How AI is Forcing Startups to Rethink Pricing w/ Madhavan Ramanujam

Recorded at the NFX SF HQ, this episode features Madhavan Ramanujam (author of Monetizing Innovation and Scaling Innovation), alongside Pete Flint (GP at NFX, founder of Trulia) and Anna Piñol (Partner at NFX). Together, they break down how AI is changing the rules of pricing, defensibility, and growth. He covers the shift from services to venture capital, AI monetization, and how early discussions on willingness to pay shape value capture. Strategies for seed-stage startups, successful POCs, and enterprise deals are examined, highlighting simple pricing communication. The episode also addresses outcome-based pricing, AI's potential to reduce pricing bias, and tactics for profitable growth. As startups navigate AI adoption, the significance of the 20-80 axiom and overcoming resistance to price changes are emphasized.

Episode Transcript

(00:00):
20% of what you build in tech drives 80% of thewillingness to pay.
This I've seen it over and over again.
Why is AI making us rethink pricing generally?
I think products have very increased autonomyand very increased attribution.
That actually gives you insane monetizationpotential.
And if you don't capture that from the get go,you're training your customers to expect more

(00:23):
for less and then that's a slippery slope.
Right?
So how do you capture that value?
Alright.
Madivan, so good to have you and so good to seeyou again.
I'm Pete Flint joined by Anna Pineau from NFX.
And so it's such a delight to have you back onthe NFX podcast.

(00:44):
We go back a long Way back.
Way back.
So a little bit of context.
So we were together like a dozen years ago whenyou were at SKP doing some pricing work at
Trulia.
And I think you'll get into this.
But we at Trulia, we started with a verysimplistic pricing idea, like what can we sell

(01:10):
and what is easily understood really, reallyquickly.
And we left a lot of value on the table.
And then we were lucky to be connected withyou.
And you came in and really helped to improveand add a level of sophistication about pricing
and insight, which not only economically supervaluable, but I actually found it fascinating

(01:33):
professionally because it's just a mix ofpsychology and economics.
Yeah, And it was also a time date.
It was before the IPO, I think.
Exactly.
So yeah, I think it sort of pretty quicklyadded 7 figures to the bottom line.
We've stayed in touch over that dozen years.

(01:54):
And so maybe share a little bit about kind oflike what a little bit of kind of how you spend
your time and perhaps what you're doing rightnow.
Absolutely.
And it's super awesome to be back.
Thanks for having me.
So, I mean, the last, fifteen years, I prettymuch spent working with tech companies on
helping them with monetization.
So I worked with over 250 companies, more than30 unicorns, navigating monetization

(02:19):
challenges.
I did this in a professional services capacity,SKP or Simon Kutcher and Partners, like you
called it.
You know, me and, my co GP, Josh, who was alsoat Simon Kutcher, we, left last year towards
end of last year and we started a venture firm.
That's what is keeping me busy now.
I mean, combined the two of us have worked withour finite companies.

(02:40):
But the reason we actually pivoted to likeventure was to specifically also work with very
early stage AI companies and we can unpack abit of that.
But my, you know, life right now is invest incompanies, roll up my sleeves and work with
founders.
And you've and you've written a couple ofbooks.
You've written the first one, which ismonetizing innovation, which which I've highly

(03:05):
recommended to so many founders.
And then the the most recent one, whichlaunched just a couple of weeks ago, is scaling
innovation, which is really thinking aboutmonetization in a AI first environment, which
we're in now.
Exactly.
I mean, not just building great breakthroughproducts, but how do you build a great
business, especially AI focused.

(03:26):
Great.
So I think so today, we really want to pack inWe spent a lot of time, Adam and I and the rest
of the firm at NFX, thinking about how dofounders think about pricing in this crazy AI
world where you've got these breakthroughproducts.
But you've also got a world where you're seeingsoftware become increasingly ubiquitous and

(03:47):
potentially commoditized as well.
So maybe, Anna, you'll kick things off.
Yeah.
Just to kick things off, so ever since this newwave of AI companies started, it was pretty
obvious to all of us that this new technologywas unlike anything we have seen before.
By investing early in some of these companies,we were quickly exposed to the new
possibilities in terms of value creation, andas a result, like emerge in terms of value

(04:12):
capture.
And we often find ourselves discussing pricingwith our founders as I'm I mean and and one of
the things that I wanted to kick this off withwas how have your own conversations around
pricing evolved over the last few years inwhich we've been in the era, and why is AI

(04:33):
making us rethink pricing generally?
Yeah.
I think the big there are a couple of bigchanges that have happened.
Right?
I mean, if you think about, AI monetization orpricing, when should I think about it has
changed dramatically.
Because in the previous vintage of companies,we could still say, let's just grow and figure
out monetization when you're running a 80% SaaSmargin business to some extent.

(04:57):
Right?
You can't do that in AI for two reasons.
One, there's cost dynamics to navigate from theget go, and there's also like value capture
like you rightly said.
I mean, if for the first time, I think productshave very increased autonomy and very increased
attribution that actually gives you insanemonetization potential.
And if you don't capture that from the get go,you're training your customers to expect more

(05:21):
for less and then that's a slippery slope,right?
So how do you capture that value?
If you're building something as an agentic, youknow, AI product for the taps into labor
budgets, labor budgets are 10x compared tosoftware and IT budgets.
So if you use use the old playbooks, you'llcompletely under monetize.
So what we are seeing is monetization and GTMis becoming really really important even in the

(05:44):
pre seed and seed companies.
And even in the previous, you know, vintage ofcompanies, we could say that if I have a two
year coding head start, that is a mode.
You can't say that anymore.
Right?
I mean, you can probably code things up inovernight.
So what is the mode?
You need to have some, you know, proprietarytraining data, network effects, and also like
GTM becomes a moat.
And in that perspective, your monetizationmodel becomes a moat and how can you have

(06:07):
durable revenue.
So all these questions kick in from day one.
So what has really changed is the focus startsmuch early.
I mean, that's kinda also why I alluded to thefact that, you know, that's why we also pivoted
to like work very early in a venture settingwhere we are investing and operating as opposed
to being on a fee for service model ourselves.
We we changed our own pricing model.

(06:28):
If you think about it, right, it was more onthe usage, now we are on outcome basis.
Yeah.
That's awesome.
And have you seen this happen before?
I guess there's been like prior waves, priortechnology waves that have also been known for
setting new pricing models.
Yeah.
I think with every technology wave, there'sbeen a new pricing model innovation that's
kicked in.
Right?

(06:49):
I mean, if you take Salesforce back in the day,you know, SaaS pricing was a huge shift from,
like, on on prem, you know, perpetual licenses.
I mean, to take someone like AWS for instance,the, you know, pay as you go for
infrastructure, that was a big wave thatactually started.
Even companies like Uber started like dynamicpricing as a wave on its own.

(07:12):
With AI, what we are seeing is there's probablya move in impetus to be more outcome driven
because we are moving from a, you know, buysoftware for access to buy software for work
delivered.
And I think that is where the industry isheading, the way I see it.
Mhmm.
And you are you are a big proponent.

(07:32):
I mean, in your book, you talk a lot aboutencouraging founders to have willingness to pay
conversations early, a little bit aligned withthis idea of, like, pricing is very important
since the get go.
What are some tactics that you can share to doa good job at that?
Yeah.
Sure.
I mean, early willingness to pay conversationis really important.
I mean, let's talk about the why and then wecan talk about the how.

(07:54):
The why because if you just build a product,slap on a price and you throw it out, you're
just hoping, you just don't know.
I mean, what we talk about testing forwillingness to pay is like testing for just
like product market fit.
Right?
I mean, entrepreneurs know that.
I mean, if someone comes and asks me, do youlike the sparkling water?
I like it.
Do you like it for $25?
The whole conversation is different, right?
So unless you put actually pricing as part ofyour product market fit, you often hear what

(08:18):
you wanna hear, right?
So willingness to pay is critical, so you canat least identify even before you're launching
your product.
Is this product something that people needvalue and are they willing to pay for?
And then architect the product around it.
If if you find there's no willingness to pay,the most important question is to ask why?
And then you start hearing all kinds of thingsthat you can actually productize around jobs to

(08:41):
be done and unmet needs.
So that's the why, it's very critical.
It's like test and learn, you know,monetization before just slapping on a price
and hoping.
On the how to do it, in the book monetizinginnovation, we devoted an entire chapter to
that, it's chapter four.
That's the most important chapter to read forthe listeners.
But I might like, let me just unpack maybe onespecific tactic that actually Rahul Wara used

(09:07):
when he came up with his own monetization forsuperhuman, right?
So what we call is, it's like the acceptableexpensive and probably really expensive
questioning to understand psychologicalthresholds.
So the way that works is you know, you takeyour product, know, your wireframe, blueprints,
demos, free trials, whatever.
Mean, just put people through the experience ofthe product, so you're having your same sales

(09:31):
and marketing conversation that you'd actuallyhave, you know, and then and then have the
pricing conversation.
So once they understand the value, ask themwhat do you think is an acceptable price.
You know, clock that answer, then ask them whatdo you think is an expensive price.
Clock that answer and ask them what's aprohibitively expensive price.
This is a very stylized way of asking.

(09:52):
If you just go and ask something like, youknow, how much should I charge for this
project?
You know, I should charge for this product,you'll probably get garbage bag.
Right?
I mean, that's your job.
But if you ask it this phase after you pitchthe, you know, entire product, the sales
marketing conversation, you start hearingsomething reasonable because acceptable price
tends to be the price where people arenegotiating with themselves.

(10:13):
That's the price that they love, not just yourproduct, so they're gonna lowball all day long.
Expensive pricing tends to be where it isaround your value price, and prohibitively
expensive tends to be where they'll laugh youout of the room.
Now if you do this a bit statistically withlike, let's say even hundred, two hundred
people on an online study or how you administerthis, you start seeing that these demand curves

(10:34):
have cliffs.
Like for instance, after 29 if you go to like31, suddenly 20% of people actually think it's
expensive or you know, or 40% don't find itacceptable, etcetera.
So then you start seeing these psychologicalthresholds.
That's how you know that okay, you need to beright around that price point.
If you cross it, it's gonna be a threshold.

(10:55):
So Rahul actually used this for superhuman andfound that, you know, $30 was a great price
point for the product that he had and that'salso how we actually launched it at a $30 price
point.
And he was talking about this in an a 16 zpodcast, that's where I learned that he read
Modernizing Innovation and did this and we'vebeen great friends since then.

(11:15):
Out of these out of those three differentsegments, acceptable, expensive, prohibitively
expensive, like, where do you wanna anchor?
Yeah.
So if you're in the look.
If you're if you truly wanna be price valuealigned, it's typically on the expensive.
Probably expensive is like, you know, youshouldn't be there.
That's like, it's a price premium paradox whereyou just wanna overprice thinking it's good,

(11:38):
you're actually gonna hurt yourself.
If you're in the, acceptable zone, maybe in thegrowth phase it's still okay to be there
because you can actually then you're gonna geta lot more acquisition.
Yeah.
As long as you have a land and expand strategy,it might be just fine.
Yeah.
Okay.
Yeah.
But if you wanna start off with a value price,then the expensive price is probably more
closer to your value price.

(11:58):
It's the price where, you know, people don'thate you, they don't love you, they're just
neutral, they'll pay you.
Yep.
So Mhmm.
I'm curious, thinking about, like, popularlike, ChatGPT, Cursor, there are there are many
claims that they might be not fully capturingthe value that they're delivering.
Like, what do you make?
Yeah.
I I think it's there are some self inflictedanchors in that space.

(12:22):
Right?
I mean, is a $20 price point actually, youknow, good or can it be more?
I mean, back in the day, Copilot, GitHub,everyone started at ten, they moved it to like
twenty, thirty.
I mean, there's some anchors.
Right?
I I really think that for for that, you need toreally understand what value you're actually

(12:42):
bringing to the table, and can you charge avalue price based on that?
And can you contextualize that, you know,pricing?
I mean, we talked about superhuman, but just todrill down a bit on that, one of the chapters
we write in scaling innovation is calledbeautifully simple pricing.
How do you keep it simple?
And when you think about it, when Rahulactually introduced superhuman, he was

(13:02):
competing with free alternates, Gmail andothers.
Like, why would people even pay money foranother email app was a question mark.
But he was actually delivering core value,which is, you know, I can free up your hours
and increase your productivity because you can,you know, log into an outbox, etcetera.
But the key there was the beautifully simplepricing talk the value story.

(13:27):
So he didn't just say it's a $30 price point.
He said it's a dollar a day to get five hoursof, productivity back in a week.
Now that $30 doesn't look too expensive.
Right?
And that's actually how everything took offbecause, okay, will you pay the price of a
latte to get five hours back?
Absolutely, I would do it, right?

(13:47):
But so the entire premise was on the value.
Where many of these coding agents, whitecoding, etcetera, while they're emphasizing,
you know, the fact that you can do things fast,they're not emphasizing necessarily the value.
So instead of a $20 per month, if it's a $30,$11 a day to get incredibly efficient at coding

(14:08):
and save you, like, five hours or ten hours aday, would you pay for it?
You would, but you probably never charge, sowhy should I?
So I think if you start wrong, you kind of endwrong.
Then, of course, the different strategy, youcan say I wanna grow, I mean, you you see some
of, you know, some of these companies having,like, very fast ARR, but we can talk about

(14:28):
whether that's durable, what are the margins,there are a lot of question marks.
Do you have a do you have a point of view onmargins?
It's because it's it's such a it's such acompetitive environment out there, and any good
idea is replicated very quickly.
And with the cost of software coming down, itseems the sort of incumbent SaaS businesses are

(14:48):
kind of holding onto margins.
But are we in a world where, you know, the youyou see many of these AI companies launching
and their margins are 90 plus percent becausethey're first mover and they're rep and they're
replicating labor budgets.
Whereas you're mentally like, well, howsustainable are these margins long term?

(15:09):
Do you have a point of view on how things willevolve?
Yeah.
I think the the key is to focus on, you know,both market share and wallet share.
Right?
That is that's how I see it.
So it's more profitable growth.
It's not profits, it's not growth, it'sprofitable growth.
That's also the subtitle of the scalinginnovation book, how to architect profitable

(15:30):
growth.
And what that means is it doesn't mean that youneed to have, you know, equal efforts at any
given point in time on market share and walletshare, but you need to have equal attention in
the sense that, you know, even if you, gaveaway on price to actually acquire customers,
are you thoughtful about the fact that you canland and expand later and you have a clear

(15:53):
vision on how to actually, you know, go towardswallet share?
And similarly, you know, if you started more onthe wallet share side because you think there's
a new market that you can start shaping, do youhave an alternate to actually create a low end
product to actually gain more market share?
So it's being thoughtful about it and havingequal attention, but not necessarily equal
efforts because at certain points in thecompany, you might actually wanna index more on

(16:15):
one level or the other.
But the best CEOs have been the ones that canactually think about the interaction effects
between, you know, acquisition, monetization,and retention.
And the and then you start building towardsprofitable growth.
So while we talk about some AI companies havinghigh margins, on the flip side, some of them
have really low margins, like, especially ifyou take, you know, some of the coding ones

(16:38):
that we talked about.
I mean, there was a TechCrunch article thatit's either neutral or negative in terms of
margin.
Right?
I mean, and if you have a lot of ARR atnegative margin or neutral margin, we can
question, is that a great business?
Or do they have a pathway to get to, you know,better margins?
Would they build their own model?
Is there efficiencies that we will see?
Or if it's just hoping that the cost would comedown, hope is not a strategy.

(17:03):
So founders, you know, ask us every day, like,just how do you think about monetization
strategies?
And what are what are some of your frameworksto think about monetization strategies for
early stage startups?
Yeah.
I think there are two questions that come up,and maybe I'll be curious to see if it comes up
in your conversations with founders.

(17:24):
And if those are the right ones, we can unpackeach of those.
The first question that comes up is, you know,how do I charge for this product?
Like, what's the pricing model?
Because often we say how you charge is way moreimportant than how much.
Should I be on consumption based?
Should I be on seed?
I saw someone else doing outcome, should I dothat?
So, like, what should I do?

(17:44):
Right?
I mean, that's closely tied to your operatingyour business that it it comes up and that's a
sort of choice that you take earlier on.
And the other question that comes up especiallywith b to b AI companies is, hey, how do I
navigate POCs?
I'm getting into these commercial agreements.
My buyer wants to see whether these productsdeliver value.

(18:05):
How do I charge for it?
How do I navigate these big deals?
Right?
So those two questions keep coming up in thepre seed and seed stage.
And so and so let's
just Is that similar same with your company?
Yeah.
It it absolutely.
They're like, okay.
We have a breakthrough product idea.
We know that this is I mean, I think there's ain consumer, it's you know, that in some ways,

(18:27):
the superhuman story is a reference point forsome of these consumer applications.
But in b to b, it's kind of more complicatedbecause there's a sort of deeper engagement.
So maybe just walk us through how you might howfounders might think about kind of navigating
the price discovery with with customers who arewho are which we see today, like enterprises

(18:50):
and and and SMBs are so open to AI.
They've kind of they're experiencing it intheir daily life.
They say, I know this can be helpful.
So they're very open and receptive toconversations.
And founders are building amazing tools, butthey are not clear how to navigate this dynamic
between what is the value I'm delivering andwhat is the price I'm able to to charge.

(19:14):
Yep.
No.
Totally.
I think let's probably then talk aboutnavigating those big deals first, and then we
can come back to the pricing models later.
So these POCs have become critical because likeyou said, there is a lot of curiosity on the
buyer's side.
Right?
And also a lot of budgets to experiment.
They wanna see if AI can actually help theirinternal efficiencies and things like that, but

(19:36):
they don't know how.
So they keep asking these AI startups andcompanies saying prove the value.
So now the classic mistake that a founder makesis approaching the POC as a technical
validation, Right?
Because if you're just approaching it as, willmy tech work in the environment of your
customer, you're not really proving out anybusiness case at all.

(19:58):
Right?
So we actually talk about when you think aboutPOCs is to frame a POC as a business case
validation exercise.
Tech is tech validation is part of that.
So which means that, you know, you try to cocreate an ROI model with your customer.
So what that means is, you know, you start thePOC and say, okay.

(20:18):
It's a finite amount of POC, maybe a month, twomonths, three months, whatever, not more than
three months, typically.
And then you say, okay.
For that period, we are going to jointly createa business case.
Why is this important?
Because the buyer on the other side nowactually participates in that co creation and
becomes the smarter person in theirorganization where they can actually shepherd

(20:40):
it after that, you know, two to three monthsand say, hey, this product will actually unlock
x millions for us, and we should buy this.
Right?
I mean, so you also inevitably make themsmarter.
And the other reason to do this is if you justwork on something and show up with an ROI
model, no one is gonna believe you.
If they work with you on the inputs, they will,you know, believe the outputs.

(21:01):
As simple as that.
So framing the POC as a business case exercisewhere you're building a business case saying,
is there value generated from that AI?
And being on the same page with customers.
This is the key thing and if you don't do that,it's a mistake.
And when you actually do that, there arevarious, you know, things that you need to

(21:22):
think about in terms of how do you value sell,how do you create an ROI model, how do you
negotiate, all of those things become critical.
But you postpone the pricing conversation toafter the POC.
So the POC is typically a fixed engagement onlyto build the business case.
Then you tell the customer that, okay, look,commercial discussions will follow because you
want to clearly upfront state that.

(21:43):
Otherwise, your POC becomes, you know, POCprice becomes the anchor for your pricing.
They just multiply by 12 times.
How do you handle, like, one of these customersbeing like, no.
I don't wanna I don't wanna postpone thispricing conversations because it's important
for me to know now.
Absolutely.
So that's a that's a great question.
If you're asked for price during a POC andpushed, what would you do?

(22:06):
I would say you should talk about price, but ina, you know, more, let's say strategic manner.
So there are a couple of ways to deflect thatquestion and that's the most important thing.
Right?
So you can say, hey, look, no, the goal of thePOC is to actually, know, create that value
case and we can talk about, you know, whatportion of that we deserve.

(22:27):
Let's assume the buyer on this other side saysthat looks theoretical, I still want a price,
right?
So another way to deflect this would be, youknow, you can say, you know, customers like
yours have been able to unlock, you know, tensand millions of values, and we are typically on
a one is to 10 x in terms of, you know, yourinvestment in us and the ROI that you get out

(22:48):
of it.
So you basically just communicated that you'reprobably a million dollar deal and actually it
comes to it, but without actually saying it.
Some customers will be satisfied by thatbecause they're like, yeah, one is to 10 sounds
fair.
We will deal with it.
We'll finish the POC and we'll come to it.
If they push you even more, then don't givejust a price point because that'll be the most

(23:10):
artificial thing you can do because you're alsoguessing.
Right?
So in that case, I would give a range.
I would say, look, it can be anywhere from 500k to a million for the first year.
Where we would be will depend on how much valueunlock we can actually do for you, and that is
why we are bringing that is why we need to dothe value case.
So in all of these conversations, you'rebringing the focus back to the POC is a

(23:31):
business case exercise, and how do we co createvalue.
But I just answered that, okay, it's a range.
I gave you predictability.
Beyond that, you don't need to.
And where you are depends on the business case.
And if you unlock 10,000,000, you can be on theright side.
If you're unlocking three, you're probably onthe left side.
Right?
So I think that's also how you can navigatethis, more.
The best negotiators or the best, you know,founders who are selling hardly reveal their,

(23:57):
you know, price because if you don't understandvalue, what is price?
Is there any are there any tactics tocommunicate value?
Because I think it's like you might be able toMhmm.
It may be that I don't know.
There is the VP of sales which is Mhmm.
Using the product Mhmm.
But they the CFO may deeply understand Mhmm.

(24:18):
The kind of value story.
And so just in incorporating into the product,the demonstration, the value, have you seen any
companies that do a really good job ofdemonstrating to constituents the value that
they create?
Yes.
I think, absolutely.
And the lesson learned in those situations isbeing, you know, very structured and systematic

(24:39):
in terms of how you communicate value.
Right?
Random statements of I'm actually saving you,you know, this or that, just it's kinda lost.
It has to be systematic.
So you're almost training your buyer to repeatthe message that you're giving them internally,
and they become internal champions.
So the best ones actually say, hey.
Look.
There are three categories of, you know, valuethat we actually provide.

(25:03):
The first one is incremental on your top linebased on your business KPIs.
So that could be we generate more revenue foryou.
We reduce churn.
So these are all incremental.
Right?
So that how are we participating in that?
If you are, communicate that.
That's separate from every other value element.
So we actually improve your top line.
The second one is we actually save costs.

(25:26):
That could be other license cost savings.
It could be headcount reduction.
It could be, you know, some tangible costsavings that just happened because of AI.
Right?
So these are the cost savings, which a CFOwould actually like.
Right?
And the third one is opportunity cost, whichusually a CEO would like.
Right?
Because you said, I'm also freeing up, youknow, ten to twenty hours for the team on a

(25:49):
weekly basis.
That can also be quantified.
What would they do with that time?
You know, what does that actually work for theorganization?
So when you put it into these three buckets,the incremental, you know, top line, which is
really important, everyone cares about it, thecost savings, typically the CFO function and
others care about it, the opportunity cost,definitely the management team actually cares

(26:09):
about it, then you can start putting your valuestory across these categories and then train
the buyer to actually go paraphrase thatwherever they are in the organization.
And when you say trained, you mean you meanprompts within the product?
I mean, not prompts in terms of AI prompts, butjust kind of visual prompts in terms Yeah. Of
just
Of just just reinforcing the value that's beingcreated at every interaction.

(26:30):
Correct.
And I would even, you know, in a negotiationwhen I'm I tell founders this, you know, pause
and ask them the questions.
Hey, this is what I said, how we will addvalue.
What do you think?
What did you get out of it?
Like, you had to repeat that back to me, whatwould you say?
I mean, this is a very like, I just wanna knowyou understood what we are saying.
Right?
I mean, like like, how do you think about it?
Yeah.
So They say the best products are those thatget people promoted internally.

(26:54):
Right?
Absolutely.
Like,
get the champions of yeah.
Promoted internally.
Exactly.
And and this is a I mean, if you ask it in themost, innocent possible way, it's a great test.
The we talked about, you know, beautifullysimple pricing.
Right?
One of the tests for whether you have abeautifully simple pricing is Monday morning,
go back and ask one of your customers to playback your pricing strategy to you.

(27:17):
If they cannot, you don't have a beautifullysimple pricing.
It's just complex as hell and you probablysomehow sold it, and they don't understand it.
If they didn't understand how they werecharged, they don't understand how the value is
created.
That's a churn situation waiting to happen atsome point.
But if they can articulate and say, hey, yourpricing makes sense because we get this, The

(27:38):
price value realization is aligned.
So we've seen we've seen the the evolution ofSaaS when and in this AI world move from this
per seat licensing to a lot of exciting stuffin on outcome based pricing.
Because how do and you've you've got this twoby two matrix.

(27:59):
Maybe break that down for us and and kind ofwhat types of companies are kind of able to
capture most of the value.
For sure.
And I think it it the two by two, it goes backto the, you know, same two dimensions I talked
about in the beginning, autonomy andattribution.
Right?
That's really what's changed with AI.
So if you think about a, you know, two by twowith autonomy on the y axis and attribution on

(28:22):
the x axis Yeah.
And low high, low high.
If you take the, you know, bottom left quadrantwhere autonomy is low and attribution is low.
When we say autonomy is low, that means youstill need a human in the loop.
You're operating as a copilot.
Attribution is low in the sense that, you know,your product probably is good, but you cannot
it's not directly tying into any kind ofbusiness metrics that your customers are

(28:45):
tracking.
Right?
So if you are in the if you're in thatquadrant, you're kind of relegated to a
perceived model.
Right?
I mean, even if you take a company like Slack,for instance.
You you can say, you know, I use Slack and myproductivity went up, but you can't measure it,
you can't meter it, you can't monitor it, youcan't charge based on it.
Yeah.
Right?
So the attribution is low and, it's autonomousautonomy is also low at Scopilot, so that's

(29:10):
necessary in a seed based licensing model.
But if you take the bottom right quadrant whereattribution becomes higher, and autonomy is
still low, you're still in Copilot, but you'readding a lot of value.
This is also where, you know, some of thecoding platforms have started moving, like
Cursor, for instance, is here or Clay is herefor instance, right?
Where it's a hybrid model makes sense.

(29:31):
So it's still a seat, but then you also overlaya usage component.
So like certain packages might come withcertain number of AI credits And if you use it,
after that, you know, you can buy AI credits ontop.
So there is a blend between a seat and a usagemodel.
That makes sense because it's still Copilot,but the more people actually use it, the more

(29:52):
value they're getting, so I wanna monetize onthat.
Right?
If you're on the top left quadrant, autonomy ishigh, but attribution is low.
What that means is there's no human in the loopneeded for these AI products.
They kind of live in the background and do dotheir stuff, but they're not directly
influencing the KPI of your businesses.
So they are more background infrastructuretools, platforms.

(30:15):
So they have to be purely on a usage basedbasis because that's your best proxy for value.
There's no seats involved, so there's no point,and they it'll be bad.
But a usage is the best proxy for value.
Like, in a company like even the classic Twiliowould be probably in that kind of quadrant.
Right?
If you take the top right quadrant, that iswhere autonomy is high and attribution is high.

(30:37):
That's the kind of exciting quadrant if you canbe on.
What that means is your AI is, you know, fullyautonomous and can also do stuff that is highly
attributable.
Then you can be on an outcome based model.
That's, you know, the holy grail of, AImonetization.
It's not for everyone because many products,you can't show attribution.

(31:00):
You I mean, even if you show it, do do peoplebelieve it?
Is the loop closed?
Is it fully autonomous?
So I think there's still work to be done.
We are seeing about, you know, less than 5%probably around 5% of companies that are right
now in AI on outcome based.
We do predict that this will go to, like, 25 to30% in the next three years, and I think that's

(31:22):
kind of where people are moving, and we cantalk about that.
But a good example of a company here would be,like, if you take Intercom, they develop FinAI.
So the way it actually works is if the AI agentis able to, like, you know, autonomously
resolve a customer support ticket without anyhuman intervention, then they charge for it.

(31:42):
If a human intervention is required, then theydon't charge for it.
And there is self attribution loops built inhere because the customer might say, I'm
satisfied with this ticket.
They're actually closed with an AI agent.
No human in the loop.
It's clear outcome, right?
So they charge for that.
Or there are companies that actually havedemonstrable savings, like for instance, a
company that, you know, recoups chargebacks.

(32:04):
They do a 25% of the recoup money.
So that actually is directly, you know, becausethey measure it, they they understand it, they
take a portion of it.
Right?
So if you're, and it's auto autonomous.
So if you're highly autonomous, highlyattribute attribute attributable in the on the
top right quadrant, you can be an outcomebased.
So I think this is the key thing.
The the the thing is to really understand, youknow, what is the right, you know, pricing

(32:30):
model or archetype for you based on yourproduct in terms of, like, how autonomous an
attribute it is.
Where I see founders making a mistake ischasing, you know, shiny objects.
Like, they just heard from some, you know,networking event that they went to that outcome
based is cool.
Like, I need to be an outcome based.
And actually talking about outcome basedpricing, when the attribution of the product is

(32:54):
incredibly unclear, that's setting yourself upfor failure.
So, like, understanding where you are in thisquadrant is super important.
Then you can build pathways to also move aroundif you need to.
But if you stop wasting time in trying to,like, just copycat and, like, see really what
is the right situation for you.
It's it's also the the outcome based pricingalso creates an alignment internally between

(33:18):
the product efficacy and and tools and alsocustomer expectations.
And so that alignment is just terrific becauseit rather than start focusing on like, okay,
how do we sell more seats?
It's like, does the product actually deliver?
But as you say, I think it's more morechallenging.
Yeah.
But that's a great point because for instance,if you take these, you know, customer support

(33:42):
ticket resolution, like, right, I mean, if Iwhen I started, for instance, only 20% of them
got done by AI without any human intervention,then everyone in the company is now
incentivized on how the hell do I make that,you know, 60 or 80% because that's when the
product is actually delivering on its value.
So you're completely tied in destiny in termsof, like, your vision, everything else with the

(34:03):
customer, and you're partaking on that.
That is where it becomes a very beautiful modelwhere you switch to, like, you know, charging
for, like, work delivered as opposed to accessto software.
You talk about wallet share and market share.
And I you can see that outcome based pricingcan be critical because it or or capture a huge
amount of value.

(34:24):
But at the same time, the the concern is thatunless there's a real commitment, which is
like, you're paying whatever, a particular flatfee, people are less invested in the product.
They'll just use it episodically or as anoption against many other channels.

(34:46):
Do you see that in practice as a realchallenge?
Or do you see strategies for companies to kindof mitigate this sort of one of many outcome
based companies?
No, that's an excellent point because there'salso some characteristics around when does
outcome based model make sense of a company ina market, and also, you know, when do the other

(35:10):
ones make sense?
So we actually talk a lot about this in scalinginnovation, but you talked about episodic, for
instance.
If my, you know, value delivered is episodic,you don't want to be on an outcome based model
because that almost looks like, you know,holding someone hostage, like, when when the
value was delivered, you're actually comingthe, you know, bill collector is actually

(35:32):
showing up.
Think about this in the, you know, previousvintage of LifeLock.
It's it's operating in my background, checkingmy credit, you know, like identity theft,
everything else.
And then you say, okay, I found identity theftbreach, I'm gonna charge you.
It's like episodic.
Like, it just happens once in a while.

(35:52):
Right?
That actually that but at that time, it'sinsane value.
You don't wanna monetize on that because thatactually looks like a really wrong thing to do.
But you're actually paying for the, you know,peace of mind, and it's like an insurance.
So in those kind of cases, you wanna actuallyhave a, you know, either a fixed fee or a
recurring revenue basis.
So, like, whenever it happens, it happens.
But, of course, you need to choose your levelof pricing commensurate with value.

(36:16):
But if it's like a more, let's say, you know,more frequent, you know, deliverables, outcome
kinda makes sense like a ticket resolution.
There is a ticket.
It's resolved.
You get monetized on it, and then it adds up.
Right?
So I think there are some real characteristicson when each of these apply.
If you're in an episodic one, probably not.

(36:36):
Do you do you see any consumer based pricingmodel consumer applications which have outcome
based pricing.
You can imagine a fitness app, which is like,okay, if
you If you get feed, yeah.
Yeah.
If you lose 10 pounds or kind of like do yousee anything happening there?
The customer is perhaps not sophisticated ortoo much noise going on?

(36:57):
No.
I mean, we've actually seen these, kind ofmodels.
Like, I that's more of a gamification for me.
I don't know if it's an outcome based.
You could claim it's, like, driving outcomes.
Like, if you lose weight, then we like, youstart with a $100 a month for instance, just
making it up, and then if you lose weight, thenwe give you like, you know, $20 back, or like
if you study well in a course and you actuallyget a good grade, we've seen some of these

(37:20):
things, we get some credit back because thenyou can actually have tie ins where people
submit their scores and everything else and youknow that the product actually improved their
performance.
It actually works well.
It's like it's more of a gamification.
I think an outcome based model in in theconsumer side probably has not taken off as
much as in the, you know, b two b side.
Yeah.

(37:40):
Probably, more to come.
One of the key characteristics for outcomebased pricing apart from autonomy is being able
to prove I mean, there needs to be a key metricthat you impact.
And and the company needs to have some senseof, like, what's their current cost without AI
or without your product.
What what percentage of do they like, do theseAI companies are charging?

(38:06):
Like, how much are they capturing?
Because, obviously, if you you charge the sameas their current cost, they're gonna say no.
But I wonder what's the discount Yeah.
That is common.
For for sure.
I mean, like like you said, first of all, issuper key.
And the fact that you can attribute it and it'salso closed loop in the sense that at the end
of the day, your customer independently cansay, I got this incremental revenue or cost

(38:29):
savings or opportunity cost because of thecompany.
And then, you know, the question then really iswhat is a if you can show that attribution and
you unlock value, what can you charge?
Right?
In the in the historical like, I mean, theprevious vintage, we used to say if you're one
s to 10 x, it's good pricing in SaaS.
In AI companies, we're actually seeing that youcould even capture 25 to 50% of that

(38:54):
attributable revenue because it's trueincremental and autonomous.
Right?
So 25 to 50% is the benchmark that we have forthat we are seeing actually some companies
actually do it.
And do you think this is gonna sustain, or arethere any because another thing that that that
makes me think, like, this outcome basedpricing is that it's so simple and clear that

(39:14):
it's also very easy to potentially switchproviders.
Mhmm.
Right?
Like, if someone comes and it's able to resolvethat ticket as, you know, the the current
vendor and it's not charging 50% or 25%, but iswilling to go to 10.
Mhmm.
Like, the switching costs, yeah, makes me think
switching cost is probably can be builtinternally with the product and and as opposed

(39:40):
to, like, having your pricing model be theswitching cost.
In fact, I would argue that if your pricing iscomplex, that is when people actually wanna
leave you to, someone else.
If your pricing is simple and they understandwhy they're paying and is based on outcome,
it's actually hard to, like, for someone toleave because you're putting skin in the game
unless someone's gonna charge you lower foroutcome.

(40:00):
But then that's a different question becausethen your product needs to have some switching
costs in the sense that, you know, it's verywell integrated with things.
It's hard to rip and replace.
It'll take some another AI agent to, like, dothe training all over again, and you put some
guardrails, and you build some new, you know,let's say, enterprise RL models that actually
can solve things, then, of course, it's noteasy to rip and replace because then there are

(40:24):
models that you're building.
There's training data.
People get used to it.
They understand the user interface.
They understand how the agents work.
Then it's not that easy.
The I I've seen actually, if pricing iscomplex, that's when people invite other people
in the room.
Right?
Because then it's like, okay, I want, you know,simplify my pricing.
But if it's outcome based, is a moat, is whatI'm trying to say.

(40:47):
Yeah.
Everything's aligned, you certainly have alsojust this it's easy to communicate and easy to
track and measure.
And how do you see folks do you see folksmoving around the map or revisiting pricing?
Because it's there's you know, in this, youknow, you you we see a number of AI sellers
which are entering the market with an outcomebased pricing, and then building these compound

(41:11):
startups where they're like we're tacking on abunch of other value after this very attractive
initial wedge.
How do you see how should founders think aboutthat evolution and revisiting pricing?
Yeah.
I think, like I said, it is when we when youstart based on your, you know, product level of
autonomy and attribution, you need to pick theright quadrant.

(41:33):
But you also need to build pathways to, like,move around the quadrants if that is something
that you can actually aspire to do.
And and this has actually happened in manyindustries already.
Maybe we can take an example to unpack that.
If you take, I mean, we talked about coding,you know, agents and coding assistants.
So if you think about the classic, you know,GitHub Copilot for instance, they started in

(41:58):
the bottom left quadrant, you know.
Attribution was low, autonomy was low, so theywere a per seat model.
Back in the day, GitHub was per seat per user,right?
Mean, we all know that.
When you take the cursors of this world, theyactually move to the bottom right, which is,
you know, attribution's higher, you're saving alot of, you know, time for the developer,

(42:19):
you're creating code that can be almost reusedas code attribution, but it's still on auto,
you know, copilot mode.
So they are in a hybrid of seats and usagemodel.
But you already hear, you know, companiestalking about, I'm building an entire
autonomous, you know, coding platform, like I'mgonna hire you a QA person who can actually do

(42:42):
QA and you don't need Jim or Jen doing QA, youcan have my AI do it.
And I can actually show you how many bugs willfix everything else.
Autonomy and attribution is increasing in thatspace that you could actually say, okay, then I
might wanna actually charge based on outcome.
How many bugs did you resolve, and is thathow's that compared to like a human, and should
I charge for that agent differently?

(43:03):
Then you get into more interestingconversations.
But the key is to understand that where you areand what do you need to do.
Like, how can you build more things in yourproduct that will demonstrate more attribution
over a period of time?
And how can you build stuff in such a way thatyour product can get more autonomous over a
period of time.
And for attribution, the some simple hacks arethings like, okay, you actually wanna have some

(43:29):
kind of, you know, dashboard where I log in asa buyer and I can actually see some charts
saying how is this AI actually increased my topline, my cost savings, my opportunity cost, you
know, sort of make that the front page.
I mean, this hey.
We we have actually saved things.
There's a report that's commonly available.
We are training people that attribution exists,and how do you build pathways towards that

(43:52):
before unlocking outcome based pricing,etcetera.
So I think you can move around, but you need toplan for it.
The the the pace of AI is getting so muchbetter so quickly.
And, you know, we're we're you know,superintelligence is, you know, a tough
definition.
But as you kind of roll this forward a coupleof years, do you see outcome based pricing

(44:18):
being you you mentioned 25%, but do you see itperhaps kind of more prevalent than that over
time as as sort of artificial superintelligencebecomes kind of more pervasive?
Because I think it we have to be building forthis world because it's getting better at such
an exponential rate.
Yeah.
I think that in the next three years also basedon, like, studies that we have seen, we have

(44:43):
done ourselves, stocks, etcetera, where thebuyers are actually getting more comfortable,
right, if you look at CIOs and organizations,even the ones who used to say, I want
predictable budgets, they're like, you knowwhat?
I'm actually willing to, like, see if outcomewould work because our incentives are aligned.
Right?
So that's also how we get to that 25 to 30% inthe next three years.
If I take a more fall forward look of, let'ssay, you know, five, ten years, you know,

(45:08):
superintelligence, AGI, we can debate what ourworlds will look like.
But I actually think intuitively outcome basedpricing model should make a lot of sense there.
Right?
Because, I could even envision a world whereAIs talk to AIs and they reconcile how much to
pay each other, and they basically you know,it's based on the outcome, and there's actually
no bias like humans.

(45:30):
Right?
I mean, it can actually do that, and it has tobe an outcome.
If you if you take a world with less bias,outcome is the right model.
Yeah.
Yeah.
There's no debates.
Yeah.
There's no you know, let's say, I it's it'slike, what is the value you're doing to me?
And what is my willingness to pay?
And Right.
And it's a pure, like, individual economicdecision, which lends itself to, you know, some

(45:54):
sort of quasi auction type situation in a in aa real time basis.
Yeah.
Exactly.
My AI agent hired a, you know, recruiter agentbecause those models are actually better.
I'm a general purpose AI, and I hire them, andthey do the work, and I pay them based on the
outcome.
Yeah.
And and it all happens in the background.
Yeah.
Right?

(46:14):
You know?
Yeah.
It's a it's a yeah.
It's a bit interesting to see how the worldwill evolve, but, it's anyone's guess.
Yeah.
But then it's in that environment, I think thefounders need to think about what is the true
defensibility beyond the the sort of the AIproduct that they're building, and which is a
lot of data, network effects, workflow,etcetera.

(46:40):
So so if you're if you're a start up competingagainst an incumbent, and you talk you know,
when we spent time together a dozen years ago,there's a lot of thinking about bundling and
kind of and and pricing and different kind ofcomponents.
You can see an environment where you have a asort of a an incumbent which arguably has a

(47:04):
sort of bloated product set, adding an AIcomponent, and they're looking to kind of,
okay, this sort of like machine of like, okay,we need to kind of ratchet up the kind of ACV.
And then you have a startup which is saying,okay, I'm going to monetize an outcome based on
my high value AI product and then giveeverything else away for free.

(47:29):
What are some of the merits of that approachand any tactics for have you seen that working?
Have you seen and have you seen tactics forfounders to execute
I on mean, like, look, when when you have aincumbent in in town that are and you wanna
compete as a startup, there are probably, youknow, few ways that you can actually do it.

(47:51):
You can say I would try to be a low costprovider compared to the incumbent, and that's
the reason to switch.
But guess what?
The incumbent probably has a lot more capitaland they can drop the price faster than you can
drop, right, in some ways.
So that's a losing proposition.
It's always the other person who started theprice war.
Right?
I mean, so it's that's one way you could thinkabout it.
But the more smarter way actually to thinkabout it is to say, are there some strategic

(48:14):
things that I can do in terms of, like, how Icharge my pricing model?
Can I actually make it different?
Are there some core pain points with thecurrent incumbents that I'm actually solving
and I how can I leverage that?
Right?
Even back in the day, when you think aboutNetflix, right, and Blockbuster used to have
all these movies and, you know, you have pricebased on movies, late fees, everything else,
but a subscription price on Netflix to keepyour DVD however long you wanted was a

(48:38):
different pricing model.
It actually worked.
I mean, and the rest is history.
So this has been done in various vintages,like, where a pricing model conversation itself
is the reason for disrupting an existingincumbent.
So if a incumbent because think about it.
A a a really big incumbent with multiproduct,many different teams, you know, just building

(49:00):
AI into their existing arc you know, techarchitecture, which does not have AI, what are
the chances they will move into an outcomebased world?
Zero.
They're gonna have 20 debates, consensus, andthey will shut it down as they know.
Let's just preserve our margins for our currentbusiness, and they won't do it.
But if you're in if you're if you're coming newto the market, you have nothing to lose.
If you say, look, I win when you win, and mymodel is outcome based, great.

(49:23):
Maybe that's how you start stealing accounts.
Yeah.
Right?
So I think thinking about those things would bekey, and I've seen it work all not just now.
We're we're not just seeing it now.
We've actually seen it historically.
Mhmm.
And we're seeing this this trend, right, like,with AI at the end delivering work.
Right?
It's reducing the the need for so many peoplein a company, and and, like, a seat based

(49:45):
pricing thrives when a company adds moreheadcount.
Yeah, it's
like catching a falling knife if you're on seatbased pricing.
Exactly, yeah.
It's kind of like the classic innovator'sdilemma.
Yeah.
So in the book, you talk about these founderarchetypes and perhaps failure modes and kind
of things that folks don't do so well.

(50:06):
Can you talk through a little bit of those thefailure modes and archetypes?
Sure.
I think it ties back to the same market shareand wallet share.
Right?
I mean, so I love two by two, so I gotta useone more.
Oh, we love two by two.
Fact that they're like frameworks.
Yeah.
Exactly.
So so when you think about, you know, marketshare on the y axis and wallet share on the x

(50:30):
axis.
Right?
And let's take the top left quadrant first.
High focus on market share, as in a leadershiparchetype or a person who has high focus on
market share but low focus on wallet share.
You know, we In the book, we call them thedisruptors, right?
These are people who say, I'll grow at allcosts and I'll figure it out in terms of

(50:52):
monetization, right?
If you take the bottom right you know, quadrantwhere wallet share is the big focus, but market
share is not that big focus for the CEO or theleadership, we call them the moneymakers.
These people actually think about from day onehow to build a great commercial business, but,

(51:12):
you know, not focusing more on the marketshare.
And then you have this bottom left where you'reneither focusing on market share nor wallet
share.
We call them the community builders.
Right?
They're focusing on a core set of customers andthey wanna do right by them and just keep
working with them.
And then the you know, if you take each ofthese archetypes, I'm sure all of us have seen
many of these.
Right?
Let's take the disruptor one, focusing more onmarket share, but not paying attention to

(51:38):
wallet share.
Not equal efforts, equal attention.
You're not even paying equal attention towallet share.
And you're basically selling a dollar and 80¢.
Literally, that's what's happening.
So you fall into two traps.
You know, you're probably landing withoutexpanding in the sense that you gave the farm
away in your entry product, and then you'rechasing your tails to, like, build something
and hoping to monetize.

(51:59):
That often does not, you know, sort of,translate, and that happens with disruptors all
day long.
And the other one is making the mistake ofthinking that market share one is market share
earned.
What that means is you're so focused onacquisition that you keep thinking about
getting new customers.
You're not focusing on keeping those customers,retailing them, adding more products, value to

(52:23):
them, and retention is not the focus.
Acquisition is the focus.
So you won market share, but it's not durable.
Right?
That happens with the disruptors.
If you take the moneymakers, you know, focus ismore on making, you know, money and or thinking
about that before the, market share, they fallinto a couple of, traps.
One is the price premium trap, which is, hey.

(52:45):
You know, I'm I wanna charge a premium becauseI learned that premium price means that it's
value, and, you know, I'm the Nextiva.
And, you know, a $200 wine is, value andwhatever.
I mean, they've learned stuff that but the parI mean, while there are obvious connotations
that have, you know, prices signal a value, theprice premium paradox is when you charge it so

(53:08):
high that you become irrelevant to, like, youraudience.
Right?
So that actually happens all the time.
Like, when you start charging for a, you know,a juice Aero machine at, like, whatever, $700
when you can probably squeeze the packets andyou have the same result, you're on a price
premium paradox.
Right?
I mean, so that's different.
Or you also fall into a, you know, nickel anddiming kind of trap, which is you're so focused

(53:34):
on the wallet share that you have these yourpricing is incredibly complex, money, maybe
even different, you know, elements of the feestructure, things like that, because you're
only thinking about that, not the market share.
If you're the community builder, this is aninteresting one because there's also some
literature around, let's just focus on a fewcustomers, build a product, and scale it.
CEOs who have actually done that have stillbeen very thoughtful about wallet share and

(53:58):
market share and paid attention even thoughthey started community builders.
But the community builders who don't payattention to these, they fall into traps like,
you know, giving away too much, for too lessbecause they're so you know, wanna please their
customers in that community.
They keep giving.
They keep giving.
And they train their best customers to expectinsane value for less, and they can never undo

(54:21):
it because once those customers becomereference customers, they'll be like, yeah, I
got that for, like, $10.
Are you kidding me?
Like, it just doesn't make sense because p doyou just train someone to, like, get insane
value low price?
They're not even gonna be good referencecustomers because they're they're gonna say
what price they actually got it at, and that'sgonna be the reference point for everything
that you actually do.
That's a trap that you fall in.

(54:43):
Or the other one is, you know, you fall intothis trap of, you know, you're solving for, you
know, current, let's say, base, but you'remissing the frontier, which means you're so
focused on the current customers that you'renot even thinking other adjacent markets or
others who look different to my loyal base thatI should be building towards, so you miss

(55:04):
adjacent markets, you know, opportunities toacquire new types of customer segments.
So the best quadrant to be in is the top right,which is the profitable growth architect is
what I call it, where, you know, you'refocusing both on market share and wallet share.
Like I said, not equal efforts at all point,but equal attention.
So profitable growth architect is actually adisruptor, a community builder, and a

(55:27):
moneymaker all at the same time.
How do you do that?
And that's really the thesis of book as in, youknow, we talk about nine strategies to build
towards profitable growth and, you know,demonstrate that you could become a profitable
growth architect if you follow thosestrategies.
Four of them for the, you know, zero to onestartup phase and five of them for one to five

(55:47):
when you're scaling up kind of thing.
That's the whole thesis of the book.
We actually have this thing called Axioms.
I wanna unpack that too if you guys are openfor Yeah.
That was gonna be our next question.
Okay.
I mean, so the the the Axiom related to thestart is the what I call the 2080 Axiom.
This is my favorite one.
I've, you know, seen this over and over againwith tech companies.

(56:08):
I don't know if you'll agree with it, but let'slet's let's see how you'll agree with it.
Right?
20% of what you build in tech drives 80% of thewillingness to pay.
This I've seen it over and over again.
Right?
I mean, any product that you say, okay, 20 ifyou ask people recall on, like, why do you buy
this product?
What are you paying?
It's always, like, 20% of, like, what someonehas built.

(56:29):
20% of what you build drives 80% of willingnessto pay.
The biggest irony in tech is that this 20% isthe easiest thing to build.
So what happens?
If you're in that disruptor mindset, you willbuild that 20%.
You'll say, okay, you know, that end is thefastest thing to build.
You'll say, okay, let's build it, put it out inthe market, let's call it MVP, give it away for

(56:51):
free.
So basically, what have you done?
You've basically given away the form, and nowyou're gonna build 80% of ridiculously hard
stuff that's only driving 20% of willingness topay.
Right?
So you're basically disrupted, but you have nopathway to, like, get to profitable growth or
monetization.
You just gave away, and you're hoping thatsomething would happen.

(57:14):
The right person would say, okay, this is the20%, you know, that's driving willingness to
pay.
How do I probably get it in such a way thatmaybe there's some usage things?
I wanna give it away for free, but after acertain point, you have to monetize on that.
So can I actually compensate on a land andexpand?
And you'll have that equal attention kick in.
And then you'll actually put it in such a waythat you will, you know, cross both market

(57:35):
share and wallet share.
But if you didn't, you'll just go on leaning onone side.
Right?
I mean, so that we call it the, the twentyeighty axiom, which is is is so true.
Every time people will give it away and andthen they're just chasing their tails.
Yeah.
And it's surprising how founders, like, havesuch a hard time sometimes, like Yeah.
Being afraid to charge a lot for their I

(57:56):
I mean, in this case, they don't even charge.
They just give it Go charge a we should stopcalling things minimum viable product.
We should call it most valuable product.
This whole MVP definition needs to change, Ithink.
It's, it's, I also heard another definition,most lovable product.
That's a good one, actually.
I think that's a better definition.
But this MVP, which is that 20% that you canbuild, is the core of the willingness to pay if

(58:19):
you gave that free.
Tough luck.
Mhmm.
What are other axi axioms that are yourfavorite?
Yeah.
I think there is, the axiom that I talk about,you know, on the price increase, axiom.
So usually I mean, the price increase Axiom isthat to to do a price increase often, you know,
the, reluctance to do it is internal andemotional.

(58:44):
It's not external and logical.
And we unpack that axiom in the sense that andI think Warren Buffett said this well.
He said if if you need to have, you know, fordoing a 10% price increase in a company, if you
need to have a prayer session, you have aterrible business.
Right?
I mean, so how do you do a price increase ifit's a 10%?
And we talk about that, like, you know, how toactually achieve that.

(59:06):
But the, axiom there is that every single timewe have found a price increase being more
internal and emotional as opposed to externaland logical.
There's always a way to do it because, youknow, the price of, like, everything that you
consume goes up year over year.
Your software or AI cannot be on the same pricefor the last five years.
There's something off.

(59:27):
I mean, it's internal and emotional.
It's not external logical.
So that's one that I
That's why we that's why we love networkeffects.
Right?
Because it's like if you as you as you scalethe business without necessarily providing more
features from a software perspective, the valueof the product increases over time.
And so if you and, you know, you and thenactually sort of pricing and increasing pricing

(59:51):
over time is sort of like a natural part of theservice you provide or increasing value within
the product you're providing.
Oh, totally.
And every person who brings in another personmakes it valuable for the whole network, right?
I love network businesses too.
Another accent that I like is it says somethinglike attract customers who won't leave.
Oh, that's a good one, yeah.

(01:00:11):
And the importance of choosing your customers.
I mean, always, but also especially early on.
Yeah.
That goes to the, I mean, promotion examplethat I was giving.
Right?
I mean, if you acquired customers with threepromotions who are gonna leave, that's not
robust revenue.
Right?
I mean, that's just revenue.
It's not durable.
The best way to stop churn is to acquirecustomers who won't leave.

(01:00:35):
That is the axiom.
Right?
Because most people try to stop churn at thetime that someone says, I'm going.
It's too late.
You can prolong it by a few more months, butthat person is gonna leave.
Right?
And it's reactive.
The proactive way of understanding churn issay, look at my customer base and say, who are
the types of customers who tend to stay longer?

(01:00:57):
Who are the ones who actually tend to, youknow, engage with me more?
The usage, buying more products over a periodof time.
Who are they?
What are they you know, how can I find more ofthem?
Can I transfer all my acquisition dollars tofind more of them?
Yeah.
Then you're stopping churn because you acquiredthe right set of customers.
Yeah.
It's interesting how sometimes, like, aretention problem is really an acquisition
problem.
Yeah.

(01:01:17):
Know?
That's it is it is totally right.
Nice way to phrase it.
And last question on this one.
How would you relate this to, like, the what wewere discussing before about POCs?
Like, it's very critical.
Right?
For sure.
All of these tie back because if you choosecustomers I mean, first of all, you know, you
need to separate the, you know, tire kickersfrom the people who really want to use your

(01:01:42):
product.
For that, you need to charge for a POC.
That itself is a lead qualification mechanism.
Like, many founders ask, should I charge for aPOC?
I'm like, hell, yes.
Because otherwise, you're gonna get somecurious buyer who will take you down a three to
six months pathway.
Might never buy.
They're just curious to see the AI.
How do you know they have budget or they wannado something?
Right?
So charging for a POCs and sell you know, atleast identifying some customers who wanna

(01:02:05):
partake in that because they have to put someeffort for it.
And also, like, how do you, you know, frame itas a business case so that your monetization is
part of the value delivery that becomes key sothat you're not giving the farm away.
So all of these principles actually applythere.
So what we talk.
So if you're so let's just say you're an earlystage founder, you've raised your PreSeed or

(01:02:26):
Steve Steve Round led by NFX and forty ninePalms.
That's great.
Let's do it.
And you're building an AI product.
Like, what are, like, what are perhaps threepricing tips that they should do in the first
ninety days?
So the first thing that I would probably, youknow, look at is, you know, how do they charge

(01:02:50):
or how do they plan to monetize?
Because that's a more strategic and fundamentalquestion as opposed to how much.
How much can wait?
Right?
So that's a ninety day question.
Like, should I
The tactics of specifics.
Specifics around how they will charge, whetherthat's outcome, whether And
that's unpacking their entire product, seeingwhat value they actually offer to their
customers, how the customers realize value.

(01:03:13):
Do you have some value elements?
For instance, you know, can you charge based ona resolution, tickets, whatever?
Or is it like consumption on tokens?
Is it like usage based?
Is it hybrid?
What all of that stuff can be, you know, ironedout pretty fast based on the archetype and
everything else that we talk about.
So that's the first thing that I would do.
The second thing that I would do in the firstninety days is to actively start, framing POC

(01:03:38):
conversations as business case conversations sothat to your point, Anna, before that I start
selecting customers who actually wanna investtime to jointly investigate with these founders
that there is value in this AI product asopposed to some just technical diligence.
So I would probably, you know, coach them on onon that.

(01:03:59):
Right?
And, that would be the, second thing.
And the third
thing By by case, you really it's really deeplyunderstanding the the needs of the customer in
terms of their expectations, their coststructure, business model, etcetera.
Exactly.
And the third one is also, like, preparing thefounders on how how to have these conversations

(01:04:22):
with the the customer.
Right?
I mean, there are some because what I oftenfind is founders will show up with a product
and demonstrate what they can actually do froma technical standpoint.
But, like, are they actually having the rightvalue messages?
Are they actually talking to that?
So, like, you know, coaching founders on how toarticulate value, create needs, not just

(01:04:43):
discover them.
And how do you value sell and negotiate becomeskey.
So actually, like, for instance, the optionsthat we talk about.
Right?
I mean, things of that nature that you canactually start being more strategic in terms of
how you negotiate.
Yeah.
And I think that's the other training that wecan vastly do.
I'd love to have a a situation of a jointcapital with

(01:05:04):
you.
So
I'm sure.
I'm sure.
I'm sure.
great.
So anything else that we missed as as foundersthinking about pricing in this in this new
world?
One thing that probably, you know, I I keepgetting asked, and we sort of unpack that, but
if there's interest, we can unpack it, was allthese AI companies are getting to, like, you

(01:05:26):
know, revenue pretty fast.
Is that good?
Is that have they cracked the pricing code?
Is this durable?
I think that's an interesting topic.
We kinda talked about the negative margin orneutral margin based on the TechCrunch article.
I mean, so that's one aspect of that.
But there are several aspects of it, is veryinteresting, I think, which even investors need
to know.
Right?

(01:05:46):
I mean, there is there's a there's a there'salso, like, you know, where am I getting that,
let's say, revenue from?
Is it contracted revenue, or is it POC revenue?
So there's a lot of, you know, things that youactually see.
Okay.
I'm I hit a 10,000,000 ARR, and, you know, Istart unpacking it.

(01:06:06):
It's probably more POC revenue than contractrevenue.
I got contracts from, like, Tesla, Apple,Google, and other companies.
Like, okay.
It's a ninety day POC.
That's not a contract.
Right?
So I think so let's be all careful about, like,what these reported revenues mean.
That's one aspect.
And then there's also, you know, the otheraspect of, like, is this revenue durable?

(01:06:27):
That's also important question because there'sa lot of curiosity on the buyer side to
actually, you know, look at these AI products.
Is it working for me or not?
So there's a lot of curious buying, which meansare they gonna be there after three to six
months?
Question mark.
So you cannot take something and extrapolate itto twelve months when you've only been there
for, like, three months.
You don't even know how churn is actually gonnaaffect you.

(01:06:48):
Is that durable revenue or not?
Key question for us to think about.
Right?
I mean, this do they have foundational modes?
Is it is it truly delivering value that peoplewill actually have an ongoing monetization
conversation?
Yeah.
It's you see it all the time where you've gotthe boards of directors pushing down into their
kind of CEOs and and VPs saying, what's our AIstrategy?
And so they go out and sign a bunch of POCs orexperimental budgets to try sort of things that

(01:07:12):
tick the box, and then they and then they moveon.
Is there any and just from a founderperspective, is that really just looking at,
you know, does the engagement and retentionincrease over time?
Is it is it as as simple as, like, watchingcore usage and and core monetization within on
a per customer basis on on specific cohorts?

(01:07:34):
Yeah.
I would nuance that to say on a segment basis.
Like, what are the types of segments ofcustomers I'm attracting?
What is their usage intensity?
You know, are they actually who are the onesthat are using?
Are they gonna tend to stay?
So, like, doing cohort analysis, exactly,that's the that's the key.
Because if you just look at it on on average,averages will always lie.

(01:07:54):
Right?
And there's also the all these pressures on,like, what is ARR?
I think we also need to, like, in especially inAI, think about is ARR the only right metric?
No.
We there are probably other things that we alsoneed to look at for the health of the business.
And even ARR, how is it even reported?
I mean, some of the things that we saw, I don'tknow what you see, like, and we we we met a
founder who was actually we talked aboutseasonal products, for instance.

(01:08:17):
Right?
Seasonal products, seasonal product, I mean, wedidn't come up in the conversation because it
was seasonal.
We understood that it was seasonal aftertalking.
But if you look at the financials in terms ofhow the ARR is done, it's like, take the
maximum in a five month period and multiply itby 12.
I'm like, no.
That was the peak month.
What happens the other month?
You can't just do that to extrapolate your ARR.

(01:08:38):
So, like, how is the ARR even computed is is aquestion mark.
Right?
I mean, like, if you don't account for, like,Shannon, how do you do it?
So I think being thoughtful about this as acommunity of, like, founders, investors, and
others, like, what KPIs are we looking at?
Usage, retention, you know, ARR?
I think
And the the seasonal one is an interesting onebecause you could look at let's just take

(01:09:00):
auditing or taxes.
Like, actually, you know, to manyorganizations, like, I don't wanna, like, staff
up for a three month period and then staff downagain.
I like if there's an AI that can do that forme, then it's terrific.
And so actually so your kind of your your kindof fixed labor becomes variable.
And so and so you might look at seasonality asnegative, but I think we see a lot of companies

(01:09:25):
doing very well because they're just purelyseasonal because they don't need to go through
the headache of hiring and firing.
Yeah.
This one was like usage exists in other months,but in certain months, the usage peaks.
Yeah.
Let me leave it at that, which is a bitdifferent case than what you're saying.
But, yeah, it could be negative or or positive.
And then thinking through the the ICPs, we wesee there a number of small companies intrigued

(01:09:51):
by AI, but they don't necessarily have theeconomic sophistication to think through, okay,
if I substitute this action with this piece ofsoftware, then I'm able to see an ROI, where
you see a lot of the kind of mid marketcompanies that are perhaps more aggressive or

(01:10:12):
professionally run that actually see a lot ofadoption for these types of products.
At the same time, like, it it's been I mean, itused to be that when in b to b in particular,
like, you started selling to mid market moreand, like, enterprise would come later.
And now we're seeing all these founders beingable to close deals very fast with with
enterprise.

(01:10:33):
But but to your point, I completely agree thatit's a little given, like, how much curiosity
it is.
And it's also kind of our jobs to, you know,learn
Mhmm.
To assess also, like, the quality of thatrevenue and also Well, it changes.
Well Yeah.
In this process.
That's the that's the right
And because sometimes, you know, we don't havetime to wait for a renewal.

(01:10:54):
Right?
Like, to Mhmm.
Yeah.
For sure.
For sure.
But I think that's also where I mean,especially in the businesses that you're
probably investing in, that network effectsitself become a moat, and is that strong
enough?
Is something I'm sure is part of your, youknow, thesis, and is it durable, and is it
quality revenue?
I think those are the diligence that needs tobe done as investors, but also as founders

(01:11:16):
being thoughtful about is my own revenue, youknow, durable or am I just reporting something
that do you actually believe it?
Ask yourself that question in the mirror.
If you can sleep well, okay.
If you can't, what do you need to be answeringto actually see if it's durable or not and then
work towards it.

(01:11:36):
Thanks so much for joining.
Great conversation, great insights.
I'm excited to do some co investing together.
That would be awesome.