Moonshots with Peter Diamandis - The Successful Entrepreneur Formula w/ Salim Ismail | EP #47
Episode Date: June 1, 2023In this episode, Peter and Salim take a deep dive into Exponential Organizations and how experimentation can help exponentially build a business. You will learn about: 02:52 | The New School ...Is Surpassing The Old School. 18:50 | Trial & Error Will Give You The Data Necessary To Grow.  29:09 | The Pillars Of Exponential Experimentation. Salim Ismail is a sought-after strategist and a renowned technology entrepreneur who built and sold his company to Google. He’s been featured in the most prominent publications such as NYT, Forbes, Fortune, and Bloomberg and has led lectures at the world’s greatest companies and about the future of Tech. Currently, he’s the founder and chairman of ExO Works and OpenExO. I'm launching a new book with Salim Ismail called Exponential Organizations 2.0. Our launch event is on June 6th. It's a 3-hour workshop covering practical strategies for achieving exponential growth in your business. Join the launch event here. _____________ I only endorse products and services I personally use. To see what they are, please support this podcast by checking out our sponsor(s): Levels: Real-time feedback on how diet impacts your health. levels.link/peter _____________ I send weekly emails with the latest insights and trends on today’s and tomorrow’s exponential technologies. Stay ahead of the curve, and sign up now: Tech Blog _____________ Connect With Peter: Twitter Instagram Youtube Moonshots and Mindsets Learn more about your ad choices. Visit megaphone.fm/adchoices
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Jam.
You know, in the old school companies
you would hire a consultant to tell you
what to do. Well, that's gone today because the market is changing too fast.
The day before something is truly a breakthrough, it's a crazy idea.
It's the most fundamental archetypal process in life.
You never know where the breakthrough idea is going to come from.
Your ability to adapt is going to drive market value.
Value is okay.
So you just got to go with it.
And so you have to be able to build that deeply into your business to succeed properly, especially
in a volatile world.
So if you're an entrepreneur starting a company, one of the things I, you know, beseech you
to try is...
Welcome to our next episode of Moonshots and Mindsets.
I'm here with my dear friend, Salim Ismail, my co-author of our newest book, Exponential
Organizations 2.0, the first CEO of Singularity University.
Salim, let's talk about one of my favorite subjects of an EXO, which is experimentation.
You know, we're living in a world where your ability as an entrepreneur to experiment on
your products and services at lightning speed is better than ever.
And ultimately, you know, we're giving up our belief that we humans know what's right and saying,
forget about that. Let's find out what actually works as a product and a service. But before we
get into that, my friend, would you refine, define what is an exponential organization? So an EXO, as we
call it, is a 21st century organizational design that goes away from the top-down hierarchical
pyramid-style command and control structures of the 20th century and moves to a much flatter
experimentation-driven, purpose-driven, agile, flexible, scalable organization structure.
And we found that we looked at the fastest growing unicorns and teased out the model.
So we're not kind of inventing something.
We're putting labels on what already exists.
And EXO is delivering typically 10x better, faster, cheaper than its peers in the same space.
Just to give you a hard data point, we mapped the Fortune 100 against this model
and found that the top 10 most EXO-friendly of the Fortune 100 outperformed the bottom 10,
like the least flexible, least agile of the Fortune 100 over a seven-year period,
delivered 40 times better shareholder returns between the top 10 and bottom 10. This just
blows your mind. As the external world becomes more
volatile, your ability to adapt is going to drive market value, right? So if you're an EXO,
a key driver of that adaptation is running experiments and constantly sensing the outside
world. Yeah. I mean, people need to wake up to the fact that things have changed. This is not
your dad's or your granddad's old business environment. People are building brand new types
of companies that are outperforming multi-billion dollar conglomerate global companies at lightning
speed. So we talked about in previous podcasts, the idea that we have internal attributes that
your company uses, your employees use to run an exponential organization and external ways that you manage
the external world or you leverage the external world. And experiments are, you know, they cross
both, right? You can run internal experiments and external. I'll mention this, you know, I have an
EXO, my PhD ventures that manages a lot of my companies and products. And I am constantly just demanding
that the team be running experiments. And it's like, one of the things I realized is a lot of
companies that are being born today, these are startups by entrepreneurs started today, are born
with a culture of experimentation.
From the very beginning, they're running experimentation.
Versus the old school, which was, you know, in the old school companies,
you would hire a consultant to tell you what to do.
And that consultant had, over time, built a model in their mind,
and you were paying them for their knowledge.
But that's just broken right now.
It's completely broken. And this is a really key point that the difference between the old and the
new, right? In the old, you rose to the leadership of a big company. Let's say you were the head of
supply chain for BMW. It's because you ran supply chain at some local level and understood the
dynamics of that. Then you rose to a country supply chain level. Then you were supply chain for one type of a car and you understood, okay, if the bit of a
recession, what suppliers do I go after, et cetera. Then you rose in prominence over usually by
seniority and having deep intuition about that domain space. Yes, intuition is really important.
Intuition. You drove your thing by deep experience and intuition, and you had a gut sense of how the market was operating.
Well, that's gone today because the market is changing too fast.
Anybody who's got 20 years of experience with supply chain of combustion engine cars is
irrelevant as electric cars come along because the dynamics are completely different, right?
So now the only way to make sense and do sense making of the outside world is constantly running experiments, testing the outside world.
You think of an amoeba, right?
Constantly probing outward from itself, trying to see what's going on and then absorbing the things that it sees as food.
That's kind of the way we think of organizations in the future.
You know, it's interesting.
As a young startup, you go in with an assumption.
You go in with what I think people are going to want.
And then the ability to run not just a couple of experiments like, you know, what subject
line should we use, but thousands of experiments simultaneously, given the rise of generative
AI and algorithms is massive.
And a lot of times our intuition is wrong about what people want or what they're going to react to.
And it's only when you run these experiments
do you find yourself evolving the product rapidly.
And you've got to be building an internal culture
of experimentation, one in which failure is okay,
because if you're going to experiment,
probably 90 to 99.9% of the time, you're gonna be failing.
And a failure means, okay, I've learned something,
I'm not gonna do it that way.
Exactly.
You know, I got a little story here.
When I was at Yahoo, we came across this,
because A-B testing on a website
is kind of one of the original forms of experimentation.
You throw out a million pages with this and a million pages with this,
see what the response is, and you have hard-driven data as to what works.
On the Yahoo homepage, there used to be seven headlines in the middle box, okay?
And we found over tweaking this that if you reduced it to six or increased it to eight,
the click-throughs dropped off radically.
But seven, for some reason, was a magic number that worked.
Nobody knew why
it worked. Nobody had any rationale for why that number worked. It doesn't make any sense at all.
But for some reason, and we found that just from A-B testing and trialing and experimentation,
that number works. So you go, okay, it works. You go with it. But you have no idea why and how. And
that's the thesis of the external world. You may come across something that works, you can't explain how or why.
So you just got to go with it.
And the only way you're going to find that
is running lots and lots of different tests and experiments.
I was on stage with Steve Wozniak
for an hour and a half debating this
and he called it tinkering, right?
Can you just get in and bang, just play.
Let your people just play with stuff
and interesting things will happen.
A quick break from our episode.
On June the 6th, Salim and I are going to be running a free three-hour workshop on how to actually build and design an exponential organization.
Would love to have you join us.
If you join us on June the 6th, first of all, you'll get free access to the book, Exponential Organizations 2.0.
Access to an AI that we've built that allows you to query the book and helps
you design your exponential organization. It's June the 6th. It's three hours. It's free. We've
never done this before. Click on the link below, diamagnes.com backslash EXO and join us. All right,
now back to the episode. Yeah. And, you know, it's a lot of, for larger companies that are trying to figure out
where they go next, right? Your products and services are stayed and you're trying to design,
what do you do? I remember in my book, bold, we wrote about something called a five, five, five
plan, which was a form of experimentation. Now, if you have a thousand employees, imagine
forming groups of five. And you say to them, listen,
over the next five days, we want you to, in your group of five, which by the way, diversity
in the group, like having an engineer and a scientist and an executive assistant, like
different groups, it's not all engineering or not all marketing.
We're going to give you a $500 budget.
We want you to go and experiment out there with designing your product or service.
It works really well in the digital world, right?
And if you get hundreds of ideas and they're experimented on, then you find a signal in
the noise like, huh, this idea that we didn't expect.
And if you're running a 5555-5 experiment, it's really
important to incentivize people to try crazy ideas, right? One of the things I like to say
is the day before something is truly a breakthrough, it's a crazy idea, right? If it wasn't a crazy
idea yesterday, then it wouldn't be a breakthrough today. It would be an incremental improvement.
And so if in fact breakthroughs
require experimenting with crazy ideas, you know, when I'm in the boardroom or I'm on stage like you
are, I say, where's your crazy idea department inside your company? If you don't have one,
if you don't allow your team to play with crazy ideas, you're stuck on incrementalism.
You know, Amazon, in fact, actually measures this down to that level. They've asked for every team inside Amazon,
you're asked how many experiments did you run this quarter? How many succeeded? How many failed?
If you're not running enough experiments and not enough are failing, your bonus gets dinged,
right? Because you're constantly pushing the learning of the organization as a whole,
not by accident as Amazon, one of the biggest companies in the world.
Yeah. Jeff Holden, who's a friend, I haven't seen him in a while though, unfortunately,
but Jeff was on my board at XPRIZE and he was the chief product officer at Amazon and also at Uber.
And he was deeply involved. In fact, I think Amazon built a experimentation engine. I think
it was called Morpheus. Morpheus, yeah. Yeah. And they were exactly doing that. It was like, they're running thousands of experiments.
I remember Jeff Bezos, I quoted him, said, you know, the success of Amazon is a function of the
number of experiments we run per year, per month, per day. And because we actually, as humans,
per day. And because we actually as humans are biased, but we don't know what works until you try it, until you try with check writers out there. So if we lift up a level, this gives the
rationale for this, I think very powerfully, because the external world today is so volatile
and so unclear as to what's coming. We have 20 Gutenberg moments. You call them asteroid impacts.
We've got pandemics. We've got bank closures. We've got geopolitical risk at a kind of a crazy level. The only way, you know,
in the past, your senior executives, based on their intuition, would go off and hunker down
and come up with a strategy. And you can't do that anymore. That's irrelevant. What you need
to be doing today is basically running a thousand experiments, constantly probing the edges of the
world and seeing what works and doing sense-making in that way, seeing what works and ruthlessly following that,
even though it goes against your gut, that it might say it goes against your experience,
goes against your intuition, just ruthlessly following that. Eric Rieskopf talks about this
as a startup being an experiment looking for a business model, right? That's a startup. And so
you just got to run tons of startup. And so, you just
got to run tons of experiments. And you look at the biggest companies in the world, all of them
started with tinkering, okay? Larry and Sergey playing with algorithms and Steve Jobs and Wozniak
tinkering with a computer, playing around with Facebook groups. All of them started as little
companies that experimented a lot and iterated like hell. And sometimes your intuition, like you said, is wrong. So when Jeff Holden was
talking about at Amazon, when Prime was first proposed, you know, the idea of free shipping
for people, it was thought of as a crazy idea. And Bezos said, let's try it. And of course,
Amazon Prime is now driving, you double-digit majority of their revenues
and their profits.
It's incredible when people come across those things.
In hindsight, it looks so obvious, right?
And at the time, it looked like a crazy idea, just as you talk about.
And you won't find them unless you have that culture.
What I think is one of the most powerful developments today is with the rise of chat GPT and auto GPT and some of the
generative AI capabilities, we can now train AIs to run those experiments and even conceive of
those experiments. So you should be kind of going, hey, AI, go run a thousand experiments on this
domain and figure out what works. Yeah, we's, we're getting there very quickly. And, you know, one of the companies out there, that's one of probably the great
experimenting companies of our, of our lifetime is Google, right? And Google not only experiments
at the, at the tiny level of, you know, bits on a, you know, sort of pixels on a page,
at the tiny level of, you know, bits on a, you know, sort of pixels on a page,
they built something called Google X. When Google went to Alphabet, it became known as X.
And Astro Teller runs that. And he's been on my stage now a number of times, a good friend and a brilliant individual. And he talks about the importance of rapid experimentation with companies.
And he talks about the importance of rapid experimentation with companies.
So Google, Google X, I'll call it for the moment versus X, has built and experimented with thousands of companies.
And you wouldn't know that because it's kept somewhat internally secret.
I asked him, why do you keep all the companies you're experimenting with secret?
And he said, because we kill so many of them so rapidly, we don't want to have on the front
page of the news in San Jose, Google fails another company, right? It looks like we're
doing poorly. But the idea of starting an experiment and failing it quickly is critical
because if you have a startup, and a startup can be a single person spending their afternoons or weekends or a small team, and you have a,
you know, a thesis for what you're going to create,
but after a period of time you realize it's not working,
the worst thing you want to do is keep spending your time and your money on
that.
So the best thing you can do is kill it quickly and then recycle those
individuals into another idea.
And make sure you trap the learning.
I may have some small part to play in this, Peter.
In 2010, we had a singularity event and Larry Page was there.
Remember, he came and spoke at the closing ceremonies.
I remember that.
And he grabbed me at the reception afterwards and he said, hey, your brick house unit at Yahoo is really great.
Should I do that at Google?
And what did you say? And he said, hey, your brick house unit at Yahoo is really great. Should I do that at Google? And I said, no.
I said, don't do it because Yahoo used our innovation unit as a PR exercise to show the world that we're really cool, which put a massive spotlight on us, which meant we couldn't fail.
I said, keep it stealth and point it into adjacent areas.
And now, obviously, lots of his own thinking.
But then that essentially is google x
where they keep itself you have to be able to fail elegantly and take the learnings the the thing
that i remember that was the most powerful from your conversations with astro was that when they
do a project at x they they will say what are the 10 reasons that this might fail can i let them go
it's a really important heuristic it's called a pre-mortem so we all know what a post-mortem 10 reasons that this might fail. Can I take them? Go ahead. Tell us.
It's a really important heuristic.
It's called a pre-mortem.
So we all know what a post-mortem is.
Like after a project has failed or product or service or company, you look back and say,
okay, why did it fail?
And he said, what we do is something called a pre-mortem. So before we launch a product or a service, we get together with the team and we say,
OK, I want you to imagine that we are three months after the launch of the product or
the service and it failed miserably.
And you know why it failed.
Write down on a piece of paper the reason that this product failed.
And they collect all of those and then they discuss them.
And sometimes they find actually great reasons why this is going to fail but no one was was felt permission
to share their idea so anyway that's uh for me these ideas of a premortem are are what i loved
about what i loved about that approach was they take the reason the biggest reasons why it might
fail and they and they test
those first right and then you you should be able to knock that idea off the perch pretty quickly
if you take the top highest reasons it may fail and then just work your way down the list but if
you get to the end of the list this is going to be a successful product because you worked out all
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I mean, there's so many other things that have changed in the world that allow us to do rapid experimentation.
Like, you know, basically being able to launch a website product even before it exists, or go out with Google search terms and
see whether people will search on your term. Or you can describe an offering, get people to the
credit card page where they would click to buy and say, I'm sorry, this product is not available
right now, but if it becomes available, we'll let you know. Thank you for your willingness to buy.
available right now, but when, if it becomes available, we'll let you know, thank you for your willingness to buy. I mean, you can run virtualized experiments on virtualized products
and get the data to the point where, you know, I'm pretty clear this is going to function.
We talked about this in the last episode a bit, but it's worth restating Kickstarter.
Yes. I love Kickstarter.
Crowdfunding means that for the first time in the history of business, you can get market
validation for a product before you build a product, right? That's just unbelievably powerful
to getting an idea out to market, especially for consumer facing products. And I think this is
where this in time, even think about the idea that the evolution itself operates on an experimentation
basis, right? We throw out gene mutations and you see what works
and those survive by natural selection.
It's the most fundamental archetypal process in life.
And so you have to be able to build that deeply
into your business to succeed properly,
especially in a volatile world.
So if you're an entrepreneur starting a company
or you're in a company and you're managing a team, one of the things I
beseech you to try is building a culture of experimentation that constantly be describing
experiments that you're going to run, what you're looking for as the answer, and then run those
experiments. And at a minimum, it's the subject line of the emails
you're sending out. At a maximum, it's like, let's come up with 10 variations of the business and try
an MVP in some of those and see what actually works. MVP for those unfamiliar is from Lean
Startup. What's the minimum viable product, right? What's the smallest set of features that get it
out there and allow you to test and iterate? When we were building products at Yahoo, Peter, I remember Katerina, we brought
Katerina Fick to come in. She was the founder of Flickr. And she would say to the teams,
okay, great, you're building this product with 20 features. Fabulous. It's going to take you
two years. Give me the two features that are going to have it succeed. Which are the two out
of the 20 that go, oh, this and this? She'd go, great, build those two, show me that the product succeeds at all,
and then iterate and add the others rest. Don't wait till you build 20 features before you get
out there, you may fail. So that's essentially the birth of that entire idea of MVP, critical idea.
You take the smallest feature footprint, get it out there and iterate very, very fast. Yeah. I mean, what you're battling as an EXO is what I'd call the tyranny of confidence.
Like, you know what the right answer is. And the reality is you don't. And you've got to be
running these experiments. And it's easy for a startup, especially at T equals zero in the culture for you as the founder or founders to say,
just, you know, every time you're meeting, it's like, what's the experiments we're running?
What are the variations we're running? What's the data we're collecting? And just getting into that
mindset of rapid experimentation. If you're a large company and you're dealing with the tyranny of confidence, the tyranny of seniority, you know, which is a problem.
It's a huge issue.
I love that phrasing tyranny of confidence.
You know what solves that is the dedication to the MTP, right?
If you're really trying to solve that problem, okay, it doesn't matter how many times you fail.
It doesn't matter. You just keep plugging away at it because you're so emotionally excited and connected to the problem space.
So let's talk about experimentation in large companies.
I mentioned the idea of a large company running these five, five, five experiments.
It's unleashing. You never know.
And one of the important things here is you never know where the breakthrough idea is going to come from.
You think it's going to come from your head of engineering or your, you never know. And one of the important things here is you never know where the breakthrough idea is going to come from. You think it's going to come from your head of engineering or your,
you know, but it could be the person in literally the production in the mailroom or the executive assistant who happened to put two or two together. It's typically, again, a crazy idea. It's not
coming from your normal sources. So how do you tap into the wealth of knowledge inside your
organization? This is the hardest thing for big companies to adopt because big companies don't
tolerate failure, right? It's what we call a CLM, a career limiting move. You fail, you're done,
right? That's the basic ethos. So people stay, keep it safe and they never test and experiment.
And this is the hardest cultural paradigm to shift.
That's why you have to build a company as an EXO to start or start EXOs at the edge
in order to do this.
And you can turn it into a game.
You know what Adobe did that was really successful?
They gave every employee a red box, a shoe box, with startup instructions and a $1,000
check.
And they said, if your manager won't let you build some feature or some product
that you think was worth building, here's a thousand dollars.
Go build it.
Go hire some developers in Estonia or India or wherever and start building that.
So people got together, pooled their Redboxes,
got together 10, 20, 30 grand and started building features.
And it turned out something like 50% of Adobe's revenues
three years later came from those Redbox programs.
It's crazy.
It's crazy.
If you let them go,
and you know, Google talks about this as their 20% time,
right, which yielded Gmail.
3M, I think, is the most legendary.
They would give their researchers 30% time
to tinker and play, okay?
I think in today's world, it's got to be 50% to 70% of
time. Let people just play around and you'll find those results are where things work.
One of the other places you can go to get great ideas that you might not think about
is not inside your organization, but it's the community out there, right? It's your customers
and people who
love what you do and what you stand for well this is where community and crowd are so critical as
elements right if you can run experiments in the community it gives you a free place to test things
and then you bring them in and you know you've given an example before of actually going out
to community and saying what features should we add? What products should we create?
Yeah, this is Chris Anderson doing DIY drones did this.
You know, you've got 300,000 people
that are drones enthusiasts.
When they want a product, they just go,
what do you guys want?
And they go, oh, we want a DIY kit.
Great, that drives your product development.
And I think successfully running and asking the community
or getting your community to run experiments
and sourcing that
back in is essentially the future of most products going forward in the world. But in order to run an
organization that is that experimental, it's got to be agile. It's got to be data driven.
You have to be able to actually collect the information, measure it, and make decisions based upon the data.
There's some critical cultural prerequisites, right?
You have to have the culture allowing failure.
You have to have an MTP, by the way.
And you have to, the third one you really need, we'll talk about this in another episode,
is autonomy.
You know, GE worked with Eric Ries and they ran the biggest corporate training exercise
in business history.
They trained 60,000 managers on lean startup. Okay. And it failed and it failed. Why? Because
they didn't have autonomy. Okay. They were expected to experiment only in that particular
domain, which blows the reason for experimentation. It's antithetical to experimentation and play
and tinkering. Right. And so there's some prerequisites.
It's not an easy attribute to put into legacy organizations, maybe one of the hardest, but it's the most critical.
You know, it's interesting.
I was just at a board meeting yesterday of VATM, which is Eric Poulier's company that creates these extraordinary metaverse experiences. And they've built the
toolkits that allow people to build on top of their platform. And the stuff that was coming
out of it, it would have, you know, the company's relatively small engineering staff and what these
other companies were building was crazy, right? So it's like Roblox as well.
You know, Roblox offers a platform that allows other people to build, you know, games on top of.
And so they get thousands of new games.
And there's no way that the internal team could have built any of these successful games at scale.
Yeah. So this becomes incredible if you can
build a platform and offer tool sets to a community and let them build on top of you,
then you're onto a total winner and nobody will unseat you from that because you're,
you're the coral reef, right? And a million little organisms are running around building
on top of your coral reef and adding to it as time goes by. Hey everybody, this is Peter,
a quick break from the episode.
I'm a firm believer that science and technology and how entrepreneurs can change the world is the only real news out there worth consuming. I don't watch the crisis news network I call CNN
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challenges, what the breakthroughs are in longevity, how exponential technologies are
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These technologies are transforming what you as an entrepreneur can do.
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Now back to the episode.
So we just to wrap this up, I want to just bring back how all of these EXO internal and
external attributes work together.
So we've been talking about experimentation here and experimentation works when you've
got access to, first of all, AI and algorithms to help you analyze the data you're experimenting with.
The second is you have dashboards that allow you to measure and track which experiments are working and which are going in the wrong direction.
Because if you're building an EXO, things move fast.
And you need those dashboards to be live and visual to everybody involved autonomy like
you just said to allow teams to go off and try crazy ideas because if they can't have the autonomy
to try to follow their you know their gut and try things out then then you're then you're stuck and
then you know we talk about community and crowd which is you can tap the community and crowd
to help generate ideas for you and then engagement for you to be able to like engage them,
incentivize them to play these games with you. And then the MTP becomes the guiding directive
thing saying, okay, this is the direction in which we're going. You know, if you look,
think about your X prizes, Peter, right? The super proud to be on the board. And the way that what got me so excited is you have a huge
problem like curing cancer or fighting wildfires, right? And then you get, you're essentially
allowing the entire world to run experiments and win an incentive prize as a result of that
experiment, right? So you've, I think, XPRIZE has learned how to run experiments at scale in the crowd at
a global level, unlike any other organization in the world.
Thank you for that.
And I'm very proud of what the team has done.
You know, I think it's important to realize that MTP as the guiding light, and we'll come
back to that again.
And I think everybody here isn't please if you're
an entrepreneur if you're running a company even if you're running a you know part of a company
or for yourself or for your family having a massive transformative purpose that helps you
decide what to do and what not to do you know i'll go back to that quote from martine rothblatt
where she said listen the difference between successful and very successful people
is successful people learn to say no to a lot of things. Very successful people say no to almost
everything. They're focused, right? And if you're running experiments inside of an organization,
you know, you want to make sure that your experiments, if you're a coding company,
don't take you into making shoes i mean it's like what's
your what's your purpose in life and running experiments that all are marching in the right
direction because you might find yourself in a business area that you don't care about anymore
and and money is not a reason to be making a business work it really is to make a difference
on the planet and money comes along with that you You know, I struggle with this because I get excited about so many things.
I'm terrible at this.
The focusing and the narrowing down.
I'm like, oh, let's do that.
Let's do that.
And then you end up chasing a ton of butterflies and you're not effective at all.
So the MTB becomes critically important to kind of keeping yourself on the rails.
All right, buddy.
Well, this was fun.
Again, just to echo,
experimentation is something you can now do.
It wasn't something easily done even 20 years ago,
but today experimentation is table stakes and your ability to use AI,
to use the crowd,
to be running experiments
is fundamental to being an exponential organization
because your intuition may not be
what actually is the best decision for your product or service an easy thing to try go to chat
to pt and say here's my company what experiments should i be running yeah and just query just run
some iterative queries on that you'll find something you know some amazing things to test
and try out pricing models customer action behavior action, behavior changes, etc., etc.
All right, pal.
Good to have this conversation.
Great.
Excited for Exponential Organizations 2.0 to make a difference in the world.
It's a big experiment.
It is.