The full conversation.
Arvind
0:00
My
number
one
advice
to
founders
is
conviction
and
persistence.
If
you
see
a
problem
that's
out
there,
then
don't
think
too
much
about
who
else
is
solving
it
or
how
big
the
market
is.
Just
go
and
solve
the
problem
and
persist
and
believe
in
it.
There's
going
to
be
ups
and
downs.
There's
going
to
be
enough
people
telling
you
that,
hey,
look,
I
see
this
problem,
but
I
don't
see
myself
paying
for
it.
Don't
worry
about
all
of
that
part.
If
you
think
that
it's
a
large
enough
problem,
a
lot
of
people
face
it,
having
that
conviction
and
belief
and
staying
on
course
is,
I
think,
the
most
important
thing.
Pablo
0:35
Welcome
to
the
Product
Market
Fit
Show,
brought
to
you
by
Mistral,
a
seed-stage
firm
based
in
Canada.
I'm
Pablo.
I'm
a
founder
turned
VC.
My
goal
is
to
help
early-stage
founders
like
you
find
product
market
fit.
Arvind,
welcome
to
the
show.
Arvind
0:53
Thank
you
so
much
for
having
me.
Pablo
0:54
Listen,
I've
got
your
LinkedIn
open
right
here.
I'm
looking
through
it.
Ten
years,
distinguished
engineer
at
Google.
The
claim
to
fame,
as
far
as
I
understand
it,
is
you
made
Google
Search
as
fast
as
a
blink
of
an
eye.
Then
you
go
off,
you
start
Rubrik.
That
actually
is
filing
for
IPO
now.
They're
doing
half
a
billion
dollar
on
revenue,
worth
$5
to
$10
billion,
but
that
wasn't
enough
for
you.
You
left
halfway
through
that
story,
started
Glean,
which
is
what
you're
working
on
today.
You
just
raised
$200
million
for
that
at
over
$2
billion
valuation.
My
first
question
honestly
is,
what's
the
secret,
man?
What
am
I
doing
wrong?
Arvind
1:27
No
secrets.
I
would
just
say
I've
been
so
fortunate
to
actually
be
with
people
who
want
to
build
great
products
and
achieve
some
success
with
them.
Excited
with
what
we've
done
with
Rubrik,
what
we're
doing
with
Glean.
Pablo
1:41
Then
let's
dive
in
a
little
bit.
We'll
spend
almost
the
entire
episode
on
Glean,
but
just
to
get
some
context,
walk
me
through
just
leaving
Google,
especially
at
the
state
that
you
were
at.
Obviously,
let's
call
it,
very
comfortable
position
for
a
bit
of
a
euphemism,
but
to
decide
to
go
off
on
your
own
and
start
your
startup,
what
drove
you
to
do
that?
Yeah,
just
walk
me
through
that
thinking.
Leaving Google
Arvind
2:02
I
really
enjoyed
working
at
Google.
I
always
got
to
get
a
chance
to
work
on
products
that
were
really
meaningful,
that
everybody
around
me
uses.
It
was
amazing.
I
had
no
plans
as
such
to
actually
go
and
start
a
company.
I
was
not
feeling
any
unrest.
Sometimes,
problems
come
to
you.
In
this
case,
my
co-founder
Bipul
and
I,
we
chatted
about
this
problem
that
we
ultimately
built
Rubrik
for,
and
it
was
exciting
to
me.
I
just
felt
that
it
would
be
great
to
actually
go
and
do
something
on
your
own,
not
have
this…
always
have
this
big
support
system
that
you
have
behind.
Because
sometimes
I
feel
like
at
Google,
I
was
not
feeling
challenged
anymore
because
we
are
such
a
successful
company
and
we
could
always
take
big
problems
and
work
on
them.
It
didn't
matter
if
they
failed
because
as
an
individual,
yeah,
you
move
on
and
you
start
a
new
project.
Sometimes
that
also
makes
you
dull.
Here,
it
was
actually
interesting
for
me
to
actually
see,
okay,
let
me
see
what
I
can
prove.
Pablo
3:08
No
safety
net,
burn
all
boats.
It
either
works
or
it
doesn't.
Arvind
3:12
Yeah,
and
of
course,
it
was
the
–
we
know
that,
if
you
succeed,
that
actually
is
going
to
feel
totally
special.
Pablo
3:20
You
go
through
this
journey.
Things
are
going
quite
well.
I
believe
you
raised
this
series
E
or
so.
This
is
the
2018,
2019
time
frame.
How
does
the
idea
of
Glean
come
up?
Then
how
do
you
work
through
–
you're
the
founder.
You're
one
of
the
founders.
How
do
you
work
through
exploring
that
and
ultimately
leaving?
Walk
me
through
that
period.
Coming up with Glean
Arvind
3:39
We
ran
into
this
problem
that
Glean
solves
at
Rubrik.
We
were
really,
really
lucky
at
Rubrik
to
grow
the
business
really
quickly.
In
four
years,
we
were
actually
more
than
a
thousand
people
in
the
company,
but
with
that
growth
came
challenges.
One
of
them
was
that
our
productivity
actually
dropped
quite
a
bit.
As
engineers,
they're
not
able
to
write
as
much
code.
Salespeople
are
not
able
to
sell
as
much
stuff.
Overall,
we
felt
that
you're
investing
so
much,
we
actually
tripled
the
size
of
the
engineering
team,
but
still
write
the
same
amount
of
code.
It
doesn't
matter
how
many
people
you
bring
in,
you
don't
get
more
things
done.
We
would
run
these
surveys,
poll
surveys,
and
ask
people
what's
wrong
with
the
company.
What
are
the
things
we
can
do
better
on?
Always
you
would
see
this
one
problem
that
was
top
of
mind
for
people.
This
was
one
of
the,
I
think,
default
questions
in
the
survey,
which
was
that
people
would
complain
that
I
cannot
find
any
information
in
this
company.
I
don't
know
where
to
go
and
look
for
things,
and
I
don't
know
who
to
go
and
ask
for
help.
This
was
a
big
problem.
When
it
became
clearly
the
largest
problem
there,
I
thought
about
it
and
it
resonated
with
me
because
I
felt
the
same
way.
In
fact,
everybody
in
the
company
felt
the
same
way.
There's
so
much
data,
so
much
knowledge
across
so
many
different
systems.
Nobody
knew
what
stuff
was
there.
Pablo
4:58
Would
you
say
that's
even
worse
at
a
fast-growing
startup?
Just
because
if
you
think
about
zero
to
a
thousand
employees,
that
means
most
of
them
got
hired
in
the
last
year.
They
don't
even
know
what
they
don't
know
sort
of
thing.
Was
that
exacerbated
at
Rubrik?
Arvind
5:10
Yeah,
it
was
definitely
exacerbated
because
it
was
a
fast-growing
company.
When
we
saw
this
problem,
we
wanted
to
solve
it.
We
went
and
talked
to
a
few
other
companies
just
to
see
if
they
were
running
into
this
problem,
what
are
the
solutions
for
this.
We
realized
that
this
was
such
a
common
problem.
Every
employee
and
every
company
in
the
world
struggles
with
this.
They're
struggling
more
and
more
as
we’re
going
through
this
SaaS
transformation
where
suddenly
businesses
started
to
use
hundreds
of
systems
and
applications
and
your
knowledge
got
really
fragmented.
Pablo
5:43
What
was
your
role,
by
the
way,
at
Rubrik
at
that
time?
Arvind
5:46
I
was
the
head
of
R&D
so
I
actually
was
responsible
for
all
product
development,
but
I
was
also,
I
guess,
founder.
I
would
also
look
at
issues
these
internally,
how
can
we
make
our
company
better.
Initially,
and
I'm
a
search
engineers,
when
I
see
that
people
can't
find
things,
I
say,
okay,
let's
go
and
buy
a
search
engine.
Pablo
6:04
It's
deep,
yeah.
Arvind
6:05
We
tried
to
go
and
find
one
and
I
didn't
find
anything
to
buy.
I
was
really
shocked.
I
said
this
is
such
a
commonplace
problem.
How
come
there
is
not
even
a
single
product
that
I
can
go
and
buy
for
this?
That
led
to
that
initial
thought
process
of,
hey,
maybe
I
should
go
and
solve
this.
We
thought
about
maybe
I
should
build
a
second
product
in
Rubrik,
but
it
just
felt
like
it
didn't
make
sense
for
us.
We
were
in
such
large
market
already
with
the
small
market
share
so
all
of
our
focus
there
had
to
be
on
our
existing
product.
Pablo
6:40
Was
that
a
tough
conversation
internally?
You
ultimately
going
to
your
other
co-founders
and
saying,
actually
I
think
I'm
just
going
to
go
off
on
my
own
and
start
something
new.
Arvind
6:49
It
was
tough
for
me
internally
first,
before
I
even
discussed
with
somebody.
I
had
to
figure
out
why,
how,
does
it
make
sense,
why?
We
actually
built
the
organization
to
an
extent
where
we
had
great
leaders
and
they're
doing
great
job.
In
fact,
they're
better
than
me.
I
felt
I
had
the
ability
to
do
a
really
good
smooth
transition
and
start
Glean,
but
I
was
so
excited
about
it.
It's
a
problem
that
is
something
that
I
feel
is
really
fundamental.
We
believe
that
we
make
such
a
big
impact
on
the
lives
of
people
who
use
our
product.
Pablo
7:26
Now,
weren't
there
–
just
thinking
through
this
problem,
like
you
said,
it
was
a
problem
that
everybody
faced.
In
a
sense,
it
classified
in
the
world
of
obvious
problems
that
are
just
really
hard
to
solve,
but
weren't
there
some
–
I
remember
Dropbox
I
think
had
put
something
out
in
this
space
or
was
at
least
marketing
that
they
had
a
solution.
Were
there
a
lot
of
big
names
going
after
this
problem
as
well?
Building a Product in a Neglected Space
Arvind
7:47
Historically,
this
is
not
a
new
problem,
helping
employees
find
information
at
work.
There've
been
companies.
Google
had
a
product,
too,
but
nobody
really
solved
it
in
a
way
where
somebody
liked
the
product,
where
the
problem
actually
got
solved.
Overall,
I
would
say
it
was
more
of
a
neglected
space
as
opposed
to
a
space
where
a
lot
of
companies
were
thinking
about
doing
something.
When
we
came
in,
we
built
the
product,
we
felt
that
we
were
the
only
ones
who
were
truly
focused
on
bringing
assistance
to
employees
with
a
product
like
ours.
Most
of
our
journey
has
felt
more
like
creating
the
market
for
it
as
opposed
to
competing
with
other
vendors
with
a
better
product.
Pablo
8:30
Walk
me
through
those
early
days.
You
finally
do
decide
to
leave
Rubrik.
My
understanding
is
you
raised
that,
I
think
it
was
$15
million
round,
right
out
of
the
gate.
What
was
that
process
like?
I
assume,
was
it
relatively
straightforward
just
because
of
your
background
and
what
you've
proven
so
far?
Arvind
8:46
Yeah,
the
process
of
raising
capital
was
relatively
smooth,
but
I
think
it
was
interesting.
There
were
investors
who
would
tell
me
that
they
would
back
me
because
I
have
experienced
building
a
company
before,
but
they
didn't
want
to
back
the
idea
that
I
was
working
on.
There
was
some
struggle
because
I
think
this
was
a
difficult
problem.
There
were
no
successes
in
enterprise
search
which
is
how
people
clubbed
us
as
into
that
category,
and
so
rightfully
so,
there
was
some
hesitation
from
investors,
but
you
always
find,
ultimately,
there
are
great
investors
who
have
the
capacity
to
actually
take
on
big
challenges.
They're
not
afraid
of
all
the
risks.
Pablo
9:31
What's
the
first
step?
You
already
validated
the
idea,
so
do
you
just
go
right
into
building
the
product?
What
do
you
focus
on
in
those
early
days?
Arvind
9:40
First
thing
first,
right?
I
think,
for
me,
the
validation
happened
just
it
was
actually
something
that
was
fundamental,
something
that
just
I
believed
in.
I
didn't
need
anyone
to
validate.
In
fact,
the
more
people
I
would
talk
to,
especially
people
who
have
business
acumen,
they
would
actually
turn
me
farther
from
this
idea.
I
actually
chose
not
to
talk
to
too
many
people.
Pablo
10:08
How
come?
What
would
they
say?
Were
they
not
aware?
They
didn't
feel
the
problem
themselves
or
was
it
something
else?
Arvind
10:14
Everybody
feels
the
problem,
but
everybody
felt
that
in
those
days
that,
hey,
I
can
live
with
it.
I
can
live
with
this
problem.
Pablo
10:23
Like
a
nice
to
have.
Arvind
10:24
Yeah,
I
feel
this
is
a
nice
to
have.
This
is
a
vitamin.
This
is
not
a
painkiller.
I
have
a
much
more
simplistic
thought
process.
I
don't
think
about
those.
I'm
not
a
business
person
either,
but
for
me,
it
was
like
I
was
going
with
the
engineering
mindset,
which
is
that,
look,
I
know
all
these
engineers,
they're
spending
one
third
of
their
time
just
trying
to
find
things.
They're
frustrated
and
there's
some
value
to
be
created
here.
Part
of
it
was
that,
just
that
belief,
and
actually
not
just
me,
whoever
we
hired
in
our
initial
founding
team
and
the
people
who
we
hired
after
that,
all
the
people
who
came
to
work
at
Glean
had
the
same
level
of
belief
in
the
problem
that
we're
trying
to
solve.
That's
the
only
reason
they
came,
that
it's
a
problem
that
they
faced
in
their
work
lives,
and
they
knew
it
was
important.
They
were
also
engineers.
Initially,
you
hire
engineers,
so
you
don't
think
about
the
vitamin
and
the
painkiller
and
the
nice
to
have
versus
must
have.
That's
not
how
you
think
users
go
and
solve
a
problem.
That's
our
initial
journey
is
to
–
and
I
think
it's
important.
It's
important
sometimes
not
to
over-analyze
and
actually
focus
on
the
end
user
and
the
problem
and
just
go
and
solve
it.
Skipping Lean Startup
Pablo
11:38
It's
interesting.
A
lot
of
these
vitamins,
they
feel
that
until,
like
you
said,
you
have
the
thing
and
then
you
realize
you
can't
live
without
it
anymore.
Then
it's
effectively
a
painkiller
because
you
create
the
pain,
right?
Did
you
do,
I'm
curious
back
then,
you
talk
about
over-analyzing,
which
this
is
a
theme
that
I've
seen
through
and
through
in
so
many
of
these
early
stories.
Things
work
because
people
build
something
that
solve
problems
and
then
the
market
presented
itself.
How
much
thinking
did
you
do
at
the
time
of
TAM
analysis,
market
size,
pricing,
all
these
things?
Arvind
12:07
That's
a
great
question.
Sometimes
we
talk
to
our
team
about
it.
We
didn't
do
any
TAM
analysis.
How
do
you
do
TAM?
There's
no
product
in
the
market.
Nobody
actually
is
even
solving
this
problem.
You
had
to
really
–
basically
my
mindset
was
that
this
is
fundamental.
Initially,
when
people
are
–
investors
ask
me,
okay,
what's
the
TAM
or
how
big
is
this
opportunity?
How
would
you
even
figure
out
how
much
people
would
pay
for
it?
What
should
be
the
price
and
what's
the
ROI?
How
are
you
going
to
prove
the
ROI?
You
won't
be
able
to
prove
the
ROI
because
saving
time
is
so
nebulous.
My
question
to
them
would
be
always
that,
okay,
think
about
email.
Do
you
think
you
need
email
in
your
company?
Nobody
doubts
it.
I
said,
what's
the
ROI
of
it?
Nobody
can
come
up
with
the
ROI
either.
Pablo
13:00
Slack
was
a
great
one
like
that.
I
remember
when
it
came
out,
we
were
paying,
we
were
a
startup
paying
for
Slack,
and
our
CFO
was
like,
you
guys
really
need
to
pay
for
this?
I'm
like,
yes,
do
not
take
this
out.
Arvind
13:10
Some
things
are
fundamental
and
we
felt
that
search
is
like
that.
Look,
you're
trying
to
find
things
and
to
get
work
done.
It's
important.
Then
especially
in
this
new
world
where
knowledge
is
exploding,
every
year
you
double
your
knowledge
inside
your
company
and
you
spread
that
knowledge
across
30%
more
systems
at
300
different
places.
Enterprises
have
thousands
of
applications
and
all
your
knowledge
is
spread
across
all
those
places.
How
are
you
going
to
find
anything?
Just
like
on
the
internet,
think
about
the
internet.
Are
you
keeping
track
of
like,
hey,
if
I'm
looking
for
a
recipe,
I'm
going
to
go
to
this
place.
If
I
want
to
look
for
news
on
certain
topic,
I'm
going
to
go
there.
You
don't
do
that.
It's
not
possible
anymore
because
there's
so
much
information.
It's
across
so
many
different
places.
Pablo
13:58
You
got
now
this
core
group
of
engineers.
You
have
the
funding.
You
need
to
build
the
product.
Do
you
just
go
heads
down
and
build
or
do
you
partner
with
some
design
partners
to
figure
out
the
subtleties
of
it?
How
do
you
make
that
MVP
work
out?
Using design partners
Arvind
14:11
You
absolutely
have
to
have
people.
There's
no
way
to
build
a
product,
especially
like
this
one,
without
any
design
partners.
That
was
the
first
task.
As
we
started
to
think
about
technology,
I
was,
although
I'm
an
engineer,
but
I
had
all,
any
non-engineering
task,
whether
it's
ordering
coffee
for
the
office
or
figuring
out
design
partners,
those
are
my
tasks.
Actually,
it's
very
interesting.
I
followed
a
very
different
process
than
typical.
I
didn't
actually
go
and
hit
my
friends
and
say
that,
hey,
can
you
actually
take
this
product
and
give
me
feedback
because
I
felt
they'll
all
be
very
nice
to
me
and
they
will
do
it.
Even
if
they
don't
have
a
need.
I
actually
went
on
LinkedIn
and
I
would
actually
do
call
outreach
to
people,
and
I
would
like,
look,
I'm
building
a
product
this.
Do
you
have
this
problem?
If
you
have
this
problem,
I
would
love
to
talk
to
you
and
get
your
feedback
so
that
I
can
build
my
product
with
direction
from
you.
That
was
the
journey
that
we
went
through.
Did
a
lot
of
–
Pablo
15:13
Do
you
remember
the
specifics
of
that?
I'm
curious.
Did
you
have
to
send
100
of
these
to
get
10?
Do
you
remember
how
high
level,
how
much
volume
you
need
to
go
through?
Arvind
15:21
Yeah,
I
had
to
do
a
lot.
I
don't
think
I
was
getting
one
out
of
ten
responses.
Maybe
I
was
initially,
but
then
I
was
the
BDR
for
my
company
for
the
first
two
years.
The
response
rates
would
be
low.
I've
sent
thousands
of
outreaches.
I'm
looking
for
–
and
I
understand
everybody's
busy,
but
when
you
get
the
response,
that's
from
a
person
who
has
that
pain
because
they're
responding
to
somebody
who
they
don't
know,
right?
Somebody
who
has
no
brand
in
terms
of
nobody
knew
about
our
company,
but
so
that
means
the
problem
must
mean
something.
The
problem
is
an
acute
pain
for
them
because
that's
when
they're
responding.
Pablo
16:02
To
be
clear,
your
message
wasn’t,
hey,
I'm
building
this
thing.
Do
you
want
to
buy
it?
It
was
very
much,
you
might
have
this
problem,
let
me
ask
you
a
few
questions.
That’s
how
you
framed
it
in
the
early
days.
Building for 2 years, with 0 revenue
Arvind
16:13
Yeah,
it
was
never
about
selling.
Those
outreaches
were
never
about
selling
because
in
fact,
we
actually
were
not
selling
the
product.
We
had
no
pricing.
We
had
no
plans
to
make
revenue.
That
was
an
intentional
decision
we
made
that
we
would
actually
not
even
charge
for
our
product
for
the
first
two
years.
Pablo
16:26
I'm
curious.
In
those
two
years,
how
did
you
structure
the
team?
Because
you
can
easily,
given
the
funding
you
had,
I
mean,
you
could
build
a
very
big
team
or
you
could
keep
it
small,
five
to
ten.
I'm
just
curious
how
you
structured
it.
Arvind
16:38
We
got
the
team
to
about
20
people.
That
was
our
goal,
which
is
large.
Sometimes
for
companies
you
don't
start
that
way,
but
we
knew
that
this
is
a
difficult
problem.
Search
requires
a
lot
of
R&D,
lots
of
technology
to
be
built.
We
wanted
to
build
a
team
of
about
20
people
and
divide
it
into
three
different
areas
part
of
our
technology
stack.
We
felt
that
that
was
basically
a
good
team
to
actually
make
a
lot
of
progress
and
build
a
great
product.
Then
we
stayed
there.
It
was
like
I
would
say
we
got
to
about
ten
people
within
the
first
five
months.
Then
gradually
we
got
to
20
over
the
next
five
months.
By
the
end
of
the
first
year,
we
were
more
than
20.
Then
we
stayed
out
there
for
some
time.
There
was
a
sufficient
strength
that
we
had
in
our
engineering
team
to
keep
making
a
lot
of
progress.
Pablo
17:28
You
mentioned
taking
a
different
approach.
I
mean,
I
can
see
it
because
if
you
go
for
two
years
building
a
product
without
necessarily
charging
for
it,
you're
certainly
not
following
the
Eric
Ries
Lean
Startup,
fast
iteration,
MVP
approach.
Why
not?
Why
didn't
you
just
build
the
MVP,
the
lowest
thing
that
somebody
would
pay
for,
put
it
out
and
just
do
what
most
startups
tend
to
do?
Arvind
17:45
Yeah,
because
we
had
a
fundamental
belief
in
the
problem
that
we
were
solving.
We
didn't
feel
we
had
to
pivot.
Our
journey
was
not
about
that
we
are
going
to
actually
try
something,
we're
going
to
learn
something,
we're
going
to
change
it
and
irate.
Sometimes
we
talk
about
product
market
fit
here.
For
me,
I
think
there
was
something
about
this
problem.
I
had
no
doubts
that
we
will
solve
this
problem,
but
I
also
was
aware
listening
to
customers,
we
can
get
a
lot
of
different
ideas.
There
are
some
decisions
that
you
have
to
make,
which
are
fundamental
yourself.
Pablo
18:19
That's
pretty
incredible.
I'm
trying
to
make
sense
of
it.
I
mean,
there
is
analogies,
right?
If
you
look
at
hardware
as
an
example,
whether
you
take
the
iPhone
or
now
the
Vision
Pro
or
whatever,
you
just
can't
iterate
at
that
level.
You
have
to
have
–
you
of
course
talk
to
customers,
but
at
some
point,
you
got
to
have
that
leap
of
faith,
that
conviction
that
puts
you
in
a
room
for
two
years,
so
to
speak,
and
builds
a
thing
that
really
delivers
value.
I
guess
the
challenge
is
when
you,
let's
say,
go
against
the
grain.
In
your
example
there,
the
market's
saying
one
thing,
you're
like,
no,
I'm
sticking
on
that
vision.
Obviously,
you
might
end
up
two
years
later
and
the
thing
you
built,
nobody
wants.
I'm
just
curious
how
you
think
about
that.
How
do
you
balance
that?
Even
your
advice
to
founders,
because
on
the
flip
side,
the
Lean
Startup
method
is
so
ingrained
that
almost
everybody
is
just
blindly
running
that
motion.
Maybe
in
some
cases
it
just
doesn't
apply.
Arvind
19:05
Part
of
it
is
actually
what
is
the
goal
that
this
founder
has.
Is
the
goal
to
actually
build
a
successful
company
or
is
the
goal
to
solve
a
problem,
something
that
you're
passionate
about?
For
me,
it
was
the
latter.
I
was
not
trying
to
get
a
win.
I
was
actually
trying
to
solve
that
problem.
That's
why
we
made
those
decisions.
We
want
to
actually
bring
help
to
every
single
person.
We
want
to
make
work
more
exciting.
We
want
to
make
work
less
frustrating
for
every
single
person
in
the
world.
For
a
first-time
founder,
they're
actually
trying
to
–
their
goal
is
actually
succeed
as
an
entrepreneur.
They
want
to
actually
learn
that
art.
It's
personal
in
that
sense.
For
me,
that
was
not
what
I
was
looking
for.
For
me,
my
focus
and
to
date
now,
all
the
decisions
that
we
make
even
today
are
driven
by
that
thing,
which
is
we
want
to
actually
solve
this
particular
problem
for
people.
Pablo
20:02
As
you're
doing
this,
what's
the
threshold
where
you
do
launch?
What
are
you
trying
to
get
to
where
you
feel
like,
okay,
this
product
is
ready
to
be
sold?
Arvind
20:12
Yeah,
When it's time to launch
Arvind
20:13
so
as
we
said,
for
the
first
two
years
we
didn't
charge.
We
wanted
to
see
engagement.
We
wanted
to
see
how
much
people
are
using
the
product
on
a
daily
basis.
When
we
saw
that
it
crossed
ten
searches
per
day
on
average,
that's
when
we
knew
that,
well,
look,
now
people
are
dependent
on
this
product.
They
are
actually
getting
value
from
it.
That's
when
we
felt
we
were
ready
to
charge
for
this
product.
In
our
metrics,
we're
showing
that
both
that
they
are
actually
finding
things
that
they
need
and
also
they're
actually
using
the
product
a
lot.
They're
finding
it
useful
to
actually
come
and
search
here
as
opposed
to
using
their
old
methods
of
finding.
Pablo
20:54
By
the
way,
what
was
so
hard
about
this
product?
Do
you
remember
as
you
went
through
that
development
cycle
parts
that
just
were
really
hard
to
make
to
work
properly
or
even
places
where
you
might've
thought
I
wonder
if
we
can
actually
get
this
to
the
vision
that
you
have?
Why AI was a key tailwind
Arvind
21:12
Well,
I
mean,
if
you
think
about
search,
it
is
like
magic.
You
can
come
in
and
ask
any
question
and
now
we
have
answered
that
question
for
you,
doesn't
matter
what
question
you
came
and
asked.
It's
a
difficult
thing.
You
have
to
now
think
about
this,
just
imagine
the
process
of
how
are
you
going
to
actually
solve
this
problem.
First
you
have
to
actually
connect
Glean
with
all
of
your
company
information
and
data
across
hundreds
of
these
systems
that
you
have,
all
of
them
with
clunky
APIs
or
interfaces
and
data
models.
You
have
to
bring
information
from
all
these
different
systems.
You
have
to
normalize
it.
What
information
is
stale?
What
is
out
of
date?
When
you
answer
questions
for
people,
don't
show
them
stuff
that's
no
longer
source
of
truth
anymore.
You
have
to
think
about
how
do
you
semantically
understand
data
and
knowledge
because
people
are
not
going
to
be
–
you
want
people
to
be
able
to
ask
answer
questions
very
freely
in
natural
language.
They
can
use
terms
that
don't
exist
in
the
documents.
There's
a
lot
of
technology
that
goes
behind
the
scenes
to
actually
build
a
product
this.
We've
seen
this.
We've
seen
how
complicated
the
Google
Search
stack
was.
Most
of
it
actually
did
come
from
Google.
We
worked
on
search
there.
We
understood
the
complexity
of
it.
Then
we
had
to
think
about
the
security
aspects
of
it,
which
is
that
–
imagine
this,
I
go
to
Pepsi
or
some
large
company
and
tell
them
that,
hey,
look,
we
have
this
great
search
product.
What
we
need
is
we
need
you
to
give
all
of
your
data
to
us.
Then
we'll
actually
make
it
searchable
for
you.
They're
going
to
wonder,
okay,
who
are
you?
No
brand
company
and
you
want
all
my
access
to
all
my
data?
That's
an
issue.
If
you
start
to
think
about
the
problem,
although
the
problem
is
actually
very
meaningful,
there
are
a
lot
of
challenges.
Pablo
23:08
How
much
did
the
advances
in
AI,
like
LLMs
and
all
these
sorts
of
things,
did
that
play
into
what
you
were
able
to
build
at
Glean?
Was
that
a
tailwind
for
you
guys?
Arvind
23:17
Absolutely,
and
actually,
it's
always
been
part
of
Glean.
Even
on
Day
1,
our
product,
we're
using
LLMs.
Now,
of
course,
everybody
talks
about
LLMs
and
we've
all
seen
how
powerful
they
are,
but
they
were
actually,
initially,
all
of
this
research
happened
in
Google
and
LLMs
were
actually,
or
these
language
models
were
actually
built
with
one
purpose,
which
is
to
make
search
better,
to
make
Google
Search
better.
When
we
started,
we
were
actually
able
to
use
these
BERT
family
of
language
models
that
Google
had
actually
published
in
Open
Domain.
These
were
language
models
that
were
trained
on
all
of
the
world's
knowledge.
They
understood
things
like
a
user
manual
and
a
product
guide
are
semantically
equal
and
things.
This
model
actually
has
all
of
that
language
understanding
buried
inside
of
it.
We
were
able
to
use
these
models
from
Day
1
to
build
a
really
smart
semantic
search
experience.
We
were
doing
vector
embeddings
and
now
everybody
calls
this
vector
search.
There's
no
name
for
it
like
when
we
were
using
it
initially.
The
journey
has
been
a
continuous
one
for
us.
It's
not
that
four
years
later
we
realized
that
there's
this
massive
new
language
model
thing
and
we
need
to
change
our
stack
with
it.
We're
progressively
using
it.
These
models
just
kept
getting
better
and
better.
It
allowed
us
to
actually
also
make
our
product
better.
Initially,
it
looked
more
like
the
traditional
Google
where
you
come
and
ask
questions
and
we'll
surface
that
information
back
to
you.
The
technology
has
been
amazing
enabler
in
terms
of
making
a
product
better,
but
it's
also
amazing
for
us
in
terms
of
helping
us
push
our
business.
This
is
where
the
transition
happened
from
the
vitamin
to
the
painkiller.
People
saw
that
if
only
I
had
something
like
Chat
GPT
inside
my
company
or
all
of
my
company
knowledge,
people
realized
that,
whoa,
no,
this
is
something
I
absolutely
have
to
have.
Pablo
25:09
It
makes
sense.
I
think
a
lot
of
these
products
that
are
step
changes
you
only
realize
later
how
much
of
a
painkiller
they
are.
I
mean,
Google
itself,
search
itself
is
that.
I'm
sure
before
it,
you
ask
people,
hey,
you
could
ask
a
million
different
questions
a
day,
you’d
be
like,
well,
I
don't
have
that
many
questions.
Then
you
realize
you
do
and
you
just
constantly,
everything
that
pops
in
your
brain,
right?
Let
me
ask
this
final
question.
You
take
these
two
years.
In
2021,
you
raised
the
$40
million
series
B.
My
question
is,
around
that
time
frame,
I
mean,
once
you
launch
this
product,
how
fast
did
revenue
grow?
How
long
did
it
take
to
get
to
$1
million
in
revenue
or
$5
million
in
revenue?
Do
you
remember
those
days?
Arvind
25:43
We've
been
actually
growing
about
3x
to
4x
every
year
in
terms
of
multiplying
our
revenues.
We
probably
hit,
right
after
we
launched,
because
we
did
have
a
good
set
of
design
partners.
There's
a
big
pipeline
that
was
already
built
for
us.
I
think
our
first
year
of
selling,
we
did
$3
million,
if
I
remember
right.
Pablo
26:06
Perfect.
Well,
we'll
stop
it
there.
I
appreciate
you
taking
us
through
the
journey.
I'll
just
end
with
two
questions
that
we
always
end
with.
The
first
one
is,
I
mean,
in
your
case
specifically,
you
understood
the
problem
deeply,
but
I'm
still
curious,
when
did
you
really
know
that
you
had
true
product
market
fit?
Finding Product Market Fit on Day One
Arvind
26:25
I
think
I
knew
it
on
day
one.
I
mean,
that's
it.
I
knew
that
we
were
going
to
go
through
this
challenge
of
trying
to
convince
people
of
the
value
of
the
product,
but
we
were
ready
for
that.
We
were
ready
to
actually
build
our
team,
evangelize,
and
convince
people
because
there's
never
a
doubt
in
my
mind
that
the
people
want
this
product.
Whenever
I
go
and
talk
to
anybody,
they
tell
me
they
want
this
product.
Then
there's
no
doubt.
It
was
just
a
matter
of
cultivating
the
market.
We
thought
that
the
journey
would
be
slow,
but
in
the
sense,
if
we
had
to
constantly
go
and
create
the
market,
evangelize,
it
changed
in
the
last
18
months
and
now
suddenly
we
have
something
that
everybody
in
the
world
wants.
It's
accelerating
us
and
our
business.
Pablo
27:14
Perfect,
and
the
last
question
is
after
going
through
founding
Rubrik
and
now
founding
Glean
and
creating
two
multi-billion-dollar
companies,
what
advice
do
you
have,
taking
everything
you've
learned,
for
first-time
founders
that
are
starting,
or
maybe
not
even
first-time
founders,
but
founders
that
are
starting
something
new
today?
One Piece of Advice
Arvind
27:32
Yeah,
I
mean,
my
number
one
advice
to
founders
is
conviction
and
persistence.
If
you
see
a
problem
that's
out
there,
then
don't
think
too
much
about
who
else
is
solving
it
or
how
big
the
market
is.
Just
go
and
solve
the
problem
and
persist
and
believe
in
it.
There's
going
to
be
ups
and
downs.
There's
going
to
be
enough
people
telling
you
that,
hey,
look,
I
see
this
problem,
but
I
don't
see
myself
paying
for
it.
Don't
worry
about
all
of
that
part.
If
you
think
that
it's
a
large
enough
problem,
a
lot
of
people
face
it,
then
having
that
conviction
and
belief
and
staying
on
course
is,
I
think,
the
most
important
thing.
As
engineers,
a
lot
of
times,
founders
are
engineers
and
our
mindset
is
to
doubt.
I
tell
people,
you
hear
these
stats
that
nine
out
of
ten
startups
fail.
I
like
to
tell
them,
look,
no,
it's
not
nine
out
of
ten.
It's
99
out
of
100
because
you
didn't
count
all
the
first
90
startups
that
the
founder
killed
themselves.
Sometimes
we
say
the
startup
–
but
most
of
them
fail
in
the
mind
of
the
founders.
If
there's
a
problem
and
you
can
solve
it,
then
it
doesn't
matter
who
else
is
out
there.
Pablo
28:41
Perfect,
love
that.
Well,
Arvind,
thanks
a
lot
for
spending
the
time.
This
is
great.
Arvind
28:46
Appreciate
that.
Thank
you
for
having
me.
Pablo
28:48
If
you
listened
to
this
episode
and
the
show
and
you
liked
it,
I
have
a
huge
favor
to
ask
for
you.
Well,
it's
actually
a
really
small
favor,
but
it
has
huge
impact,
but
whichever
app
you're
listening
to
this
episode
on,
take
it
out,
go
to
Product
Market
Fit
Show
and
leave
a
review,
please.
It's
going
to
help.
It's
not
just
going
to
help
me,
to
be
clear.
It's
going
to
help
other
founders
discover
this
show
because
the
algorithms,
whether
it's
Spotify,
whether
it's
Apple,
whether
it's
any
other
podcast
player,
one
of
the
big
things
they
look
at
is
frequency
of
reviews.
It's
quantity
of
reviews.
The
reality
is,
if
all
of
you
listening
right
now
left
reviews,
we
would
have
thousands
of
reviews.
Please
take
literally
a
minute,
even
if
you're
just
writing
great
podcast
or
I
love
this
podcast,
whatever
it
is,
just
write
a
few
words.
Obviously
the
longer
the
better,
the
more
detailed
the
better,
but
write
anything,
leave
five
stars
and
you'll
be
helping
me,
but
most
importantly,
many
other
founders
just
like
you
discover
the
show.
Thank
you.