Welcome to the deep dive. We are going on a very
specific mission today. But before we get into
the mechanics of it, I want you to picture something.
Oh, I know the exact scenario. You finally sit
down to work on a major project, you open up
a totally fresh chat window, and immediately
you just feel this agonizing sense of exhaustion.
Yeah. Because you suddenly realize you have to
upload the exact same PDF. You have to explain
your entire brand voice. Again, every single
session basically starts from absolute zero.
It is a profound friction. I think we are constantly
introducing ourselves to our own tools. We totally
are. It's exhausting. Today, we are looking at
a brilliant guide on curing AI amnesia. The goal
here is simple. We're going to build a long -term
memory system for your work. And the best part
is we'll use two completely free tools for this,
Cloud Projects and Notebook LM. There is no coding
involved, there are no complicated scripts, and
it takes under 20 minutes to actually set up.
Yeah, and once you finally build this system
out, you'll never have to brief your AI from
scratch again. It honestly changes everything
about how you work day to day. Let's explore
the hidden cost of this amnesia first. Before
we can actually build the solution, we have to
understand it. Why is the current way we use
AI quietly draining our productivity? Well, it's
sneaky. It feels like a minor annoyance in the
moment. But it actually scales terribly across
a work week. Right. Every time you start a new
chat, you're wasting valuable time. You're wasting
your own mental energy just doing setup work.
The source material uses a really great analogy
here. Claude's memory is basically like a dry
erase whiteboard. The exact moment you close
that chat tad, it's wiped completely clean. Exactly
that. It just vanishes into thin air. Now Claude
does try to synthesize your conversations every
24 hours, right? It does, yeah. But that synthesis
only applies to new standalone chats. It's very
broad. So if you had this incredibly deep work
session on Tuesday, By Friday morning, it is
entirely forgotten. You are completely back to
square one. Yep. You're re -explaining all the
core concepts before you can do any real work.
And then there is the token tax. Oh yes. This
is the part almost nobody talks about. Let's
define that quickly for everyone. Tokens are
tiny pieces of words AI uses to charge you. Perfect
definition. So, I mean, think about pasting a
5 ,000 -word brand guide. Right. If you drop
that into every single new session you open,
you are repeatedly paying for that exact same
data. Over and over again. Exactly. Across a
busy month, that financial cost really adds up.
It is deeply inefficient, but I think there is
also an intangible loss here. The text describes
it as losing the feel of your project. Oh, this
is so incredibly real. When you work with an
AI for a solid hour, it actually starts to learn
your unique rhythm. It picks up on your tone.
It learns exactly what you're going to push back
on. It starts to feel like an actual creative
partner. And then you just close the tab. It's
gone. That shared feeling completely resets.
The very next morning, it is a total stranger
again. You lose that incredibly valuable shared
context. It's tragic, honestly. I actually have
to admit something here. I still wrestle with
this terrible habit myself. I catch myself pasting
the exact same context brief three times a week,
just out of sheer laziness. It's such a ridiculously
common trap. We just default to the easiest immediate
action in the moment. Even if we know it is going
to cost us more time later. Exactly. So why is
this specific cycle so incredibly hard for us
to break? Well, because the AI sounds so confident.
It's conversational every single time. So we
naturally project human traits onto it. We subconsciously
assume it remembers us, because the human colleague
would. And when it obviously doesn't, we just
panic -paste our documents to catch it up. We
project human memory onto a machine that sounds
confident. Yeah, that's it entirely. Which leads
us directly to the actual fix. To stop starting
from zero, we need to combine two very different
tools. Wait, I want to push back on that a bit.
Isn't the whole point of these massive AI models
that they do everything? That's the marketing
pitch, sure. So why would I complicate my life
by using two different tools? Because people
fail. when they expect one tool to do absolutely
everything. You can't use a hammer to turn a
screw. Ah, I see. Claude Projects and Notebook
LM are built for entirely different jobs. When
you finally put them together, the entire system
just clicks. Okay, let's look at that first tool
then. Claude Projects. This basically acts as
your persistent, everyday workspace. Right. You
upload a file once and it stays there forever.
It uses AI to constantly remember your unique
context. And just to clarify, Rag, for a second,
it is a way for AI to pull your exact files instantly.
Yeah. Great way to put it. So inside Claude projects,
the AI can constantly read those files. Right.
But it can also still search the broader open
web. It still has its vast general knowledge.
Yeah. Your specific files just add an extra layer
of personal context. But Notebook LM works in
the exact opposite way, doesn't it? It acts strictly
as the archive. This is the massive difference.
Notebook LM only pulls from the specific documents
you provide it. Interesting. It has incredibly
strict data adherence. There is absolutely no
external web knowledge allowed in there. So it
is kind of like having a brilliant creative director
in Claude and then an incredibly strict literal
archivist in Notebook LM. They're doing totally
different jobs. That's a really great way to
visualize it. They're a team. Now here's why
we actually do this workflow manually instead
of using a script. You mean advanced things like
MCP. Right. Which is basically code that connects
apps together automatically in the background.
Yeah, exactly. Advanced users absolutely love
setting up those automated complex scripts. But
they require you to do complicated terminal work.
You constantly have to authenticate tokens through
Google. That sounds fragile. It is. For most
normal people, those setups just break without
any warning. a random library updates overnight,
and boom, your entire workflow is totally dead
right before a major deadline. So this manual
method is just much more resilient. It is completely
free. There is zero coding required. Not at all.
You can even do it on your phone. It stays perfectly
stable. It actually stays working. That's the
entire point of building it this way. I want
to linger on Notebook LM for just a second, though.
Why are strict boundaries sometimes better than
having endless web knowledge? Because the open
web is totally full of contradictions. It's full
of generic advice. That is very true. When you're
making critical business decisions based on your
own specific client data, you want the AI locked
in a room with only your proven facts. Endless
internet knowledge dilutes the truth when you
need factual boundaries. Yeah, exactly. So let's
get hands -on and actually build out this creative
director's workspace first. Let's do it. Setting
up Claude projects. The guide is incredibly clear
about the pacing here. You do not need to do
absolutely everything in one single sitting.
You start simple. People always overcomplicate
this step. You just go into Claude. You click
on new project. Right. You give it a highly specific
name, something like newsletter Q2 or client
strategy redesign. Inside that project, you will
see a file section. This acts as your new long
term memory. And the golden rule here is. Exactly
three files to start. Right. Do not upload 20
chaotic files on day one. Just three. First,
you need your context. .md file. This explains
who you are, your core goals, your specific tone.
Keep it super lean, under 500 words. Second,
you upload your formal brand guidelines. Third,
and most importantly, your decisions log. The
decisions log. This is basically a running document
of choices you have made and the reasons why.
Yeah. Once those three are finally uploaded,
you set up the project instructions. These are
basically standing rules. Claude has to follow
them before you even type a single word. You
literally tell it, check my decisions log before
answering. always match my brand guidelines.
You essentially hand it a custom instruction
manual for your own brain. But I know people
assume AI just naturally learns over time. Oh,
they do. Without this next manual step, all that
brilliant brainstorming just vanishes into the
ether. It vanishes completely. You absolutely
cannot just close the tab when you're done working.
Right. At the end of every single session, you
have to run the wrap -up habit. The prompt they
suggest for this is actually really simple. Summarize
what we worked on, decisions made, and next steps.
Keep it under 200 words. You just copy that short
summary, you paste it directly into your decisions
log document, and you re -upload it to the project.
The whole thing takes two minutes, Tops. Literally
two minutes. So why is this specific decisions
log the Absort secret weapon here? Well, human
memory is honestly terrible. I mean, we forget
what we had for breakfast, let alone why we discarded
a marketing angle three weeks ago. Yeah. If the
AI doesn't have a log of that specific choice,
it's just going to suggest the exact same bad
angle next month. It records the logic of your
choices to prevent recurring arguments. Yeah,
it creates a perfectly linear history of your
own logic. We are going to pause for a brief
moment. When we come back, we will explore adding
the heavy research layer, mid -roll sponsor read
placeholder. Welcome back to the deep dive. We
have successfully built the active workspace
using Claude, but Claude naturally hits upload
limits very fast. It really does, even if you're
on the expensive paid plans. You upload a few
massive research PDFs and you immediately run
out of contextual space. So where do we actually
put those massive industry reports? Where do
we store our giant competitor analyses? This
brings us to the second tool. Notebook LM. This
serves as your heavy research layer. It comfortably
handles up to 50 different sources per notebook.
Right. You can upload dense PDFs, long Google
Docs, or endless website links. You can even
drop in YouTube transcripts and huge audio files.
And you just organize them by topic. Put your
audience research in one notebook, competitor
landscape goes in another, industry trends in
a third. The actual workflow here is fascinating.
You do not ask Claude first. Right. Never ask
Claude first for hard research. You go directly
to Notebook LM. You ask a highly specific, targeted
question. Something like, what are the top three
audience patterns found in these sources? And
Notebook LM gives you a grounded, perfectly cited
answer. It is only using your uploaded files.
Exactly. You then take that clean answer, copy
it, and paste it back into your Claude project.
You basically tell Claude, here is my verified
research. Based on this exact data, write out
the new strategy. Whoa. Imagine having your entire
project history perfectly recalled in an instant
without a single hallucination. It is a superpower.
You get the strict factual recall of Notebook
LM seamlessly combined with the creative reasoning
of Claude. It's the best of both worlds. A quick
note on data safety here. People always ask if
their private data is actually safe. Notebook
LM is officially a Google product. It follows
standard Google workspace privacy terms. So it's
perfectly fine for general market research and
creative drafts. But you still need to be careful.
Right. Don't go uploading highly sensitive legal
or financial data unless you explicitly clear
it with your IT team first. Let's talk about
prompt drift for a second. How exactly does this
dual step process prevent the AI from slowly
drifting completely off topic? Well, when you
just chat loosely with an AI for hours, it naturally
starts losing the plot. It gets overly creative,
just starts filling in the blanks. By forcing
the AI to start from notebook elements hard facts
every single session, you constantly reset its
compass back to reality. Anchoring Claude to
factual sources stops it from making up creative
data. Precisely. It keeps the final output highly
rigorous. Let's look at how this actually applies
in the real world. Real use cases. Because this
definitely is not just a system for writers.
Not at all. Think about digital marketers for
a second. You create a totally separate cloud
project for each individual client. Okay. You
upload their specific brand voice. You upload
all their past campaign results. So every single
time you open up that client's project, Claude
already knows them intimately. Right. There's
no tedious re -briefing. You just jump in and
ask, what specific content format worked best
for them last quarter? Educators are using this
heavily too. You upload your massive core site
line. You upload anonymous student feedback.
You can easily ask Claude to rewrite a confusing
lesson based entirely on your specific teaching
philosophy. And for solo founders, this setup
is just brilliant. They call it creating a business
brain project. This is honestly my favorite application.
You upload your big yearly goals, your external
communication guidelines, your internal pricing
rationale. Yeah. You can actively use it to fight
against scope creep. A client wants a brand new
service, right? Right. You ask, based on my past
decisions about scope, what should I actually
propose here? It essentially acts as a perfectly
objective business partner. It forcefully holds
you to your own established rules. It totally
does. But obviously, any system has its traps.
The guide highlights four major mistakes that
will completely break this setup if you aren't
careful. We definitely have to cover these. Mistake
number one is uploading way too much data all
at once. People always want to just dump 30 chaotic
documents in on day one. Yeah, you have to start
with three to five. Mistake number two is never
bothering to update your core files. Your business
context changes. Your goals shift. You really
need to review those core foundation files every
four weeks. It's a really small habit, but it
makes a massive difference. Mistake number three
is skipping the wrap up. We said it before, but
it absolutely bears repeating here. Without that
two minute summary step at the end of a session,
you are not building a memory. You are just having
totally isolated, forgettable chats. Yep. And
mistake four is using Claude projects to hoard
all your heavy research. Right. Do not treat
Claude like a giant filing cabinet. That is exactly
what Notebook LM's job is. You have to keep the
tools in their respective lanes. Keep them separated.
I am actually curious about that very first mistake.
Why does giving an AI more files actually make
it less smart? Shouldn't more data be better?
You'd think so, but no. It's this phenomenon
called context dilution. OK. When you give it
50 vaguely related files, the AI's attention
mechanism really struggles to weigh what is actually
important. It might pull a totally mediocre point
from an outdated file instead of the critical,
nuanced point from yesterday's file. Too much
background noise hides the critical signals the
AI needs. Yeah. Keep the active workspace lean.
Keep the archive layer deep. Let's recap the
big idea we were exploring here. We have all
been paying for this incredibly powerful evolving
partner, but we have been treating it like a
basic, completely amnesiac question answering
machine. We've seriously been limiting its true
potential just because of our own lazy habits.
The roadmap to fix this is genuinely simple.
Week one, build the Claude Foundation. Right.
Right. Your short context file. Upload it. Start
practicing that two minute wrap up habit. Week
two, you add the heavy research layer. Set up
your notebook LM, add your massive reference
sources, but strictly keep the two tools separated.
Absolutely crucial. This fundamentally transforms
the tool into a true creative partner. It finally
stops being a complete stranger every morning.
Because it already knows where you are. It knows
exactly what you are building toward. So here's
the immediate challenge for you. Okay. In your
very next work session, don't just close the
window. Force yourself to ask for that 200 -word
summary. Start your decisions log today. Stop
starting from zero. It is a relatively small
shift with incredibly profound leverage, but
it really does make you think. If you successfully
build an AI partner that perfectly remembers
every decision, every pivot, and every preference
you have ever had, five years from now, where
exactly does your original thinking end and the
AI's memory begin?