If
you
haven’t
come
across
OpenClaw
yet
here’s
the
short
version
it’s
an
open
source
personal
AI
assistant
that
runs
on
your
own
machine
Mac
Windows
or
Linux
You
talk
to
it
through
whatever
chat
app
you
already
use
WhatsApp
Telegram
Discord
Slack
Signal
even
iMessage
and
it
can
actually
do
things
It
has
access
to
your
file
system
can
browse
the
web
run
scripts
manage
your
email
calendar
and
much
more
through
a
growing
ecosystem
of
skills
and
plugins
It
has
persistent
memory
so
it
remembers
your
preferences
and
context
across
conversations
Think
of
it
as
a
24
7
AI
teammate
that
lives
on
your
computer
and
gets
better
the
more
you
use
it
Like
everyone
else
in
the
AI
space
we
jumped
into
OpenClaw
testing
early
on
However
true
to
our
core
company
philosophy
we
didn’t
just
want
to
play
around
with
it
We
wanted
to
find
use
cases
that
deliver
real
value
as
soon
as
possible
We
didn’t
have
to
look
far
Every
one
of
us
is
always
short
on
time
and
we
all
need
an
extra
pair
of
hands
to
get
everything
done
So
we
decided
to
put
the
agent
to
the
ultimate
test
could
OpenClaw
work
as
a
genuine
Executive
Assistant
Turns
out
with
the
right
setup
it
absolutely
can
With
a
big
asterisk
none
of
this
is
perfect
yet
and
we’ll
be
upfront
about
that
throughout
this
series
Why
an
Executive
Assistant
The
EA
role
is
one
of
the
most
demanding
jobs
out
there
It
requires
managing
communications
across
dozens
of
channels
keeping
calendars
in
order
tracking
promises
and
follow
ups
monitoring
relevant
news
and
doing
it
all
with
the
right
tone
depending
on
who
you’re
talking
to
It’s
also
a
role
where
AI’s
strengths
processing
large
amounts
of
information
endless
patience
and
being
available
around
the
clock
could
genuinely
shine
The
challenge
was
turning
a
raw
AI
agent
into
something
that
could
actually
handle
all
of
this
reliably
That
meant
building
plugins
integrations
security
layers
and
an
entire
ecosystem
of
tools
around
it
What
We
Built
The
project
grew
into
something
far
more
comprehensive
than
we
initially
expected
Before
we
go
through
the
individual
capabilities
it’s
worth
understanding
how
this
actually
works
under
the
hood
There’s
a
primary
agent
that
handles
most
of
the
communication
and
big
picture
management
Think
of
it
as
the
main
brain
But
it
doesn’t
work
alone
Each
plugin
we
built
comes
with
its
own
set
of
specialized
sub
agents
dedicated
experts
that
handle
specific
tasks
within
their
domain
The
M365
plugin
for
example
has
a
sub
agent
that’s
an
expert
on
composing
emails
it
knows
our
communication
etiquette
inside
out
another
that
processes
and
organizes
incoming
messages
and
more
The
Micro
Apps
plugin
has
a
builder
agent
that
constructs
apps
using
our
framework
a
project
manager
that
handles
larger
multi
step
tasks
execution
agents
that
the
project
manager
can
spin
up
as
needed
a
researcher
agent
that
knows
all
the
research
tools
available
and
several
others
This
architecture
isn’t
just
for
show
It
solves
real
problems
Each
sub
agent
carries
only
the
context
it
needs
which
helps
with
LLM
context
limitations
A
sub
agent
that
only
needs
to
know
about
email
composition
doesn’t
need
to
be
loaded
up
with
health
monitoring
rules
or
micro
app
schemas
It
also
means
each
sub
agent
can
be
deeply
specialized
carrying
detailed
knowledge
about
its
narrow
domain
without
diluting
the
primary
agent’s
ability
to
coordinate
everything
The
real
value
though
isn’t
in
any
single
agent
or
capability
It’s
in
how
the
primary
agent
combines
everything
on
the
fly
based
on
whatever
the
situation
requires
It
already
has
broad
AI
capabilities
out
of
the
box
and
each
plugin
sub
agent
or
integration
we
add
becomes
another
tool
it
can
reach
for
When
you
ask
the
EA
for
help
it
doesn’t
think
in
terms
of
which
feature
do
I
use
It
pulls
from
its
calendar
access
email
communication
skills
health
data
micro
apps
and
whatever
else
is
relevant
all
at
once
assembling
a
response
or
action
that
fits
the
specific
moment
The
magic
is
in
the
combination
not
the
parts
Building
this
level
of
functionality
wouldn’t
be
realistically
possible
without
this
layered
approach
Some
tasks
need
a
dedicated
expert
agent
Others
need
teams
of
sub
agents
working
together
And
the
primary
agent
needs
to
know
when
to
handle
something
itself
and
when
to
delegate
Getting
that
orchestration
right
has
been
one
of
the
most
interesting
challenges
of
this
project
Here’s
the
big
picture
of
what
we’ve
built
so
far
Microsoft
365
Integration
Every
EA
needs
email
and
calendar
access
We
built
a
proper
M365
plugin
that
gives
OpenClaw
its
own
email
calendar
tasks
and
contacts
plus
carefully
scoped
access
to
shared
accounts
and
resources
It
monitors
my
inbox
group
mailboxes
like
info
and
knows
the
purpose
and
context
of
each
shared
account
We’ll
cover
this
in
detail
in
a
dedicated
post
Communication
Intelligence
The
agent
doesn’t
just
read
and
write
emails
It
knows
how
to
communicate
We
built
a
communication
etiquette
system
that
adjusts
tone
depending
on
the
situation
Talking
to
a
coworker
Professional
but
casual
The
CEO’s
family
member
reaching
out
Warm
and
personal
Group
conversation
with
mixed
participants
It
reads
the
room
and
adapts
If
the
tone
of
the
conversation
shifts
or
new
people
join
it
adjusts
accordingly
Organizational
Memory
One
of
the
weak
points
of
current
AI
is
context
loss
To
handle
this
we
built
clear
processes
for
how
the
EA
organizes
its
mailboxes
and
calendar
Everything
is
categorized
by
status
processed
in
process
needs
processing
so
even
if
context
is
lost
the
agent
can
immediately
pick
up
where
it
left
off
Security
Firewall
An
AI
that
communicates
with
the
outside
world
is
a
target
for
prompt
injection
attacks
This
is
a
real
concern
and
the
security
of
LLMs
isn’t
fully
solved
yet
So
we
teamed
up
with
heySec
and
built
a
firewall
that
analyzes
and
filters
all
external
content
before
it
reaches
the
agent
Today
it’s
fully
functional
More
details
coming
soon
on
heySec’s
channels
Micro
Apps
Sometimes
the
help
you
need
from
an
EA
isn’t
about
emails
or
chat
Sometimes
you
need
it
to
help
you
organize
everything
that’s
happening
around
you
ongoing
projects
things
that
are
constantly
changing
information
coming
in
from
all
directions
actions
that
need
tracking
The
world
around
an
executive
is
chaotic
and
keeping
all
of
that
structured
and
accessible
is
a
job
in
itself
The
hard
part
is
that
these
needs
change
constantly
sometimes
daily
and
there’s
no
time
to
wait
on
development
So
we
built
a
plugin
with
a
companion
web
and
mobile
app
that
lets
you
create
use
and
change
apps
on
the
fly
We
call
it
Micro
Apps
More
on
this
in
a
separate
post
Health
Monitoring
Executive
jobs
are
tough
on
your
health
It’s
easy
to
skip
meals
during
busy
times
ignore
rising
stress
levels
or
push
through
when
your
body
is
telling
you
to
slow
down
We
built
a
companion
app
that
syncs
Apple
Health
data
to
a
central
database
giving
the
EA
access
to
vitals
sleep
patterns
eating
habits
and
workout
data
It
doesn’t
just
report
It
proactively
monitors
trends
and
makes
recommendations
when
they’re
actually
useful
This
deserves
its
own
deep
dive
post
Promise
Detection
The
EA
monitors
all
of
my
communications
and
detects
when
commitments
are
made
like
agreeing
to
meet
someone
at
a
specific
time
If
there’s
no
matching
calendar
event
the
EA
catches
it
and
creates
one
automatically
Morning
Briefings
Every
morning
the
EA
scans
relevant
news
sources
and
social
media
channels
and
sends
a
briefing
about
everything
the
executive
should
know
The
big
unlock
with
LLMs
is
that
there’s
no
language
barrier
It
monitors
sources
in
Chinese
Estonian
Ukrainian
and
more
surfacing
relevant
information
regardless
of
the
original
language
Not
All
Rainbows
and
Unicorns
I’d
be
lying
if
I
said
this
was
smooth
sailing
We’ve
had
many
failures
along
the
way
We
even
had
to
completely
restart
and
reinstall
everything
from
scratch
once
when
the
agent
broke
itself
so
thoroughly
that
fixing
it
wasn’t
worth
the
effort
And
let’s
be
honest
about
where
things
stand
right
now
none
of
these
capabilities
are
perfect
They’re
more
like
MVP
status
Things
work
as
expected
roughly
70
to
80
percent
of
the
time
The
other
20
to
30
percent
Sometimes
that’s
down
to
the
real
limitations
of
current
LLM
technology
Other
times
it’s
simply
the
reality
of
a
project
that’s
still
in
its
early
stages
This
is
roughly
a
one
month
old
system
and
there’s
a
lot
of
maturing
left
to
do
on
our
side
too
The
agent
forgets
things
it
agreed
to
do
It
silently
fails
on
tasks
and
doesn’t
tell
anyone
It
does
the
same
task
differently
on
Tuesday
than
it
did
on
Monday
for
no
apparent
reason
If
you’re
imagining
a
flawless
digital
employee
that’s
not
what
this
is
Not
yet
Context
management
has
been
one
of
the
biggest
challenges
Figuring
out
how
to
give
the
agent
all
the
information
it
needs
without
drowning
it
in
massive
prompts
And
yes
we
once
accidentally
blew
up
the
context
window
so
badly
that
it
burned
roughly
200
a
day
in
tokens
just
trying
to
process
basic
functions
before
immediately
crashing
We’ll
cover
the
challenges
and
lessons
learned
in
a
dedicated
post
because
there’s
a
lot
to
share
there
Where
We
Are
Now
There
is
a
lot
we
have
done
already
and
yet
we
have
not
even
scratched
the
surface
of
what
we
have
planned
and
what
is
possible
The
EA
is
evolving
every
day
and
with
each
iteration
it
becomes
more
capable
more
reliable
and
more
genuinely
useful
But
it’s
important
to
go
into
this
with
the
right
expectations
This
is
not
a
finished
product
It’s
a
very
promising
work
in
progress
built
on
technology
that
has
real
and
fundamental
limitations
today
Over
the
coming
weeks
we’ll
publish
detailed
posts
covering
the
M365
integration
Micro
Apps
health
monitoring
capabilities
and
the
challenges
we’ve
faced
along
the
way
Stay
tuned
this
is
just
the
beginning