November 3, 2024 • 10 mins
💡 Unlocking the Power of Prompt Engineering! 💡
In this informative episode, our AI hosts, Kai and Sarai, explore the essential strategies for crafting effective prompts from the insights of two key documents.Â
What makes a prompt clear and specific?
Discover how context, iteration, and the integration of external tools can enhance your results with language models.
With tips on decomposing complex tasks and optimizing prompts for Google Workspace, this episode will elevate your prompt engineering skills to the next level!
In this informative episode, our AI hosts, Kai and Sarai, explore the essential strategies for crafting effective prompts from the insights of two key documents.Â
What makes a prompt clear and specific?
Discover how context, iteration, and the integration of external tools can enhance your results with language models.
With tips on decomposing complex tasks and optimizing prompts for Google Workspace, this episode will elevate your prompt engineering skills to the next level!
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:00):
Hey, everyone, welcome back. Ready to dive into something really interesting.
Speaker 2 (00:03):
Today absolutely should be a good one.
Speaker 1 (00:05):
We're talking all about prompt engineering, which.
Speaker 2 (00:07):
Is becoming a seriously sought after skill set these days.
Speaker 1 (00:11):
It really is, And I think sometimes people hear prompt
engineering and think, oh, that's for the AI experts.
Speaker 2 (00:16):
Right, Like, it takes years of study to master.
Speaker 1 (00:19):
Exactly, but it's way more accessible than it sounds.
Speaker 2 (00:23):
It really is. At its core, prompt engineering is basically
about how to talk to AI, so it actually gets you,
you know.
Speaker 1 (00:29):
Yeah, how to get the results you actually want exactly.
Speaker 2 (00:31):
Because as AI tools become more integrated into everything.
Speaker 1 (00:36):
Our workflows, our creative projects, everything.
Speaker 2 (00:38):
Yeah, knowing how to clearly articulate your needs to these
AI tools can be the difference between like having a
helpful assistant totally and just having this frustrating experience where
you're like, why aren't you understanding me?
Speaker 1 (00:52):
Like, come on, I know you can do this exactly. Okay,
So before we get into the nitty gritty, let's make
sure we're all on the same page.
Speaker 2 (00:59):
So that's good.
Speaker 1 (01:00):
We've got to talk about these things called large language.
Speaker 2 (01:01):
Models, right, which is a mouthful.
Speaker 1 (01:03):
It sounds very intimidating, very technical.
Speaker 2 (01:06):
Yeah, it sounds way more complex than it really is. Basically,
imagine a system that has read more text than any
human ever could in a million lifetimes.
Speaker 1 (01:17):
Like the entire Internet and then.
Speaker 2 (01:19):
Some pretty much we're talking books, articles, code, everything. You
can imagine, it's absorbed at all.
Speaker 1 (01:25):
Wow.
Speaker 2 (01:26):
And that's essentially what a large language model is. And
it uses that vast knowledge base to try to understand
your requests and then hopefully respond to them in a
meaningful way.
Speaker 1 (01:36):
So it's like having access to this incredible library, but
we need to know the right keywords.
Speaker 2 (01:41):
Yes, a perfect analogy. You need to know how to
search for what you're looking for, right, You're not just
going to wander around aimlessly.
Speaker 1 (01:47):
Exactly, don't get lost in the stacks, precisely.
Speaker 2 (01:50):
And that's where prompt engineering comes in.
Speaker 1 (01:52):
It's the key.
Speaker 2 (01:53):
It's about moving beyond just simple questions like you know
what's the weather, and learning how to communicate with AI.
That unlocks its full potential.
Speaker 1 (02:02):
Which I think we all want because these AI tools
are just getting more and more powerful.
Speaker 2 (02:07):
Oh. Absolutely, the possibilities are pretty much endless. It's really
quite exciting, and that's what we're going to dig into today.
Speaker 1 (02:14):
Yeah, and we've got two really interesting sources we're going
to be drawing from.
Speaker 2 (02:18):
Perfect lay it on me.
Speaker 1 (02:19):
So we've got this technical guide. It's great. It breaks
down the mechanics of prompt engineering, so almost like a
workshop manual. I like it, like how to actually craft
the perfect command?
Speaker 2 (02:31):
Awesome? What about the second source?
Speaker 1 (02:32):
The other one's cool. It's a fascinating look at how
prompt engineering is actually being used in the real world
in different professions.
Speaker 2 (02:40):
Because it's not just for coders, is it.
Speaker 1 (02:42):
No, not at all, Writers, marketers, educators.
Speaker 2 (02:44):
Really, anyone who interacts with AI at all.
Speaker 1 (02:47):
Probably exactly. Yeah, Because at the end of the day,
it's about communication, right, and everyone can benefit from communicating
more effectively.
Speaker 2 (02:55):
Okay, So I'm excited. Whether you're just looking to like
stream line your workflow, sure, or you're ready to unlock
some serious next level AI wizardry.
Speaker 1 (03:06):
I love it. We've got something for everyone here today.
All right, So let's dive into some of these strategies
for prompt engineering because I'm ready to level up my
prompt game.
Speaker 2 (03:14):
It's like learning the secret handshake.
Speaker 1 (03:16):
Yeah, exactly. I want to go from novice to like prompt.
Speaker 2 (03:20):
Pro I love it. And you know, the good news
is a lot of these strategies they're really rooted in
common sense.
Speaker 1 (03:25):
Okay, that's good to hear.
Speaker 2 (03:26):
It's not about like knowing some secret code or anything.
Speaker 1 (03:30):
Right, because I mean, we see these AI tools do
amazing things.
Speaker 2 (03:35):
It's true they can be really impressive, but at.
Speaker 1 (03:37):
The end of the day, they're operating on the instructions
that we give them precisely.
Speaker 2 (03:42):
They're not mind readers, not yet anyway. And that's where clarity.
Speaker 1 (03:46):
Comes in, right, so important.
Speaker 2 (03:47):
Our sources really emphasize this. Being crystal clear in your
prompts is absolutely crucial.
Speaker 1 (03:53):
So it's like if you're explaining something to a friend,
you know, the clearer you are, the better they'll understand exactly.
And AI is no different.
Speaker 2 (04:01):
It's the same thing with AI. Don't be afraid to
like over explain, especially when you're dealing with complex tasks,
you know, instead of just saying, write me a report
on climate change.
Speaker 1 (04:12):
Yeah, that's pretty broad.
Speaker 2 (04:13):
Right, You want to be specific. What kind of data
are you looking for, what timeframe, what are the key
arguments you want to address? So give it the structure
basically totally, and that actually leads us to another really
key strategy, which is breaking down those complex tasks.
Speaker 1 (04:27):
Okay, good to know, because some of the stuff I
want to do is a little complex.
Speaker 2 (04:30):
It makes a huge difference. See, AI, it can only
handle so much information at once, right, Like, just like
you wouldn't try to eat a whole pizza in one
byte one byte, Yeah no, you got to break it down,
make it manageable, smaller chunks exactly. So you do the
same for AI. You break those large tasks into smaller,
more digestible.
Speaker 1 (04:50):
Steps, divide and conquer exactly.
Speaker 2 (04:52):
And here's a little bonus tip. When you break down
a task like that, you're essentially creating a step by
step process for the AI, like a to do list.
Yeah yeah, and you can actually tell the AI to
follow those steps explicitly, which can really improve accuracy, you know,
and it gives you more control.
Speaker 1 (05:10):
Oh interesting, So you're not just telling you what to do,
but how to do it exactly, like a roadmap.
Speaker 2 (05:15):
I love that analogy. A roadmap. It's perfect. And speaking
of control, another really powerful technique is actually specifying the
output that you want.
Speaker 1 (05:24):
Oh interesting.
Speaker 2 (05:25):
Okay, don't just accept whatever the AI spits.
Speaker 1 (05:28):
Out, you know, don't just take it at face value.
Speaker 2 (05:30):
Exactly, you have the power to actually shape those results. So,
for example, instead of just letting the AI write you
a paragraph, you can say, hey, give me a bullet
point summary of this, or I need this in a
table format, or even write this in a specific tone
of voice.
Speaker 1 (05:47):
Oh like, if I need to sound like really formal.
Speaker 2 (05:49):
For something precisely, you can say, you know, write this
like a news headline, or I need this to sound
really encouraging and upbeat, whatever it might be.
Speaker 1 (05:57):
That is amazing.
Speaker 2 (05:58):
Okay, you're basically giving the A a blueprint for the
kind of response you want.
Speaker 1 (06:02):
It gives you so much more control.
Speaker 2 (06:04):
Exactly. You're no longer just a long for the ride.
You know, you're in the driver's seat.
Speaker 1 (06:10):
I'm into that. Yeah, And that's what.
Speaker 2 (06:11):
It's all about. It's about understanding how to communicate effectively
with AI to get the results you need.
Speaker 1 (06:17):
Okay, So we've covered a lot of ground here, but
I'm seeing in our notes that things get even more
interesting when we start talking about advanced prompt engineering techniques.
Speaker 2 (06:28):
Oh yeah, this is where it gets really fun.
Speaker 1 (06:30):
Okay, fun, I like it. So are you ready to
blow my mind a little bit?
Speaker 2 (06:33):
I think so get ready, because when I first started
exploring some of this stuff, it really blew my mind. Okay, good,
It's like, you know, you're stepping behind the curtain and
you start to see how the AI actually works.
Speaker 1 (06:44):
Yeah, like you're getting under the hood a little bit exactly.
Speaker 2 (06:47):
And one of the things that really fascinates me is
this idea of giving an AI a memory.
Speaker 1 (06:52):
Giving it a memory, what did they even mean?
Speaker 2 (06:55):
So it's almost like teaching the AI to take notes
as it reads, right, right, Because these large language models,
you know, they have a limited window of how much
information they can process at once.
Speaker 1 (07:05):
It's like their short term memory or something exactly.
Speaker 2 (07:08):
It's like short term memory. So you know, if you
feeded a whole research paper.
Speaker 1 (07:12):
For example, Yeah, it's a lot of info.
Speaker 2 (07:14):
There's a good chance it's gonna forget what it read
at the beginning by the time it gets to the end.
Speaker 1 (07:18):
Oh that makes sense, okay, right.
Speaker 2 (07:19):
And that's where this technique comes in.
Speaker 1 (07:21):
Okay.
Speaker 2 (07:21):
You can train the AI to basically summarize each section
as it goes, and it creates this kind of condensed
version of everything it's.
Speaker 1 (07:30):
Learned, so later on you can ask it about the
whole thing.
Speaker 2 (07:34):
Exactly instead of just like the last couple of paragraphs
it's processed. That's really cool, right, It's a game changer.
You can say, like, hey, you know, what were the
key arguments against this particular theory.
Speaker 1 (07:45):
And it can go back and pull from the whole thing.
Speaker 2 (07:47):
It remembers from the whole document, not just the conclusion.
Speaker 1 (07:51):
That would have been so helpful for like my thesis.
Speaker 2 (07:54):
Oh my gosh, right, think of all the time it
could save you.
Speaker 1 (07:57):
Okay, So we're giving our AI a long term memory.
Speaker 2 (07:59):
Now, exactly, extending that capacity.
Speaker 1 (08:03):
Love it. Okay. So, speaking of like getting more out
of AI, there's another advanced technique that I wanted to
ask you about, and it's this idea of making the
AI think before it speaks.
Speaker 2 (08:14):
Yes, it sounds kind of strange when you say it
like that.
Speaker 1 (08:17):
It does sound a little strange yeded like what does
that even mean?
Speaker 2 (08:20):
But it's really cool, I promise, because you know, sometimes
if you just ask the AI for an answer directly,
it might just rush to a conclusion, you know what I.
Speaker 1 (08:28):
Mean totally It just wants to please.
Speaker 2 (08:30):
Yeah, it wants to give you an answer, so it
might jump the gun a little bit and miss some
of the nuance.
Speaker 1 (08:35):
You know, Yeah, like that friend who just blurts out
an answer before you've even finished asking the question exactly.
Speaker 2 (08:41):
But if you actually prompt the AI to kind of
walk through the problems step by step, almost like show
its work, you know, Okay, it often arrives at a
much more nuanced and a much better reason to answer.
Speaker 1 (08:52):
Oh interesting, So you get a better result and you
get to see how it got.
Speaker 2 (08:55):
There exactly, Yeah, which is so valuable because it allows
you to understand like it's thought process.
Speaker 1 (09:01):
You get to peek inside its brain a little.
Speaker 2 (09:03):
Bit exactly, and that can help you refine your prompts
even more, right, because the more you understand how it's thinking,
the better you can guide it.
Speaker 1 (09:09):
Wow, Okay, we've covered some seriously cool stuff today. I
feel like we've gone from like AI one oh one
to some seriously next level stuff.
Speaker 2 (09:19):
That's a whole new world, isn't it.
Speaker 1 (09:20):
It really is? So any final thoughts for our listeners
before we wrap things up today.
Speaker 2 (09:25):
You know, I think the biggest takeaway here is that
prompt engineering it's not this mysterious art, right, It's not
just for like coding geniuses or AI experts.
Speaker 1 (09:35):
It felt a little intimidating at first.
Speaker 2 (09:37):
I'm not gonna lie, right, but like we were saying,
it really is a skill, you know. It's like learning
a new language. Yeah, And like any language, the more
you practice, the more fluent you become.
Speaker 1 (09:47):
So it's really about understanding how to communicate effectively with
these really powerful tools.
Speaker 2 (09:52):
That we have exactly, and they're just going to become
more and more prevalent in our lives, right, So the
better we are communicating with them, the better equipped will
be to actually use them to our advantage.
Speaker 1 (10:02):
That is a great point to end on. That's it
for today's deep dive into the world of prompt engineering.
Until next time, keep experimenting, keep learning, and keep talking
to those ais. Everyone,
Hey, everyone, welcome back. Ready to dive into something really interesting.
Speaker 2 (00:03):
Today absolutely should be a good one.
Speaker 1 (00:05):
We're talking all about prompt engineering, which.
Speaker 2 (00:07):
Is becoming a seriously sought after skill set these days.
Speaker 1 (00:11):
It really is, And I think sometimes people hear prompt
engineering and think, oh, that's for the AI experts.
Speaker 2 (00:16):
Right, Like, it takes years of study to master.
Speaker 1 (00:19):
Exactly, but it's way more accessible than it sounds.
Speaker 2 (00:23):
It really is. At its core, prompt engineering is basically
about how to talk to AI, so it actually gets you,
you know.
Speaker 1 (00:29):
Yeah, how to get the results you actually want exactly.
Speaker 2 (00:31):
Because as AI tools become more integrated into everything.
Speaker 1 (00:36):
Our workflows, our creative projects, everything.
Speaker 2 (00:38):
Yeah, knowing how to clearly articulate your needs to these
AI tools can be the difference between like having a
helpful assistant totally and just having this frustrating experience where
you're like, why aren't you understanding me?
Speaker 1 (00:52):
Like, come on, I know you can do this exactly. Okay,
So before we get into the nitty gritty, let's make
sure we're all on the same page.
Speaker 2 (00:59):
So that's good.
Speaker 1 (01:00):
We've got to talk about these things called large language.
Speaker 2 (01:01):
Models, right, which is a mouthful.
Speaker 1 (01:03):
It sounds very intimidating, very technical.
Speaker 2 (01:06):
Yeah, it sounds way more complex than it really is. Basically,
imagine a system that has read more text than any
human ever could in a million lifetimes.
Speaker 1 (01:17):
Like the entire Internet and then.
Speaker 2 (01:19):
Some pretty much we're talking books, articles, code, everything. You
can imagine, it's absorbed at all.
Speaker 1 (01:25):
Wow.
Speaker 2 (01:26):
And that's essentially what a large language model is. And
it uses that vast knowledge base to try to understand
your requests and then hopefully respond to them in a
meaningful way.
Speaker 1 (01:36):
So it's like having access to this incredible library, but
we need to know the right keywords.
Speaker 2 (01:41):
Yes, a perfect analogy. You need to know how to
search for what you're looking for, right, You're not just
going to wander around aimlessly.
Speaker 1 (01:47):
Exactly, don't get lost in the stacks, precisely.
Speaker 2 (01:50):
And that's where prompt engineering comes in.
Speaker 1 (01:52):
It's the key.
Speaker 2 (01:53):
It's about moving beyond just simple questions like you know
what's the weather, and learning how to communicate with AI.
That unlocks its full potential.
Speaker 1 (02:02):
Which I think we all want because these AI tools
are just getting more and more powerful.
Speaker 2 (02:07):
Oh. Absolutely, the possibilities are pretty much endless. It's really
quite exciting, and that's what we're going to dig into today.
Speaker 1 (02:14):
Yeah, and we've got two really interesting sources we're going
to be drawing from.
Speaker 2 (02:18):
Perfect lay it on me.
Speaker 1 (02:19):
So we've got this technical guide. It's great. It breaks
down the mechanics of prompt engineering, so almost like a
workshop manual. I like it, like how to actually craft
the perfect command?
Speaker 2 (02:31):
Awesome? What about the second source?
Speaker 1 (02:32):
The other one's cool. It's a fascinating look at how
prompt engineering is actually being used in the real world
in different professions.
Speaker 2 (02:40):
Because it's not just for coders, is it.
Speaker 1 (02:42):
No, not at all, Writers, marketers, educators.
Speaker 2 (02:44):
Really, anyone who interacts with AI at all.
Speaker 1 (02:47):
Probably exactly. Yeah, Because at the end of the day,
it's about communication, right, and everyone can benefit from communicating
more effectively.
Speaker 2 (02:55):
Okay, So I'm excited. Whether you're just looking to like
stream line your workflow, sure, or you're ready to unlock
some serious next level AI wizardry.
Speaker 1 (03:06):
I love it. We've got something for everyone here today.
All right, So let's dive into some of these strategies
for prompt engineering because I'm ready to level up my
prompt game.
Speaker 2 (03:14):
It's like learning the secret handshake.
Speaker 1 (03:16):
Yeah, exactly. I want to go from novice to like prompt.
Speaker 2 (03:20):
Pro I love it. And you know, the good news
is a lot of these strategies they're really rooted in
common sense.
Speaker 1 (03:25):
Okay, that's good to hear.
Speaker 2 (03:26):
It's not about like knowing some secret code or anything.
Speaker 1 (03:30):
Right, because I mean, we see these AI tools do
amazing things.
Speaker 2 (03:35):
It's true they can be really impressive, but at.
Speaker 1 (03:37):
The end of the day, they're operating on the instructions
that we give them precisely.
Speaker 2 (03:42):
They're not mind readers, not yet anyway. And that's where clarity.
Speaker 1 (03:46):
Comes in, right, so important.
Speaker 2 (03:47):
Our sources really emphasize this. Being crystal clear in your
prompts is absolutely crucial.
Speaker 1 (03:53):
So it's like if you're explaining something to a friend,
you know, the clearer you are, the better they'll understand exactly.
And AI is no different.
Speaker 2 (04:01):
It's the same thing with AI. Don't be afraid to
like over explain, especially when you're dealing with complex tasks,
you know, instead of just saying, write me a report
on climate change.
Speaker 1 (04:12):
Yeah, that's pretty broad.
Speaker 2 (04:13):
Right, You want to be specific. What kind of data
are you looking for, what timeframe, what are the key
arguments you want to address? So give it the structure
basically totally, and that actually leads us to another really
key strategy, which is breaking down those complex tasks.
Speaker 1 (04:27):
Okay, good to know, because some of the stuff I
want to do is a little complex.
Speaker 2 (04:30):
It makes a huge difference. See, AI, it can only
handle so much information at once, right, Like, just like
you wouldn't try to eat a whole pizza in one
byte one byte, Yeah no, you got to break it down,
make it manageable, smaller chunks exactly. So you do the
same for AI. You break those large tasks into smaller,
more digestible.
Speaker 1 (04:50):
Steps, divide and conquer exactly.
Speaker 2 (04:52):
And here's a little bonus tip. When you break down
a task like that, you're essentially creating a step by
step process for the AI, like a to do list.
Yeah yeah, and you can actually tell the AI to
follow those steps explicitly, which can really improve accuracy, you know,
and it gives you more control.
Speaker 1 (05:10):
Oh interesting, So you're not just telling you what to do,
but how to do it exactly, like a roadmap.
Speaker 2 (05:15):
I love that analogy. A roadmap. It's perfect. And speaking
of control, another really powerful technique is actually specifying the
output that you want.
Speaker 1 (05:24):
Oh interesting.
Speaker 2 (05:25):
Okay, don't just accept whatever the AI spits.
Speaker 1 (05:28):
Out, you know, don't just take it at face value.
Speaker 2 (05:30):
Exactly, you have the power to actually shape those results. So,
for example, instead of just letting the AI write you
a paragraph, you can say, hey, give me a bullet
point summary of this, or I need this in a
table format, or even write this in a specific tone
of voice.
Speaker 1 (05:47):
Oh like, if I need to sound like really formal.
Speaker 2 (05:49):
For something precisely, you can say, you know, write this
like a news headline, or I need this to sound
really encouraging and upbeat, whatever it might be.
Speaker 1 (05:57):
That is amazing.
Speaker 2 (05:58):
Okay, you're basically giving the A a blueprint for the
kind of response you want.
Speaker 1 (06:02):
It gives you so much more control.
Speaker 2 (06:04):
Exactly. You're no longer just a long for the ride.
You know, you're in the driver's seat.
Speaker 1 (06:10):
I'm into that. Yeah, And that's what.
Speaker 2 (06:11):
It's all about. It's about understanding how to communicate effectively
with AI to get the results you need.
Speaker 1 (06:17):
Okay, So we've covered a lot of ground here, but
I'm seeing in our notes that things get even more
interesting when we start talking about advanced prompt engineering techniques.
Speaker 2 (06:28):
Oh yeah, this is where it gets really fun.
Speaker 1 (06:30):
Okay, fun, I like it. So are you ready to
blow my mind a little bit?
Speaker 2 (06:33):
I think so get ready, because when I first started
exploring some of this stuff, it really blew my mind. Okay, good,
It's like, you know, you're stepping behind the curtain and
you start to see how the AI actually works.
Speaker 1 (06:44):
Yeah, like you're getting under the hood a little bit exactly.
Speaker 2 (06:47):
And one of the things that really fascinates me is
this idea of giving an AI a memory.
Speaker 1 (06:52):
Giving it a memory, what did they even mean?
Speaker 2 (06:55):
So it's almost like teaching the AI to take notes
as it reads, right, right, Because these large language models,
you know, they have a limited window of how much
information they can process at once.
Speaker 1 (07:05):
It's like their short term memory or something exactly.
Speaker 2 (07:08):
It's like short term memory. So you know, if you
feeded a whole research paper.
Speaker 1 (07:12):
For example, Yeah, it's a lot of info.
Speaker 2 (07:14):
There's a good chance it's gonna forget what it read
at the beginning by the time it gets to the end.
Speaker 1 (07:18):
Oh that makes sense, okay, right.
Speaker 2 (07:19):
And that's where this technique comes in.
Speaker 1 (07:21):
Okay.
Speaker 2 (07:21):
You can train the AI to basically summarize each section
as it goes, and it creates this kind of condensed
version of everything it's.
Speaker 1 (07:30):
Learned, so later on you can ask it about the
whole thing.
Speaker 2 (07:34):
Exactly instead of just like the last couple of paragraphs
it's processed. That's really cool, right, It's a game changer.
You can say, like, hey, you know, what were the
key arguments against this particular theory.
Speaker 1 (07:45):
And it can go back and pull from the whole thing.
Speaker 2 (07:47):
It remembers from the whole document, not just the conclusion.
Speaker 1 (07:51):
That would have been so helpful for like my thesis.
Speaker 2 (07:54):
Oh my gosh, right, think of all the time it
could save you.
Speaker 1 (07:57):
Okay, So we're giving our AI a long term memory.
Speaker 2 (07:59):
Now, exactly, extending that capacity.
Speaker 1 (08:03):
Love it. Okay. So, speaking of like getting more out
of AI, there's another advanced technique that I wanted to
ask you about, and it's this idea of making the
AI think before it speaks.
Speaker 2 (08:14):
Yes, it sounds kind of strange when you say it
like that.
Speaker 1 (08:17):
It does sound a little strange yeded like what does
that even mean?
Speaker 2 (08:20):
But it's really cool, I promise, because you know, sometimes
if you just ask the AI for an answer directly,
it might just rush to a conclusion, you know what I.
Speaker 1 (08:28):
Mean totally It just wants to please.
Speaker 2 (08:30):
Yeah, it wants to give you an answer, so it
might jump the gun a little bit and miss some
of the nuance.
Speaker 1 (08:35):
You know, Yeah, like that friend who just blurts out
an answer before you've even finished asking the question exactly.
Speaker 2 (08:41):
But if you actually prompt the AI to kind of
walk through the problems step by step, almost like show
its work, you know, Okay, it often arrives at a
much more nuanced and a much better reason to answer.
Speaker 1 (08:52):
Oh interesting, So you get a better result and you
get to see how it got.
Speaker 2 (08:55):
There exactly, Yeah, which is so valuable because it allows
you to understand like it's thought process.
Speaker 1 (09:01):
You get to peek inside its brain a little.
Speaker 2 (09:03):
Bit exactly, and that can help you refine your prompts
even more, right, because the more you understand how it's thinking,
the better you can guide it.
Speaker 1 (09:09):
Wow, Okay, we've covered some seriously cool stuff today. I
feel like we've gone from like AI one oh one
to some seriously next level stuff.
Speaker 2 (09:19):
That's a whole new world, isn't it.
Speaker 1 (09:20):
It really is? So any final thoughts for our listeners
before we wrap things up today.
Speaker 2 (09:25):
You know, I think the biggest takeaway here is that
prompt engineering it's not this mysterious art, right, It's not
just for like coding geniuses or AI experts.
Speaker 1 (09:35):
It felt a little intimidating at first.
Speaker 2 (09:37):
I'm not gonna lie, right, but like we were saying,
it really is a skill, you know. It's like learning
a new language. Yeah, And like any language, the more
you practice, the more fluent you become.
Speaker 1 (09:47):
So it's really about understanding how to communicate effectively with
these really powerful tools.
Speaker 2 (09:52):
That we have exactly, and they're just going to become
more and more prevalent in our lives, right, So the
better we are communicating with them, the better equipped will
be to actually use them to our advantage.
Speaker 1 (10:02):
That is a great point to end on. That's it
for today's deep dive into the world of prompt engineering.
Until next time, keep experimenting, keep learning, and keep talking
to those ais. Everyone,
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