So we're looking today at this really interesting
mismatch, you could say, how people are using
these incredibly powerful new research tools
like Perplexity. Yeah, it's striking, isn't it?
The core issue, really, is that most folks are
using this massive computational power almost
like a basic phone. They ask simple questions,
get simple answers, and they're completely missing
what's actually under the hood. Exactly. It's
like having a Formula One car and only driving
it to the grocery store. They're getting these
basic results because the inputs are, well, basic.
They're kind of misusing what ought to be this
tireless, super specialized research partner.
Right. So our mission here in this deep dive
is to help you map out a different way to operate.
We need to shift our thinking, yours and ours,
from just using AI or an LLM that's a large language
model to really working with it. The aim, creating
real professional measurable value, stuff that
can actually generate income. And the source
material we're diving into gives us four pretty
distinct models for doing just that. We're going
to cover... building high -value digital assets,
becoming a trusted kind of affiliate advisor,
how to sell specialized business intelligence
services, and the last one is creating these
living learning programs that stay current. It's
a totally different way to think about monetizing
what, you know, using these tools. Definitely.
So let's start with the tool itself, Perplexity.
Why is it fundamentally different, say, compared
to Google search or even some other AI chat tools.
Well, what's really fascinating, and I think
key, is the immediacy. You know, most older AI
models, they're trained on data that might be
maybe even months old. Perplexity, though, uses
the Internet right now. Right now. So if you're,
say, a market analyst, you could literally track
breaking news or watch stock trends shift or
see what's blowing up on TikTok. Like, as it
happens, that speed. That's a huge competitive
edge. Huge. And then there's the trust factor.
This is big. Every answer it gives includes clear
source links, you know, those little numbers
you see. That's how you, as a professional, prove
your points. You can cite authority. That ability
to instantly cite sources. That's incredibly
valuable if you're dealing with clients. You
can say, look, this finding, it's based on this
specific Forbes report, or this data comes from
a Stanford study. It's verifiable. Right. And
that ability, it enables much deeper conversations.
It's not like those single shot question and
answer tools. Perplexity lets you follow a real
research path. Start broad. then dig in, ask
follow -ups, iterate. It's like stacking Lego
blocks of information until you uncover those
non -obvious connections. And the Smart Summaries
feature, that feels like where the real leverage
comes in. The AI does the heavy lifting, right?
Reading multiple articles, pulling out the key
info, synthesizing it into one clear answer.
It frees you up from the grunt work of just gathering
information. Yeah, it does. But that brings up
a really important question, doesn't it? If the
AI is handling all that information gathering,
the rote stuff, Where does the human add the
value, the part someone actually pays for? That's
the core of it. We provide the thinking, the
analysis, the prioritizing, the context for making
decisions, and maybe most importantly, the wisdom,
turning that raw data into something truly useful
and actionable outcome. Precisely. It's that
wisdom, that judgment, that we're going to figure
out how to monetize with these methods. Okay,
so let's move into that first method for generating
income. building what the source calls citation
-worthy digital assets. The idea here is shifting
focus from just, say, writing a disposable blog
post to constructing something more permanent,
a digital asset that can potentially earn passive
income. Yeah, and the goal isn't just to answer
one question. It's about becoming the go -to,
most trusted, most complete source for a whole
specific topic area that you've targeted. And
that process starts with step one. You've got
to find the content gaps. And critically, you
use actual search data for this. You don't just
guess what people might want to know. Find those
questions people are asking a lot, but where
are the existing answers? They're just not very
good. Exactly. And this is where using a professional
prompt structure is absolutely crucial. You don't
just ask perplexity, you know, what should I
write about guitarist? That's way too vague.
Right. You need to instruct it more specifically.
Something like, act as an expert SEO analyst.
For the topic, acoustic guitar for adult beginners
identify subtopics that get high search volume
but lack comprehensive, high quality content
based on analyzing forums like Reddit and popular
guitar sites. Perfect. And that detailed approach
reveals really specific gaps. The example they
used was great. Singer pain for beginner guitarists.
Most articles just say, practice more, which
is frankly useless advice on its own. Yeah, totally
unhelpful. The gap is the lack of specific finger
strengthening exercises or maybe tips on getting
your guitar professionally set up to make it
easier to play. That's the actionable advice
that's missing. And that gap, that's where the
value is. That's your opportunity. Once you find
it, the article you create needs to deliver.
It has to provide a direct, simple answer right
near the top. And use specifics. Numbers. Proof.
Don't you say practice makes cords faster? Come,
get precise. Practicing these specific cord changes
for 15 minutes daily can reduce your change time
from, say, three seconds down to under one second
within about four weeks. That's concrete. That's
provable. So boiling it down, what's the absolute
key element that makes this digital asset trustworthy,
both for the AI search crawlers and for your
human leaders? Specific, accurate facts and proof
points. And crucially, Those facts need to be
backed up by verifiable sources that perplexity
itself can see and reference. That's the foundation.
OK, solid. Let's pivot to method two, then. This
one is about becoming a trusted advisor, specifically
using affiliate marketing. Yeah, this model is
interesting. It positions you as like a champion
for the consumer. Your income comes from helping
people make genuinely smarter buying decisions
and importantly helping them avoid the costly
mistakes, the lemons. So the core task here using
perplexity is to act almost like a detective,
a financial detective maybe. You're digging for
that hard truth that the stuff product marketing
teams often try to sweep under the rug. Exactly.
So you're prompting the AI really strategically,
like analyze all the one -star and two -star
reviews for this popular espresso machine, not
just on Amazon, but go look at Reddit threads,
check dedicated forums like homebarista .com,
list the top five most common technical complaints
people have. Or you could go beyond just features.
Calculate the real cost, ask the AI. Calculate
the total three -year cost of ownership for this
machine purchase price, plus the cost of replacement
filters, the special cleaning solutions. estimate
the electricity usage, now compare that total
cost with top three competitors. That comparison,
that's valuable content right there. Totally.
And then you frame your articles with these really
sharp angles. Things like five things you absolutely
must know before buying this. The unfiltered
truth from unhappy customers. Or maybe creating
comparison guides based on user types. You know,
why this product might be a disaster for a casual
user, but actually fantastic for a serious hobbyist.
You're giving tailored advice. Building that
long -term trust, though, that seems absolutely
crucial here. And it's probably not always easy,
I have to admit. Sometimes even I messle with,
like, prompt drift. Making sure my questions
to the AI are genuinely neutral. And I'm not
subconsciously nudging it towards recommending,
say, a product just because it has a higher affiliate
commission. Beat. Maintaining that integrity
takes real, constant effort. It's difficult.
It really, really does. Because one slip -up,
one lazy recommendation, or even just failing
to update an old review when a product changes
or has known issues, that can just shatter your
reputation instantly. Trust is incredibly fragile
online. But, okay, think beyond just the immediate
commissions. What's the real long -term asset
you gain from doing this affiliate advisor strategy
right? It has to be the loyal audience. People
who genuinely trust your recommendations and
keep coming back because they know you're giving
them the straight scoop, the honest advice. That
loyalty. That's the ultimate prize. That's the
sustainable value. Okay, let's explore method
three. This one sounds like it has the highest
income potential, providing high -value business
information services. Yeah, the idea here is
you essentially become the outsourced part -time
research department for small to medium -sized
businesses, SMEs. These are companies that need
sophisticated market intelligence but maybe can't
afford a full -time internal research team. You're
selling them professional answers packaged up.
Right, and you package it very clearly. Clients
aren't buying your time, they're buying a specific
product. Things like a deep dive competitor analysis
report or a monthly market trends briefing or
maybe a new market entry feasibility study. defined
deliverables. And just think about the complexity
of the research one person can manage now with
a tool like Proplexity. Imagine a client, say
a small company, wanting to launch a new artisanal
coffee brand, maybe specifically targeting Hanoi
in Vietnam. Okay, yeah. That professional prompt
you'd feed, Proplexity would be intense. You'd
be asking it to do a lot. Analyze competitor
pricing, find out where they're selling online,
specific cafes, retail locations, what's their
social media strategy, then... Gather demographic
and psychographic data on the target customer,
say 25 to 35 -year -olds in Hanoi. What are their
buying habits? Where do they hang out? Then,
based on all that, recommend a channel strategy.
Should they use local influencers? Focus on events.
And finally, list the specific risks and opportunities
for entering that market. Slowing down slightly.
Whoa. I mean, just pause and think about that.
The amount of traditional consulting work, the
cost associated with generating a report that
deep. We're talking thousands, maybe tens of
thousands of dollars. And now, potentially, one
person with the right skills and the right AI
partner could generate that level of insight
in hours, maybe days. That scalability, that
power in the hands of one person, that's pretty
revolutionary. That's the moment of wonder right
there. It really is. But here's the catch. Just
dumping raw data on a client, that's useless.
No CEO has time for that. The real value, the
part you monetize heavily, is turning all that
data into a compelling narrative. You must provide
an executive summary, one page, talks hitting
the key findings and clear recommendations for
that busy executive. And those recommendations
need to be shark -specific, actionable. Don't
just say, oh, the Hanoi market looks promising.
No. Say, based on the data, you should collaborate
with these five specific food bloggers. Or consider
opening a pop -up shop in the Tejo district during
the lead -up to the Tet holiday. concrete steps.
Okay, so here's the strategic question then.
If the underlying data itself is becoming more
accessible, potentially to anyone with a perplexity
subscription, what are clients really buying
from you, the human advisor? Confidence. They're
buying the confidence to make expensive, high
-stakes business decisions based on your analysis
and interpretation. That's it. Confidence is
the product. Okay, moving to our final method,
method four, building what are called living
learning programs. The problem this tackles is
pretty obvious to anyone who's got an online
course. They get outdated, fast, especially in
tech or marketing fields. So your competitive
advantage here isn't selling a static course,
it's selling freshness. You sell a knowledge
update service, usually through a subscription
or a membership model. Right, and you use the
AI, again strategically, to design a course that's
perpetually better than the competition. How?
You prompt perplexity to analyze the content
and the student reviews of, say, the five top
-selling courses in your niche on platforms like
Udemy or Coursera. OK, so you're using AI to
basically perform competitive intelligence on
other courses. And that analysis instantly highlights
maybe advanced topics they missed, or more likely,
recent algorithm changes or new platform features
that those older static courses haven't covered
yet. You build your curriculum specifically around
what's currently missing elsewhere. Exactly.
And the key is structuring the program itself
for easy, ongoing updates. You might set it up
like part one is the foundational stuff, the
basics that don't change much. Part two covers
core strategies, but you commit to updating that
section every, say, three months. And part three
is maybe a news and trends module that gets refreshed
monthly with the latest developments. And the
marketing angle flows directly from that structure.
You position your program explicitly on the promise
that it is the most up -to -date source of practical
knowledge in that specific industry. That commitment
to freshness justifies the subscription model
and hopefully creates stable recurring revenue.
So thinking about that model. What's the value
proposition for the teacher running the program
and for the students subscribing? For the teacher,
it's stable, predictable income, which is huge.
For the student, it's the confidence that they
always have access to the best, most current,
most relevant knowledge to succeed in their field.
Win -win. Yeah, that makes a lot of sense. So
that gives us four really practical frameworks.
Pulling it all together, the big idea seems crystal
clear. AI isn't about replacing human expertise.
Not at all. It's here to augment us, to make
us better, faster, more capable. The future really
belongs to those individuals who learn how to
partner effectively with AI to tackle complex
problems, problems that maybe seem too big or
too time -consuming before. Absolutely. And to
make that partnership successful, the source
material highlighted four critical mistakes that
professionals need to avoid when they start using
these powerful tools. Number one, you absolutely
must be specific in your requests. That's right.
The old way, the sort of amateur approach, is
asking a vague question like, how do I do marketing?
You'll get a generic, useless answer. The professional
way is much more detailed, like create a comprehensive
three -month marketing plan for a new B2B sauce
product. The target audience is tech startups
with 1050 employees. The total budget is under
$5 ,000. Focus exclusively on digital channels
like LinkedIn ads, targeted email, and maybe
one relevant industry webinar. Outline key metrics
for success. See the difference. That kind of
prompt gives you something you can actually work
with immediately. Huge difference. OK, mistake
number two to avoid. You have to dig deeper.
Never, ever just accept the first answer the
AI spits out. You need to constantly push it.
Ask why. Ask, what are the potential risks or
downsides of this approach? Ask, can you provide
three alternative examples or strategies to your
probing? Number three is about integrity. You
must be honest and accurate, always. This means
taking that extra step to verify the original
sources that perplexity provides in its citations.
Double check the facts. Your professional credibility
is entirely built on that foundation of accuracy.
Don't get lazy here. It's so important. And the
final one, number four, you have to understand
the why. Remember, the AI is brilliant at providing
the what, the data, the information and synthesis,
the summaries, but the human, you, provide the
so what. The interpretation, the strategic insight,
the ethical considerations, the wisdom, that's
your unique contribution. It really feels like
we're in this golden window of opportunity right
now. These AI tools like Perplexity are incredibly
powerful, but the knowledge of how to apply them
professionally, strategically, that's still relatively
rare. building that skill set now, learning how
to genuinely work with AI, that's what will establish
you as an expert, maybe even a leader, in the
very near future. Yeah, think about it. Soon,
maybe in just a few years, basic AI literacy
might be as common and expected as knowing how
to use a spreadsheet or send an email. The people
who started today, who put in the effort now
to master these collaborative workflows, they'll
be the ones who are already established, the
recognized leaders, when everyone else is just
catching up. So let's leave our listeners with
a final thought to mull over. A provocative question,
perhaps. If AI truly is this tireless, incredibly
capable research partner available 24 -7, what
complex human problem, maybe something in your
field or even a societal issue that you previously
thought was just too complex, too data -intensive,
too time -consuming to even attempt to solve?
What problem can you now realistically tackle?
That's the challenge. Pick one of those four
strategies we talked about, building digital
assets, becoming that trusted advisor, offering
high -value business info services, or creating
living learning programs. Choose one that resonates,
and then start that conversation. Start working
with your AI research partner today. That's genuinely
how you step into the future of high -value,
meaningful work.