i have learned all the AI things for you

So here's the cliffnotes version of

everything you need to know about AI in

my opinion in 2025 We'll be going from

beginner to intermediate to advanced and

I'll be giving you a crash course on

each topic as well as providing more

resources for you if you want to dig

deeper into any of them By the end of

this video you will know more about AI

than like 99% of the population But not

if if you don't actually retain that

information So there will be little

assessments throughout the video Now pay

attention Let's go A portion of this

video is sponsored by Retool Here's the

structure of the video First we're going

to go over the basic definitions of AI

and how they work Then we'll be covering

prompting followed by agents very hot

these days followed by AI assisted

coding We're building applications

through what is called vibe coding and

finally looking at some emerging

technologies going into the second half

of 2025 All right let's get started by

first defining artificial intelligence

Artificial intelligence refers to

computer programs that can complete

cognitive tasks typically associated

with human intelligence Now AI as a

field has been around for a very long

time And some examples of traditional

artificial intelligence which back in

the day we used to call machine learning

include things like Google search

algorithms or YouTube's recommendation

system for recommending you content like

this video But what we typically refer

to as AI these days is what is called

generative AI which is a specific subset

of artificial intelligence that can

generate new content such as text images

audio video and other types of media The

other IG posts that you like This way

the AI can take inspiration from this

example Providing examples can be so

powerful because you can describe things

with words as much as you like But you

know if you just provide it with an

example there's like so much there that

you can capture the nuances that you can

incorporate into the results And voila

you press enter and here is your IG post

Now you want to evaluate Do you like it

is there anything that you want to tweak

or want to change if so you go into the

final step of the framework which is to

iterate When interacting with AI models

it is a very iterative process So even

at the first time it doesn't get what

you want you can tell it like tweak a

little bit about this add something over

here change the color of something and

you work alongside AI to get the result

that you finally want Tiny crabs ride

enormous iguanas If you can remember

this pneummonic and how to use it you

would be better than 80% of people at

prompting Let's call it 88 because that

is a lucky Chinese number But if you

want to be better than 98% of the

population I have one more framework for

you This is when you do the tiny crabs

ride enormous iguanas framework and you

feel like the results are still not

quite there Well you can elevate this

even further using the ramen saves

tragic idiots framework First part of

the framework is just to revisit the

tiny crabs ride enormous iguanas

framework See if you can add in

something else maybe a persona Be more

detailed about the output more

references Also consider taking out

something Is there any conflicting

information in there that could be

confusing for the AI second part of the

framework is to separate the prompt into

shorter sentences Talking to AI is

similar to talking to a human if you

just like word vomit all over them and

just say like a bunch of things It can

be confusing for the AI So you can

consider splitting what you're saying

into shorter sentences to make it more

clear and more concise So instead of

just being like blah blah blah blah blah

blah blah blah blah blah blah blah blah

blah all over the place you could just

be like blah then blah then blah Make

sense third part of the framework is to

try different phrasing and analogous

task For example maybe you're asking AI

to help you write your speech and it's

just like not quite there you know it's

just like not really hitting it So maybe

you can reframe this Instead of saying

"Help me write a speech," say instead

"Help me write a story illustrating

whatever it is that you want to

illustrate." After all what makes a good

speech is a compelling and powerful

story Hello So this is Tina from the

future I have just gotten back to Hong

Kong from Austin and it seems like in my

jetlegged state I have forgotten to

record the last part of this framework

So I'm going to do that now which is

introducing constraints Do you have one

of those friends where you know maybe

you are that friend when someone asks

like hey what do you want to get for

lunch and they're just like oh anything

Yeah not very helpful Similarly if you

feel like the output from your AI is

just like not quite there You can

consider introducing constraints to make

the results more specific and targeted

For example maybe you're making your

playlist for a road trip that you're

going on across Texas and you know

you're just really not quite vibing with

it You can introduce a constraint like

only include country music in the

summertime Much more suitable vibes All

right now back to pastina Got that ramen

saves tragic idiots With these two

frameworks together you'll be better

than 98% of people at prompting By the

way I also just want to say that I

didn't just make up these frameworks

myself I only take credit for the cool

pneumonics The actual framework comes

from Google itself So if you want to

dive even deeper and be better than like

99% or even 100% of people at prompting

I recommend that you check out this

video over here which I'll link in which

I summarize Google's prompting course

which is the best general prompting

course that I found so far Also I would

recommend checking out some of the

prompt generators for specific models

like this one from OpenAI this one from

Gemini and this one from Anthropic These

are helpful for generating a first draft

and for getting the most out of specific

models For anybody that thinks that

prompting as a skill is going to become

obsolete think again Especially for more

advanced applications like building

agents and coding prompting is getting

more important than ever It's like the

glue that holds everything together to

make sure that you get the results that

you want consistently Now speaking of

more advanced skills let's now move on

to the next topic which is agents

AI agents are software systems that use

AI to pursue goals and complete tasks on

behalf of users When we refer to AI

agents we usually refer to it as an AI

version of a specific type of role For

example a customer service AI agent

should be able to receive an email maybe

of somebody being like I forgot my

password and I can't log in And it

should be able to reply to that email

and should be able to reference the

forgot password page on the website As

of today it can't do everything and it

can't handle all of the queries that a

customer service person should receive

but it can handle a lot of these kind of

generic or common questions that people

may have all autonomously Similarly for

a coding agent if you prompt it well and

you tell it to build like a web

application it should be able to come

back with an MVP version of that web

application Still got to like add on a

bunch of things and tweak it for sure

but it can write the code for the first

version of it AI agents is a space where

there's a lot of interest and a lot of

money that is being poured into it and I

really expect them to get better and

better over time and incorporate into

all sorts of products and businesses In

fact the most golden piece of advice

that I have ever heard about AI agents

was from this YC video which is for

every SAS software as a service company

there will be a vertical AI agent

version of it Every company that is a

SAS unicorn you could imagine there's a

vertical AI unicorn equivalent So what

exactly makes up an AI agent well there

are a lot of frameworks out there but

the best one that I've seen so far comes

from OpenAI They list six components

that make up an AI agent The first one

is the actual AI model Can't have an AI

agent without a model This is the engine

that powers the reasoning and the

decision-m capabilities of the AI agent

Second is tools By providing your AI

agent with different types of tools you

allow it to be able to interact with

different interfaces and access to

different information For example you

can give your AI agent an email tool

where it's able to access your email

account and be able to send emails on

your behalf Next up is knowledge and

memory You can give your agent access to

say like a specific database about your

company so that it's able to answer

questions and be able to analyze data

specific to your company Memory is also

important when it comes to specific

types of agents Like say if you have a

therapy agent and you have like a really

great session with it and then next time

around it just like completely forgets

what you're talking about That probably

wouldn't be great So that's why you want

to allow your agent to have access to

memory So it's able to remember all the

different sessions that you've had

previously Then we have audio and speech

This gives your AI agent the capability

of interacting with you through natural

language like being able to just to talk

to it in a variety of different

languages Then we have guardrails Be no

good if your AI agent goes rogue and

starts doing things that you don't

intend it to do So we have systems for

that to make sure that your AI agent is

kept in check And finally there is

orchestration These are processes that

allow you to deploy your agent in

specific environments monitor them and

also improve them over time After you

build an AI agent you don't just run

away and hope that it works by itself

Speaking of AI agents Retool just

launched its enterprisegrade agentic

development platform Right now there's

still a big gap between building AI

demos and AI that actually does useful

stuff in your business Retool allows you

to build apps that connect to your

actual systems and take real actions You

can use any LM like Claude Gemini OpenAI

whatever you want Your agents can

actually read and write to your

databases not just chat with you It also

has endto-end support including test and

emails to track performance monitoring

access control and a lot more These are

all things that are not flashy but

really crucial to real implementation in

your business Companies that are using

retool plus AI are already seeing really

genuinely impressive results For example

the University of Texas Medical Branch

has increased their diagnostic capacity

by 10 times Over 10,000 companies

already use Retool So if you want to

build AI that is actually useful instead

of just look impressive do check out

retool.com/tina

also linked in description Thank you so

much retool for sponsoring this portion

of the video Models provide intelligence

tools enable action memory and knowledge

informs decisions voice and audio

enables natural interaction Guard rails

ensure safety and orchestration manages

them all I do also want to point out

that prompting is also really really

important when it comes to agents

especially if you're building multi-

aent systems where you're not just

having a single agent but you actually

have networks of agents that are

interacting with each other Your prompts

need to be very precise and produce

consistent results So how do we actually

build these AI agents like what are the

technologies for this there are quite a

few currently available for no code and

low code tools I personally think nend

is the best for general use cases and

gum loop is great for enterprise use

cases If you do know how to code I

recommend checking out OpenAI's agents

SDK which does have all these components

built into it Or if you want something

that is free there is Google's ADK agent

development kit There's also the Claude

Code SDK which is specific for coding

agents Honestly these different

technologies implementation methods are

going to keep changing over time and I'm

sure within the next few months there's

going to be even more agent builders for

you to build agents with That's why I

really recommend that you actually focus

on this fundamental knowledge about the

components of AI agents what are the

different protocols and the different

systems because this foundational

fundamental knowledge is not going to

change so quickly and it's going to be

applicable to whatever new tool and

technology comes out So if you do want

to dive a little bit deeper into AI

agents I have a video over here that I

made about AI agent fundamentals And if

you want to get started in building your

AI agents I also have another video

called building AI agents which you can

check out over here as well And I go

into a lot more detail about AI agents

So these are the components that make up

a single AI agent But often times you

may also want to build multi- aent

systems in which you don't have just one

agent but you could have a system of

agents that are working together And the

reason for this is kind of like if you

have a company and you just have like

one person trying to do everything in

the company it's probably going to not

be great right that person is going to

get very confused trying to manage

everything at the same time So it's much

better to have people with specific

roles that make up that company Very

similar with agents If you just have one

single agent trying to do everything

then it's going to get confused there's

going to be like a lot of stuff that's

happening So it's often good to break it

down into different sub aents that have

specific roles and work together in

order to get the result that you want If

you want to learn more about multi- aent

systems Anthropic has a really great

article for that and I'll link it in the

description By the way I'll link all the

resources that I'm referring to in the

descriptions You may also have heard

about MCP which is what a lot of people

are talking about these days This is

also developed from Anthropic and it's

basically a standardized way for your

agents to have access to tools and

knowledge You can think about it like a

universal USB plug Prior to MCP it was

actually quite difficult to give your

agents access to certain tools because

all the different websites and all the

different APIs they do it in a different

way and databases as well They're all

configured slightly differently So it

was kind of a pain in the ass trying to

like connect that with your agent But

with MCP because there's a universal USB

plug you're now able to give your agents

any type of tool and any kind of

knowledge very easily assuming it

follows the MCP protocol All right here

is a little assessment on this agent

section Write the answers in the

comments Next up let's move on to using

AI to build applications aka AI assisted

coding aka vibe coding

In February of 2025 Andre Kaparthy the

co-founder of OpenAI made a viral tweet

He says "There's a new kind of coding I

call vibe coding where you fully give

into the vibes embrace exponentials and

forget that the code even exists It's

possible because the LMS are getting too

good You simply tell the AI what it is

that you wanted to build and it just

handles the implementation for you And

this in my opinion is the new way of

incorporating AI into your products and

your workflows using vibe coding to

build things For example you can simply

tell an LM please create for me a simple

React web app called Daily Vibes Users

can select a mood from a list of emojis

Optionally write a short note and submit

it below Show a list of past mood

entries with a date and a note And you

just click enter And the LLM writes the

code for you and generates this app And

voila there you go But it doesn't just

end there There still are skills

principles and best practices for how to

work with AI in order to vibe code

properly and produce products that are

actually usable and scalable Let me

present to you now a five-step framework

for vibe coding with the pneummonic tiny

ferrets carry dangerous code dangerous

code because if you don't do it properly

you could potentially end up like this

guy over here who vibe coded an app and

then lost all of it because he didn't

understand something called version

control Tiny ferrets carry dangerous

code stands for thinking frameworks

checkpoints debugging and context

Thinking as it sounds is about thinking

really hard about what it is that you

actually want to build If you don't even

know exactly what it is that you want to

build how do you expect AI to be able to

do so the best way of doing this in my

opinion is to create something called a

product requirements document or a PRD

This is where you define your target

audience your core features and what it

is that you're going to use to build the

product with I'll link an example PRD in

the description but basically you just

want to spend significant amount of time

thinking through what it is that you're

trying to build Next up is frameworks

Whatever it is that you're trying to

build there has probably been very

similar things that have been built

before So instead of just trying to

reinvent everything and telling the AI

to figure everything out it's much

better to point the AI towards the

correct tools for building your specific

product by telling it to use React or

Tailwind or 3.js if you're making 3D

interactive experiences But Tina you may

ask how am I supposed to know what to

tell the AI to use if I don't even know

what it's supposed to use great question

AI can help you with that too When

you're building your PRD ask the AI

directly I'm trying to build something

that's like you know like this and it's

very 3D animationheavy for example and I

want it to be a web app What are the

common frameworks for building something

like this when you're asking in this way

you're also learning yourself what are

the common frameworks for building

specific things And over time you're

going to have a much better grasp of

what you need to use as well In the era

of vibe coding you may not need to code

everything by yourself but it still

serves you very well to understand the

common frameworks that are used for

building different types of applications

You should also know how different parts

and different files in your project are

interacting with each other This is

going to help you out so much as you're

building more and more complex features

into your product Third step of the

framework is checkpoints Always use

version control like Git or GitHub or

else things will break and you will lose

your progress and you will feel very

very sad like this guy who vibe coded an

entire application and then lost all of

it because he didn't understand version

control Fourth step debugging you are

probably going to spend more time

debugging and fixing your code than

actually building anything new That is

the reality Be methodical and be patient

and guide the AI towards where it is

that it needs to fix When you're

debugging if you understand the file

structures and what's happening then

you're much better at providing specific

instructions for where in your codebase

the AI should be debugging The first

place to start when you come across an

error is to copy paste the error message

directly into the AI and tell it to try

to fix it If it's something visual that

needs to be fixed also provide a

screenshot for the AI The more details

and the more context that you give the

AI the better it would be at figuring

out how to fix the problem And speaking

of context the final part of the

framework is context Whenever you're in

doubt add more context Generally

speaking the more context that you

provide to AI whether you're building or

debugging or you're doing whatever the

better the results are going to be This

includes providing the AI with mockups

examples and screenshots The pneummonic

to remember for this five-step framework

is tiny ferrets carry dangerous code

thinking frameworks checkpoints

debugging and context A helpful way of

thinking about how these principles of

the framework work well together in the

process of vibe coding is to realize

that there's only two modes that you're

ever in You're either implementing a

feature where you're debugging your code

When you're implementing features you

should be thinking about how to provide

more context mentioning frameworks and

making incremental changes You always

want to approach building new things one

step at a time Implement one feature at

a time as you build your product When

you're in debugging mode you should be

thinking about the underlying structure

of your project where it is that you

should be pointing the AI towards

changing as well as providing more

context like error messages and

screenshots So we now know the

fundamentals of what makes good vibe

coding So what are the actual tools that

we use there are a full spectrum of

development tools available On one of

the spectrum is for complete beginners

people who have no engineering

background and no coding background Some

popular beginnerfriendly vibe coding

tools include lovable vzero and bolt

Then slightly more intermediate we have

something like Replet This is still very

beginner friendly but it also showcases

the codebase so you can actually dig

into a little bit more and understand

the structures of the projects Then a

little bit more advanced you have

something like Firebase Studio Firebase

Studio has two modes to it It has the

very user-friendly prompting mode as

well as a full ID experience which

stands for integrated development

environment an interface that is

specifically designed for writing and

working with code In this case it was

built on top of VS Code which is a very

popular ID With Firebase Studio you can

alternate between the no code prompting

view and decoding mode Firebase Studio

also has the benefit of being free Now

moving on to the more advanced vibe

coding tools This will include AI code

editors and coding agents like Windsurf

and Cursor Everything that we talked

about earlier was all web- based so the

setup is really easy The environment is

isolated and it takes care of a lot of

things for you But if you really want to

produce productionready scalable code

then you generally need to start

migrating to using something like

windsurf and cursor Development is going

to be on your local machine So the setup

is going to be a little bit more complex

but you also have access to a full suite

of development tools and different

features for Windsor and cursor You just

directly have that coding environment

that IDE Then on the most advanced side

of the spectrum you have command line

tools like cloud code for example These

are tools that live directly in your

terminal in the root of your computer

With these tools you need to be

comfortable working in the terminal or

the command line But it does give you so

much more functionality and you can use

it with any type of ID of your choosing

Something like cloud code really begins

to shine when you're working on complex

code bases But the expectation here is

that you do really need to know how to

code and know your way around a computer

and have a deep understanding of

software All right that is a crash

course on vibe coding If you do want to

dig into this more I made a full video

called Vibe Coding Fundamentals where I

go into a lot more detail I also made a

video specifically about Firebase Studio

which I'll link over here and another

one where I talk about the cloud for

models and cloud code which I'll link

over here too Now I will put on screen a

little assessment to see if we have

retained information about vibe coding

Final section out What are things

looking like going into the future

in the AI world we don't measure things

in terms of years or even months We

measure things in terms of weeks And the

timelines are just getting more and more

compressed When I was at the code with

cloud conference Daario the CEO of

Enthropic made a really good analogy He

says that it's basically like being

strapped on a rocket that is going

through time and time and space are

warping so that everything is speeding

up faster and faster and faster And

especially because of this if you're

just trying to keep up with all the AI

news all the things that are coming out

all the new models all the new tools all

the new technologies you will never be

able to catch up with everything and

probably get really stressed along the

way too So that's why my advice is to

not pay too much attention to all the

new things that are coming out but

instead focus on the underlying trends

that are happening And I think there are

three major underlying trends The first

one is integration into workflows and

existing products 2025 is definitely the

year in which people are taking the AI

and actually integrating it into their

existing workflows Prime example of this

is Google itself I was at their Google

IO conference and they are putting a lot

of effort into just making Google

products better by integrating AI

throughout And I think this should be a

model for all companies Think about how

do you improve your processes by

incorporating AI to have a better user

experience and also to reduce your cost

And when it comes to implementation of

this there's massive productivity boost

if you learn how to do AI assisted

coding or vibe coding With this full

spectrum of coding tools there's a

dramatic decrease in barrier of entry

for people who want to build things and

who may not know how to code But there's

also a big push towards increasing the

productivity of developers After

experiencing command line tools like

cloud code I can absolutely see the

massive benefits of tools like this And

I think there's going to be massive

focus of developing and improving

command line tools So I think if you are

technical or if you're someone who's

willing to learn technical things

learning command line tools like cloud

code is going to be where it's at And

finally the focus on AI agents is not

going away at all In fact there's more

and more interest in building AI agents

because AI agents have so much potential

in improving existing products and for

building new products as well AI agents

allow experiences to be personalized

available 24/7 and at much much lower

cost Like Weissy said for every SAS

unicorn company there will probably be

an equivalent AI agent company I'm sure

in the coming few months there's going

to be more and more tools that will

allow you to implement and build agents

even more easily So if you want to build

something build a business do a startup

whatever I would recommend looking into

AI agents All right that is all I have

for you today Here is a final little

assessment Please answer these questions

in the comments Thank you so much for

watching till the end of this video I'm

so excited to see all the things that

you guys are going to do and build using

AI I really hope this is helpful and

good luck on your AI journey I will see

you guys in next video or live stream

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Every Essential AI Skill in 25 Minutes (2025)

Transcription