Have you ever had that feeling, that little flicker
of annoyance? You ask a powerful AI, you know,
maybe chat GPT, for something simple. Yeah. Like,
just a short email. Maybe a summary. And what
comes back is confusing. Or super complicated.
Right. Overly complicated, or sometimes just
plain wrong. Uh -huh. And you spend, what, 10
minutes trying to fix it, and then you just go,
you know what? Forget it. I'll just do this myself.
It's faster. It feels faster. Mm -hmm. And that
happens because... Honestly, most of us, we're
using these incredibly powerful AI tools kind
of the wrong way. How so? We treat them like
a slightly smarter Google, a talking search engine.
And we're just missing the real potential there.
OK. Welcome to the deep dive today. Our mission
is really to get past that basic prompting that
surface level stuff and unlock the actual efficient
power hidden in generative AI Yeah, absolutely.
We boiled it down to six simple skills and these
aren't like coding skills or anything super technical.
They're more like Shifts in how you approach
it and these shifts can turn AI from being this
frustrating roadblock into a genuinely efficient
teammate One that actually gives you what you
need. Okay, so let's map this out. We're going
to cover the whole workflow, basically. Starting
with building your toolkit, your AI team, if
you will. Right. Then getting really clear on
what you want before you pipe anything. Crucial.
How to give clear instructions, the absolute
necessity of checking the AI's work. Verification,
yeah. Then using these tools together, stacking
them, and finally adding that indispensable human
touch, the polish. Okay, let's dive in. Skill
number one. Which is... Stop trying to make one
tool do everything. This is, I think, the biggest
foundational mistake. People grab one AI, usually
Chad GPT, and expect it to handle 100 % of their
tasks. Right. But that's just, it's illogical,
isn't it? Like, you wouldn't hire a fantastic
baker to fix your motorbike. No. Or ask your
accountant to design the company logo. Doesn't
make sense. Right, and yet we somehow expect
one single AI model to write great emails, analyze
complex spreadsheets, draft code, and create
stunning images. It's setting it up to fail.
You need specialists, a team. Exactly, a team.
I like to group them into three main categories
that you really need. First up, the brains. Okay.
These are your large language models, the LLMs.
They're the generalists, the thinkers. Good for
talking, writing, brainstorming, that kind of
stuff. And knowing the specific ones helps, because
they do have different strengths. Like, chat
GPT is kind of the Swiss army knife, right? Good
for first drafts, quick ideas. Collectible, but
Gemini, because it's Google, tends to be better
if you need something about current events or
recent news. It's more plugged in. For sure.
And if you need writing that feels really human,
my personal favorite is Claude. I find it's consistently
better for more, say, emotional writing, like
a blog post. Or, and this is key, summarizing
really long documents. Like, if you throw a 100
-page PDF at it, Claude generally handles that
long context better than others. Interesting.
OK, so that's the brains. Group two. The researchers.
And this is critical. You really shouldn't trust
a brain AI for hard facts, ever. Right. You need
a dedicated fact checker. Yeah. For me, Perplexity
is a daily driver. It's essentially a much better
search engine because it shows its work. How
so? It gives you the information, but also shows
exactly where it came from with direct links
you can check, verifiable sources. It's a must
have. OK. And then there's Notebook LM. Which
is pretty fascinating. It doesn't search the
web. It searches your stuff. My own documents.
Your uploaded notes, PDFs, research papers. You
can basically have a conversation with your personal
library. Wow, okay. And the third group. The
creators. These are for visuals. Yeah. The Journey
is famous for those incredibly detailed, often
beautiful images. But you have to use Discord,
which is a bit of a hurdle for some. It is, yeah.
But then there's ideogram. An ideogram is fantastic
for one... really practical reason. Which is?
It's actually pretty good at putting text, like
words, onto images without messing it up completely.
Ah, the classic AI text problem. Exactly. It's
still a major weakness for most image AIs, but
ideogram handles it much better. So for someone
just starting out, what's the minimum toolkit?
Keep it simple. Start with one brain, maybe chat
GPT, one researcher, definitely perplexity, and
maybe one creator. like ideogram, if you need
images with text. So the big takeaway here seems
to be that separating the thinking tools, the
brains, from the fact -checking tools, the researchers,
is absolutely fundamental. Absolutely. It prevents
those confident -sounding factual errors right
from the start. It avoids misuse. So why is separating
tools by function brains versus researchers the
foundational step for mastery? Because it stops
powerful LLMs from confidently making stuff up
when you need accuracy. prevents fabricated facts.
OK, that makes sense. Which brings us neatly
to skill number two. Clarify the problem. Know
what you actually want. Yes. This is probably
the single biggest time saver. What do beginners
usually do? They open chat GPT and just type
a vague thought, right? Experts. They pause just
for like 30 seconds. They think first. Because
if your question isn't clear, the answer you
get back is never going to be clear. It sounds
simple, but. Think about it like this. The I'm
hungry analogy. If you call a friend and just
say, hey, I'm hungry. What can they do? Not much,
right? Right. Where do you start? But if you
say, OK, I'm hungry. I'm feeling like Vietnamese
food, but nothing spicy. And I've got about $100
budget. Now what happens? Yeah, they can actually
help. They have specifics. Exactly. They can
act immediately. AI is like that helpful but
naive friend. It needs specifics. So I always
recommend this quick 30 second pause checklist
before typing. OK, what's on it? First. What
is the real, specific, final result I need? Not
just write an email. More like... More like,
write a polite email to my boss asking for next
Friday off, making sure to mention that Project
X and Report Y are already completed. See the
difference. Yeah, much clearer. Okay, what's
next? Second, who is this actually for? The audience's
everything for tone is for your boss, an angry
customer. You're friendly social media followers.
That changes everything. Vocabulary. Formality.
Right. Third. Third. What does a good answer
look like, structurally? Do I want a bullet point
list? A short, concise paragraph? Maybe a table
comparing options? Define the format. So those
details, the goal, the audience, the format,
those are the constraints the AI needs to succeed.
They are. And honestly, I gotta admit something
here. I won. Even now, I still sometimes wrestle
with prompt drift myself. and the conversation
goes off track. It usually happens when I rush
and skip this initial planning step. So it happens
to everyone. Oh, yeah. We all fall into that
trap of vagueness if we don't consciously pause
and clarify first. So how does pre -defining
the desired final result format save the most
time? A clear problem is 90 % of the solution
beat. It just cuts out all that back and forth
editing. Right. It eliminates the need for endless
revisions because you got closer the first time.
Precisely. And if avoiding edits is the goal,
that leads us right into skill three. Communicate
well, giving clear instructions. You mentioned
prompting. Yeah, and I kind of hate that word
prompting. It sounds so technical, so jargon
-y. Just think of the AI like a brand new assistant.
Super smart, incredibly tireless, never gets
bored, but also completely naive. They need really
clear step -by -step instructions to do good
work. You can't just hint at things. OK, but
wait. A lot of the advice you see online involves
using these really complex multi -part frameworks
for prompts, like a six -part structure. Doesn't
that feel like writing a whole project plan just
to ask for an email? Is that really faster than
just typing a simple request? Seems like overkill.
It can feel like overkill up front. I get that.
But it's about structure. And that structure
actually saves you time down the line, especially
for important tasks. It gives you a repeatable
formula. So the six -part framework, what is
it? It's basically a checklist to make sure you
cover all the bases. Role, context, task, format,
rules, and sometimes an example. Okay, let's
see it in action. Like a bad prompt versus a
good one. Sure. Bad prompt. Write a social media
post about drinking water. Vague. Generic. What
do you get back? Probably something boring. Totally
boring. Now the good prompt. Using the framework,
role. You are a friendly, knowledgeable health
expert. Okay, persona set. Context. This is for
busy office workers scrolling Facebook during
their lunch break. Audience and platform. Got
it. Task. Write a 100 -word post focusing on
three surprising benefits of staying hydrated.
Specific action. Format. Start with an engaging
question. Use bullet points for the benefits.
End with a simple call to action. Structure defined.
Rules. Do not use complex medical jargon. Keep
the language simple and encouraging. Boundary
set? Example. Maybe use a style like this. Feeling
that 3 p .m. slump. Maybe you just need water.
Ah, so you give it a style guide too. That detailed
prompt completely changes the game. Right. It
turns that vague idea into a concrete, executable
plan that the AI can actually follow properly.
So beyond just complexity, what's the most important
role that six -part framework fills for a beginner?
It structures scattered thoughts, beat, turns
ideas into an actionable project plan for the
AI. OK, that makes sense. What other techniques
help with communication? Technique two is one
I really love, especially with newer AIs. Show
it. Don't just tell it. I mean. Use the vision
capabilities. Instead of spending five minutes
trying to describe, say, the simple and clean
aesthetic of a website you like. Which is hard
to describe accurately. Right. Just take a screenshot
and upload it. Say, match this style. The result
is usually way faster and 10 times closer to
what you wanted. Oh, that's smart. OK, technique
three. Ask the AI for help. Seriously. If you
get a boring answer, tell the AI, say, that last
response was a bit dull. How could I rewrite
my prompt to get something more creative or fun?
Use its own knowledge against it, kind of? Exactly.
Leverage its understanding of how it works best.
It often gives great suggestions for improving
your own prompts. and technique four. Do it again,
but better. This is simple but powerful. After
the AI gives you an answer, just ask it. Okay,
read your answer again. Find three specific things
you could improve. Then give me the new, better
version. Huh, you make it critique itself. Yep.
You basically build in a quality control loop
without doing the editing yourself initially.
So by using these frameworks and techniques,
we shift from just asking for stuff to actually
directing a process, directing the AI. That's
the perfect way to put it. You're the director.
And now that we have the content created, we
absolutely need to talk about safety verification.
Right. The trust issue. OK, let's take a quick
pause here. And when we come back, we'll tackle
verification and how to combine these tools effectively.
Mid -roll sponsor break. Welcome back to the
deep dive. We've talked about choosing tools,
clarifying intent, and communicating effectively.
Now let's hit skill number four, verification,
addressing that big fear. Yeah, this is probably
the number one concern people have, right? Using
wrong information from AI. And the hard truth
is AI can be a very, very confident liar. They
call it hallucination. Right. Which is just a
fancy word for making stuff up. Right. But it
does it with such confidence. Yeah. So your mantra
has to be, trust, but always check. OK. So how
do we check? Method one. Use the researcher tool
we talked about earlier. Never, ever take a specific
fact or number from a brain AI like ChatGPT at
face value. And never. Not if accuracy matters.
So if ChatGPT says, studies show 80 % of office
workers experience back pain, What do you do?
Check it somewhere else. Exactly. Copy that exact
sentence. 80 % of office workers have back pain
and paste it straight into perplexity. And perplexity
will? Perplexity will go find actual studies
and sources. It might come back showing, well,
study A found 60%. Study B over here found 75%.
And crucially, it will give you the links. Ah,
so you get the real data plus the proof. Precisely.
Now you have reliable information, not just an
AI's assertion. OK, that's solid. Method two.
Force the source. Ask the AI directly within
the chat. Where did you get that specific piece
of information? Can you give me the name of the
original article or study or maybe a link? And
what if it avoids the question? That's your red
flag. If it gives you a vague answer like, as
an AI language model, I access information from
a vast database. The classic dodge. That's a
huge warning sign. I probably fabricated it.
Oh, and a little trick here. Start the conversation
by explicitly giving the AI permission to not
know. What do you mean? Tell it right at the
beginning. Hey, if you're not sure about something
or you don't know the answer, please just say,
I don't know. Ah, that lowers the pressure for
it to invent an answer. Exactly. It preempts
some of the fabrication tendency. It's smart.
OK, method three for verification. Get a second
opinion. This is super easy. Take the answer
you got from one AI, say chat GPT, copy it, and
paste it into a competitor. Go ask Claude or
Gemini, can you review this answer? Are there
any mistakes or important things missing? Use
AIs to check other AIs. Yep. They're often surprisingly
good at catching each other's errors or omissions.
It takes maybe 10 seconds and significantly boosts
your confidence in the result. Why is deliberately
asking the AI to show its source so essential
now? It directly challenges the AI's tendency
to make things up with total confidence. BEAT
confronts that confident fabrication head on.
Okay, so verification is non -negotiable for
building trust. That leads us to skill five,
combine your work, stacking the tools. Right,
because the real magic, the real efficiency boost,
happens when you get these specialized tools
working together. Think of it like a band again.
Okay. You don't just want a drummer. You need
the drums, the guitar, the bass player, the singer,
each specializing. but playing together in harmony.
And we're talking about manual stacking here,
right? Where we are the ones coordinating the
different tools. Exactly. You are the director,
passing the work from one specialist to the next.
Automation with things like Zapier or N8N is
possible later, but master this manual stacking
first. Let's walk through an example. Say the
goal is a well -researched blog post about hobbies
that reduce stress. How does the stacking work?
Okay, step one, the researcher. You go to perplexity,
ask it. Find five science -backed hobbies proven
to reduce stress. Please include links to the
studies or sources. Proplexity does that, gives
you the list with verification. Okay, research
done. Step two. Step two, the brain. You take
that verified research from Proplexity and go
to Claude, maybe. Why Claude? Because we want
a warm, engaging tone, right? So you give Claude
the role. You're a warm, empathetic, mental health
blogger. Got it. Then you give it the research
and the task. Write a 500 -word blog post based
only on the provided research points about these
five hobbies. Based only on the research. Key
constraint. Crucial. So Claude writes the draft.
Now step three. The visuals. The creator. Exactly.
You go to ideogram, you ask it to create a custom
image, maybe something cozy, showing someone
watering plants or knitting, matching the blog's
theme. Okay. So research, write, illustrate,
using specialized tools for each step. And what's
the result? in maybe, I don't know, 15, 20 minutes.
You have a thoroughly researched, well -written
blog post with custom visuals. The quality you
get from that workflow, it's just leagues beyond
asking one single AI to write a blog post about
stress. Whoa. Yeah, I can see that. And imagine
scaling that kind of researched quality workflow
across tons of different... tasks or queries.
That's the transformative potential right there.
Real efficiency, but also high quality. So what's
the biggest advantage of this manual stacking
compared to just using one tool? Guaranteed quality
by using each tool's proven strength for its
specific job. Beat. Leverage a specialization
for a better outcome. Excellent. Okay, that brings
us to the final, and you said maybe the most
crucial, skill. Skill number six, the human polish.
Yes, the final touch. Because, let's be honest,
a lot of raw AI content, it feels Cold. Generic.
Corporate. Yeah, all of that. Yeah. Devoid of
real personality. And the second a reader senses,
oh, a robot wrote this. What happens? They disconnect.
They stop trusting it. Exactly. Because AI, for
all its power, lacks three key human elements,
vision, taste, and care. And providing those,
that's still our job. OK, I understand the goal
making it feel human. But isn't spending time
polishing the text after the AI did the heavy
lifting kind of inefficient? If the goal is speed.
Why slow down at the very end? That's a fair
question. But think about the 80 -20 rule. Primitive
principle. Right. Let the AI handle the 80 %
of the initial draft, the research compilation,
the outlining. That's where the massive time
savings are. But that last 20%, that's the human
polish. And that 20 % is where the value is added.
That's where you turn a fine or OK draft into
something genuinely great, something that connects,
that people actually trust, remember, and share.
It's the difference between competent and compelling.
Okay, I am sold on the why. Now how? What does
this human polish actually look like in practice?
Technique one. Technique one. Add your voice.
Inject your vision. AI gives you general truths.
You replace them with specific stories, anecdotes,
personality. Insanity. AI might write, consistency
is key to achieving fitness goals. Which is true,
but, eh. Your human polish adds a story. My old
track coach used to hammer this into us. He'd
say you don't get faster on the days You feel
great and want to run you get faster on the days.
It's raining You're tired and you run anyway
much more memorable connects better. Okay technique
to cut the AI words Exercise your taste AI loves
empty formal jargon like what? Oh, you know In
the context of furthermore a it is imperative
that In today's fast -paced digital world, ugh.
Yeah, those definitely scream AI -generated.
Delete them. Simplify the language. Make it sound
like a real person talking. Use shorter sentences.
Use contractions. That's taste. Got it. And technique
three. Add connection. Show some care. Insert
empathy. AI is often very cold and instructional.
Example of that. Yeah, might output. Users experiencing
login difficulties should follow the prescribed
password reset procedure. Super robotic. You're
already detached. Your human polish changes it
too. I know it's incredibly annoying when you
get locked out of your account. Honestly, we've
all been there. Here's the quickest way to reset
your password. That little bit of empathy, we've
all been there, totally changes the feeling.
Completely. It shifts the dynamic instantly.
How does adding personal stories and empathy
fundamentally change the reader's relationship
with the content? It moves it from machine -to
-machine instruction to human -to -human connection.
Beat. Builds trust and relatability instantly.
Okay, let's pull this all together then. A recap
of the process. Yeah, let's summarize. We covered
the six core skills. First, choose your specialized
tools. Build that AI team. Second, clarify your
problem before you start typing. Know your goal.
Third, communicate clearly used frameworks. Show,
don't tell. Fourth, and this is huge, verify
the facts. Always check the AI's work, especially
with researchers. Fifth, combine tools through
stacking used specialists for each step. And
sixth, finish with that crucial human polish,
add your voice, taste, and care. Essentially,
AI is the incredibly capable doer. But you are
the director. You're guiding the process, ensuring
quality, adding the value. So for listeners,
what's the first step? It feels like a lot to
implement all at once. Oh, definitely don't try
to master all six today. That's overwhelming.
Just pick one skill to focus on this week. Seriously,
just one. Like maybe. Maybe just really commit
to using that six -part framework for your next
important prompt. Or maybe just build the habit
of always running AI facts through perplexity.
Just one small change. Exactly. Even just doing
the verification step consistently will dramatically
improve your results and safety almost overnight.
Okay. So here's a final thought to leave everyone
with. Something to chew on. If AI can now reliably
handle, say, 80 % of the grunt work, the research,
the drafting, the summarizing, then maybe the
new essential human skill in this era isn't really
about becoming a master prompt engineer or knowing
the tech inside out. Maybe it's shifting more
towards cultivating taste, expressing empathy,
and having a clear vision. Interesting. If basic
content production is becoming commoditized,
almost solved, what entirely new kinds of creative,
strategic, or editorial roles might emerge that
really lean into those uniquely human skills?
What does work look like when the doing part
is largely automated? That's a deep question.
Something to really think about. Thanks for tuning
in to the Deep Dives, everyone. OTero music.