Full Tutorial: GPT-5 vs Claude 4.5 vs Gemini 2.5 for 10 Tasks (Oct 2025)

Hey everyone. All right. So today I want

to share an updated guide on how I use

chat GPT Claude and Gemini. I will also

cover nine AI projects that I rely on

daily and how I use deep research to

make important decisions. So if you want

to learn how I actually use AI to get

stuff done, this video is for you. All

right, so let's get started. Okay, so

here's my table showing what

capabilities each AI model has. I'm

going to walk through each use case and

then pick my favorite. All right, let's

start with everyday answers. For

everyday answers, GPT5 is fast and

concise, which makes ChatGpt a great

choice. Claw is pretty good, too, but I

keep running into rate limits on the $20

a month plan. So, my choice here is Chat

GPT. Now, let's talk about writing and

editing here. I think the winner is

still Claude. Let me go ahead and mark

Claude as the winner. And that's because

I think Claude is the best writer and

editor if you give it examples of your

best writing. You know, Chad Chbt likes

bullet points a little bit too much and

generalized writing is way too verbose.

Claw is my go-to here. And this is what

I use AI for 80% of the time.

Okay, so next for coding, it is a lot

more competitive. And actually, I'm

gonna mark two winners here. So, let's

make two stars and let's get rid of

this. And let's actually move chat GBT

as one of the winners and claude as the

other winner. And you know personally I

prefer using cloud code but I have many

engineering friends who swear by opening

codeex with GPD5 high. Codeex is a

little bit slower than cloud but can

often fix gnarly bugs in just a few

lines of code. And overall it's pretty

remarkable how fast OpenAI has caught up

to anthropic in this area. All right.

Next, let's talk about deep research.

For this one, my preference is Claude.

And I think the main difference here is

that Claude is only deep research tool

that actually writes maybe four or five

pages of report that you actually want

to read instead of chat GBT and Gemini

that go off and create 30 and 40 pages.

I'll cover deep research a lot more

later in this video. Next, let's talk

about web search. So, web search, I

would say uh I'm going to give the

winner actually to Gemini. And I think

it's pretty close here between chat GPT

and Gemini, but I'm giving to Gemini

because the AI mode is just a lot faster

than waiting for the chat to generate in

chat GPT. And when I'm looking for web

searches, like looking for nearby

restaurants or something quick, speed is

the most important thing. Okay, so I'm

going to cover the rest pretty fast. For

voice chat, I think I still prefer chat

GPT. I think it has the most personal

and the most authentic voices. Now, that

being said, a lot of my AI voice

dictation is actually using other tools

like Whisper Flow because I find that,

you know, all three models tend to

interrupt me a little bit too much when

I'm trying to talk. So, yeah. So, I

prefer to use other apps for AI voice.

For image generation, I think uh Gemini

has the best image model right now. So,

let's put it here. Gemini's Nano Banana

is a incredible image model. It also

generates I think a little bit faster

than ChatBT. And uh I have a full

tutorial on how you can build nano

banana apps that you can check out in

the description. Okay. Now, for video

generation,

this is actually a pretty tight race,

but I'm have to give the winner to Chad

GPT. And uh in my opinion, VO 3.1 from

Gemini, which was most recently

released, is actually arguably a better

model, but I just really enjoy creating

videos of my family and friends using

Sora. Chat GPT, OpenAI, they hired a ton

of people from Meta, so they definitely

get social a lot better than Gemini and

Google. And that's why I think Sora is

still my favorite choice. All right, for

live camera, to be honest with you, I

haven't used it too much, so I'm not

going to give it a winner. And for

computer use, I have tried computer use

across all three different providers. In

my opinion, I think computer use kind of

sucks. Like, you're basically watching

the AI click around a mouse and take

screenshots and it just takes forever.

And yeah, I I just feel like I haven't

really found the right use case for it

yet. you could just leave it alone and

you know ask it to help you book a

restaurant or buy some flowers or

something but I also don't trust AI

enough to do that. So for me personally

I I don't think AI is really good for

computer use right now. All right and

let's quickly talk about something else.

So OpenAI also recently launched a new

web browser in Atlas. So let me actually

open it up and this is actually pretty

amazing. OpenAI seems to be taking a

path of launching MVP product and using

their massive user base to iterate with

users as quickly as possible. But you

know just using Atlas I think um you

know let's say I search for uh my

favorite good restaurants nearby and it

just basically calls chat GPT and the

time it takes for this thing to generate

the chat it just a little bit longer

than I want. Right. So, it took like

what, one or two seconds to generate.

But if I go back to regular Chrome and

search favorite restaurants nearby,

you know, it's like near instant. And of

course, it comes up with much better

results. These are actually near where I

live versus catchy looking up places

like San Jose. So, I I think there's

still a uh a bunch of room for

improvement in Atlas, but I'm sure

OpenAI is going to improve it quickly.

Now, you may see here that I have Grock,

right? I have Grock here and I haven't

given a single award to Grock and and

that is because

going to next slide. I I just feel like

Grock may be a great model but honestly

I cannot take the product seriously

because it markets AI companions so

aggressively. These AI companions, some

of them are waifuss, some of them are

weird characters. I don't know. I I I

just feel like this kind of stuff

doesn't actually appeal to the regular

user, regular consumer. And personally,

I think XAI isn't making a big branding

mistake by pushing these companions so

hard. And I think they need to hire some

real marketing people to the company.

Okay, so there you have it. This is kind

of my takeaway on my favorite models.

And again, I have a post in the

description where I've linked this

table, but let's keep going, right?

Let's talk about some something else.

Okay, so let's talk about my go-to AI

feature for all three models, which is

projects. And you know, maybe I'm

old-fashioned, but I think projects is

far more useful of a feature than AI

agents, AI browsers, or whatever is hot

in AI right now. And all three big labs

have this feature, but I prefer clawed

projects because it lets me paste in

simple text files, lets me attach Google

Docs, and it even has memory. So, let me

kind of show you how things works. Okay,

so first let me talk about kind of three

quick tips that you might not know about

to get the most out of projects. So, tip

number one is to attach Google Docs

directly. This ensures that your project

is always aware of the latest updates in

your Google Docs and other files. I also

like to add plain text files and deep

research outputs as context. Okay, tip

number two is to include your output

style in the prompt. So, this ensures

that whatever the AI spits out will

always be in the style and format that

you want. And for me, my preferred style

is to use short bold stems followed by

two or three short sentences so that the

entire output is easy to skim. All

right. And last but not least, and this

is more of a pro tip, is to get AI to

iterate on your prompt. So let's imagine

you have a long conversation with AI in

your project and you finally get to the

output that you want. You should follow

by asking, can you update the project

prompt to produce this output in one

shot the next time? And then you should

save the updated prompt so that you can

get to the desired output faster the

next time you talk to the project. So

let me kind of make this really

practical by walking through a real

example. Right? So as a product manager,

let's be honest, we spend a lot of time

editing documents, editing strategy

documents, editing PRDs and so on. And

here's an example from Clarvo on just

how much internal iteration it takes to

produce a typical strategy document.

Right? First you have to think really

hard. You got to talk to customers. Then

you got to get feedback from

stakeholders. You get a flood of Google

comments on the right side. Then you got

like go back and iterate and think hard

again. And then you do another round of

feedback. And then you know this whole

process can take probably a couple of

weeks. And you know you spend your day

just kind of editing these Google

documents, right? So here's how a

project can help you with this process.

Okay. So I'm going to use a kind of like

hypothetical example. So let's say we

are uh working on boat which is an AI

coding startup and AI coding is an

incredibly competitive space and we want

to create a strategy document for boat.

Okay. So first I'm going to create a

project for boat. So I have a project

right here and uh I've uploaded three

different files. So the first file I've

uploaded is the working backwards

template from Amazon. I like this

template because it starts with the

customer and it kind of like expresses

the strategy from the customer's point

of view. But the point here is you want

to upload some sort of template or some

sort of example of what a good output

is. All right, the next document is I

actually did some deep research on both

strategy and here's the deep research

document, right? So there's a pretty

long document. I I think I use Gemini

for this and then I'm just going to

attach this document to the project too.

And last but not least, I have my own

document on uh how I think each AI

coding tool will play out. Uh right,

there's a bunch of stuff here and

doesn't have to be like this. It can

just be like your voice dictated notes

and your overall thoughts on the

strategy. But basically, it's like a

very rough first draft of the strategy

that you just kind of spit out in in

your head. Now that I have all three of

these documents, right? So now I can

actually ask AI to go ahead and draft

the PRD. And before I do that, let me

just kind of show you the prompt. Uh the

prompt is basically talking and giving

some context about three different

documents that I've uploaded to the

project and then asking it for help to

synthesize these materials into a

compelling strategy. Let's look at uh

one of our past conversations here.

Right? So let's go up here and uh

basically I asked it to create Amazon

style PR FAQ document for boat. I want

you to be my thought partner and figure

this out. And first I asked it to try to

draft some answers to Amazon's working

backwards questions. And that's exactly

what it did. Who is the customer? And so

on so forth. And then I asked to make

the PR FAQ and it drafted it right here.

Right. And this is pretty good. And then

I gave it some feedback. And I can use

like a voice dictation tool or something

to give it feedback. But basically my

feedback is like personally I think

where the money is is in the enterprise

space and I think uh you know Bo needs

to figure out how to compete with Figma

make and some of these other tools. So

given all this can you come up with some

more strategies and it it did and you

know we can keep going back and forth

like this. So you know this is the key

behavior change that I want you to

remember today right? So basically

create projects for any kind of

important work or thing that you're

working on and then give AI the right

context and then use voice dictation use

your feedback to work with AI as your

thought partner to refine the output.

You know you can go through many

iterations with AI to make your document

much better before you start sharing

with stakeholders and other customers.

Okay, it just makes the iteration loop

for editing documents much faster. All

right. So, here are my top three AI

projects for product creator and

personal work. And I already showed you

how I create strategy documents and

PRDs. So, let's talk about this show

notes project that I have. So, this is a

project that I use after doing a podcast

interview to create a bunch of other

artifacts. So basically all I have to do

is pasting a raw transcript from the

interview and then this project turns it

into a list of top quotes, moments to

cut, YouTube titles and thumbnails and

even social posts. And honestly, this

project alone probably saves me 3 to

five hours a week. And is pretty

involved here. You see this? So the

prompt is very long. Uh it has a bunch

of stuff about top quotes that you want

to pull out, top moments to cut, right?

It has a bunch of thumbnail and title

output formats using best practices. It

has a bunch of social post examples down

here. It is a very long prompt and uh

you can find this prompt in the

description where I've linked my

newsletter post. Uh however, uh I'd have

to say it is only available to pay

subscribers of my newsletter post, but

it it's worth it. If you're if you're

making a podcast, it's worth it to get

this prompt. But anyway, let me show you

how this prompt works. So, let's take

one of these files. So, let's take an

interview that I did with Zapier CEO

Wade recently. And here's kind of like

the full raw transcript, right? And

based on this raw transcript, what has

done is created the top quotes from our

intro reel. It has created the moments

to cut where we had some audio issues or

repetitive chatter. And uh most

importantly is created a bunch of

thumbnail patterns from myself and uh

other YouTubers that I respect. A

thumbnail and title copy which you know

normally would take me a very long time

to come up with done that. Uh if I keep

scrolling down it's created show notes

with the right timestamps and it's

created takeaways from the interview. It

has even created the social preview and

social posts. Now this stuff isn't

perfect in one shot, right? So the next

prompt that I asked it is, let's work on

social post. Can you make it more

interesting and engaging and here's some

feedback? But the point is like it

created like a really solid first draft

for all of these artifacts which is

honestly just saves me a ton of time and

then I can iterate with this project to

make these assets actually good. Okay,

so that is the shown project and now

let's talk about the family trip

project.

So this one I actually created in uh

Chat GPT just to show you that you can

create projects in Chat GPT and Gemini

2. And here the project is basically a

bunch of instructions for things that me

and my family likes. Right? So for

example, we want to create memorable

family experiences. Here are some

favorite places we've been to in the

past. Montter Bay Aquarium. So on so

forth. And there's different types of

trips that I want you to plan out. A

half day trip, a day trip, so on and so

forth. and also kind of when we are

available. So for example, my daughter

has taekwond do practice Saturday

morning. So we're actually not available

then. So we're available Saturday

afternoon and on Sunday and use this

project, I can basically ask it, you

know, what kind of familyfriendly

events this weekend, right? And just ask

it that. And because it has all that

context, it can search everything and it

can find a bunch of really cool

family-friendly events that are topical.

not this headless forcement might be a

little bit too scary for my kids but

yeah it can find all these awesome

events because it has a context okay so

that is on projects and if you want a

deep dive on all nine projects again

check out the newsletter post that I've

linked in the video description for more

right I got one more topic which is deep

research now deep research is the real

extended thinking mode for AI and it is

honestly useful for much more than just

market research you should think about

using it whenever you need to make a

difficult decision, okay? Or try to

evaluate two different trade-offs. So,

uh, every provider now offers deep

research. So, I tested each model with

this prompt, right? Research the AI

coding market and share both strategy to

compete. And here's kind of like a

sampling of the results. And the point I

want to make is that Claude produced a

seven-page report. You see this here?

It's like a pretty short report. and

pretty concise while both chat GBT and

Gemini produced a much longer report

like this is like a lot to to read. So

because of this again I think I prefer

Claus deep research because it's

actually able to synthesize information

to something concise instead of just

dumping a bunch of information on you.

But honestly like all three deep

research are totally usable and they're

also pretty good. All right. So now, how

do you get the most out of deep

research? Most people just type a single

question into deep research and then

they wonder why the output sucks. So

here's five steps that you should follow

instead to get much better out. So first

start with a clear goal. Tell it the

specific decision you're trying to make

or the problem that you're trying to

solve. And then very importantly, share

relevant context. And this is probably

the biggest lever. So share a full page

of context including any documentation

or any kind of voice dictated notes that

you have. The more context you provide

up front, the better the research output

becomes and the more personalized it

becomes. Okay. Number three is specify

the sources it should rely on. So for

example, if you're trying to decide what

kind of product to purchase, ask it to

research both professional reviews and

user reviews on websites like Reddit,

right? point it to the right sources

that you want and always ask it to ask

you questions first before it starts his

research. So just include in your

initial prompt ask me questions before

you begin your research and this way the

AI can clarify things before it gets

started. And finally um deep research it

naturally integrates with projects in

cloud you can easily one tap to add an

entire research report to the project.

All right so let's make this super

practical. Let me show you examples of

how I use deep research. So, here's the

first example. So, I'm learning how to

play the piano and I want to find a

great app to help me read sheet music

and practice the piano. And note how

detailed my prompt here is, right? I I

told it that I I have a kauawaii piano.

I'm advanced beginner. I've been playing

my favorite songs using YouTube videos

that have floating notes. and I want to

learn how to read sheet music more and

learn proper fingering and pedal

technique. So, give me the right app and

look up uh recent reviews and ask me any

questions before you get started. And

therefore, it asked me a bunch of

questions about my budget and so on and

so forth. Okay, so based on this, it did

a bunch of research and here is the

research report. Now, I'm only aware of

certain piano apps like Simply Piano,

but the recommendation that I came up

with, I actually had no idea about. The

recommendation is called Playground SE

sessions. And Playground Sessions is an

app that has audio feedback, is a lot

more professional. It teaches the right

lessons more than simply piano. And uh

it just has a bunch of uh really good

content here. and it's kind of explained

how it actually meets my requirements

because I've given it all the

personalized context up front. So that

is a playground sessions and it has a

bunch of runner ups and you know it's

pulled together this like pretty awesome

report right this is like something that

maybe someone who is an expert in piano

apps would give you. So again the more

personalized you can be in your context

the better the deep research is. Okay

let's keep going. Let's cover another

quick example. I'm going to skip the

creator business one. Uh you can read

about it in my newsletter post. Let's

talk about the family trip example,

right? So here's uh some deep research

that I did for a family trip. So I'm

looking for a place to go in December

with my parents and my kids. So it's

going to be a multi-generational family

trip. And in this project is what I

showed you before, which has a bunch of

personal context on what kind of trips

my kids like, what kind of places we

like to go in the past, and so on and so

forth. So, because it has all this

context, I'm asking it, "What are some

great places to go that are under

$10,000 total trip expense?" Okay, so

it's asking me a bunch of questions and

I answered them and then it went off and

did deep research and the top

recommendations for December trips are

New Orleans, Mexico's Riviera, Maya,

Costa Rica, and some other places. Okay.

So again, we just asked in a random chat

window to do deep research on family

trips. It might not have come up with

these answers, right? It came up with

these answers because I have a project

that has a bunch of personal context on

what kind of preferences that I like.

And then I can go off and go back and

forth with this chat to figure out

exactly where we're going. And uh it

turns out that we are going to Mexico

based on my chat with uh Claude. Okay,

there you have it. We covered a lot in

this video and I want to make it as

practical as possible. So let's do a

quick recap. So number one, use

different models for different use

cases. Use chat GPT for everyday

questions. Use claude if you spend a lot

of time writing and editing. And if

you're already into AI coding, either

use claw code or open AI codeex.

Gemini I think is great for images, any

kind of multimodal stuff and I think

Gemini 3 is coming out fairly soon too.

All right, so that's uh number one.

Number two, use projects for any kind of

major work stream that you're doing

because projects let you upload relevant

context so you don't have to do it each

time you chat with AI and it's just

incredibly useful. So I use it for uh PM

work, I use it for creative work, I use

it for personal stuff, too. And and

number three is uh use deep research

whenever you need to make an important

decision.

Again, give it a bunch of personal

context. Ideally, all this context is

already available in your project. Get

it to ask you a few questions before it

gets started. And uh once you get the

deep research report, add it to your

project to give your project even more

context. If you enjoy this video, please

like and subscribe to this channel and I

will make more practical AI tutorials

for busy people exactly like this. All

right, until next time.