This content provides an in-depth, long-term perspective on using OpenClaw, an always-on AI agent, moving beyond initial impressions to showcase practical, daily use cases, evolving workflows, and the realities of its limitations after over 50 days of continuous use.
Mind Map
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คลิกเพื่อสำรวจ Mind Map แบบอินเตอร์แอคทีฟฉบับเต็ม
Most OpenClaw videos right now are either first-week impressions,
or set up tutorials, or showing use cases after three days of usage.
Nobody can tell you what happens after the first month, because
they haven't been there yet.
I have.
Every single day. For over 50 days. Through every single
iteration of this tool:
when it was ClawdBot, when it was MoltBot (which I refused
to call it that) and when it is now OpenClaw. I made the
setup video that ended up in the official OpenClaw documentation.
I built Clawdiverse, the community directory of use cases, and the
most common post on Reddit is still:
"I set up OpenClaw, but I don't know what to use it for."
This video is the answer: 20 real use cases from my daily life, plus the
honest truth about what breaks, how it breaks, and how to deal with it.
Quick context for anyone new.
OpenClaw is an always-on AI agent that runs on your server, your VPS, a
Mac Mini or even a Raspberry Pi, 24/7.
It connects to your messaging apps that you already have
on your phone, like Telegram, WhatsApp, Discord, iMessage.
If you need the full setup, I have a video for that
(link in the description)
This video is about what you *do* with it once it's running.
And a super important thing:
Every single prompt for every use case I'm about to show
you is in this document
(also link in the description)
It's ready for copy-pasting and using with your own agent.
Let's go see how it all works.
Before the use cases, let me walk you through what
50 days actually look like.
Because the way you use this thing in week one is
nothing like in week seven.
Week one is novelty.
You're asking it random questions, testing what it can do, kind
of using it like a ChatGPT.
But one decision I made from day one saved me over and over in
coming weeks markdown-first.
A lot of people build their workflows around SQLite, databases,
vector stores, custom schemas.
I put everything in Obsidian from the start in plain text files.
Any person can read them, I can read them.
Any program can work with them.
It's just plain text when the next thing after OpenClaw or the next
iteration of OpenClaw comes along.
My data moves with me in five seconds.
No lock-in, just files.
I can do anything with them.
By week three, you start building automations, warning
briefings, background checks.
It starts being more useful and you can feel it in week five when
you start using it more and more.
You hit a wall, everything is in one conversation and
everything is mixed together.
Research, bookmarks, analytics, daily tasks, and there's more and
more context pollution, and that's when I learned to separate contexts.
I now have one Discord channel per workflow.
This way, research doesn't bleed into analytics.
Bookmarks don't pollute daily assistant tasks, and I'll show you the
full architecture later in week seven.
Another lesson.
Not every channel needs the same brain.
You need to match the model to the task.
So Opus is for deep thinking and cheap models are good enough for
routine work, and that's when costs stop being scary and crazy.
And by week eight and onwards, it stops being a chatbot and becomes
a system and lesson from this.
Is three important principles after 50 days that I would recommend everyone
is to have everything in markdown from the beginning to separate context
and to match the model to the task.
Here's what we are covering, 20 use cases across six categories,
and I'm going to move fast, real screenshots, real conversations,
real results, and if you only steal three ideas from this entire video.
I'll tell you exactly which three closer to the end of
the video, so stick around.
It's gonna be worth it.
Most of my setup runs in Discord now, which wasn't the case from
the beginning, and I'll show the channel architecture and model
routing later for now, starting with the things that run every single
day without me touching anything.
Every morning at 7:00 AM my agent scans a bunch of tweets
from accounts they follow.
Picks the top 10, writes them to my Obsidian notes.
Appends any video ideas to my shipping backlog and sends me a summary.
I wake up and I don't need to scroll through the feed
to know what happened.
The most important and interesting part is already waiting for me
and it's tailored to my interests or what I'm currently working on.
So today's stories are about Anthropic and OpenClaw,
new Gemini model dropping.
And this is already saved in Obsidian, and a couple video
ideas are also added to a note in Obsidian, and the value compounds
with time because it doesn't just summarize, it connects the dots.
Like, Hey, this tweet about model pricing connects to
your video idea about cost optimization, that kind of thing.
But briefings are the gateway drug.
Everyone starts there.
Let me show you what comes after.
This is my favorite use case.
Every morning my agent fetches Wikipedia's 'On This Day' events,
picks the most impactful historical event and then generates a woodcut
style image showing 10 seconds before that event happened, like the
iceberg approaching the Titanic or the apple, about to fall on Newton's
head, this kind of stuff, and then it pushes to my TRMNL e-ink display.
In a mystery mode, it only shows the date and location,
and I need to guess the event.
Sometimes it's obvious, sometimes it's a lesson for me.
So for example, this is February 1st, 2003 over Texas.
This is seconds before shuttle Columbia Disaster.
Where it blew up, and these are the kind of images that it produces.
For example, this is just before the last public appearance of
the Beatles on the rooftop.
And this is the beheading of Mary Queen of Scots, which changed
the course of Europe's history.
And this is part of my daily ritual.
Now I walk past the display, look at the new picture, try to guess what it
is, learn something new about history.
Every single day a new one is waiting for me.
This is maybe less of a use case and more like part of my daily routine and
also an important part of the routine.
So I have two cron jobs that I now never think about every day at 4:00
AM when I'm sleeping, my agent updates its own skills from ClawHub updates.
The OpenClaw package itself restarts the gateway, and
then reports the results.
When something breaks during an update, it tells me and every day,
half an hour later, a separate cron job backs up everything
important, all configuration files, workflow directory, crown
schedules, SOUL file, MEMORY files, skills, everything that defines how
my agent works or who he even is.
So if my server dies tomorrow, I'm back up in half an hour, not
rebuilding from scratch, not trying to remember how I configured things.
Just restore and go, and that's the whole point.
It just runs.
And if something goes wrong, I can recover easily.
And just as a reminder, all of the prompts to achieve all these
tasks and use cases are in this.
Just on GitHub, so you can just go there, copy paste to
your agent, and be good to go.
Always on checks, like for example, background health checks.
This used to feel like the headline feature, but now I think of it as
background guardrails useful, but it's only one piece of the system.
My agent runs routine heartbeat checks every 30 minutes.
And I can define what it does every 30 minutes.
For example, it scans my emails, checks my calendar, monitors
my services, and it catches things I would have missed.
For example, one time it just sent me this message out of the blue
about a Netflix payment failure, and I had no idea about it.
It found it during a routine email scan.
I paid it five minutes later so I could safely watch more TV shows.
Or rather, I don't really watch TV shows.
I don't have time.
Rather, my kids could safely watch more hunters and catches a lot of
other things like domain renewal coming up, or a meeting I was about
to miss, or a relevant newsletter article that it found during a Sunday
heartbeat scan that connected to a video that I was currently working on.
And none of these were tasks that I assigned.
My agent just found them.
It knew what I'm working on and the things that would normally
fall through the cracks.
That's exactly what gets caught by the agent.
And an important piece of setup here is that the agent is in
a draft only mode for email.
It can read my inbox.
It can flag what's important.
It can even draft responses, but it cannot send it.
I need to review and send the email.
And, and it doesn't happen without my approval.
For now, there's no robust general solution yet for
prompt injection via email.
So I treat inbox content as potentially hostile research
and content creation.
And I love the research part of working with OpenClaw.
It just appeals to me to do it on the go when I have ideas
and I want to discuss it.
For example, for this video, I told my agents to research what people
are doing with OpenClaw, and then it spawned five parallel sub-agents.
One Search Twitter, one crawled Reddit, one hit Hacker News.
One analyzed YouTube competition and one scraped multiple different forums.
They all ran simultaneously and produced massive
structured research files.
Each one of them with competitive analysis ranked video ideas, full
outlines, with source links, and it took them minutes, not hours.
The research files for this video alone produced by these
agents are over 50 pages.
And it gave me a clear understanding of what people are doing.
And more importantly, not yet doing with OpenClaw and what I need to
focus on to give the most value.
And it's not just for video research, it's for any kind of research.
You can define how broad it should go.
How fresh the data needs to be.
Is it the last seven days?
Is it the last three months?
And then let it run and come back with results so you don't
start from scratch and you have a solid base to start with.
And speaking about YouTube, I have two dedicated Discord channels
related to YouTube creation.
The first is my YouTube analytics channel.
It has access to all my stats via the API, and I can query anything in.
Natural language, like how did my last five videos compare on retention or
which topics get the most engagement?
Or compare my OpenClaw videos to my Claude Code videos, and
then it slices and dices the data anyway I want on demand.
It's like much more flexible than YouTube studios built in dashboards,
and it also synthesizes the numbers.
And gives ideas and advice based on that.
You're not getting this from any kind of analytics.
For example, this was just a random question how my last two weeks went,
and then it gave me the view numbers.
It showed me when I published the videos to understand where was the
spike, how it goes down, where is the uptick, what were the key insights?
What was the watch time, which I didn't even ask about, and
what was the bottom line?
So everything related to what I care about, which I didn't even ask.
It just knows and gives me the details.
As granular as I want them to be, and the second channel is
my video idea research channel.
Throughout the week, I drop links, articles, tweets, half warm thoughts,
what I want to include or what I don't want to include in the next video.
And then the agent goes and enriches those snippets.
It connects the dots across different sources and builds context over time.
And by the time I sit down to work on the video, I don't start from scratch.
I have weeks of accumulated organized research waiting for
me, and this exact video is a great meta example of it.
The research for this video accumulated over probably like
three weeks, maybe even more.
Links from Reddit, insights from Discord, competitive
analysis, audience pay points, all fed over time.
As ideas came to me as I got some data, as I got some numbers.
And then everything got organized and connected by the agent so that I
have a solid baseline to start with.
And having those two different channels for YouTube are important
because the separation matters, analytics context, stays isolated,
and then research builds over weeks without polluting other conversations.
Next is summarizing practically anything.
Throw any URL at it, like an article, a YouTube video, a research paper,
A PDF, and you get a summary back and I use it multiple times a day.
For example, let's summarize my last video.
/summarize and a URL and it goes to work, and a few seconds
later I get the summary.
What's the video about?
What's the core message?
What are the key numbers?
What are the practical steps?
And from there, I can tell it to either expand or this is good enough,
or maybe save it to an Obsidian note.
I can do anything.
Infrastructure and DevOps.
My agent migrated me from the alt ClawdBot package to OpenClaw.
It found both packages running at the same time.
It killed a zombie process running at 160% of CPU.
It deleted the old system services fixed seven days of silently broken
cron jobs that went unnoticed and all from one message, go fix everything.
It's also connected to my VPS server via API, and I host everything there.
And the first time I connected it, it reviewed more than 20 apps.
Running there, flagged some unhealthy services.
Did some fixes and right now I can do anything with it.
I don't need to SSH to my server.
I can check the health of the whole server or specific apps and it can
fix the apps, restart the apps.
I have basically like a remote control to my whole server just in my
Discord, and again, about security.
There is an allow list of commands that it can do, and there's
also a deny list of commands that it cannot do by itself.
It has to ask my permission first.
Works pretty well and I haven't had any issues so far.
It allows me also to code from my phone.
I can tell my agents to go fix a bug.
Build a feature, create a PR, all from my phone while I'm away from my
desk, and you don't need your laptop because your AI has your laptop.
But to be completely honest, I do not use it for production
as my main way of programming.
I only use it for some quick fixes or simple ideas that come to my mind,
and I wanted to test them on the go.
For my main workflow, I still use Claude Code and Codex on my
desktop Daily Life assistant.
And to start with, what everybody's doing is email, triage and draft
replies beyond the proactive catches that I already showed you.
The day-to-day email workflow is simple that it reads my inbox.
Flags what's important and drafts responses.
I review and send.
This way I can easily reply to an email the same day rather than
during the weekend when I have more time to go through my inbox.
This one is useful.
Calendar and family management, not just for
myself but for family as well.
For example, I have a group chat on WhatsApp this time.
Because my wife doesn't use Telegram or Discord, and in
WhatsApp group, I can drop messages like Schedule Dentist
Thursday at 3:00 PM and it's done.
And my wife can add events, check the schedule, get
reminders all through that same group chat and chat interface.
It is simple, but it is helpful as well.
And once it works, you start asking like, what else can you do?
Voice note transcription.
This is something that I always thought I would be using on my phone
because I can dictate stuff and it's there, but when I tried it, I never
went back to listen to those messages.
Now it can actually be done automatically.
So for example, I send a voice message on WhatsApp, telegram or
Discord, and it transcribes it with Whisper model and responds in
text, quick thoughts while driving.
Shopping lists, while walking, meeting notes on the go.
I just talk and then it handles the rest.
And if it's something important, it puts it in maybe a file in Obsidian.
Or sends a message or drafts an email so that I don't even
need to go back to those notes.
They are already taken care of and more small stuff from daily
life, like find me a good coffee shop within walking distance.
It uses Google Places API, so it has access to ratings reviews.
Walking distances from my home, what people like or dislike in that place.
What are the prices?
So it can do much more in seconds than I would do myself, and it's
helpful for one of searches as well.
I was searching for snowboard boots to go snowboarding, and
I have a large foot, so it's an issue to find my size.
So it serves multiple shops.
Where I could buy one, it checked online whether they had
my size and it gave me three options where I could go and buy.
So I went to the first one, bought one, which were not available anywhere
else in the city or almost, and.
Took me 20 minutes for weather forecast.
It doesn't tell me just like tomorrow is gonna be sunny.
I have it on my watch, but it did warn me once, for example,
about minus 19 degrees cold snap coming up, which is like minus
two, minus three Fahrenheit.
And that was quite helpful.
And then there are reminders about maybe rehab exercises
with snooze capability meeting reminders before my weekly calls.
These are all small things on their own, but they do add up and they are.
Genuinely helpful in everyday life, helping friends with their
technical issues and problems.
And this one is personal.
So my friend wanted to set up his own OpenClaw after watching my videos,
and I added him to a WhatsApp group with my own agent, and myself and my
agent spent three and a half hours.
Guiding him step by step through the entire setup in a non-English
