I was looking at my credit card bill the other
day. Oh, no. And the numbers were just, well,
they were telling a grim story. I was paying
for five separate AI writing tools, three different
image generators. It felt less like a strategic
toolkit and more like, I don't know, a digital
mess. That is the classic trap. The problem isn't
that you need more tools. The real struggle is
that bouncing between tabs, hoping the next shiny
thing is going to fix it. Yeah, and all it really
does is create more friction. Exactly. I thought
I needed this huge arsenal, but the core idea
we took from the source material is that The
big players, you know, Chad GPT, Claude, Gemini,
they're actually enough. They are, but only if
you have a strategic system for how they talk
to each other. And that's our mission for this
deep dive. We've pulled out eight specific high
leverage workflows. These are practical methods.
They're designed to stop you from working randomly
and instead start integrating your AI tools like
a real pro. We're looking for structure, efficiency,
and those genuine aha moments. And the core philosophy
here is really crucial. Stop asking one single
AI to do everything. That's where quality just
collapses. Right. You need to use them like a
specialized team. I mean, if you're building
a house, you need a hammer, a saw, and a drill.
You don't need 50 different hammers, right? So
let's define the five core tools these workflows
rely on. They each have a very specific job.
Right. So first up is ChatGPT. It's your general
helper. Great for writing, generating text, anything
that needs some personalized context. Then there's
Perplexity. This is our fact checker, our link
finder. Think of it like a super fast librarian.
And Notebook LM is the deep document reader.
This one is key because it studies your files
and sources and structurally it just cannot make
things up. Okay, and Gemini. Gemini is the builder.
It's for creating tangible things like charts,
slides, and code, and it often has these really
essential file exports. And lastly Claude, the
artist. The aesthetic expert, yeah. It makes
things look polished, beautiful. It ensures that
visual consistency. If you can keep those five
roles straight, these workflows become incredibly
intuitive. OK, let's unpack this. We can start
with research and analysis. So focusing on context
and truth. The first method is what they call
the smart brain method using chat GPT. Right.
So the biggest mistake people make is they open
chat GPT, ask a question, and then close the
tab. And next time you come back. The AI has
forgotten everything. You're starting from zero.
every single time. And that locks you into a
cycle of just generic low -quality answers. So
what's the solution? The solution is to leverage
the project's feature. A project is kind of like
a dedicated physical folder for one objective.
You create it, say, my Q3 marketing plan, and
then you preload it with knowledge. So you're
uploading your brand guidelines, maybe last quarter's
performance data, your budget notes, all the
necessary background. Yes. And now, when you
prompt it, act as an agency copywriter and draft
a social media campaign passed on my budget,
it's immediately smarter. Because it's grounded
in your specific reality, not just the general
internet. Exactly. And what's really fascinating
here is the loop effect. This is the mechanism
that stops that prompt drift. Ah, that's the
secret sauce for compounding the knowledge. When
ChatGPT produces something good, like a competitive
analysis, you download that report. And then
you upload it back into the project folder. Yes.
So now the AI's own research becomes part of
its permanent memory for that project. So you're
constantly reinforcing its knowledge base. You
are. And when you later ask for five Instagram
captions, the tone and the content are guaranteed
to match the brand document you fed it. It's
locked into your world. That makes perfect sense
for context, but what about facts? When you need
something that's 100 % verifiable, Context isn't
enough. And that brings us to workflow 2, the
trustworthy researcher. This gets at that core
fear, AI just hallucinating. Making things up.
Right. So for high stakes facts, you need a combination.
We use perplexity as the hunter, but, and this
is important, we restrain it. You don't ask for
a summary. You only ask for the links. Ah, so
you'd prompt something like, find the top five
scientific articles on sustainable concrete and
give me the URL links only. You want the source,
not the AI's interpretation. Correct. You take
those links, download the actual articles, and
you feed them directly into Notebook LM. Which
is the Google tool designed for deep reading.
And it's structurally incapable of making stuff
up because it only uses the documents you provide.
You can verify every single output. If it gives
you a summary, you can instantly see which document
and page number that fact came from. And we add
the persona trick here, too. In the Notebook
LM settings, you can tell it to act as, I don't
know, a skeptical engineering peer who demands
empirical proof. So the analysis it generates
is critical. honest, and fact -grounded, based
only on the sources you gave it. That combination
is how you guarantee verifiable truth. OK, let's
shift gears. Segment two, strategic visualization.
We've done the deep thinking. Now we need to
actually show the results to people. And quickly.
So workflow three, turning long reports into
infographics using perplexity and Gemini Canvas.
The pain point here is always dense PDFs. Right.
So perplexity finds the detailed report, let's
say, global Q4 sales data. You download that
PDF. Then you go over to Gemini and its visualization
space, which is called Canvas. Think of Canvas
as Gemini's workspace for visual outputs and
code previews. You upload the PDF there. And
instead of asking for a text summary, you prompt
it for a structure. Something like, create a
visual flowchart showing the revenue breakdown,
highlighting regions with over 5 % growth. Exactly.
And Gemini Canvas will generate a visual diagram
based on code, not just static text. It jumps
you from raw text analysis straight to a presentation
-ready visual. That's speed for sure, but sometimes
those generated visuals lack polish. If we need
professional aesthetics, the source suggests
moving to Claude for workflow 4. making beautiful
dashboards. This is where we need to understand
Claude's unique advantage. Claude excels because
of its exceptionally large context window. What
does that mean exactly? It means it can hold
complex style guides, like your entire company
brand guide, in its memory way better than other
models. It ensures visual consistency. So the
key step here is teaching it your style first.
That's it. You set up a Claude project. You upload
an image or a PDF that defines your color palette,
say, rich blue and silver, and a specific font.
And you literally tell Claude, use these specific
hex codes and fonts for all charts you make for
me. Then you upload your data, like a CSV file
of website engagement, and ask it to create an
interactive dashboard with that exact look and
feel. And Claude generates what they call an
artifact. It's a code pop -up that looks and
acts like a real interactive dashboard. Whoa,
imagine scaling that. You teach it the style
once, and it maintains that aesthetic for every
single monthly report forever. That saves a massive
amount of design time. It's engineering consistency,
not just making a picture. Which leads right
into workflow five, social media images using
Claude SVG and a tool like Figma. Exactly. Stop
paying a designer 50 bucks for a simple graphic
with three bullet points. So first, perplexity
finds the list. The seven best habits for remote
workers. Then you take that to Claude. and you
prompt it to generate a clean modern graphic
for Instagram, but critically... You demand an
SVG file. And SVG is a special image file type,
right? It's made of math, not pixels. It's made
of mathematical code. And because it's math,
you can download it, drop it into a free tool
like Figma or Canva, and suddenly you have total
control. So if Claude misplaced a text block,
you just fix it instantly. Change the font, swap
a color. It's a one -second edit. You get the
speed of AI design, but the precise control of
a professional for those final tweaks. It's a
game changer for content velocity. All right.
Let's transition from thinking and visualizing
to our last segment. Building real things. Creating
high value assets. Workflow six. Instant presentations
using Gemini gems. A gem is basically Gemini's
version of a custom GPT. You train it once to
do one specific repeatable job, like investor
deckmaker. So you'd instruct this gem to always
follow a specific structure. Slide title, three
bullet points, two image suggestions. And when
you need a deck on the impact of rising interest
rates, you just talk to the gem. It spits out
the perfect outline structured exactly how you
like it. But then comes the magic export. This
is the feature that really sells it. It is. You
ask Gemini to create the slides from that outline,
and it generates a file that opens directly in
Google Slides. So no more copy pasting. It eliminates
the single greatest friction point in making
presentations. No more copy, paste, and reformat.
That is huge for momentum. Yeah. Okay, now. Workflow
7. Creating a full training course with Notebook
LM and Gemini. This sounds like it turns weeks
of work into an afternoon. It can. You start
by gathering all your training documents, your
technical manuals, into Notebook LM. That's your
authoritative source. And then you use a feature
called Notebook LM's audio overview. Yeah, this
is cool. It turns your documents into a synthesized
two -person discussion podcast, an mp3 lesson
that's an instant piece of training content generated
directly from your own documents. That is immense
leverage. And because Notebook LM is fact -grounded,
when you ask it to create a 10 -question quiz
or a one -page cheat sheet for the course, you
are guaranteed that the output sticks strictly
to the facts in your original source materials.
That consistency is essential for educational
tools. Finally, workflow eight. building a landing
page website. We start with strategic research.
I love this example. Scraping real complaints
people have about a service, say, dog walking
from a form like Reddit, and pasting them into
Notebook LM. So you know the exact emotional
pain points of the market before you write a
single line of copy. Precisely. Notebook LM generates
the strategy brief from those complaints. It
identifies that people hate lateness, so it suggests
the headline, the only dog walker who is always
on time. You take that high leverage brief, copy
it, and take it to Gemini. Prompt it to write
the basic HTML and CSS code for a landing page
based on that strategy. And you immediately see
a live preview of the website in the Canvas view.
I mean, I still wrestle with prompt drift myself,
you know, especially asking for code. I was asking
for some Python code the other day, and it started
trying to write me a limerick. Right. But seeing
a code preview instantly just takes away all
that friction. You can deploy it right away.
OK. We just covered eight intense workflows.
The big idea here remains. You don't need more
tools. You need a strategic system to connect
the five major ones you probably already have.
And to recap their roles one last time for you,
perplexity is for reliable fact finding. Notebook
LM is for trustworthy, deep reading of your documents.
ChatGPT gives you that personalized context and
custom content creation. Claude handles the aesthetics,
giving you professional polish on visuals and
dashboards. And Gemini builds the final structures,
the charts, the code, with those essential file
exports. But start small. Please do not try all
eight of these today. That's just a recipe for
overwhelm. The practical advice from the source
is this. Pick one problem you have right now.
Maybe you hate writing emails or you waste time
formatting slides. Choose the workflow that fixes
that one thing. And commit to trying it five
times. The first time will feel slow, it'll feel
clunky, guaranteed. But by the fifth time, it'll
be fast, it'll be automatic. And that's when
you stop paying for the tools and you start leveraging
the system. The true power here isn't just the
output. It's not the quiz or the code you made.
It's the fact that you've engineered a predictable,
repeatable system that consistently understands
your context. You've stopped managing a collection
of apps and started directing a high -performing
team. And that repeatable system is what scales
your knowledge across any future idea, any future
business need. It's an infrastructure of automated
intelligence. Go build something powerful. We'll
see you next time.