►
Description
🙏 Thank you for watching! Hit 👍 and subscribe 🚩 to support this work
🌱Join the Community🌱
on Discord https://discord.gg/DDr5kYU
or say hello on Telegram http://t.me/CommonsStack
Join the conversation https://forum.tecommons.org/
Follow us on Twitter: http://twitter.com/CommonsStack
Learn more http://tecommons.org/
A
A
B
A
B
A
B
B
Well,
you're
getting
really
good
at
it.
You
sound
like
a
dev
okay,
so
I
mean
this
is
just
so
timely.
I
mean
today
I
want
to
bring
up,
and
this
is
kind
of
a
casual.
B
We
were
supposed
to
go
over
token
logs
today,
but
wesley
couldn't
make
it
so
we're
kind
of
taking
a
break,
a
step
away
from
all
the
parameter
hatch
stuff,
and
I
just
wanted
to
jump
into
the
luna
swarm
and
the
one
hive
cad
cad
modeling
that
luke
has
been
working
on
and
the
luna
swarm
has
been
all
working
on
together.
It's
it's
been
nice.
They
have
calls
every
every
friday
about
five
hours
after
this
one.
It's
one
pm
pst
for
anyone
in
in
this
who's.
B
Coming
to
the
tec
labs,
you
might
be
interested
in
the
luna
swarm
meetings,
so
I
think
let's
get
started.
Let's
come
back
to
our
sort
of
ritual.
So
I'll
just
remind
everyone
hop
into
the
tec.
Labs
channel
check
the
pinned
messages
and
go
ahead
and
open
up
the
notion,
workspace
and,
let's
pop
open
the
attendance
we're
starting
a
bit
slow
today,
so
we'll
just
see
how
far
we
get.
But
it's
all
good.
There's
no
pressure
to
you
know
whatever
happens
happens.
Oh
are
people.
Okay,
let's
see,
let's
insert
left.
B
B
Yep
so
find
your
way
to
the
attendance
sheet.
It's
nice
to
get
a
log
of
of
who's
attending
the
labs
and
have
some
emoji
play
first
thing
to
get
warmed
up
some
participation
marks
and
yeah.
If
anyone
has
any
questions
or
anything
like
always
just
feel
free
to
jump
in
at
any
point,
so
we
see
the
calendar
calendar
here,
we're
on
lab
nine
and
I
just
am
going
to
whip
up.
B
I
have
some
notes
in
my
notebook,
so
the
first
thing
I
want
to
do
again
a
little
bit
of
a
sidetrack,
but
I
want
to
see
if
I
can
find
this.
I
want
to
remind-
or
let
everyone
know
here
in
this
call,
because
you
some
of
you
might
be
interested.
This
is
the
last
day
to
register
for
a
program
that
is
being
hosted
by
token
engineering.
B
Let's
see
there
is
an
application
process,
just
one
left
day
left
to
apply
okay,
so
this
is
a
research
track
that
is
being
hosted
by
the
token
engineering
community.
It's
like
an
eight-week
program
kind
of
similar
to
the
labs
here
and
then
also,
if
you've
been
tracking
the
labs
that
danilo's
putting
on
on
thursdays.
B
B
B
So
that
was
the
first
thing
I
wanted
to
cover
te
research
track.
A
B
So
everything
everything
starts
with
the
notion
workspace
so
come
into
the
tech
labs,
hit
the
pinned
messages
at
the
top
and
open
up
the
notion
page.
There.
B
Oh
yeah,
okay,
good
questions,
okay,
so
the
number
two
thing
that
I
want
to
take
a
moment
to
pause
and
and
have
everyone
check
this
out
is
also
linked
in
here-
is
the
cad
cad.education
course,
and
for
me
I
don't
know
if
this
is
just
for
me
like
on
linux,
but
it
only
works
on
chrome.
B
It
doesn't
work
on
firefox
there's
this
this
like
educational
platform,
so
I
would
like
to
recommend
everyone
right
now
to
open
this
up
and
sign
up,
because
what
this
one
thing
that
this
offers
and
you
can
get
in
for
free
if
you
use
the
promo
code
block
science,
so
whoever
wants
to
just
sign
up
for
this
kind
of
while
I'm
going
it'll
take
a
couple
minutes.
B
B
So
this
is
a
cad
cat
cheat
sheet
and
it
might.
The
font
might
be
kind
of
small
for
you
to
see
over
the
stream,
but
it
sums
up
everything
you
need
to
know
for
creating
cad
cad
models.
It's
got
all
the
steps
and
it's
really
neat
how
it
breaks
it
down.
If
you
can
really
digest
all
the
steps
here,
then
you'll
have
a
complete
understanding
of
the
process
of
cad
cad,
so
there's
essentially
the
modeling
and
the
simulation.
B
So
the
modeling
is
where
you
set
everything
up.
You
define
your
state
variables,
so
we'll
see
those
in
our
one
hive,
modeling
system
parameters,
policy,
functions,
state
update
functions.
This
is
how
the
the
model
is
going
to
change
over
time
and
then
partial
state
update
blocks.
So
in
one
moment
of
time
or
one
time
step,
there
might
be
a
series
of
things
that
happen,
so
we
can
break
down
our
state
update
functions
into
update
blocks.
B
B
We
have
to
plug
everything
into
the
execution
engine
and
then
once
it
runs
we're
going
we're
going
to
get
our
output
and
we
can
do
our
analysis,
so
I'm
just
kind
of
stalling
here
to
give
anyone
who
wants
to
go
through
this
process
an
opportunity
I'm
going
to
hit
sign
in
with
your
account,
because
I
have
an
account
and
once
you're
in
see,
I
can
only
get
97,
I'm
such
a
completionist
and
it's
driving
me
crazy.
I
can't
figure
out
how
to
get
100
completion
in
this
course.
I
feel
like.
B
I
think
I've
done
everything
and
checked
every
box,
but
that's
kind
of
driving
me
insane,
but
yeah.
You
can
also
download
the
cheat
sheet
right
here
and
it's
super
valuable.
I
think
just
everyone
should
have
this
like
just
even
kind
of
what
metaverde
was
saying,
like
speaking
the
language
right,
if
you,
if
you
open
this
up
and
take
a
look
at
it
and
see
the
eight
step
process,
you'll
you'll
start
to
have
a
really
good
idea
of
what
people
mean
when
they're
talking
about
creating
cad
cad
simulations.
B
So
that's
number
two
that
I
wanted
to
cover
and
then
so
I'll
just
lay
out
the
next
things,
and
I
don't
know
if
we'll
have
time
for
all
of
it,
but
one
hive
fork
and
run
locally.
This
is
really,
I
should
say,
like
a
luna
swarm,
one
hive
model,
one
hive
model.
B
A
I
want
to
let
people
vote
on
the
sprint
planning,
for
this
run
run
oh
cool.
B
B
B
B
Actually,
you
know
what
I'm
going
to
do.
Don't
go
to
that
repository,
there's
a
better
one,
because
there,
I
think,
there's
an
open
pull
request.
Unless
it's
been.
Oh,
no,
it's
been
merged.
Sweet!
Oh
no!
It
hasn't
where's.
My
pull
request
on
here.
B
Oh
this,
here,
okay,
so
my
pull
request
is
still
open.
So
I
think
what
you
guys
should
do
is
go
to
this.
B
Let's
see,
this
might
be
too
complicated
this.
This
has
a
few
updates.
So
if
you
want
to
work
on
the
latest
branch
I'll
link,
it.
B
Here
but
this
will
be,
this
should
be
merged
into
luna
swarm.
Pretty
soon
I
think
luke's
been
pretty
busy,
but
yeah
I've.
I've
kind
of
I've
done.
We've
done
some
conviction,
voting
modeling.
We
did
this
last
week
in
the
lunasworm
meeting
and
some
iterations
on
the
honey
supply
visualizations
like
results
visualizations
after
the
simulator.
B
B
You're
gonna
wanna
fork
it
because
then
you
can
easily
push
updates
like
if
you,
if
you
make
some
cool
modeling
or
if
you
make
some
changes
to
the
model,
you
can
just
push
them
to
your
local
repo
and
if
you
ever
have
a
nice
model
that
you
actually
think
you
want
to
share
with
the
community,
then
you
just
go
to
luna
swarm
on
one
hive
and
you
go
pull
requests
and
you
go
new
pull
request
and
when
you
do
this,
you'll
it'll
give
you
the
option
to
select
the
fork
that
you've
made,
and
this
way
you
can
actually
push
your
models
back
up
to
the
to
the
one
hive
repo,
but
for
ease
of
of
working
sort
of
rapidly
working
and
and
having
a
repository
to
push
updates
to.
B
It
is
best
to
fork
it.
So
you
have
your
own
copy
that
you
can
work
on
so
I've
forked
this
to
long
tail,
financial.
B
So
you
can
come
here
to
get
the
latest
changes,
and
so
you
want
to
fork
this
and
then
once
you
have
your
fork,
bring
it
down
to
your
local
working
environment
by
cloning.
It,
let's
see,
terminal.
B
I
think
I
always
lose
people
here
in
the
like
github
stuff,
but
just
the
way
it
is
so
if
you're
getting
lost,
then
you're
going
to
want
to
take
some
time.
You
know
just
just
to
get
comfortable
with
the
github
flow
and
cloning
and
forking
and
that
kind
of
stuff,
if
you
just
keep
doing
it,
it
gets
more
and
more
familiar.
B
B
Okay,
so
I've
opened
up
my
jupiter
lab
and
jupiter
lab
is
really
nice,
it's
so
powerful,
especially
when
you
get
it
nice
and
organized.
So
I
have
my
workspace
directory
that
I'm
in-
and
this
is
just
where
I
clone
all
my
repos
and
then
I
can
access
them
all
from
jupiter
labs.
So
I
can.
I
have
cad
cad
demos
right
here
like
this
is
github.com
cadcad
demos.
B
B
I
get
examples
of
update
functions
and
partial
state
update
blocks,
yeah
having
a
nice
organized
jupiter,
lab
environment,
and
I
have
cad
cad
education
here.
So
I
have.
This
is
the
course
content
and
like
modeling
and
simulation,
and
if
I
open
up
the
notebook,
then
this
is
a
whole
cadcad
model
for
modeling
predator
prey
dynamics
and
it
takes
you
through
all
the
mathematical
specification
and
all
the
steps
of
the
cheat
sheet.
B
A
B
So
basically,
the
trick
there's
one
trick,
and
it's
so
I
have
everything
is
to
is
the
trick-
is
to
choose
one
directory
where
you're
gonna.
It's
like
your
root
work
workspace.
So
from
my
home,
I
have
my
workspace
where
I
put
everything-
and
these
are
just
like
kind
of
my
highest
level
like
the
different
organizations
I'm
involved
with
and
all
this
cat
cat
whenever
I'm
doing
like
cad
cad,
modeling
or
generally
anything
open
source.
I
just
go
into
my
tec
directory.
I
think
I
also
have
a
I
have
a
one
hive.
B
I
made
a
one
hive
directory,
so
sometimes
I
have
a
bit
of
redundancy,
but
if
I
just
go
into
my
tec,
then
I
just
bring
everything
open
source
I
put
here
so
I
I
did
like
this
ocean
hackathon.
I've
got
luna
swarm,
git
coin
cad,
cad
modeling,
and
so
what
I
mean
by
being
organized
is
the
first
thing
I
always
do
is
come
into
this
directory
and
then,
whatever
github
repository,
I
need
to
clone.
B
I
clone
it
into
that
space
and
it
says
okay,
it
already
exists.
So
I
have
all
my
github
repositories
here
and
then,
if
I
open
up
jupyter
lab
from
this
directory,
then
I
have
access
to
all
all
of
my
repositories,
my
mouse.
B
I
have
access
to
all
all
of
my
repositories
from
one
area,
so
I
can
easily
like
cross
reference,
see
here's
like
here's
source,
cred
and
there's
no
notebooks
in
there.
Is
there
see
here's
a
source,
cred
notebook
that
I
haven't
even
really
looked
at
yet
so
I
can
see
what
kind
of
research
is
going
on
with
source
cred.
I
think
this
is
tec.
Source
grid
research.
B
Okay
and
I'm
missing
all
these
dependencies,
but
let's
see
okay,
so
I
won't
get
too
stuck
on
that
now
but
see
I
could
cross
reference.
I
could
say:
okay,
what
were
what
have
we
been
working
on
here
with
source
cred
and
then
I
could
jump
back
and
I
could
say
how
does
that?
Compare
to
the
git
coin,
cad
cad
modeling
that
danilo's
been
working
on,
and
so
then
I
could
and
of
course
I'm
always
getting
wrecked
by
by
these
dependencies.
B
But
once
you
have
your
virtual
environment
all
set
up,
then
dependencies
won't
be
such
a
problem
and
what
I
mean
by
that
is
just
once
you
pip
install
something
you'll
have
it,
so
it
makes
it
easy
to
really
cross-reference
things
very
quickly.
B
B
Point:
okay,
oh
yeah,
so
I
wanted
to
just
basically
take
this
time
to
do
an
overview
of
this
model.
I
haven't
done
much.
I
haven't
really
taken
some
time
myself
to
just
actually
really
read
this
and
think
about
everything.
That's
happening
here
and
I
think
it's
a
bit
too
much
for
us
all
to
read
everything,
but
I
think
we'll
do
a
bit
of
a
in
between
we'll
skim
through
this
together
and
if
anyone
wants
to
jump
in
definitely
feel
free.
B
So
this
is
the
one
hive
economy
and
honey
supply
model.
This
is
an
abstract
model
of
the
onehive
economy,
where
outflows
from
the
common
pool
are
used
to
produce
inflows
and
explores
how
this
dynamic
would
impact
a
proposed
change
in
the
honey
supply
policy
which
would
mint
and
burn
honey
based
on
a
target
ratio
between
the
common
pool
and
the
total
supply.
In
order
to
use
the
model,
we
must
make
some
assumptions
about
system
dynamics.
B
These
assumptions
include
things
that
we
can
control
like
how
the
protocol
behaves
and
things
we
can't
control
like
humans
and
the
markets
and
how
they
behave.
Since
we
cannot
know
for
certain
what
to
expect
from
things,
we
cannot
control,
we
can
do
our
best
to
design
and
parameterize
the
protocol,
such
that
it
behaves
acceptably
across
a
broad
range
of
simulated
situations.
B
So,
what's
the
model,
we
assume
that
outflows
from
the
common
pool
will
be
used
productively
to
create
applications
which
utilize
honey.
These
products
may
contain
mechanism
mechanisms
which
capture
I'll
just
edit
that
may
contain
mechanisms
which
capture
a
portion
of
cash
flows
as
honey
and
return
them.
As
inflows
back
to
the
common
pool.
B
B
Price
of
honey
is
modeled
as
a
stochastic
process
that
is
correlated
with
a
fundamental
valuation.
Heuristic.
We
model
this
as
a
correlated
random,
walk
towards
a
price
target
determined
by
the
level
of
market
saturation
market
size
and
circulating
supply.
A
production
function
is
used
to
translate
outflows
into
marginal
production
and
market
saturation.
B
B
That's
okay,
so
we
have
this
dynamic
supply
policy
which
will
mint
or
burn
tokens
from
the
common
pool
in
order
to
target
a
ratio
between
common
pool
balance
and
total
supply.
Adjustments
are
made
proportionally
to
distance
from
the
desired
ratio
and
are
bounded
by
a
throttle
parameter
which
limits
the
magnitude
of
these
changes
over
time
cool.
B
B
B
B
I'm
not
sure,
but
I
would
guess
it
might
be,
like
recently
moved
or
like
in
there's
this
a
concept
called
velocity
of
money
and
it's
like
differentiating
between
money
that
is
just
sort
of
locked
away
or
stored
in
savings
accounts
and
money
that
is
it
flowing.
So
money
that's
been
essentially
recently
recently
transacted.
A
Feel
like
active,
may
I
don't
know
and
I'll
find
out
and
I'll,
let
you
know
next
time,
but
I
feel,
like
active,
may
be
related
to
being
used
to
vote
on
proposed,
but
I
don't
know
if
the
numbers
yeah,
I'm
pretty
sure,
that's
exactly
what
it
is.
It's
the
effective
supply,
that's
just
the
tokens
that
are
actually
not
active,
the
tokens
that
are
being
used
for
voting
in
conviction.
Voting
at
that
moment.
A
And
then
the
common
pool
is
locked
up
too
right,
yeah,
exactly
we're.
Basically
looking
at
14
000
out
of
28
000.
That
is
gone
like
you
can't
so
there's
really
we're.
Only
we're
talking
about.
Only
half
of
that
supply
is
actually
available,
so
it's
available
for
the
markets
in
this
moment,
but
anyone
who
has
the
active
tokens
there's
no
lock-up
periods,
so
they
can
be
withdrawn.
A
B
So
this
is
pretty
neat
it's
telling.
So
what
this
means
is
like
the
more
participation
we
have
in
the
governance,
the
higher
the
price
will
go
because
proposals
are
going
to
be
locking
up,
circulating
supply.
So
if
there's
like
constantly
all
these
proposals
happening
and
everyone's
voting,
then
there's
going
to
be
no
honey
on
the
market,
which
means
it's
going
to
be
very
expensive.
So
that's
like
the
price
to
access
the
governance.
The
more
active
the
governance
is,
the
more
expensive
expensive.
B
It
is
to
buy
your
way
in
because
that's
I
love
this
stuff,
that's
so
cool!
So,
let's
see
where
we
were
this
dynamic
minting
and
burning.
Oh
yeah,
I
was
saying:
there's
two
essential
heuristics
here
we
want
to
maintain
a
particular
ratio
between
the
common
pool
and
the
total
supply,
and
we
also
we're
going
to
model
the
price
as
a
function.
B
We're
going
to
say
that
essentially,
our
model
at
every
step
is
going
to
say,
there's
a
real
price,
there's
a
real
value
of
honey
and
that
real
value
is
based
off
of
market
saturation
market
size
and
circulating
supply.
But
then
that's
like
the
true
underlying
price.
Then
there's
going
to
be
a
market
price
that
that
won't
necessarily
be
equal
to
the
the
true
underlying
price,
and
so
the
model
is
going
to
slowly
do
a
random
walk,
which
means
yeah.
It's
a
random,
literally
a
random
walk,
so
it
like
how
a
price
moves.
B
Is
there
a
chart
here?
But
if
we
go
to
like
coinmarketcap.com,
so
basically,
prices
move
in
a
random
walk
towards
some
underlying
trajectory,
like
a
price,
might
have
a
trend
to
move
up
to
because
it's
increasing
in
value,
but
along
that
trend
it
takes
there's
there's
randomness
in
the
system.
That's
called
the
stochastic
process.
B
B
And
so
those
are
the
two
sort
of
heuristics
I'm
getting.
Is
that
maintaining
that
ratio-
and
I
mean
having
this
model
of
the
price
and
the
more
outflows
we
have
the
more
production
we're
gonna
make
the
more
production
we
make
the
more
inflows
we're
going
to
have,
which
is
a
cool
kind
of
way
to
look
at
it.
B
And
market
saturation,
I
think
I
don't
fully
understand.
Okay,
a
production
function
is
used
to
translate
outflows
into
marginal
production
and
market
saturation
production
depends
on
the
current
price
of
honey
outflows
and
the
current
level
of
production
and
results
in
the
level
of
does
anyone
know
what
market
saturation
is?
Oh,
it's
like.
If
we
have
too
many
products
or.
B
Oh
yeah
cool,
so
we
have
all
of
our
parameters.
We
have
the
outflow
rate,
productivity
price
dynamics,
throttle
target
reserve
ratio;
okay,
there's
not
so
many.
Let's,
let's
read
through
them
the
outflow
rate.
We
use
conviction,
voting
to
allocate
honey
from
the
common
pool.
Conviction.
Voting
is
parameterized
such
that
there
is
a
theoretical
upper
bound
on
the
rate
at
which
proposals
can
allocate
funds,
but
the
actual
rate
of
spending
depends
on
individuals
staking
on
proposals
for
the
purpose
of
this
model.
B
We
abstract
the
flow
of
funds
from
the
common
pool
as
a
simple
outflow
rate
parameter,
which
controls
how
much
honey
is
moved
from
the
common
pool
into
circulating
supply
supply
at
each
time
step.
Okay,
so
they're,
not
modeling
the
proposals,
there's
no
like
random.
Okay,
maybe
there's
ten
proposals
today
and
two
tomorrow,
they're
just
saying:
there's
like
there's
an
average
flow
of
honey.
There's
an
average
honey
spend
that's
happening.
A
I
remember
when
zargham
and
luke
were
talking
about
this
and
I
thought
it
was
a
really
important
point
just
to
bring
out
that
when
you're
doing
a
cad
cad
model,
you
really
you
will
ne
it's
like
looking
at
an
elephant
right
like
you.
Might
you
want
to
model
the
trunk
you
might
want
to
model
a
toenail
and,
and
everything
else
just
needs
to
be
black
boxed.
So
you
can
focus
on
the
piece
that
you
care
about.
B
Yeah
yeah
precision
in
the
modeling
you
get
to
isolate
exactly
the
thing
that
you're
most
curious
about,
and
everything
else
has
to
be.
You
basically
give
it
a
random
number
and
and
then
you
can
shift
and
then
you
can
say.
Oh
now,
we
understand
this
piece
really
well.
We
understand
the
trunk
of
the
elephant
really
nicely,
so
we
have
a
great
model
for
it.
Now,
if
we
want
to
understand
the
foot
well,
we
can
include
the
model
of
the
of
the
trunk,
because
that's
we
already
made
that
very
precise.
B
But
but
it's
you
know,
these
systems
are
very
big
and
complex.
All
of
us
on
this
call
right
now
are
participating
in
this
ecosystem.
You
know
we're
not
buying
or
selling
honey,
but
we're
sort
of
sharing
ideas
and
connecting
as
a
network,
so
this
could
be
modeled
and
so
there's
just
like
this
infinite
complexity
of
what
we
could
possibly
be
modeling.
So
it's
important
to
do
one
thing
at
a
time
and
I'll
just
see
if
I
can
whip
this
up.
This
is
what
we
did
last
week
with.
B
B
Unfortunately,
this
is
messed
up,
but
this
is
the
outflow
of
honey
over
time,
so
this
is
going
from
november
to
january
15th
and
we
can
see
that
in
mid
early
to
mid
november,
there
was
a
huge
outflow
of
honey
and
I
think
that
corresponds
to
this,
which
was
the
honey
toll
gate
refund,
which
refunded
300
honey,
and
so
what
we
can
do
now-
and
we
just
did
this
last
week
in
the
lunasworm
call
so
now
that
we
have
this
data
we've,
we
actually
were
able
to
pull
this
data
from
the
blockchain
using
the
graph,
which
is
just
awesome,
and
so
now
what
we
could
do
is
we
could
actually
take
this
data
and
get
get
like
a
trend.
B
Okay.
So
if
we
take,
how
can
we
do
this
like?
What
are
we
actually
doing
here?
This
is
cumulative
spend
over
time,
so
we
have
this
df
cumulative
spend.
So
if
we
take
okay,
let's
make
something
called
cumulative,
spend.
B
Equals
this
cumulative
spend
so
now
we
just
have
just
this
series,
so
this
is
for
each
time
step
it's
how
much
honey
we
spent
and
what
are
these
time
steps?
Do
we
have
date
time.
B
So
what
I
would
like
to
do
is
take
the
beginning
day
and
the
ending
day
and
get
the
difference
by
number
of
days
and
then
see
how
much
honey
we
spent
over
this
time
and
we
can
get
the
average
honey
spend
per
day.
So
I'm
just
going
to
do
that.
Now,
I'm
going
to
say
like
day
one
equals
cumulatives.
Oh
no!
It's
our
data
frame
date,
time,
dot,
location,
zero,
so
d1
is
this
october
21
and
we
can
get.
B
So
we
have
day
one
is
october,
21
and
day
two
is
january
19th,
and
then
we
can
do
something
we
can
go
import
date
time.
B
I
think
it's
like
from
date,
time,
import
time,
delta,
yes
and
then,
okay,
let's
google,
this
real
quick
python
number
of
days
between
two
dates.
B
B
So
this
is
what
is
referred
to
in
the
cad
cad
ecosystem
as
a
digital
twin.
So
there's
one
one
thing
to
do
with
cad
cad
modeling
is
like
before
you
launch
the
system.
We
we
model
it,
and
so
this
is
what
we've
been
doing
with
the
tech
hatch
parameters,
we're
doing
all
this
modeling
before
we
launch,
so
that
we
have
an
idea
of
of
what
can
happen,
but
you
can
also
do
modeling
after
the
launch
and
you
can
go
and
see
what's
really
happening
in
the
world.
B
A
Hey
sean
yeah,
what
you
did
with
the
days
you
could
have
also
done
with
price
right.
You
could
also
have
done
the
same
thing
for
the
price
on
day,
one
to
the
price
at
day:
80,
not
yep,
right
yeah.
You
could
have
done
the
same
thing.
So
in
a
sense,
that's
also
kind
of
looking
back
at
predictive
price
discovery.
B
A
Right,
but
if
you
went
back
to
what
the
price
was
on
each
one
of
those
days,
you'd
have
to
catalog
all
of
that,
but
you
could
do
the
same
exact
expression
you
just
did
and
you
would
know
exactly
what
the
average
cost,
what
the
average
value
just
the
average
outflow
or
inflow
of
of.
What's
you
know
dollar
wise
of
honey
during
that
89
days,
and
then
you
could
you
could
you
could
then
then
chart
that
you
could
graph
it
yeah.
B
B
A
A
A
But
is
that
what
and
a
requested
amount
of
that
group
of
these
groups
of
proposals
interesting
dude,
there's
a
application
of
that
some
of
these.
Some
of
these
also,
like
the
honey
toll
gate
refund
for
300,
the
large
one
that
tollgate
money
goes
back
into
the
funding
pool
so
like
that
300
ether
was
used
by
someone
to
create
a
proposal
and
then
that
300,
sorry
that
300
honey
went
into
the
funding
pool,
and
then
this
person
requested
it
back.
A
Oh
so
it
can
okay,
so
it's
not
exact
so
well!
I
I
guess
this
requested
amount
might
also
want
to
consider.
You
know
how
much
the
inputs,
of
course
right
like
beyond
issuance
so
like
there's
the
issuance,
but
then
there's
also
did
people
actually
put
money
into
the
funding
pool
and
then
just
request
it
back.
B
B
This
is
so
cool
because
every
in
right
in
the
data-
and
this
was
pulled
from
the
graph,
but
each
proposal
comes
with
a
link
to
a
forum
post
so
awesome.
So
we
can
see
what
happened
with
the
tool
gate.
B
A
For
dandelion
voting,
you
know
they
the
toll
gate,
as
you
know
very
well,
sean
previous
labs,
the
the
to
create
a
request
to
change
parameters
in
dandelion
costs,
a
toll
gate,
and
so
they
made
the
toll
gate
ridiculously
high
because
when
they
made
it
honey
was,
like.
You
know,
five
bucks,
so
so
when
he
made
when
he
made
that
request,
money
was
nearly
a
thousand
dollars.
I.
B
B
Cool
guys
so
we're
pretty
much
getting
to
the
end.
I
think
we
should
just
pick
this
up
in
a
future
lab,
I'm
not
sure
exactly.
What's
coming
next
week,
we
got
to
take
a
look
at
the
lab
schedules,
but
this
would
be
an
awesome
series
to
sort
of
have
on
the
back
burner.
We
can
jump
into
this
one
hive
modeling
whenever
lab
spaces
open
up
this.
B
The
modeling
here
is
awesome
like
reading
this
doc
is
so
cool,
so
even
for
those
who,
you
know
aren't,
maybe
you
don't
wanna
you're,
not
so
comfortable
with
python
things
like
that,
even
just
reading
this
document
it
makes
for
a
wonderful
overview
of
the
honey
economy.
Essentially,
and
with
that
we
have
five
minutes
left
griff.
Do
you
want
to
jump
onto
token
log
stuff.
A
I
do
I
just
want
to
give
everyone
who's
magically
in
this
call
a
chance
to
help
the
guard.
The
te
commons
stewards,
the
token
engineering,
commons
community
stewards.
I
want
to
give
them
a
chance
to
tell
us
what
to
do.
If
you
have
impact
hours
or
see
stack
tokens
which
everyone
is
called,
I
think
has
both.
When
I
look
at
it.
Oh
well,
heater
might
not
maze,
might
not
have
both,
but
I
bet
you
guys
will
have
them
soon.
Just
for
attending
calls.
You
end
up
with
voting
power.
A
You
can
go
to
tokenlog.xyz
and
find
the
token
engineering
commons
and
you
can
actually
start
voting
on
parameters.
Sorry,
not
parameters.
We're
going
to
use
this
later
to
vote
on
parameters
right
now.
We're
beta
testing
it
before
we're
designing
our
dials.
We
we
need
to
get
to
the
hatch,
and
so
we
have
all
of
our
open
issues
that
need
to
happen
and
in
about
four
minutes
we're
going
to
go
figure
out
which
ones
we
want
to
include
in
the
sprint
and
your
votes
will
matter.
A
So
if
you,
if
there's
something
that
you
want
us
to
do
in
the
sprint,
you
could
create
a
new
issue
and
actually
and
then
vote
for
it.
So
you
can
tell
us
what
you
want
us
to
do
or
you
could
find
the
issues
that
have
already
been
created
and
you
can
actually
upload
them
and
they'll
get
prioritize
the
sprint.
A
So
it's
kind
of
a
way
for
us
to
decentralize
our
community
management
and
the
process
of
how
we
decide
what
to
do
every
two
weeks,
while
also
very
importantly,
testing
this
tool
before
we
use
it
for
determining
the
parameters
of
our
hatch.
So
please,
please
just
even
just
play
around
and
vote
for
something
that
you
that
you
want
now.
It's
like,
oh
yeah.
We
need
to.
A
We
need
to
get
a
zeptimus
to
to
apply
for
a
community
to
be
a
community
steward
and
what's
cool
is
this
is
actually
using
two
tokens
and
quadratic
voting.
So
if
I
want
to
use
eight
votes,
it's
going
to
cost
me
64
voting
points,
but
I
want
septimus
to
apply
for
swiss
membership
voting
for
it
and
I
don't
think
metamask
pops
up
for
you
guys,
but
it
you
know
it
doesn't
cost
us
money
to
vote.
You
just
sign
a
transaction.
A
B
A
Yeah-
and
we
will
we'll
also,
we
can
move
your
c
stack
token
as
well.
Ygg
excellent.
B
B
A
So
I
had
to
stop
sharing
screen
before
I
expose.
You
know
personal
information
here
for
all
the
internet
to.