YouTube's Shifting Content Policies and Potential Impact
By Kristijan and Alfred the Bot
Watch Source Video
Context
This post is generated from messages in the ‘ai conversations’ channel on Mattermost. The discussion, initiated by ap811crb83fwjrmctib8nb39nw, includes a shared YouTube link and commentary on recent changes to YouTube’s content hour limits. The topic entered the daily queue due to its potential relevance to content creators and platform policy shifts.
Summary
A YouTube video discusses recent changes to content hour limits on the platform. The creator notes a pattern of initial reductions followed by increases, suggesting a potential return to previous limits. This indicates a period of policy flux for YouTube content creators.
Extracted Knowledge and AI Review
[object Object]
AI Research Notes
The source messages provide a brief commentary on a YouTube video discussing content policy changes. While the video link is provided, the actual content of the video is not directly accessible or summarized. The extracted knowledge is based on the user’s interpretation of the video’s topic and the provided messages. Further details from the video itself would enhance the summary and knowledge extraction.
Transcript
It's basically the first self-updating
agent where like other agents update
markdown files or they can like create
skills. They cannot really create the UI
for them to show to the user what's need
to be done. So like this is like a new
paradigm of self-improving,
self-updating agents.
>> Yeah, this agent is much more dynamic in
terms of communication. When you tell
the agent to show you something, it will
show it to you.
>> All right, guys. I'm here with Van, the
creator of Space Agent and the founder
of Agent Zero. And today we have a brand
new product to announce, which is Space
Agent.
>> Hello, David.
>> Let's jump right into it. uh explain
what it is and uh how people can use it.
>> What I wanted to do here was to let the
agent access all of its layers. That's a
common problem with other agents that
you have an agent running on a VPS
somewhere in Python or NodeJS and then
you communicate to it through WhatsApp
or Telegram. And there are multiple
layers where the agent works and usually
it can only affect one or maybe two of
those. Like it can install something on
the back end, it can do something there,
but it cannot really change the way it
shows you something in WhatsApp because
it's limited by the interface of
WhatsApp. It can send you a picture or
it can write you a message, but that's
about it, right?
>> So the UI is very limited for the user.
>> Yeah. And the same goes when you use a
web UI. Like for example, agent zero has
a very rich web UI, but still if the
agent wanted to do something special in
the web UI, it can either generate an
image on the back end and send it to the
front end or it needs to modify itself
on the back end level and then tell you
to reload the page or something. Even
agents that are accessible from the
browser are still limited to the layer
where they actually live.
>> So I guess let's jump straight into
space agent.
>> Yeah. And that's the big difference of
space agent because space agent is
running client side on the front end in
the JavaScript runtime. So the agent can
actually mutate the page that it's
displayed on. And uh how do we use it?
We use it in what we call spaces mostly.
>> So basically, sorry to interrupt, but
it's basically the first self updating
markdown files or they create skills.
They cannot really create the UI for
them to show to the user what need to be
done. So this is like a new paradigm of
self-improving, self-updating agents.
show it to you. Like uh we have a few
pre-built examples just uh to get a
picture like prices, charts, news and
everything or daily dashboard. It can
even render games in the browser and
play them. So whatever you tell it to
do, it has this system of spaces and
widgets where it can render anything on
demand if you tell it to do so.
>> All right. So I guess uh let's start
with an empty space how most people will
probably start.
>> So uh this is an empty space. This is
what the user is presented when the user
first enters a space agent and maybe we
should have started with the biggest
benefit of uh an agent running inside a
browser and that is that you can
actually run the agent in a browser.
>> Yeah. No setup super easy.
>> Yeah. If you want to give space agent a
try you can see our GitHub. There is a
big button try live now. That will take
you to our website space-agent.ai AI
where just like that yeah everything is
open source and free of course where you
can simply
>> of course you know people people don't
know nowadays like big companies are
launching like manos and you know
perplexity computer are completely
closed source so yeah space agent is not
only open source but you can try it for
free
>> yeah and with just two clicks you get a
guest account that is temporary and you
can try space agent for free you just
set your API key for the LLM provider
you want to use
>> right so let's just tell it something
>> I can show you two ways the agent
communicates I can simply ask
what is the weather in Prague and it
should respond
in chat and then I can tell it
show it to me in a widget. So I'm now
using the minimized mode of the chat. So
I am now seeing just the answers by the
agent but I can expand to the full mode
if I want to see the history. And the
first time the agent simply responded
because I simply asked it what is the
weather in Prague? And when I told it
show it to me, it generated a widget
based on the weather.
>> And just for context, which model are
you running right now?
>> It's Opus.
>> Okay. And so all of this is custom
JavaScript, right?
>> Yeah. I can I can show you right now how
the agent actually works because that is
quite interesting. This is the raw
history of uh the communication. This is
how the agent can actually see it. So
there is a user message, what's the
weather in Prague? And this is the raw
LLM response. There is no formatting, no
JSON, no tool calling. This is the text
that the agent generates. It first
generates the response for me fetching
procra weather whether now this is what
shows up in the chat bubble or in the
conversation history and then it uses
this special token and everything after
that the javascript gets executed
automatically in the browser.
>> This makes it also like extremely token
efficient right? Uh yeah, for example,
the weather check including the response
including the first response was 97
tokens and then it gets the response in
a YAML format like this which is also
token efficient and it responds to me
simply by not using the JavaScript
token. This ends the conversation loop.
So the agent responds in plain text just
like CH GPT. No special tool to respond,
right? No special formatting, additional
fields. If the agent simply needs to
respond, it responds and there is not a
single extra token in the response. If
it needs to use JavaScript, it uses
this. These are two tokens. Underscores
are one token. JavaScript is another
token and then followed by the
JavaScript. Again, no need for JSON
escaping nothing that would add
additional tokens. It's as efficient as
it can be. And we can see that to
generate the widget, it only took like
280 tokens.
>> Yeah. I mean, in the age where like the
cutting edge models are becoming more
and more expensive, we've seen this with
obviously Opus, but now even GBD 5.5 Pro
is like $180 per million output tokens,
I think people are going to start to
look into tokconomics a bit more and you
know which harnesses, which agents allow
you to run the best models most
efficiently because people don't want to
be spending thousands of dollars per
month running uh inference.
>> Yeah. Also, the system prompt here is
very interesting. I didn't write a
single line of it. I created the first
outline of the prompt and then I set up
an automated research in codeex to
iterate on the prompt and always create
like three new versions. One that would
be conservative with just a few changes,
one that would be mediumsiz changes and
one that would be completely wild and it
created a lot of full test fits to test
it. I also then tested it manually. I
told it it fails in these scenarios.
Create new test cases for these
scenarios. Include them into the
harness. And for a few days it was
iterating like this. And I don't know
this is like uh version number 250. And
it kept optimizing and optimizing to be
token efficient and reliable in our
cases. And
>> all right. So let's I guess show a few
more things that space agent can do.
>> We can build a full example. We can
build a full use case. But I would like
to start with the things I was doing
today. Just a
>> sure
>> just a quick showcase. So I started with
a notes app. I wanted to see if you
create multiple widgets on one space how
they can cooperate together. So I have
one here for the list. By the way, uh
the space is very dynamic. You can
resize everything, move everything,
rearrange. The agent can also do it for
you. So these can be this grid is
actually almost infinite. So the agent
can create huge dashboards or huge like
data views for you.
>> So the implications for people who don't
get it is that you can design the UI you
want for any type of use case from
scratch. Like you don't have to code an
app from scratch and then host the app
on a server. space agent runs in the
browser and all of this is just a few
seconds of JavaScript.
>> The way I see the future of operating
systems is that there would be almost no
apps and built-in interfaces because if
you can tell the agent like uh check my
email and show me the email ordered by I
don't know priority or something and it
can simply draw a window for you with
your email list like why do you need
buttons to sort it right? Why do you
need buttons to move something, remove
something, reply to something? If you
can tell your agent and it can rewrite
the screen on the fly. Okay, so uh the
first example was a notes app and it
really built a fine notes app. You can
manage folders, rename them, you can
edit, you can edit the notes visually,
you can turn into a markdown view if you
need. It supports copy pasting, images,
attachments, etc. So yeah, it's a fully
working notes app by my standards. And
another benefit of local browser is that
the data stays yours, right? Like uh you
don't have to send it somewhere.
Obviously, if you're using the free
version, it's hosted the back end is
hosted. So, you know, you can use the
open source repo or the native app. But
that's another benefit of having
everything in the browser.
>> Yeah. Yeah. I can quickly explain how it
works. Browser on its own cannot manage
files on uh on the host operating
system. That is a security limitation of
a browser. So, we have a very thin
backend layer in Node.js JS that manages
uh user permissions, user accounts and
the file storage. And if you download
the native app, all of this is bundled
into the single app. So there is no
communication to any of our servers or
anything. The backend layer as well as
the front end layer, it's all bundled
into one application. If you host it
yourself, you host it somewhere either
on your local machine or on a VPS and
you use the browser to connect to it. So
then they can both be running at the
same machine or you can have the back
end running somewhere in a VPS. This
also gives you uh the option to have
multiple users because space agent since
the beginning is optimized for many
users running on the same server and it
also includes user and group permissions
and management and shared functionality
among user groups etc. Uh yeah and the
third way is our demo site. Then the
back end is on our server. I don't
recommend anyone using it for anything
they want to persist because it's a demo
server. Files are going to be deleted
sooner or later. So my my best tip is
download the native app and everything
stays local. Everything is on your
machine. Another thing I tried today was
surveillance dashboard. I picked some
random public IP cameras from it seems
that they are all in the United States.
But uh if you have cameras at your home
or any property or anything that you
want to monitor, you can simply create a
dashboard like this just by telling the
agent. And
>> and by the way, just for context, how
long did this take to build, right? Cuz
people might assume that this is long or
you know,
>> well, this was fast. This was fast. I I
spent quite a few minutes by by picking
the right cameras that actually show
something because uh the agent picked
some cameras randomly that seemed static
at first, but like uh the thing itself
was generated in like I don't know
minute or two.
>> Yeah,
>> the notes app took a bit longer because
I had more instructions and we did more
edits. I wanted the renaming to be more
seamless and I wanted uh I wanted the
what you see is what you get editor to
be the default, not the markdown. So we
did quite a few edits. So this took me
like 10 minutes maybe. And uh these
dashboards they they bring me to what
space agent really excels at and that is
orchestrating other things like because
the UI can be so dynamic. This is the
this is the perfect harness for
monitoring other systems or controlling
other systems. Like if you have 10 other
agents running somewhere and you can
connect them all in one dashboard and
have another agent above them that can
communicate to them for you. Like this
can save you so much time. And here I
connected space agent to my agent zero
instance running on my on my local
machine here just like space agent. And
I did two things here. I told the agent
to create a new chat interface that will
use the agent zero API to communicate to
it. So if I send hi here, it will wait
for agent zero to respond in the docker
container and send the message back to
me. And this actually is an embedded
browser window. So this is the full
agent zero web UI. We don't use any API
or any shortcut here. This is a full
browser and the agent can still control
it as a browser. It's actually really
good at at controlling browsers. So I
can say uh check the settings of agent
zero if there's an update.
>> So it's also perhaps the fastest browser
use right out there.
>> Yeah, I was actually surprised how well
and how how fast this works because uh
when I develop something, I always start
with the minimal version with a very
basic what it needs to run and then I
see where it fails and I start adding
things into it to to compensate. And
usually the first prototype of
everything is very fast, right? because
there's nothing inside. Everything is
very simple and it works fast. But then
you figure out it fails here and it
fails here and it needs a memory etc.
And you start adding things and
ultimately you are inevitably going to
slow it down. But here to my very
surprise I didn't need to add basically
anything. It simply worked that well out
of the box. The way this works is that
we transcribe the page for the agent
into a format that looks like this. So
the agent doesn't see the HTML of the
page. It doesn't see the full DOM but
everything is transcribed into
references like button and its number
text here is an error button 51. So it
can see that there is a cancel button
with a number 51 and that is styled to
red color as error. It can see input
fields, it can see sliders, anything
interactive. It can see all the texts on
the page. And so when it wants to click
a button, it simply sends a command like
click button 25 and it gets a new
transcription of the page. It gets
information about what has changed. We
can probably see it here. Yeah, this is
how the agent operates, right? 19 tokens
just telling me opening self update now
space browser click browser number one
button number 47. That's it. And it gets
response like this.
>> You optimized this or was it also
another auto research?
>> Well, partly both. Partly both. But uh I
did this mostly myself. So I found a
library on the internet that transcribes
HTML into markdown and I edited it
heavily with the help of AI to produce
this format where every interactive
element gets a reference number while
text text just stays text. And then we
kept iterating and uh we had to do a lot
of optimizations and solve a lot of edge
cases because it might not seem uh like
a difficult technology the web but
websites are super hard to crawl. You
have so many different elements nested
like uh iframes and shadow doms things
that are like naturally closed. Some of
them like like the shadowdom is built
for the sole purpose of like prevent
scraping. So we even had to inject some
hacks into the browser renderer itself
so that it automatically opens
everything on the website so it's
scrapable. So yeah it was a lot of work
partly AI partly me but in the end it
works like a charm. And uh as you can
see we are now at 13.6,000 tokens. So we
only added uh what like two more
thousand tokens.
>> Oh two.
>> Yeah. since since the beginning four but
previously we did something with the
space and uh that is because another
thing we use we don't keep we don't keep
things like this in the history because
like once the state of the page is gone
in the past then we don't need it
anymore
>> confusing
>> yeah it could be confusing and it it
would eat up a lot of tokens right it's
uh what is it like uh 2,000 tokens and
that's why we use this transient space
that means the context that changes
often we always put it to the very end
of the prompt after the last caching
breakpoint. So it doesn't get cached and
it can be replaced on every turn of the
conversation. So when the agent is
editing widgets, we always load the last
state of the source code of the widget
and we put it to the transient. So the
agent can always see the source code of
the widget it works with, but it doesn't
stay in the history consuming tokens
with every other turn because this is
exactly what compounds, right? It's not
a problem if you like load 2,000 tokens
to show the agent the page. But if you
keep it the history, you have added
2,000 tokens forever. And if the agent
clicks like five pages, you have added
10,000 tokens to every turn of the
conversation.
>> Yeah.
>> And if you start removing, then you
break caching. So that's another
problem. If you
>> Yeah. If you touch something in the
history, you invalidate the cash and you
start paying more again. So th this way
we keep the prices of we keep the token
spending as low as possible and maintain
the best efficiency and long-lasting
contact windows.
>> I think we should do some more like life
changes to people really need to see
like how easy it is to update stuff you
know create the do custom UI elements
custom front end but also like change
some of the built-in stuff about the
page or about the chat. So, I guess
let's let's uh either start from scratch
or you can start with one of the
pre-built ones and modify it. Up to you.
>> Yeah, let's do it. Maybe maybe we can do
the research one because that that is
also quite interesting. I made this
today as well and I wanted to see if the
agent can create a UI that would be
connected directly back to the agent so
that the UI would be able to communicate
to the agent as well as the agent to the
UI. And I created this research harness
and I already tested it on agent zero
and GPD GPD 5.5. And what space agent
did here was to create a research input
and research output widgets and it
created some special instructions for
the space. That's another thing. Every
space can have custom instructions for
the space. So if it's special in some
way, you can instruct the agent in here.
And let's do a quick test here uh for
example on clude mythos. So I can create
mythos and uh describe what claude
mythos is and how is it different and uh
I can clear the chat to to start with
fresh context and if I click if I click
start research the agent actually
receives the message from the UI and it
starts updating I'm going to minimize
the browser for now and it starts
updating research template here on every
step it will update the planning source
gathering notes summary and it creates a
markup file with the research based on
the template and instructions. Right now
it is already using browser. It has
navigated to some anthropic article on
BBC. It will probably check one or two
more websites.
>> So for any type of workflow or task, you
can create the UI that you want for that
rather than just being limited to, you
know, WhatsApp or terminal or a web UI
that's predefined.
>> All right. Uh I'm going to minimize
this. Uh and yeah, we we already have
some progress here. Okay. We don't need
to wait for the full thing. The agent
will keep updating the research file,
but it already looks good. It's an
anthropic AI model, especially a cyber
security focused model. Restricted
release dual use risk profile. Okay, it
seems to know and it's done. It seems to
know what it's doing. Okay, what do we
change? How do we modify it?
>> Maybe add some more formatting or colors
into the research output.
>> Okay, maybe we can convert it to PDF or
something as well.
>> Sure. Yeah, let's do that.
>> Add export to PDF button. that will
convert it to a print out something like
this and let's see what it does.
>> So there's a three different stages of
the chat right like this is the middle
one then it's the expanded one and so on
the side one.
>> Yes. This is just if you want to hide
the chat.
>> I I usually use the compact one because
there's usually a lot going on on the
screen. So I don't want the full history
to obstruct. I am mostly interested what
the agent has to say now. All right. And
uh yeah we have some more formatting.
Yeah, we have tables, links, and what
does the PDF do? All right, it turns it
into a printed out.
>> Yeah, but the it seems like that's my
native print dialogue. It probably won't
show me, but I can probably save it as a
PDF here. All right, I would change the
formatting. I don't really like the
font, but yeah, it's a PDF with the
research.
>> And I think the main thing is to again
highlight is that it added the feature
to export as PDF. The space doesn't come
with that.
>> Yeah, I take it for granted. Yeah, you
take it for granted because you spent,
you know, so much time on this over the
last 3, four weeks. But like these are
not like pre-built tools. It's
completely different than other agents,
you know. None of this is pre-built UI
components. All of this is from scratch.
So your space can be like completely
unique.
>> Yeah, we can actually see it here. This
is the code that made it happen. Uh no,
this is read widget. This one, this is
the code the agent used to add the
download PDF and to add the formatting
to it. Yeah. And uh the great thing
about it is uh the persistence. When I
leave and come back, it's still here.
When I refresh the page, it's still
here. Normally, if the agent was editing
the DOM of the HTML page itself, it
would be gone when you refresh the page.
But the way these widgets work is that
the agent doesn't create the widget
itself. It creates a function that then
creates the widget. And so we store the
function that is capable of recreating
the widget. And then we can like
recreate it with this button or by
reloading the page at any time and it is
exactly the same as it was.
>> I think let's let's do another one from
scratch and let's just try to put a
bunch of different UI elements so people
can really see. So maybe start like by
adding a canban board.
>> Okay, let's do a canban board. Uh
anything specific or do we just uh do an
example?
>> Make it like in a style of um Trello and
very colorful.
>> Okay, Trello, colorful. We will be
adding more features. So keep in mind to
make it extensible. All right, let's
see. This might take a minute. I believe
this will be a few hundred lines of
code,
>> but you know, people can use like faster
models than Opus 4.7.
>> Yeah, definitely. When I started
developing this, I used the GPT 5.4
mini. It's not as smart. It wasn't
definitely as reliable as Cloud Sonet or
Claude Opus, but it has like near
instant responses. Yeah. I just wanted
to say that like if you tell 5.4 mini
high, you will get the hello response in
like I don't know 300 milliseconds or
something like that.
>> Yeah. But what you found with the
testing and the eval is that actually
Gemma 4 was better, right?
>> Yeah, definitely. It was at least on
par,
>> which is pretty crazy because Gemma 4 is
available locally.
>> Yeah. Okay. We have some canban board
here. Can we drag it? No, we can rename
it. Okay, because these are tickets.
Yeah, I tried to drag a column.
>> Nice.
>> Okay.
>> Okay. So now maybe add something
completely different like a stock graph
chart.
>> Okay. All right. Stock price chart for
Nvidia. I What is it? Apple and
>> Google.
>> And Google is what is Alphabet?
Something like that.
>> Oh yeah, I think Alphabet.
>> Okay. Uh Alphabet. Yeah, Google. Okay. I
wonder where it takes the prices from
because most APIs most APIs are going to
be limited. I think Yahoo Finance works
well. So, we'll see. Agent Zero usually
goes for Yahoo Finance in Python.
>> I think this is another like capture
concept of like capture of the was in
the training data because then future
agents will get trained on that more and
more.
>> And then it's just like it's like the
tech stack, you know, always next and
superbase.
>> Okay. It seems like it worked. By the
way, this is uh this is one of the
benefits of running the agent in your
browser because it runs the code in your
browser, not in a data center in a VPS
and so you don't get blocked by APIs for
being a robot.
>> Yeah, that's a huge disadvantage when
like agents try to do multi-step tasks
from a VPS.
>> a lot of websites block just these IP
addresses that come from a data center.
>> Yeah, exactly. Okay. Uh
>> okay, let's do something completely
different. Let's do a snake game. All
right.
>> So, I guess what are the main
limitations of Space Agent? Like what
would you not use it for?
>> I wouldn't use it for anything that
requires operating system access for
like installing Linux packages, right?
If it's something low-level you need to
do, if you need it to it cannot run a
server, for example, if you need to run
a server to test your node application
or something like that, you probably
want to go with agent zero because that
can do all of that for you. It has its
own Linux system. What I wouldn't use it
for is uh like background jobs because
we don't have these yet right now
because it works on the front end. It
requires the front end to be running. So
you cannot turn off your computer and
let it do something in the background.
Even if you host it on a VPS, the agent
still runs and executes on the front
end. So maybe we will figure out a way
to do background jobs in the future.
Maybe we will not do it because there's
already a lot of agents that can do it,
right? Maybe we don't need to replicate
everything. We will see. We will see
what the people want. So,
>> so that's useful for the people watching
this is like go ahead, try it and
comment what what do you like about it,
how you use it and you know we'll see
like what sticks.
>> Yeah, definitely. Definitely. I think we
currently know like uh 5% of its
potential what it can do like we are
doing like random things here and I do
random things for the last four weeks
since I started developing it. But apart
from the agent zero example or the
research example, I don't do much useful
stuff here because I simply don't yet
know.
>> It's a new paradigm.
>> Yeah, it's a completely new thing and I
still need to wrap my head around it. I
can imagine that it's even more
difficult for for others. Okay. Uh it
seems like a broken snake game because I
only see food. Yeah, I don't see any
food. There's And it's also capturing
And it's also capturing my input which
is wrong. So I'm going to close this
one. There was no tail, no food, and
it's capturing input keys even when not
focused. Focused. Do it again.
>> So these spaces are persistent, right?
So people can have a separate space for
their work, for messing around, for
different use.
>> Basically for any single use case like
you don't even need to group your like
life categories into spaces. You can
have hundreds of spaces. They they don't
cost you anything. It's just a folder on
a disk. And all of these are stored all
of these widgets and everything are
stored in text files. So it's it's just
a few kilobytes per space. Okay. Let's
see. Yeah. Yeah. And I can even use my
keyboard. That's fine.
>> Nice. Maybe try the music use case
something a mini synth beat.
>> Yeah. I I already did it today. Uh where
is it? Step sequencer. Uh
>> nice. So we have a step sequencer where
where you can add different instruments
at different beats. You have a control
board for the sound and you have a
guitar free play where where you can jam
with your sequencer.
>> So how long did this take to develop
roughly?
>> Wow. I think uh maybe 20 minutes. I
started with the sequencer, then I added
the knobs and uh then I added the
guitar. The sequencer was fast. That was
one shot. So that took probably like I
don't know one or two minutes to make.
Then I started adding features like uh
saving and loading and ch changing the
length of the tab etc. And then I wanted
to add something nice and visual like
these knobs. And then I experimented
with the guitar so that you could strum
chords.
>> Maybe try telling it to add to a piano
roll.
>> Well, let's see.
>> I tested something similar with Opus 4.6
and it was able to do it in one shot.
>> I have no idea what it's going to do
now. whether it's going to create
another widget or or maybe just add
something to the sequencer. Let's see.
>> So, this is probably also one of the
easiest ways for like people who are not
as deep in AI to feel the power of AI,
right? Because like people watching my
channel and you know, Agent Zero
channel, they're like in the top 1% of
interested people. They're not a free
chat GPT user. So, a lot of these people
still don't know the power of these
coding agents. Oh, there is it. Nice.
Okay. Some of these are misaligned in
the higher octaves, but you know, that's
fixable. Look at the graphic.
>> Yeah. Uh
>> oh. Okay.
>> What do we have? We have
>> No, now it's fixed.
>> One, two, three octaves.
>> Yeah, expanding it. Expanding fixed it.
>> That's strange. Okay.
>> So, like people could take their friends
and family who are not technical and not
AI focused and really have them feel the
power of what's possible by just typing
English into space agent.
>> Yeah, it's like an entry drug for new AI
people. Yeah, definitely. Like uh you
don't need to install anything. Uh you
don't need to understand the terminal
dependencies. You don't need to know how
how AI works. What you are going to need
is an API key
or any other service. Yeah.
>> Yeah. So, space agent.AI and then uh
just API key so you can run inference or
if you have a powerful computer you can
do the local um local inference.
>> You can do the local inference. We also
have a special panel for it here where
you can load the model and test it here
in the chat. I'm not sure is it going to
download or simply Yeah, it's
downloading. Okay, I'm going to stop it
because it's it's 10 gigs.
>> once it's downloaded, then it's loaded
into the memory fairly quickly. But
yeah, you are going to need a beefy GPU.
>> So, any model from hugging face like
that fits
>> any model, any model of the NNX format
from hugging face. We have a button
compatible models here and it takes you
to a community repository. There's
like,00 models converted to this format.
Okay. But the only one relevant right
now is probably Jim 4
>> because you still need a good model to
be able to, you know, write the
JavaScript and understand the system
prop.
>> Yeah. Yeah. Like uh agentic systems are
not simple. It's something completely
different to running a model in Olama
and talking to it.
>> Okay. So I guess uh let's talk a bit
more like u the theory and the
philosophy behind it, right? So how did
you get the idea to make space agent?
>> Oh wow. uh where to start? Uh I am
always carrying uh a lot of thoughts and
ideas in my head and over time some of
them connect together and start uh some
start to seem like uh efficient and
cooperative and uh I wanted to achieve a
few things like uh I wanted to make
something like agent zero that would be
easier for people to get into and
understand. I also wanted, like I said,
an agent that would be able to fully
control itself, not just the back end
layer, but to fully access everything. I
didn't talk about it much, but it's not
just about spaces. The agent can
actually modify itself completely. The
full system is built on modules, and the
agent can develop its own modules on the
fly. And uh you can do it per user. So I
can create new modules for myself for
like uh running the local inference is a
module for example or the file browser
is another module and I can create
thousands of modules myself they will be
stored in my in my user folder and they
will not affect other users of the
system if it's a multi-user system and
uh we can do the same per user group or
globally in the system. So it's not just
about spaces. It's a full development
environment that can extend itself and
uh also this is something that's
difficult to do for example in agent
zero. Agent zero can extend itself. It
has a plug-in system and everything but
it still runs on a back end in Python
and that comes with some caveats like
installing dependencies and uh solving
dependency conflicts and uh a lot of
stuff like that. So this runs completely
on the client side. So it doesn't put
any additional stress on the server.
That's why for example we already have
hundreds or maybe maybe even thousands
of users now on our demo side and we
have like 2% CPU usage and 6% memory
usage because the real work happens on
the client side and not on the back end.
>> Like when you got the idea, how did you
decide on like browser being the right
thing the right paradigm? Yeah, that's
uh uh that's a great question because I
knew from the start that if it was to be
simple for the user, it needs to be a
multiplatform and run without
installation and uh then it was
basically decided because there is no
other platform than browser that can run
without installation on all operating
systems, right? You have different uh
window management uh different rendering
on all of the operating systems and uh
browser is the only platform that has
exactly the same runtime in JavaScript
on all the platforms including mobile
the same rendering uh unified
standardized o over the years of HTML
CSS and JavaScript development. So yeah,
I I think I knew from day one that uh if
I am about to build this, it needs to be
in a browser. And uh then I started uh
solving problems because wow there were
a lot of problems like browsers are
great because uh the cross compatibility
is awesome and uh they are also
sandboxes of their own because the
internet is a very dangerous space. So a
lot of protection of the user comes from
the browser itself. It doesn't let the
website touch your files and it doesn't
let you steal data from other apps etc.
So this is great as well but this comes
with a ton of limitations like cross
origin problems. You cannot display
other websites in an iframe inside
another page for example. Some pages
like Wikipedia will let you to display
Wikipedia inside another page but
Google, YouTube and basically all of the
other modern websites will block you. So
yeah or I started doing a lot of
workarounds to fix this but uh yeah it
worked in the end. The browser works
really well in the native app because
there we can use electron features to
mitigate a lot of these security
boundaries. We can we can also use the
backend layer in NodeJS we have to
mitigate course we can proxy it through
the backend layer and remove course
headers and yep we are solving one issue
at a time we got here. So I guess how
did you manage to develop it so quickly?
Like did you use AI tools and if so like
what's your workflow?
>> Yeah, I didn't write a single line of
code here. I I used codeex for
everything. So codeex built the entire
codebase of this. How I started is I
created a agents.mmd hierarchy and
documentation framework for codecs.
There is a root agent.mmd file that the
agent always loads and the first the
agent sees his documentation first.
Documentation is the most important part
of this project because the problem with
AI coding is that it cannot hold the
full scope of the project in the context
window. Right? So it the bigger your
codebase is the more the agent starts to
do redundant things and writing new
things from scratch or overriding like
previous settings etc. So this whole AI
workflow starts by the agent documenting
everything in agents.mmd files on all of
the layers of the system.
>> All levels or the main folders only
>> all levels basically anything that is
being developed is at the same time
being documented in an agents.mmd file.
So when I tell the agent like uh go into
the file browser that we have in space
agent and change something there there
is an agents.mmd file in the f file
browser module that the agent can read
and it can immediately see how does the
file browser work what are the core
principles why does it work like this
what not to do etc
>> so people should just actually use this
approach to develop right because in the
future it's much more important for a
codebase to be optimized for agents
>> yeah definitely like uh
>> so I just make it clear that this is not
only for space agent. This is an
approach that people should adopt going
forward is that like it's the
documentation like people shouldn't have
any tokens in their head. Any unspoken
preferences, nothing like that shouldn't
be in their head. Everything needs to be
in markdown files in the repo.
>> Yeah, unfortunately we are not there
yet. I still had like hundreds of
instances where I needed to correct the
agent when I saw it was making a bad
decision. And uh even after everything
was done, I still find ways to optimize.
So it's not yet perfect, but it's much
better than it was a year or two ago.
And it's definitely much much better
when you use an approach like this where
the agent has documentation for
everything. And if it needs to change
something, it first checks the
documentation and knows why does it work
this way. So it doesn't repeat the same
mistakes again and again.
>> And we're accelerating faster and
faster. Like in the last 24 hours, we
got GBD 5.5 and DeepSc V4. GBD 5.5 is
significantly better than 5.4 at long
context. So I think a lot of these
issues are going to be greatly reduced
in 3 to 6 months.
>> Yeah, it needs to that's the only way
forward. When I started developing agent
zero two two years ago, something like
that it took me like 3 months of of
intensive development to release the
first version which was CLI only. It had
very limited powers and uh all of the
code in Agent Zero's core is handwritten
up to this day. I made space agent in
four weeks, something like that. 25
days.
>> MVP was faster. It was like two weeks.
>> Uh yeah, but the but the MVP was just a
single page with a chat changing
something on the web. It didn't have
spaces. It didn't have the backend
infrastructure. It didn't have nothing.
Uh
>> and it has like way more features than
what agent zero launched with. So yeah,
the and I did it uh I did it in one
person. So the acceleration is clearly
there. If I were to write Space Agent
manually, it would probably take me like
a year, maybe more. Maybe more.
>> So, at least 12 to 20x speed up.
>> Yeah, definitely. Definitely. Uh I I
still don't think
>> Not to mention the system pro by the
way, the system testing manually. That
would be that would be decades, you
know, human time.
>> Yeah. Yeah. Definitely. Uh I still don't
think coding is dead. I think I think
coding will be one of the most important
skills to have in the future because we
are the last generation of programmers
that did actual manual coding, right?
And I can immediately spot bad decisions
by the AI. I can immediately spot
inefficiencies and if it takes the wrong
path, I can immediately tell it, no, you
need to do it this way to make it safe
or to make it scalable or whatever. And
like I said, I did this hundreds of
times during this development. I always
give it a task and and then I watch what
it's doing. I have like six codeex CLI
windows open and I always quickly check
what each one of them is doing and I I
am simply looking for mistakes. I don't
do anything else than I try to spot
inefficiencies and mistakes.
>> So I guess why Codex over cloud code or
something else.
>> Oh uh it might be a personal it might be
a personal preference. I tried both and
I wasn't happy with cloud code. I'm not
I'm not saying it's cloud code's fault.
Maybe maybe it's a skill issue. But what
I figured out very early is that codeex
is much better at exactly this following
like hierarchy of agents.mmd files and
updating them consistently and and most
importantly following the instructions
inside. When I tried with cloth code, it
often started doing fancy things and
then forgot to update the documentation.
And like I remember one instance when
when cloud code was working for like 2
hours and like 20 iterations on fixing a
CSS on a button like alignment of a
button on the web page and it always
told me it's done now it's fixed and I
refreshed the page and told it like no
it's not done it's still the same
>> and you probably had to like sell a
liver to enthropic right in the
meantime.
>> Well I think I did this on the $20 plan
because I was just testing at the time I
used the $200 plan with codeex which is
unlimited. That's fine.
>> Yeah, that's crazy.
>> But uh yeah,
>> I think the delta is massive. Like
OpenAI now launched a $100 max plan and
I think the delta between that and the
cloth $100 plan is like unheard of. On
the cloud $100 plan, you can hit the
limits in a day of intense coding if you
want.
>> Like if you're running multiple cloud
codes at the same time with Opus 4.7
with 1 million context window and open
just gives you way more inference for
the same cost. And I agree like my
experience matches your experience but
like I like cloth for explaining and
like it's easier to talk to and maybe
like start a project and like kind of
interview you for the ideas but as soon
as any real work is getting done and
like it requires complex changes, big
refactors or some serious bugs, then CEX
is just way better.
>> Yeah, Codex is not perfect. Sometimes I
get mad but uh yeah, I have to admit
it's it's very very good. and uh for for
$200 a month uh you are getting way way
more value.
>> Let's clarify two more things. First,
how should people think about agent zero
and space agent? Like is there a
relationship between these two products?
Are they two separate products?
>> Uh they are two separate products by the
same development team. We will naturally
be working on more integrations etc. But
both of these are generic and dynamic
enough so that uh they can integrate
with anything. So they don't need any
special link between these two. Uh they
are very different products for very
different use cases. Not necessarily
different users but different use cases.
I believe most people that use agent
zero will use space agent simultaneously
for different tasks because space agent
is more dynamic lightweight. It's more
close to the user. It is way more
cooperative than agent zero. Agent zero
is instructed to run in the background
and not bother the user with any
questions. Like if you tell it to do
something, it will continue until it's
done, right? It will not stop and ask
you for something because it runs in a
Docker container in the back end and if
it stops to ask you a question, maybe
you never respond and and then what? So
space agent knows that it runs with the
user on the front end. So if it hits a
capture on the internet or something, it
will simply tell you like solve the
capture for me. I cannot do it. Right?
So you click the capture or you do the
login or something. Yeah, that's one
thing we we probably didn't show, but
the the browser is completely
interactive. So if I open the browser
and
>> that's an important thing to show.
>> Go to google.com the agent can navigate
it. But uh I can do the same, right? So
we can cooperate on the same page.
>> Okay, one last thing I would like to
show is from scratch setup. How maybe we
can do it anonymous browser, I don't
know. But like for people if they go to
space-agent.ai
I link below how does it look like and
where they need to put the API key.
>> So you can start either on the repo with
the try live now button or space-
aent.ai. There is this guest account.
Continue and that's it. And it's one of
the first buttons you're going to see
set LLM API key. And it defaults to open
router because open router is a great
service. It gives you access to open
AAI, Anthropic, Google, all of the
models. You don't need to have multiple
subscriptions. uh you just pay for the
credits you actually use. And here's the
field for the API key. So I'm going to
go to open router AI. Here I'm already
logged in. So I'll go to API keys. I
think it's in the preferences. And this
creates an API key on open router. I can
then put it here and it should work
right away. So Sonet is very proactive.
>> Yeah, it's interesting how the different
different models have different
personality.
>> Yeah. But by the way, uh the Wow.
>> Damn, that's actually good.
>> Okay. I didn't expect that. Uh actually
the first space uh that is created for
new users called Big Bang. It has these
instructions. This is a brand new user
and this is their first experience like
be more tolerant and show them something
impressive etc. But Sonet really takes
it to the next level and starts showing
off.
>> Yeah. And Sonet is a good balance
between cost and performance right now.
>> Yeah. Yeah.
>> We'll see if it releases Sonet 4.7 or
Sonet 5 right away. But uh yeah, we were
using Opus 4.7 throughout this video.
anything that's like good, you know,
either cutting edge or one step below
should be good. Try not to using like
mini models or flash models and stuff
like that.
>> Yeah. Well, most people will still use
free models, but uh yeah, the that's the
way it is now. They will not have the
best experience, but that's to be
expected. Another big feature uh that I
implemented into space agent that is
quite unique to agents is the time
travel feature. We create every user
directory and every every group
directory as a standalone git repository
which automatically tracks changes that
you make. You create new spaces, you
change the settings, uh whatever you do,
it is automatically tracked in the git
repo on the disk and this allows you to
travel back in time. Like if I want to
go two hours back in time, I can simply
do this and it will undo any changes
made in the last two hours. I now have
less spaces here and I can travel also
back into the present just like that or
revert individual changes. This is quite
unique to AI agents because normally if
you break something with an AI agent you
would use another agent or AI assistant
to fix it. Right?
>> Here if you break something you simply
go back in time and undo it. Another big
thing is that we have this admin mode
which if you break something completely
if you do a change that completely
breaks the rendering of the of the full
website that it doesn't even open the
time travel you still can fix it by
going to the admin mode. Admin mode
opens in a split view like this where on
the left there is a persistent admin
interface which is part of the firmware
of the framework. So this is not
changing. This is fixed. And on the
right side you can see the standard
space agent. And from here I can talk to
the agent and let it fix the framework.
I can go into files. I can use the time
travel from here in the admin and I can
manage my installed modules from here.
So even if you break something
completely that the UI doesn't even
start, you still have a way to fix it.
Yeah, that's the danger I guess of the
space agent like having the full
JavaScript is that sometimes it can go
too beyond and you know mess mess up
text input or side loading or whatever.
You can use the admin agent to fix
itself.
>> Yeah, exactly. Actually, any agent can
break itself even agent zero if it
uninstalls a Python dependency or
something critical like that it may
break itself completely and then it
requires some manual work to be fixed.
>> Yeah. And that's that's where beginners
get stuck on the debugging, you know,
>> having to use something else to take
screenshots and, you know, figure out
what is wrong.
>> Yeah, that's the beauty of a space agent
that you can fix it with a single click.
Even if you have the standalone
application or even if you run it in the
cloud or on the demo side, whenever you
open space agent in a new window or a
new tab, you are always greeted with
enter space or enter the admin mode. So
these pages are static. They are always
there waiting for you to go into admin
and fix the framework. All right. So I
guess where should people go to the
GitHub repo or straight to the website?
>> Well, uh they are they are
interconnected. So they can go straight
to the website. The website doesn't have
any additional information. All of the
information is in the GitHub repo. If
you go to the website space-agent.ai,
you can click the GitHub button here or
you can join our Discord X account or
the agent zero website. Here you can
also download the native app or see the
guide how to host it yourself. But uh
exactly the same information you will
see in the GitHub repo. Like the easiest
way to get started is to try the live
version.
>> And download the local app if you like
it.
>> Yeah. And let us know in the comments
how you use it, for what you use it, and
I guess suggestions for features and
updates.
>> Yeah, that's very valuable.
>> All right. So, thank you, Yan. And I
guess we'll see how people use it. Thank
you very much.