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Kind: captions
Language: en

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Somewhere in the last twelve months,

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five products shipped that answer the
same question in five different ways.

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What happens when a chatbot
finally gets its own computer?

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Not a window on your screen.

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A machine, with a browser,
a file system, and a login,

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that keeps working
after you close the tab.

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This is the story of that shift,
and of the five agents making it.

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Here is the part that matters.

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Every one of these five gives its agent
the same thing: a virtual computer,

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out in the cloud, with its own browser
and its own signed-in sessions.

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That is the whole trick.

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Before this, to get a machine
to do something for you,

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the machine had to have a clean API.

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An interface built for
programs, not for people.

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A lot of the software you need to
get work done has no such thing.

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So these agents do what a person would do.

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They open the page.

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They click.

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They log in.

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The computer is the universal adapter.

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It is also the biggest security decision
any of these companies has made,

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and we will come back to it.

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Start with the oldest of the five.

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On the eleventh of August, twenty
twenty-six, xAI opened Grok Bot in beta,

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alongside Cursor.

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The word Bot does not mean the reply bot
on X, and it is not the Grok chat app.

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It is a set of named AI teammates.

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Each one gets its own cloud computer
with a desktop, a browser, a terminal,

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and files.

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You name it, you give it a job,

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and you message it the way
you would message a colleague.

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On phone or desktop, same thread.

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Three things make Grok Bot
different from the rest.

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First, it learns by watching.

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You record yourself doing a task once,
and it turns that into a reusable skill.

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Second, it has routines, which
is a polite word for cron,

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so a bot can work on a schedule
with no prompt at all.

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Third, the bots talk to each other.

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One can ask another for help,
they share context in a thread,

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and one can spin up more.

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That is a team, not an assistant.

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And there is no free tier.

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It rides on SuperGrok and on Cursor
plans, with usage billed separately.

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It passed four hundred thousand
users in its first month.

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A month later, on the eighth of
September, Meta shipped Muse.

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Internally it was called Hatch,

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and Meta spent extra months on
security before releasing it.

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Muse runs on something
called Muse Secure VM,

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a dedicated machine in the cloud that
holds both the agent and your data.

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Sitting on that same machine,
isolated at the system level,

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is a second agent called Sentinel.

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Nothing Muse does reaches the
internet unless Sentinel approves it.

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Meta is the most aggressive
here on one specific point.

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Muse has no visibility into
your passwords or your card.

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You hand it credentials,
they go into a secure store,

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and it can use them
without ever reading them.

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It asks before it sends an email or spends
money, and it keeps a full audit trail.

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It can check out through
Link, built by Stripe,

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which makes it the first agent
covered by that purchase protection.

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And Meta says a Confidential VM is coming,

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where the whole machine is
encrypted with a key only you hold,

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so not even Meta can open it.

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It launched free with a usage limit,

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and it hit the number one free app
on the US iOS chart within days.

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Then Amazon blocked
it, on privacy grounds.

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Shopify partnered with it.

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That is the market talking back.

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Five weeks after Muse, on the
twenty-ninth of September,

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OpenAI announced Dots at DevDay.

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Same promise, new vocabulary.

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A dot is powered by GPT six Astra,

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it has its own cloud computer
and its own browser,

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and it can connect to more
than four thousand apps.

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You talk to it inside ChatGPT,
and also in Slack and Teams,

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and it carries the same context
into every one of those rooms.

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What is different about Dots
is the layer above the agent.

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OpenAI shipped specialist dots.

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These are not generalists.

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A specialist dot has its own
identity, its own credentials,

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hardware provisioned by your IT team,

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and deep integrations with
your systems of record.

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It is an employee-shaped abstraction.

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And OpenAI is wiring them
into Microsoft Agent 365,

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which is how it gets into offices.

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Dots start on Pro and Business Premium
plans, one per user, with more to come.

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Pro users in the EEA, Switzerland,
and the UK were excluded at launch.

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Now the turn.

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On the twenty-fourth of
November, twenty twenty-five,

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a developer named Peter Steinberger
released something he called Warelay.

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It got renamed twice, to
Clawdbot and then Moltbot,

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before settling on OpenClaw in January.

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It is the opposite move
from the four you just saw.

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There is no company behind it
and nothing to subscribe to.

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It is MIT licensed, stewarded
by an independent non-profit,

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and it has three hundred and
ninety-one thousand GitHub stars.

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The design decision that
defines OpenClaw is the Gateway.

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One process, running on your
own machine or your own server,

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is the control plane for everything:
your sessions, your tools, your events,

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and every chat connection.

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Channels are plugins.

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WhatsApp, Telegram, Discord, Slack,
Signal, iMessage, Teams, and more.

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And the model is a plugin too.

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Claude, GPT, DeepSeek, or something
running on your own hardware,

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and swapping it changes nothing else.

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The catch is the price of that
freedom, and it is not zero.

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It will not hold your hand.

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You secure it yourself, and
the project says so plainly.

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Hermes is the other open
one, from Nous Research,

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and it is MIT licensed with two
hundred and fifty-one thousand stars.

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Where OpenClaw is gateway
first, Hermes is agent first.

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Its whole pitch is a learning loop.

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It writes its own skills from experience,
improves them while it uses them,

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reminds itself to save what matters,
and searches its own past conversations.

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It is the only one of these five that claims
to get better the longer you leave it running.

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The memory is plain files you can read.

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A MEMORY file, a USER file,
and a personality file.

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Skills are markdown with front
matter, the same shape OpenClaw uses.

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It reaches twenty-one messaging
platforms, nineteen of them native,

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and it runs wherever
you can run a process.

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A five dollar VPS.

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A laptop.

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A container.

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Your own GPU.

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And it is model agnostic in
the same way OpenClaw is,

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which is why people
migrate one to the other.

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Where it differs is the loop.

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OpenClaw waits to be told.

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Hermes writes down what it learned.

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So put them side by side.

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The one axis that separates
them cleanly is ownership.

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Muse, Dots, and Grok Bot are rented.

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You do not choose the machine,
you do not choose the model,

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and you can only leave by cancelling.

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OpenClaw and Hermes are owned.

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You choose the hardware, you choose
the model, you can read the source,

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and leaving is deleting a folder.

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The second axis is who it is for.

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Muse and Dots are built for everyone,
with the learning curve removed.

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Grok Bot is built for people who
want automation without seeing code.

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OpenClaw and Hermes are built for
people who will read the documentation.

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The third axis is price.

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Muse is free with limits, then
twenty or a hundred dollars a month.

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Dots comes with a paid ChatGPT plan.

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Grok Bot requires SuperGrok or
Cursor and bills usage on top.

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OpenClaw and Hermes are free, and you
pay only for the model you choose to use.

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So which one.

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If you want an agent that works while you sleep
and you do not want to think about infrastructure,

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that is Muse or Dots, and the difference
is whose ecosystem you already live in.

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If you want agents as colleagues,
learnable by demonstration, on a schedule,

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that is Grok Bot.

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If you want to own the whole thing and you
are willing to run it, that is OpenClaw.

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And if you want an agent that
teaches itself, that is Hermes.

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The real answer, though,

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is that this category is twelve months old and
all five of these are the first generation.

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Every number in this film came from
a primary source: the OpenAI, Meta,

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and xAI announcement posts, the OpenClaw
and Hermes GitHub repositories,

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and the two documentation sites.

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Star counts were read from the
GitHub API on the fifth of October,

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twenty twenty-six.

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If you want the sources,
they are in the description.

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Thanks for watching.
