus works, right?
(19:05):
That the octopus has these neuralnodes that operate independently.
And just to clarify what it was sayingbefore, it's not that the octopus
asks if it can get its arm bit off.
If the octopus gets its arm bitoff that tentacle, the tentacle on
its own no longer attached to theoctopus will attack that shark.
(19:27):
And so what I'm suggesting is the levelof autonomy, the level of independence
that you give your people, them theinability to innovate when you look
at special forces operators in themilitary versus, versus infantry, right?
Especially in, in, in the uk mil military,the British military, what you'll find is
that the enlisted men in the general, theydon't have a sense of seniority and the
(19:52):
way that you might a CEO and an intern.
They operate at the same place.
They eat at the same mess.
And the reason behind that, and I hada special forces planter who, rent
used to run my strategy capability.
And, you know, he'd neverquite say what he did, what he
would do was say where he was.
(20:13):
Now imagine if you're operating 250people, 2 24 hours a day, seven days
a week the border of North Korea.
Just imagine what you'redoing every night.
Now imagine for a second what happens ifyou get caught or anything goes wrong.
the general said youshould do is irrelevant.
(20:33):
To the international disasterthat's about to occur.
My point is we need to start treating ourpeople with that autonomy because if we
don't, and if we don't put the governancemechanisms in place for them to do that
safely for the organization, we won'tget the speed we need to move forward.
(20:54):
And what AI does is it gives you, forthe first time that ability to superpower
the individual, to give them context,to give them tools, to improve executive
judgment, to think through scenariosat scale, and at the same time as a
leader, have that visibility into theorganization about what's going on.
In the Navy, it's the shift fromwhat we call kill chains, where you
(21:17):
know, the president says something,therefore the admiral says something,
blah, blah, blah, blah, blah.
Down to the swabby.
Right?
To the swabby, sees something, takesan action and It impacts strategy.
Right.
In the world that we're moving into,we're moving from what the Navy calls
kill chains into what the Navy callskill webs, where the person closest
(21:40):
to the action who has the informationand the capability to make a decision.
Or in the case of the Navy,increasingly I believe the software
they need to have the decision right.
take the action.
How are you gonna do thatin your organization?
That's the big questionof the next five years.
There's great counter examplethat comes from the Navy too.
(22:03):
, Around 1900 Navy captains had atremendous amount of authority.
To go out there and basically enact theadmiral's orders, go out on the high
seas and execute commander's intent.
And by 1930 that autonomy had almostentirely vanished, and it was due to
one form of technological progress,which was the radio, because
(22:28):
the admirals could give orders.
They did.
And that's human nature, right?
We all think that we know best.
And we're gonna give the orders.
You could use AI for that to gettremendous visibility into what's
happening at the front line, andthen be barking orders all day long.
And that is not the spirit of theoctopus organization that is gonna lead
(22:53):
you to be an ammonite, to be this, veryslow moving fossilized relic, fighting
yesterday's battles and not beingresponsive to what's happening today.
let's just be aware of ourhuman natures and realize we
have to act in a contrary way.
There's a meditation I do, andit's called Heart Brain Coherence.
(23:14):
The whole idea is that you sync yourheart and brain, and I thought of it
when I was reading the book because.
First you talk about the importanceof the nine brains, each limb having
its own brain and the central brain.
But then you talk about the beautifulconcept that I didn't know about the
octopus, that it has three hearts,and I thought about how the brain
(23:35):
and heart working together createsthis ultimate adaptable organization,
Or
an organism that if that'sadapted by the organization,
it can at least thrive for awhile in these rogue waves, in
these treacherous waters thatare in the business world Today.
Let's share this beautiful concept ofthe three hearts and what each of them
(23:55):
do and how it reflects the organization.
so an octopus has different heartsfor different purposes, it has a
heart to pump its blood, it hashearts to power its skills, and it
can direct energy to the differenthearts, depending upon the needs.
It can even give itself a heartattack, which is just astonishing.
(24:17):
so that it can just have maximal energyto do what is necessary in the moment.
Organization's, heartsare their processes.
Sometimes they're articulated,sometimes they're invisible, and
therefore we call culture, but theyoperate or should operate at different
speeds and for different purposes.
(24:38):
So we define three of them.
There's the analytic heart.
Most organizations, particularlythe larger ones, are pretty good
at being the analytic heart.
There's the agile heart of beingentrepreneurial and flexible, and
usually the bigger the organization,the worse they are at that.
(24:59):
And then critically, particularlyfor ai, there's the aligned
heart to make sure that people.
Have a common purpose.
They have a clear visionabout where things are going.
They feel that the organization is notout there to cross them, but they're sort
of, both, functionally and emotionallyaligned on what needs to get done.
(25:19):
And with all that dislocation,that AI plus everything else is
creating in organizations, youneed to have that aligned heart.
So think about what are the differenthearts you need for different purposes,
and then really take stock about how goodyou are at each, and whether people know
the rules of engagement for the differentpurposes in a particular meeting.
(25:43):
Is this more about analysis?
Is it about agility?
Is it about alignment?
Sometimes it's all three, but you needto have a sense about what the waiting
is in order to hit the right notes tomake sure that people interact in the
right way, but also that they listento the messages in the right way, too.
One of the examples, becauseyou called it out there.
the difficulty for a large organizationto have an agile heart, but an example
(26:07):
you give in the book is L'Oreal,which is a massive organization.
Maybe we'll share how theyengage the agile heart.
I could not believe this when Iinterviewed a, a friend of mine who works
as a executive at L'Oreal, so this isthe world's largest cosmetics company.
It's enormous, tens ofbillions of dollars.
(26:28):
They can go from concept in a conferenceroom to product on shelf in six
weeks, which is just breathtaking.
The reason they can do thatis because they have to.
In the cosmetics world, trends govery, very quickly, and so you have
(26:50):
to be responsive at that rate inorder to thrive, and so then they've
developed all the muscles aroundthat in order to be able to do so.
The world is picking up for all ofus in terms of its rate of change.
Maybe we don't need to go from conceptto product in six weeks, but it's
definitely gonna be a faster timeframethan it has been historically.
(27:12):
So we need to think alittle bit like L'Oreal.
How do we optimize our systems to operateat that rate rather than hope the world
optimizes to our internal clock speed.
I thought this is important.
I'd love you to give some examplesof companies either you've worked
with or you've seen that start small.
(27:32):
Like the example you give isWalmart's syntilla platform.
This, AI platform that, thatcan just really sense what's
happening in the marketplace.
But maybe some other examples ofwhat you're seeing out there would
be great, just so people can see.
You don't have to be massive.
You don't have to have hugepockets to get started.
You can get started in a smaller way.
(27:53):
You know, the, the realities hereare these right companies like
Lovable, which does vibe coding.
You can explain in English what you wanta website to do, what you want a piece
of software to do, and then AI will writethat code for you, to give a sense of
speed of scale, You can explain, I wantthis website to do so on and so forth.
(28:16):
Maybe in 15 minutes andit will write the code.
It will give you a webpageand so on and so forth.
It'll take another couple of hoursto jack in all of the APIs, get
everything tested, so on and so forth.
But when you think about whathad to happen before, right?
You had to explain what you wanted Clientmanager would listen to what you said,
(28:40):
write it down wrong, give it to an artist,a designer who would make the wrong thing,
give it to a coder who would then makethe wrong thing, and then you would get to
pay to do it over again, and six or eightweeks later or six months later, you might
have a product that kind of did what youneeded and the market would've changed.
(29:01):
Now for, call it a hundred bucksa month as a product manager,
you can do that yourself.
Now, will it get there a hundred percent?
No.
Will it give everybody on theteam everything they need to do it
right the first time in three days?
Yes.
What we're talking about is that shiftin mindset, that shift in workflow.
(29:26):
Like we said before, I don't thinkthat makes all the jobs go away.
I think everybody's gonna dothis approximately at the same
time, and therefore everybodyneeds to do 10 times as much work
with the same number of hours.
So the question that we needto ask is how are we going to
do higher quality work faster?
How are we going to innovate harder?
(29:47):
How are we going to push thatcapability, those rights, to make
decisions down into the firm?
Because unless we allow our tentaclesto explore and take action faster
than we can tell them what todo, like the Navies of the early
second World War, we will be sunk.
(30:09):
Lemme give you an example
from, uh,
from,
uh,
my work, uh, new marketsadvisors, consulting firm I
run, we're about 15 people.
So we have not changed our headcount.
We do a lot more now andwe do it a lot faster.
We have a consumer healthcare client.
Previously we might have createdconcepts with them based on
some in-depth market research.
(30:31):
Now we can.
Sketch out what these concepts willphysically look like if they're, devices.
For instance, we can get anengineering schematic for different
ways that this might work, whetherit's mechanical or electronic.
We can get a rough bill ofmaterials on the costing.
We can get a rough regulatoryanalysis around where it might
(30:51):
be easier to bring to market,at least in a test market sense.
Now, is that gonna replace an industrialdesigner or a lawyer in the end?
No, but it's gonna allow usto winnow down concepts a lot
faster than we could before.
So there's gonna be a lot fewer,dead ends that we run into.
And when we finally do the turnover, thenthey're gonna be able to devote their
(31:15):
energy and their very high cost labor tothe things that are the most promising.
we can do this all so muchfaster than we did before.
So, you know, you typically think ofcheaper, faster, and better, and so
much of the world is focused on cheaper.
I mean, in some instances, sure.
Cheaper, but there's a whole lot offaster and better that people are just
(31:37):
starting to broach the possibilities of.
To me, I think that the interesting.
about so much of AI and workflowsis you're suddenly getting all
three, faster, better, and cheaper.
that's what people are kind ofmissing, is that it's no longer
(31:57):
an A plus B equals C equation.
You can put all three on the same side.
Let's share Jonathan as well, what you'reworking on, because you're working on
a product that actually can do whatSteve is doing, but for the individual.
So if you have an idea, you can reallymove fast to market and actually see,
do you have a patent on your hands?
(32:17):
I am the head of invention at acompany called Deep Invent, and
one of the things we're doing isreinventing the patent workflow.
And it's stunning when you thinkabout how patents are created
and why they're created today.
So we create patents to create amonopoly around an area of invention.
(32:39):
The, when we do it today, right,we do it typically after we have an
idea that we think has market value.
So you're six or nine monthsoften into an invention process
before you file a patent.
And the reason is that it oftencosts about half a million dollars.
You've gotta get, an applied inventor orengineer, maybe some scientists involved.
(33:00):
You have a product manager who's figuringout what the product opportunity is.
You have, patent lawyers.
And, you know, so, so you're six or ninemonths into this thing and you haven't
protected your, your area of invention.
What would happen if your momcould have an idea on Tuesday?
Say, I have a problem inmy quilting circle, then.
(33:24):
AI could say, okay,well that's interesting.
Here are all of the companies that kindof deal with stuff around this space.
Here is everything that'sever been written about this.
Here's all of the scientificliterature that's ever been developed.
Here are some areas of inventionthat might be interesting to you.
Which of these.
Are interesting.
And then let's come up with 10 inventions.
(33:45):
It'll come up with 10 ideas for howyou might solve this problem, and you
spend maybe 20, 30, 45 minutes with it.
Say, Hey, yeah, all right, I got it.
This is really, I think, the right thing.
And you press a button andit files the patent for you.
Now what's interesting about whatwe've done at Deep Invent is our
last rev of the software, we actuallyhad the AI tools write the software.
(34:11):
Figure out what was useful.
the patent themselves in this casethrough our attorney because it had
to, you had to do that because thegovernment's not caught up to this
idea yet and file its own patents oninventions it had created, created.
(34:31):
for products we are selling.
That is the shift thatwe're talking about.
We're creating tools that are faster.
That are better and that arecheaper all at the same time.
It is incredible opportunity.
I, I want to share one thing.
I can't let you guys go without sharingbecause I want to show you have the
(34:53):
scar tissue of what it's like to havean organization block your ideas.
That's why I wanted to tee you up withthe idea of Deep Invent, because back in
2009, you both have experiences of this,and it's probably why you do the work
you do today to try and prevent peopleexperiencing the frustration you had.
So.
Another great company you worked in wasHP Jonathan, and then I'm gonna come
(35:17):
to you, Steven, and talk about Scion.
But back in 2009, you saw an opportunityjust like our friend Chuck House by
the way, a predecessor of yours in HPsaw with the screen for the computer
and he was blocked, and he wrote abook called Permission Denied, but
you saw this when you were like,how the hell are we not pursuing a
(35:38):
marketplace for touchscreen devices?
And you were told to be a fast followerand it was terrible advice, but I wanted
to share this because it's what theai, octopus Organization can solve.
It can solve bottom up information,getting blocked, get to the top of
the people, making decisions fromthe people who see it on the field.
(35:59):
Maybe you'll share your story andthen it'll come and share Stevens.
well, I think there aretwo challenges here, right?
The thing that I learned, at HP theway tops down organizations work
and most organizations today aretops down , is shareholders have
a set of shareholder objectives.
They hire a board.
The board enforces thoseshareholder objectives.
(36:20):
They hire the executive teams.
They incentivize all the way down.
If you are not aligned withthe shareholder objectives.
You are not gonna have a thing happen.
what happened at HP was it was reallyoriented toward reliable performance,
especially after Mark heard the CEO in.
(36:41):
There was a moment.
Where there was an opportunity to geta couple of years ahead, potentially on
the capacitive touchscreen technology.
I was a consultant atthat point that came in.
They said, Hey, here's the opportunity.
Here's what it looks like.
Here's what other competitors are doing.
Here's where I think the market is.
I got brought in, the president ofthe PC group came in, CTO came in.
(37:03):
We had a big.
Chat about and the said, Well, here'sthe thing is that our strategy is
we are going to fast follow Apple.
We're just gonna let them buildthe market and then take it.
That didn't.
Work.
What happened was they gotcaught with their pants down.
They tried to buy something calledWeb os, which was palm computing, if
(37:26):
you remember that, their operatingsystem, which was not set up for
the next generation of devices.
So they went there, they fastfollowed, they tried to buy the
assets they needed, they didn'twork, and then they got their pants.
Taken off of them.
They got their shirt eaten orwhatever mixed metaphors we can come
up with here, and it was entirelyknowable that was going to happen.
(37:51):
The issue was that the peopleat the bottom knew this.
in the middle weren't listening tothem or asking them to actually vet
the technology, and the leadershipwas disincentivized to think about the
world beyond their revenue windows,their personal revenue windows.
And so you ended up with an almostinevitability here of the investor
(38:13):
objectives, which are growth, butconservative, reliable growth were in
conflict with the reality that therewas a sea change in the market that
the people on the ground could see,but that investors could not yet.
it's always the case, and I get stuck inthe middle, a decade previous, Steven,
(38:36):
you had a similar experience withanother product that Apple went on and
not so successfully developed, whichwas A PDA, but this was in 99 at Psion.
Maybe you'll share yourscar tissue as well.
So I left Bain and Company in 99, becauseI wanted to do something exciting.
I was working on a private equityproject in plastics, and I thought
(38:59):
the whole world was passing me by.
So I joined up with a, another, ex baney.
he was the CEO of Scion, which isthe British company that had actually
invented the PDA back in the eighties.
And they were competing againstPalm Pilot, a different sort
of,, machine, different formfactor, and doing pretty well.
The CEO had this idea of going into,what do you called a smartphone?
(39:20):
This was very novel term at the time.
So basically, connecting a, youknow, A-A-P-D-A into being a phone.
And that was about all thatwe had, , as a concept.
And we were gonna do this on awhite label basis for Motorola and a
participant for Eric Erickson as well.
So we were the guts behind their initialentries into the smartphone, business.
(39:41):
Now, I quickly got intoxicatedby what a smartphone could do.
You could play games and you could domaps, and you can even have short videos.
It was really beguiling and so we starteddeveloping a pretty high spec device
that could do all these things based oncomponents from elsewhere, but integrating
(40:02):
them together for the very first time.
All the while there was this loneindustrial designer on the team who
said, Hey, how about we just havea basic phone, but with a keyboard
rather than just a numeric keypad?
And I said, oh, you,you, you simpleton you.
Uh, no, no.
We can do far more glamorous things here.
(40:25):
And so he broadly was ignoredbecause we were, entranced by this
high-end device and the demandsof our big demanding customers.
and we wanted the prestige.
So it was the culture, it was theclassic innovators dilemma track of
being, uh, trapped by, by what ourbig, demanding customers wanted.
(40:47):
And, sure enough, we developed allsorts of dependencies on components.
There was a critical software supplierthat led us down, in terms of the data
connectivity with early mobile networks.
And that was a big, big problem.
And it turned out that theindustrial designer was describing
what became the blackberry.
Because those guys were working onthe same problem at the same time,
(41:09):
and they came out with the blackberryand they cleaned up and they dominated
the smartphone business for sevenyears until the iPhone came out.
So I took away some lessonsfrom that, for one, listen.
Secondly, for heaven'ssake, read Clay Christensen.
I didn't read his stuff untilthe weekend before I interviewed.
(41:30):
You know, with the great man, and thenI just, I smacked my forehead and I
thought, oh, I was such an idiot for notreading this stuff beforehand, because
that's exactly the trap that I fell into.
And then, yes, have a vision aboutwhere the market is gonna go.
And this definitely applies for ai, right?
Have that futuristic vision,have your priorities and your
(41:52):
step-by-step route to get there.
Way too many companies are ateither end of the spectrum.
They've got this.
This g whiz Jetsons version of the future.
And then they have their very boringhere and now let's put a chatbot in for
something and try to replace a human.
And they're not thinking aboutall the steps in between.
(42:13):
Had we done that, we shouldhave been Blackberry.
We had every right to be Blackberry, butlargely 'cause I just, I was 30 years old,
I didn't know the trap I had fallen into.
And I learned from that experience.
I think that's why we do the work we do,because that knowledge that you can learn
from just reading an article or a bookcan change the lens through which you see
(42:37):
and you see something totally different.
You see opportunity where otherssee threat or see nothing at all.
It's why I love sharingbrilliant work like this.
We haven't even gotten near.
The amount that's in the book,there's a chapter on how do you
create strategic serendipity.
There's a chapter at the end, chaptereight, where the guys bring you
as an organization, as a leader.
Through a load of questions toask yourself and exercises to
(42:59):
implant into the organization.
Doesn't cost you money, cost youa bit of time, cost you a bit of
reorganization of the organization aswell, to become an octopus organization.
Guys, let's share each of youwhere people can find you.
I know you do keynotes.
I know you do consulting.
I know Steven, you do a lotof jobs to be done work.
And of course, the patent work that youdo now, deep invent jonathan as well.
(43:23):
Really valuable stuff.
Let's share maybe Jonathan first
My name's Jonathan Brill.
I'm a business futurist.
You can find me at jonathanbrill.com.
I do keynotes andworkshops around the world.
I'm in about 80 cities a year,so I might be near you today.
and Steven.
Best way to find me is on LinkedIn.
(43:43):
Please write, I do respond toall my emails, so I would love
to, just correspond and hear whatyou're thinking about all of this.
The company is new markets advisors andyou can find us in many places online.
Authors of AI and the OctopusOrganization, Jonathan
Brill and Steven Wunker.
Thank you for joining us.
Thank you.
(44:04):
Thank you so much.
Thanks again to our sponsor,Kyndryl and the Kyndryl Institute.
With a unique blend of AI poweredconsulting, built on unmatched
managed service capability.
Kyndryl helps leaders harness thepower of technology for smarter
decisions, faster innovation,and a lasting competitive edge.
You can find out more aboutKyndryl and the Kyndryl Institute
(44:25):
at K-Y-N-D-R-Y-L Kyndryl.com.
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