ALL ROADS LEAD to AI CODING: Cursor, Aider in the browser, Multi file Prompting

Summary

This video script showcases the transformative impact of AI coding assistants on software development. It demonstrates how a single prompt can generate significant codebases, highlighting the productivity gains and efficiency of tools like Cursor and AER. The script illustrates multi-file editing, context-aware coding, and the potential for AI to handle boilerplate, allowing developers to focus on higher-level tasks. The future of coding is painted as increasingly automated, with AI assistants writing a significant portion of the code, aiming towards full agentic tools that create value autonomously.

Takeaways

• 🚀 AI coding assistants can significantly boost productivity by generating large amounts of code from minimal prompts.
• 📈 The script demonstrates an 8X multiplier in productivity by using AI to generate code, highlighting the efficiency gains in software development.
• 🔍 AI coding assistants like Cursor and AER are leading the way in AI-assisted coding, offering powerful features for developers.
• 💻 AER, a free open-source AI coding assistant, is praised for its explicitness and ease of use, especially with its new browser-based interface.
• 📚 Multi-file editing is a standout feature of AI coding assistants, allowing simultaneous edits across multiple files, which is a significant advantage.
• 🛠️ AI coding assistants can handle boilerplate code and minor adjustments, freeing developers to focus on more complex tasks.
• 🌐 AER's use of a REO map and its lightweight approach is contrasted with Cursor's deeper integration into the IDE, showing different strategies in AI coding assistance.
• 🔎 Cursor's blog hints at future developments like next action prediction and bug detection, showcasing the potential for even more advanced AI-assisted coding.
• 🏆 AER has achieved notable success in the S bench light, beating out competitors and demonstrating the effectiveness of its approach.
• 🔑 The future of engineering is envisioned with AI coding assistants writing a significant portion of code, potentially reaching up to 99% automation.

Q & A

What is the main focus of the video script?

The main focus of the video script is to demonstrate the capabilities of AI coding assistants, particularly Cursor and AER, in generating code and enhancing productivity in software development.

How does the video script illustrate the power of AI coding assistants?

The script illustrates the power of AI coding assistants by showing how a single prompt can generate a significant amount of code, such as 70 lines of code from a sentence and a half, and how these assistants can handle complex tasks like multifile edits and updating code across multiple files.

What is the significance of the 8X multiplier mentioned in the script?

The 8X multiplier signifies the productivity gain achieved by using an AI coding assistant. It represents the ratio of the amount of code generated (208 words) to the number of words in the prompt (25 words), indicating an eightfold increase in productivity.

What is the role of AI coding assistants in handling boilerplate code?

AI coding assistants help developers by handling boilerplate code, which are repetitive and standard parts of the code. This frees up developers to focus on more complex and creative aspects of coding, thereby improving productivity and reducing mental effort.

How does the script demonstrate multifile editing capabilities of AI coding assistants?

The script demonstrates multifile editing by showing how AI coding assistants can make changes to multiple files simultaneously. For example, moving resource functions from one file to another and creating test functions in a separate file, all with a single command.

What is the significance of the browser-based editor for AER mentioned in the script?

The browser-based editor for AER is significant because it provides a user-friendly interface that makes it easier to work with AI coding assistants. It allows for quick addition and removal of files and enhances the visibility and digestibility of the code editing process.

What are the future features hinted at by the Cursor team in the script?

The future features hinted at by the Cursor team include next action prediction, which involves predicting the next steps a developer might take while coding, and bug detection, which could be triggered during different stages of the development process like commit, push, or PR.

How does the script highlight the importance of context in AI coding assistants?

The script highlights the importance of context by discussing how AI coding assistants can utilize the context of the codebase to make more accurate predictions and edits. It also mentions the potential of using large context for better performance in tools like Cursor.

What is the significance of AER writing 7% of its own code as mentioned in the script?

The significance of AER writing 7% of its own code is that it showcases the potential of AI coding assistants to not only assist in coding but also to generate parts of the code autonomously. This is seen as a step towards more advanced AI-driven development processes.

What is the ultimate goal for AI coding assistants as described in the script?

The ultimate goal for AI coding assistants, as described in the script, is to achieve full agency in coding. This means developing tools that can create value autonomously, potentially reaching a point where they can write 99% of the code, allowing developers to focus on higher-level tasks and strategies.

Outlines

00:00

🤖 AI Coding Assistants: Power and Productivity

The speaker introduces the transformative power of AI coding assistants, emphasizing their ability to generate large amounts of code from minimal prompts. They demonstrate this by creating a TypeScript application with documentation using just a sentence and a half, achieving a significant productivity multiplier. The speaker also highlights the importance of using AI coding tools to avoid wasting mental cycles on boilerplate code and instead focus on more complex tasks.

05:02

🔧 Multi-File Editing and AI Assistant Features

The speaker showcases the multi-file editing capabilities of AI coding assistants, using AER (AI Engineering Assistant) as an example. They discuss the explicit nature of AER's interface and its ability to quickly edit multiple files in response to a single command. The speaker expresses enthusiasm for this feature and its potential to further streamline coding workflows, while also noting the desire for Cursor, another AI assistant, to implement similar functionality.

10:04

🚀 The Future of AI Coding: Predictions and Developments

The speaker delves into the future of AI coding assistants, discussing the potential for next action prediction and automatic bug detection. They highlight Cursor's development roadmap and AER's achievements, such as their state-of-the-art performance on the S-bench light. The speaker also emphasizes the importance of optimal context in AI coding and the complementary nature of different AI tools, advocating for the use of large language models to handle complex coding tasks.

15:05

🌟 Embracing AI in Coding: The Path to 99% Automation

The speaker concludes by discussing the end goal of AI coding assistants: achieving near-complete automation in coding tasks. They mention AER's self-written code percentage as a testament to the progress in this field and encourage engineers to embrace AI tools to maximize productivity. The speaker also hints at upcoming resources and courses to help engineers understand and leverage AI coding technology effectively.

Keywords

💡AI coding assistants

AI coding assistants are tools that leverage artificial intelligence to aid in the coding process, automating the generation of code based on user prompts. They are central to the video's theme, illustrating how they can significantly increase a developer's productivity by generating code and handling boilerplate tasks. In the script, the use of AI coding assistants results in the creation of 70 lines of code from a single prompt, showcasing their power to expedite coding tasks.

💡Productivity

Productivity in the context of the video refers to the efficiency and output of an engineer when aided by AI coding tools. The script emphasizes the significant increase in productivity that can be achieved by using AI coding assistants, with the video's creator highlighting an 8X multiplier in coding efficiency, demonstrating the transformative impact of these tools on a developer's work.

💡Boilerplate code

Boilerplate code is the generic, reusable code that forms the basic structure of a program but does not contain the unique, functional code specific to the application. The video discusses how AI coding assistants can handle boilerplate code, freeing developers from the mundane task of writing repetitive code and allowing them to focus on more complex and creative aspects of programming.

💡Multifile edits

Multifile edits refer to the capability of an AI coding assistant to make changes across multiple files simultaneously. The script showcases this feature by demonstrating how the AI can move functions from one file to another, enhancing the workflow by reducing the manual effort required to refactor code across different files.

💡CLI (Command Line Interface)

CLI is a text-based interface used to interact with a computer program, where users input commands to execute various tasks. In the video, the AI coding assistant is used to create a CLI application that allows for the management of resources, such as adding, viewing, and deleting items, demonstrating how AI can streamline the process of building command-line tools.

💡AER (AI Engineering Assistant)

AER is an open-source AI coding assistant mentioned in the script as one of the best tools for accelerating coding tasks. It is highlighted for its ability to perform multifile edits and its user-friendly browser interface, which simplifies the process of adding and removing files from the context of the AI's analysis.

💡Cursor

Cursor is another AI coding assistant discussed in the video, known for its deep integration with the IDE (Integrated Development Environment) and its capabilities for next action prediction and code completion. The script mentions Cursor's potential for bug detection and its role in shaping the future of AI-assisted coding.

💡Code generation

Code generation is the process of creating source code automatically, which is a key feature of AI coding assistants. The video demonstrates the rapid generation of code through a simple prompt, emphasizing the efficiency and speed at which AI can produce code, thus enhancing the coding process.

💡REO map

A REO map, as mentioned in the script, is a tool used by AER to understand the codebase without making deep assumptions about its structure. It represents a lightweight approach to AI coding assistance, allowing the AI to provide relevant suggestions without the need for extensive integration with the code's underlying architecture.

💡Agentic tools

Agentic tools, as discussed in the video, are applications that perform tasks autonomously on behalf of the user. The script talks about the future of engineering where AI coding assistants like Cursor and AER could potentially write a significant portion of the code themselves, moving towards a state where these tools are fully agentic, creating value without direct human intervention.

💡Bug detection

Bug detection in the context of the video refers to the potential feature of AI coding assistants to identify and flag errors in code. The script mentions Cursor's exploration of this capability, suggesting that AI could analyze code during various stages of development, such as during commits or pull requests, to automatically detect and highlight potential issues.

Highlights

AI coding assistants can generate 70 lines of code with a single command, significantly increasing productivity.

AI coding assistants can handle boilerplate code, freeing up mental cycles for more complex tasks.

The productivity gain from using AI coding assistants can be quantified, with an 8X multiplier demonstrated in the video.

AI coding assistants can update multiple files simultaneously, streamlining the coding process.

AER, a free open-source AI coding assistant, is highlighted for its browser-based features and ease of use.

AER's ability to handle multi-file edits is a significant advantage over other AI coding assistants.

Cursor, another AI coding assistant, is noted for its potential in next action prediction, enhancing coding flow.

Cursor's integration with IDEs provides a deep dive into coding assistance, potentially leading to higher productivity gains.

AER's lightweight approach and use of the REO map allow for a hands-off method in coding assistance.

AER has achieved a significant milestone by writing 7% of its own code, showcasing the potential of AI in self-improvement.

The future of engineering is predicted to involve AI coding assistants writing a much higher percentage of code, up to 50% or more.

AI coding assistants are positioned as essential tools for engineers to stay competitive and maximize productivity.

Cursor and AER are highlighted as the top AI coding assistants, with unique approaches to coding assistance.

The video discusses the importance of embracing AI coding tools to avoid being left behind in the engineering field.

AER's recent achievements in the S bench light are noted, showing its competitive edge over other AI tools.

The video emphasizes the need for engineers to focus on leveraging AI coding assistants to generate more value.

Upcoming features for AI coding assistants, such as bug detection and optimal context, are discussed as areas of future development.

The video concludes with a call to action for engineers to join the journey of AI coding and agentic engineering.

Transcripts

if you are not using AI coding

assistants to write code I'm going to be

real with you you are running out of

time watch this we're going to run a

single prompt to generate the beginning

of an entire code base

so with one command with a sentence and

a half we've generated 70 lines of code

and let's go ahead and run this to make

sure it's real right this is a bond

typescript application I asked for docs

I asked for Cle documentation all Ron

Bond index and you can see there we got

uses docs all Ron Bond index view you

can see this file doesn't exist let's go

ahead and make sure that it doesn't bomb

when the file doesn't exist so just

highlight we another prompt don't bomb

when file doesn't

exist let that run it's going to add the

existence check it's going to run

through every single line I'll accept

run this again no error this time let's

go ahead and add an item if we check

that API via our docs we can just say

add and then we pass in a link so let's

go ahead and add a link to add a new

resource imagine we're building at a you

know small tool that allows us to store

AI resources maybe we'll read them into

an llm ADD and then we'll pass in some

link we'll use the AER website URL we'll

hit add and then we've just added

resource with i1 let's go ahead and run

our view command again and you can see

we have AER in there let's go ahead and

add another link We'll add

bun and let's go ahead and add cursor

since we're at

it okay and then we'll run our view

command again and we now have our three

resources great so if you've used AI

coding assistant before you already know

what's going on here you already know

the power of AI coding assistance you

already know how much they can multiply

productivity in this video I want to

share and show off some of my favorite

AI coding assistant features I'm going

to give you a couple tips and tricks on

how you can get started and to progress

your AI coding abilities and then at the

end I want to look over some of the

incredible blogs that the cursor Bros

and AER are working on so AER shout out

and cursor shout out the NYS spere team

you guys are building great products

these two products are by far right now

the best AI coding assistants we've

talked about them on the channel before

it's important to bring up every now and

then because the space is rapidly

evolving let's go Ahad and just

backtrack a little bit right what just

happened so we ran two prompts generated

70 lines of code I just want to contrl Z

this a little bit and I want to look at

the actual multiplier that we just

unlocked by using an AI coding assistant

right I'll just control Z all the way

back I'm going to copy the prompt that

we use

and I'm just going to go ahead and open

up a node instance paste this in as a

string and type length so you can see

there that was 125 characters now let's

go ahead and split it and what we're

looking at here is the number of words

that we use to generate 25 words to

generate what what exactly did we

generate let's go ahe and look at that

first generation here you can see I have

a word count enabled here this 25w

prompt generated 208 words so if we take

that let's just go ah and do some

rounding right we'll round down so 200

over 25 that's that's an 8X multiplier

this is incredible right I just want to

really shout out how important this is

It's very rare that you end up in a

scenario where you can directly analyze

your productivity gains as an engineer

by using a tool I think that when you

look at a coding assistants and you look

at what you can do with them it's

blatantly obvious how much you can get

out of your AI coding tool right it's

just so easy to measure the productivity

gain um adex right we had another prompt

in there let's say we had a couple or

round it down right let's say it's only

a 5x that's still insane it's still

incredible and most importantly I think

one of the big highlights of a coding

assistance is you're not wasting your

mental Cycles on the boilerplate code

right you're just you're just not

wasting it let me go ahead and show off

another feature that I'm really excited

about with a coding assistant the

ability to update multiple files so

let's go ahead and switch over to AER

the best free open source AI coding

assistant what I'm going to do here is

create another file I'm going to call it

um I'm going to call it

C.S and I'm going to open up another

browser instance and run AER B this is

my AER Shand command to kick off one of

aer's brand new features you can now run

AER in the browser so this this wrapper

makes AER a lot more pleasant to work

with so let's go ahead and just look at

this let's go ahead and add some files

so I'll add um see if that CR file

didn't get picked up so let me go ahead

and just commit my code here so ad can

pick up that file go ahead and run that

refresh and I'll go ahead and add that

crud file and I'll add index.ts you can

see here with this nice clean UI it's

very visible it's very easy to digest

I've just added two files to the context

I like AER in that it's a lot more

explicit than cursor you really know you

really know exactly what AER is looking

at and then I'll just type move the

resource functions from indexs into

credts let it rip huge shout out to GPT

40 open AI really popped off with that

model it's been incredible to work with

look at how fast this is at gp4 level

with GPT 3.5 speeds uh pretty crazy

stuff let's go ahead and check out those

edits and so you can see here we now

have our crud TTS and we also have our

index.ts you can see here we're now

operating with just some 30 lines we

have that you know CLI functionality and

then we have our import for uh the crud

ttsa right let's go ahead and just run

this again make sure everything works

the same so bun index View and Bam so

you can see here we have our same files

everything's working as as previous

let's go ahead and remove um what is it

delete and we'll say two so resource ID

to deleted that should take out the bun

resource and if we run view again bam we

have one and three AER and cursor so

really incredible stuff right um

multifile edits is a huge huge Advantage

this is something that I would like to

see cursor bring to the table I know

they're working on a lot of really

important cool features but I think

multifile editing is a huge huge win uh

again big shout out to to ader and Paul

for having this feature and I've really

been enjoying using the browser editor

here for AER it just makes it a lot

easier cleaner to work with you can more

quickly add and remove files on the

channel we've been using AI coding

assistants for over a year now uh which

is really really crazy to say the Space

is really exciting this is the tool you

need to be paying attention to if you're

an engineer our productivity as

Engineers is directly tied to the

ability and the strength of our tools

you can be a shitty engineer with great

tools and get a lot done but if you're a

great engineer and you have shitty tools

you are limited by your tools you want

to be a great engineer and you want to

have great tools AI coding assistants AI

code editors these tools are where we

need to be focusing our time and

attention to right now there is no

bigger multiplier on your productivity

than to increase your ability to

generate more code in ranges in the 2 to

10x range you do not want to miss the AI

coding train and get left behind so

that's awesome uh we can push this even

further let me just show off a quick

example let's say we wanted to create a

test we'll call this cr.

test.ts and again uh for that multifile

capability what we're going to do here

is open up AER in the browser and we're

going to let me go ah and just commit

this again and what we'll do is refresh

crud CR test index and I'll do the

following right I'll say add a new

function delete all and add bun tests

for the crud module so I'm asking to do

two things in one here usually you'd

want to go one at a time add this delete

all and then afterward add BUN test but

I'm doing it together uh just because I

know that this will work so I'm going to

fire that off and AER is going to start

making changes to multiple files getting

all this work done for us we type one

sentence it's writing a bunch of code in

the right places for us automatic Al

it's so cool to see this come out and

you can see here edits applied so it

looks like we're not actually using

delete all resources so I'll just go

ahead and say I'll hop back over to AER

and just say uh create a CLI command to

run delete all resources let that run

and so while okay so nice it it added

that so quickly so I notice here it

didn't add that delete all would just go

ahead and highlight over this you can

see we have cop Plus+ doing some work

for us uh Delete all it's adding that

into the loging for us I'll just hit tab

that's awesome that's complete um let's

go and take a look at the test you can

see here we're using just I don't want

to use just here so let's go ahead and

just use cursor for this I'll just say

remove just and I'll also say um don't

mock anything I'm fine with this just

running against uh you know my local

file

system just going to make all the

changes for us here uh we're going to

ignore this we do have bun automatically

importing this is just a problem with my

lunter that I don't care about and we

can run BUN test you can see everything

completed properly let's go ahead and

bomb a test on purpose so let's uh let's

change this to a five just to make sure

that this is real and Bam you can see

there we got one F test revert and BUN

test good so we're all good we uh wrote

test we modularized our crowd

functionality we added a new delete all

resources function and we exposed that

via our CLI application all of this

happened in a hilariously small amount

of time we are rearranging code at light

speeds thanks to our two AI coding

assistants I'm going to go ahead and say

it these are the two best AI coding

assistants right now a lot of the AI

engineering the AI coding and the

agentic engineering content that we

share on the channel gets lost in time

to the YouTube algorithm I mentioned

this in the previous video but I'm

working on a resource a website that

that will be free that will allow us to

you know kind of build up this

repository of incredible AI tools AI

resources and of course you know some of

the most important content on there is

going to be AI coding because that is

the first really big use case for

engineering productivity gains in the

age of llms in the age of AI so those

are a couple features I wanted to call

out so I hope you see the value in this

if you've been using AI coding

assistants AI code editors AI pair

programming everyone has their slightly

own different terminology for for it in

my mind it's all the same these are AI

coding assistants they help you the

engineer write more code faster than

ever if you're using these yourself or

you're going to start thanks to this

video hit the like hit the sub it helps

other engineers get exposure to these

incredible tools as well one last thing

I want to do in this video I want to

look at where the cursor Bros and where

AER are kind of hinting at what's coming

next right so let's go ah and look at

this previous blog that came out from

the cursor team and uh they're talking

about the problems that they're you know

aiming to solve in 2024 2025 right and I

think it really shows where their heads

at and what they see coming next I love

this idea of next action prediction this

is when you're in cursor you're writing

code and it's basically copi Plus+ it's

this idea that once you start coding

something and you start making tweaks

there's a flow to it right there's a

path there's a pattern to it and just by

hitting tab just by knowing the most

likely case the most likely position of

the cursor you can essentially guess

what we want to do next right and let me

show you a concrete example of this if I

started making a change here right let's

go ahead and say I wanted to suffix this

right and I said read resources method

for whatever reason cursor in copat

Plus+ will start looking ahead and

Gathering context about what's the next

move he would likely want to make given

that change so if I just highlight the

next method and hit tab it's starting to

pick up on the trend right method method

and now it's updating the method call

inside here right and now it's looking

at the next method and now it's autoc

comp completing both the function name

and the caller right so you can see how

incredible this is right I'm not

thinking I'm not wasting mental Cycles

on this stuff my AI coding assistant is

doing it for me right and that's the

incredible part your AI coding assistant

right now can handle all the boiler

plate it can handle all the you know

weird small name changes variable

placements all the stuff like that

that's you should be really confident in

using AI coding assistance right so I

just want to shout that out um again I

want to shout out the uh you know cursor

team uh great work on all this stuff

please keep pushing this this is

incredible it's been great using that so

this is really cool I'm excited to where

they take this I do think this is the

right question to ask can we take this

idea to its natural limit there is no

reason why a natural logical flow of tab

completion like this cannot be solved

completely and I think you know C Is

Right on track to do that because they

have the full editor at their disposal

pretty incredible stuff there they talk

about some of the the ways they're doing

that um I'll leave that up to you to

read I'll link these in the description

of course um perfect edits this is

something that I think will come and get

kind of close My Philosophy around you

know models and Ai and predictions

you'll never get 100% but you should try

to get as close as possible I think the

real trick here is can they make it fast

and keep it accurate right um they

mentioned multifile edits here this is a

great call out I'm glad that they are

you know taking note of this I'm sure

that they you know pick this up from

ader AER does support out of the box uh

multi file edits which is amazing you

saw us we did a couple of those here we

have three files that edited all three

in one shot um so that was pretty

incredible it would be awesome to have

that rolled into cursor as well it's

great to see them looking at that

optimal context if you're a fan of the

channel you know that I am very anti-

rag I don't think that retrieval

augmented generation is worth anyone's

time

outside of like Brute Force pulling in

relevant files and throwing it into the

context I think that this is betting

against uh the development of the next

incredible generation models which is a

dumb thing to bet against take whatever

context you need throw it at the model

and let the model handle the hard part

of it right and just make sure that your

prompt is solid I think that tools like

cursor do have a slightly larger use

case for a large context and for some

type of rag based solution I hope that

uh you know both both them but also

everyone building out these uh agenc

pipelines I hope that you don't get too

lost in this sauce context windows will

go up needle in the hay stack uh

accuracy will continue to increase uh

one last thing here on cursor's blog and

we'll hop over to a Blog from ader that

I just want to highlight um they're

looking at bug detection I think this is

a really cool idea I think the question

is when do they fire this off do they

fire it off while you're writing code do

they fire it off you know during the

commit process during the pr process

during the push process lot of

interesting questions there for

automatic bug detection I think this

could be a really really killer use case

since cursor again is operating right in

an IDE they have a lot of power and

control um it's a massive Advantage

whereas something like ader is a lot

more lightweight it's in the terminal it

can read your code base it doesn't it

uses something called a REO map and I

think it's a a nice kind of lightweight

hands-off approach I like how these

tools are different I think they

actually complement each other I think

that cursor is like your Deep dive

coating and face whereas AER doesn't

want to make too many assumptions about

your code base and it kind of stays on

that like lighter wrapper layer we'll

see how this progresses let's go ahead

and just look at a quick blog from ader

AER has taken the state-ofthe-art on the

S bench light um I think this is really

really cool it beat out um I think open

Devon and uh what was the other one yeah

open Devon beat out Amazon's agent which

is really epic um and I love this you

know just like we were talking about AER

aims to be interactive not fully agentic

this is a differentiated approach that

AER is taking cursor is going a little

deeper I do think that this like serves

as a great differentiator for both

cursor and AER being agentic versus

staying lightweight just use the prompt

put it on the code base and uh cuz

things get really really complicated

once you start uh digging your hands

into you know making assumptions about

uh the best uh agentic flows and the

best agentic pipelines to set up I love

this shout out again from Paul and ader

ader does not use rag Vector search or

you know tools or anything like that

right and I do think again this is an

advantage it might seem like a

disadvantage I think over the long term

we'll see other tools fill that space

but the fact that ader is such a

lightweight wrapper that can still do so

much I think speaks a lot to its design

but also you know the power of uh large

language models and I do think a tool

like AER will benefit the most from the

continued improvements from Models

because it's not digging its hands too

deeply into the you know the agentic of

it all so that's awesome to see um and I

think this is the coolest thing so I I

want to end on this note AER has written

7% of its own code um when I saw this I

got so excited because to me this is the

future of engineering I'm working on

several code bases right now where this

number is much much higher this is more

close to 50% now I I'm I'm putting out

so much more content so much more value

as an engineer by handing off the

writing the code the individual lines to

my AA coding assistant and I think this

speaks to this idea of you want to be

upleveling yourself you want to be

telling your AI coding assistant your AI

pair programmer what to do and you let

it figure out how to do it llms are text

generation machines let them do that

that's what they know that's what they

can do code is a subdomain of text and

llms know text better than any human

being in the past ever you know on the

channel we are basically spending all of

our time to send this number to 99% it

might sound really crazy but this is

really what we're going for this is what

we're aiming for we want to take this

number and go to 99% let's just go ahead

and hop in here and just you know

filling the dream that we're aiming for

here right we want 99% the end game

really is full agentic tools

applications workflows that create value

on our behalf while we sleep I've said

it on the channel over and over and I

will continue to say it because that is

our mission that's what we're doing

that's what we're aiming for and AI cing

assistants like cursor and AER you know

big shout out to them not sponsored by

either of these guys yet uh definitely

would would love to be would love to

work with either cursor and or AER

there's a lot happening here it's

progressing and I think this is a really

important tool if you're an engineer

right now you do not want to get left

behind you want to be on the AI coding

train you want to be using these these

tools to generate more value than ever

before if you want to stay plugged in

and you want to stay close to AI coding

and agentic Engineering hit the like hit

the sub join the journey as I mentioned

I'm working really hard on a resource

that will take everything that we do on

the channel and make it more accessible

more usable with concrete guides and

some really interesting AI coding

related courses that you're going to be

able to use sign up for and really

understand how to maximize this

technology to create value for yourself

so if you're interested in that you know

what to do thanks so much for watching

I'll see you in the next one