I still wrestle with AI news overwhelm myself.
Oh yeah. That is incredibly common right now.
I mean every single morning brings another brand
new tool. Right. It feels completely exhausting
to always be behind. You open your browser and
just feel totally lost. The landscape moves way
faster than humans can read. Exactly. We simply
cannot process that volume of daily information.
It's impossible. Welcome to the Deep Dive. Today
our main mission is escaping that information
mess. We are exploring a completely different
approach to AI. We are turning Claude Cowork
into your automated team. It researches, analyzes,
and formats data while you sleep. Yeah, it's
kind of like stacking Lego blocks of workflow
together. OK, let's unpack this. So we are moving
far past the simple chatbot interface. We're
building a localized digital workforce for you.
It lives directly on your local computer desktop,
right? Exactly. Currently, it's available for
pro and team paid plans. Before building, we
have to deeply understand this paradigm shift.
This system is fundamentally different from opening
a web browser. That's a crucial mental shift
you must make. It acts entirely differently than
a normal website does. You access it via a special
dedicated co -work tab. It isn't just another
browser tab you forget about. It sits at the
core of your operating system. Right. It actually
sees your local files directly. It seamlessly
talks to your other installed applications. Wow.
So it can read documents right off your hard
drive? Yeah. And it runs complex tasks in the
background. It continues working while you are
looking completely away. You do not have to babysit
the application anymore. I think of the main
difference like this. Regular Claude is a smart
friend you can call. Okay. But Cowork is a smart
assistant sitting directly beside you. It actually
has his hands on your own keyboard. It knows
exactly where you keep your Notion pages. Yes.
It knows who your important clients actually
are. And it absolutely never gets tired of doing
research. There are five core blocks to this
entire system. You really must understand each
part for this to work. Let us walk through these
blocks organically. You start by setting up your
distinct digital rooms. We call these different
spaces your folders. You put all related project
files into one office. Right. Next, you have
to give the system some rules. Skills act as
your saved permanent operational playbooks. Then
we get to the actual brain of the system. Memory
is where Claude learns deeply about your work.
From there, we need to export the finished work.
Connectors act as the digital bridges to other
apps. Finally, automation is the set and forget
scheduling system. Right, and if you skip even
one block... The illusion breaks. The system
just goes back to acting like a generic chatbot.
The memory feature is the most fascinating part
to me. It fixes the generic robot problem completely.
It really does. I mean, using AI without memory
is like hiring a brilliant employee, but refusing
to tell them what your company actually makes.
That captures the core problem perfectly. Haha.
Yeah. Memory uses global instructions to answer
the question, who am I? You put your general
preferences and business goals there. Right.
But you also have specific localized folder instructions.
Which answer? What is this specific project?
Yes. It tells Claude exactly what to focus on
today. How do we prevent the AI from giving us
generic corporate jargon? Well, you must use
I and B in global instructions. State your exact
business goals from a first -person perspective.
So first -person pronouns force the AI into your
specific perspective. Exactly. It completely
changes the tone of the final output. Now that
Claude knows exactly who you are, it needs the
permanent rulebook. Right. You do not want to
repeat yourself every single morning. That completely
defeats the underlying purpose of true automation.
That is exactly what a skill is designed for.
Yeah. A skill is basically just a saved, refined
prompt. Instead of explaining your needs daily,
you just call the skill. OK, let me play double's
advocate here for a second. Why go through all
this trouble? What do you mean? Why not just
ask Claude for a summary? Why spend 20 minutes
building a custom playbook? Because basic summaries
completely miss the crucial business insights.
A generic summary just adds to your daily information
overload. Ah, I see. You actually need real targeted
insights to make better decisions. We are building
the research analyzer skill today. The instructions
must be incredibly specific to work well. Exactly.
The instructions must specify finding emerging
trends in the industry. We want it extracting
hard data with real sources. It must provide
a strategic so -what for the business. Right.
And it should format everything with clean, readable
bullet points. absolutely no corporate jargon
is ever allowed. Testing this skill is a crucial
step in the process. You run a long, complex
TechCrunch article through it first. Yeah, you
really want to see if it being lazy. You need
to ensure it follows the complex instructions.
There are also powerful pre -built plugins available
to use, like the productivity plugin for your
tasks and calendar. and web search plugins can
combine with your custom skills. What do we do
if the output feels too vague during a trial
run? Just go back into the skill settings and
add specifics. You might add a line like, always
look for funding rounds. Treat vague outputs
as a missing rule and update the playbook. Precisely.
It learns exactly what you want over time. Skills
are undeniably powerful tools, but manually triggering
them is still annoying manual labor. Yeah. Let
us make the machine work while you are fast asleep.
This is the real magic of the automation phase.
You use the schedule command to set automatic
tasks. You just toggle a few switches for folders,
connectors, and instructions. You could schedule
your entire research system for 6 a .m. But there's
one major operational catch you must remember.
Because it runs locally, the computer cannot
be asleep. Here's where it gets really interesting.
Yeah. The laptop lid absolutely cannot be closed
during this time. Your physical machine must
stay active during the scheduled window. Right.
Once it is awake, you can run parallel multitasking.
Unlike older sequential AI, Cowork runs multiple
tasks simultaneously. It can run three to five
tasks at the exact same time. It is exactly like
having a whole team of assistants. It can check
Google algorithm updates in one distinct stream.
It can find new YouTube productivity videos in
another. and analyze competitor newsletters all
at the very same time. But there is a physical
hardware limit here. It uses your actual computer
processing power to function. Yeah. Running 20
tasks might make your laptop fans scream loudly.
Three to five is the ideal operational sweet
spot. It is fascinating that the limitation isn't
the AI's brain. The real bottleneck is your physical
laptop's cooling fan. It really grounds the abstract
technology in physical reality. What is the absolute
biggest mistake people make on their first automated
schedule? Oh, they close their laptop lid when
they go to bed, the computer sleeps, and the
entire AI automation dies instantly. A closed
laptop lid instantly kills your entire automated
morning routine. This is a very frustrating lesson
to learn the hard way. Sponsor. So the massive
amount of data is processed perfectly at 6am.
But where does it actually go after the AI finishes?
Data trapped inside a chat window is just more
noise. That is exactly why we deeply need connectors.
They are digital bridges to your real daily workspaces.
You can connect Claw directly to your personal
Notion workspace. You create a professional research
database inside Notion very easily. It tracks
the source, key insight, and date incredibly
cleanly. Everything stays beautifully organized
and fully automated. You can also connect it
directly to your Slack workspace. This is a total
game changer. It sends daily bullet point briefings
to a private channel automatically. You just
read them on your phone over morning breakfast.
Then there is the very powerful Zapier MCP protocol.
Can you define what that actually is for us?
A digital skeleton key letting AI talk to thousands
of apps. A digital skeleton key letting AI talk
to thousands of apps. That is a perfect, simple
way to clearly describe it. It safely connects
to over 8 ,000 different digital tools. But you
should absolutely start slow with just notion
first. Now we have to talk about the power of
subagents. Yes. There are four very smart distinct
patterns they use naturally. First is research
parallelism for running multiple tasks at once.
Second is asset parallelism for creating several
different files at once. Third is sequential
chaining. This works exactly like a digital factory
assembly line. The output of one agent becomes
the input for the next. And fourth is batch processing
for massive, demanding industry -level work.
You track all this complex activity on a detailed
visual dashboard. It constantly shows the exact
status, progress, and activity. Two sec silence.
Wow. Imagine scaling to a billion queries. or
just watching it crush 10 to 20 posts in 90 short
seconds. It truly saves at least an hour of tedious
manual labor. With 8 ,000 apps available, what
happens if we connect everything at once? The
entire system becomes incredibly messy very quickly.
AI hallucinations start triggering wrong automated
actions everywhere across your apps. Connecting
too many apps creates a tangled web of automated
mistakes. Exactly. You will completely break
your own daily workflow. Let us bring all these
Lego blocks together into the daily routine.
We need to look closely at the ultimate master
workflow. It is a beautiful five -step morning
routine that changes everything. First, memory
knows the overriding goal is practical AI. Second,
the schedule triggers the entire system at 6
a .m. shoply. Third, Sub -agents aggressively
search the web for five big news stories. Fourth,
the research analyzer skill processes those complicated
stories deeply. Finally, connectors save the
detailed formatted report straight to Notion,
and they send a quick readable summary directly
to your Slack. You wake up and simply open Slack
on your phone. You read the number one key insight
immediately while drinking coffee. Then you click
the provided Notion link. for the full report.
You did absolutely zero manual searching or tedious
summarizing yourself. You only did the high -level
strategic thinking and the final writing. That
is the massive difference between working too
hard and having a smart team. So what does this
all mean? You are no longer a manual data worker.
You are now the strategic manager of a virtual
team. You direct the complex flow of high -level
information instead. For a listener feeling completely
overwhelmed right now, what is the very first
tiny step they should take today? Build one single
research skill and link it directly to your Notion
database. Do not try anything else yet. Start
small by building one specific research skill
and connecting it. Yes. Keep it incredibly simple
until you fully trust the system. Well, let's
wrap this up. Sure. The big idea of this deep
dive is that Claude Cowork isn't a web tool.
It is a localized parallel processing team. Built
solidly on skills, memory, and connectors. And
it works tirelessly while you are fast asleep.
If your localized AI is doing all the collecting,
summarizing, and formatting before you even pour
your coffee, what uniquely human skills should
you be spending your newly freed up time on today?
Beat. Thank you for joining us on this deep dive.
Hey Curious, see you next time. Out. T -Row music.