World's First AGI Agent SHOCKS the Entire Industry! (FULLY Autonomous AI Software Engineer Devin)
Summary
TLDRCognition Labs introduces Devon, the world's first AI software engineer, capable of autonomously tackling complex engineering tasks. Devon demonstrates its abilities by benchmarking API performance, debugging, building websites, and even fine-tuning AI models. The AI's proficiency in using developer tools and learning from documentation showcases the potential for AI to revolutionize software engineering, offering a glimpse into a future where AI assistants like Devon could automate and enhance various aspects of the profession.
Takeaways
- 🚀 Introduction of Devon, the first AI software engineer, capable of performing complex tasks like a human engineer.
- 🛠️ Devon can create a step-by-step plan, build projects, and use tools such as a command line, code editor, and browser.
- 📚 Devon autonomously learns by reading API documentation and other technical materials to solve problems.
- 💡 Devon has the ability to debug code by adding print statements and fixing bugs based on error logs.
- 🌐 Devon can build and deploy fully styled websites, showcasing its capabilities in web development.
- 📈 Devon has successfully passed practical engineering interviews and completed real jobs, demonstrating its real-world applicability.
- 🤖 The development of Devon represents significant advancements in AI reasoning, long-term planning, and autonomous task execution.
- 🎥 A video from 6 months prior discussed the concept of autonomous AI agents running software businesses, which is now becoming a reality with Devon.
- 🔧 Devon is equipped with common developer tools within a sandboxed computer environment, allowing it to perform tasks securely.
- 🏆 Devon outperforms other AI models in benchmarks for resolving real-world GitHub issues, indicating its superior problem-solving skills.
- 🌟 The potential future scenario where autonomous AI agents like Devon could run businesses, performing tasks and customer service without human intervention.
Q & A
What is Devon and what makes it unique?
-Devon is the world's first fully autonomous AI software engineer developed by Cognition Labs. It is unique because it can perform complex engineering tasks, learn over time, and fix mistakes. Devon is equipped with common developer tools and can operate within a sandboxed computer environment, making it capable of end-to-end development and deployment of applications.
How does Devon tackle a problem?
-Devon approaches a problem by first creating a step-by-step plan to tackle the issue. It then builds a project using the same tools a human software engineer would use. If it encounters an error, Devon adds debugging statements, reruns the code, and uses the error logs to fix the bug.
What are some real-world applications of Devon?
-Devon has been used to complete real jobs on Upwork, fine-tune a 7B llama model, set up a computer vision model, and fix bugs in existing software. It has also been used to implement a game of life, improve user experience in an open-source tool, and autonomously learn from a blog post to generate a desktop background image.
How does Devon's performance compare to other AI models in solving real-world GitHub issues?
-In a benchmark for resolving real-world GitHub issues, Devon achieved a 13.86% success rate, which is significantly higher than other models like GPT-4, making it around 7 times more effective than GPT-4 in this context.
What kind of support does Devon provide to human engineers?
-Devon can assist human engineers by taking on tasks such as running commands, tracking their status, fixing bugs, writing test cases, and improving user experience in tools. This allows engineers to focus on more interesting problems and achieve more ambitious goals.
How does Devon's learning process work?
-Devon learns by reading documentation, running code, and understanding the context of tasks. It can recall relevant context at every step and adapt its approach based on the information it gathers, allowing it to learn from its experiences and improve over time.
What is the potential impact of Devon on the software engineering field?
-The introduction of Devon could revolutionize the software engineering field by automating complex tasks, reducing the time taken to solve problems, and enabling engineers to work on more innovative projects. It could also lead to the creation of new job roles that focus on managing and optimizing AI software engineers like Devon.
How does Devon handle versioning issues?
-When faced with versioning issues, Devon updates the code to make it compatible with the required versions. It also uses tools like pip to manage dependencies and ensure that the project runs smoothly.
What is the significance of Devon's ability to use a browser?
-Devon's ability to use a browser is significant as it allows it to access API documentation, learn how to integrate with various APIs, and gather information from the internet to assist in problem-solving and project development.
How does Devon's deployment of a website showcase its capabilities?
-Devon's deployment of a website with full styling demonstrates its ability to not only code but also to create visually appealing and functional end-products. It shows that Devon can understand design requirements, implement them in code, and deploy the final product, just like a human developer.
What is the future potential of autonomous AI agents like Devon?
-The future potential of autonomous AI agents like Devon is vast. They could lead to the automation of various aspects of business operations, from customer service to product development. As they become more advanced, they could potentially run entire businesses, allowing humans to focus on higher-level tasks and innovation.
Outlines
🤖 Introduction of Devon, the AI Software Engineer
The video introduces Devon, the first AI software engineer developed by Cognition Labs. Scott, from Cognition AI, showcases Devon's capabilities by asking it to benchmark the performance of a llama and different API providers. Devon demonstrates its problem-solving skills by creating a step-by-step plan, using tools like a command line, code editor, and browser to tackle the task. It encounters an error, adds a debugging statement, and fixes the bug using logs. The video emphasizes the advancements in AI's reasoning and long-term planning, and invites viewers to try Devon for real-world tasks.
🛠️ Devon's Problem-Solving and Debugging Skills
The paragraph details Devon's ability to handle complex tasks such as setting up a computer vision model for a client on Upwork. Despite encountering versioning issues, Devon updates the code to resolve them and proceeds to load and import packages, downloading images to run the model. Devon also performs print line debugging to understand data flow and corrects the code accordingly. The paragraph highlights Devon's persistence and problem-solving approach, ultimately delivering a report with sample images and a detailed explanation of its work.
🎮 Devon Assists in Game Development and AI Training
Devon's versatility is showcased as it assists in implementing the game of life and fine-tuning a 7B llama model. For the game, Devon creates a React application, writes code, and deploys it, making adjustments based on user feedback. In the AI training task, Devon fine-tunes a large language model, overcoming CUDA issues, and successfully running the training job. The paragraph emphasizes Devon's ability to learn and adapt to new tasks, such as understanding and applying a fine-tuning method to a language model.
🔧 Devon Fixes Bugs and Improves User Experience
The paragraph describes Devon's role in fixing bugs and improving user experience for various projects. It helps enhance an open-source tool's UX by understanding the code and making necessary changes. Devon also assists in debugging a Python algebra system, identifying and fixing an issue with log calculations. Another engineer shares his experience with Devon, who helps in writing and expanding test cases for an open-source repository, ultimately finding and fixing a bug. The paragraph highlights Devon's ability to understand and manipulate code, debug issues, and enhance software quality.
🚀 Devon's Autonomous Learning and Business Potential
The video script ends with a scenario where Devon autonomously learns from a blog post to generate a desktop background image. It also discusses the potential of Devon as an AI software engineer in a business context, where it could handle all aspects of a custom automation business, from customer interaction and solution brainstorming to software development, part ordering, and customer service. The scenario illustrates the potential for AI to revolutionize business operations, requiring minimal human intervention and leading to significant efficiency and profit.
Mindmap
Keywords
💡Devon
💡AI Software Engineer
💡Benchmark
💡API Providers
💡Debugging
💡Upwork
💡Autonomous AI Agents
💡Long-term Planning
💡Code Editor
💡Sandboxed Environment
💡GitHub Issues
Highlights
Cognition Labs introduces Devon, the world's first AI software engineer, capable of performing complex engineering tasks.
Devon can benchmark performance, create step-by-step plans, and build projects using tools like a human software engineer.
Devon has its own command line, code editor, and browser to execute tasks and learn from API documentation.
The AI software engineer can debug code by adding print statements and fixing errors based on logs.
Devon can build and deploy fully styled websites, showcasing its capabilities in web development.
Advancements in reasoning and long-term planning have made it possible for AI like Devon to tackle complex problems.
Devon has successfully passed practical engineering interviews and completed real jobs on platforms like Upwork.
The AI agent autonomously solves engineering tasks, including setting up computer vision models and fine-tuning large language models.
Devon demonstrates the ability to learn from blog posts and apply the knowledge to generate desktop background images.
Cognition AI's development of Devon represents a significant leap in AI capabilities, surpassing current tools available to the general public.
Devon's performance on benchmarks shows it is seven times more effective than GPT-4 at resolving real-world GitHub issues.
The AI software engineer can autonomously learn and improve code, fixing bugs and edge cases not covered in the original documentation.
Engineering teams can achieve more ambitious goals with Devon's assistance, as it can handle complex tasks requiring thousands of decisions.
Devon is equipped with common developer tools within a sandboxed computer environment, simulating a human developer's workflow.
Cognition Labs' creation of Devon signifies rapid progress in AI, with capabilities beyond what was anticipated just six months prior.
The potential applications of Devon include running businesses autonomously, providing custom automation solutions, and handling customer service.
Devon's ability to learn and apply new skills suggests a future where AI agents could become commonplace in various industries.
Cognition Labs has raised $21 million in series A funding led by Founders Fund to further develop Devon's capabilities.
Transcripts
so cognition Labs just drops this Devon
the first AI software
engineer hey I'm Scott from cognition Ai
and today I'm really excited to
introduce you to Devon the first AI
software engineer let me show you an
example of Devon in
action I'm going to ask Devon to
Benchmark the performance of llama and a
couple different API
providers from now on Devon is in the
driver's
seat first Deon makes a step-by-step
plan of how to tackle the
problem after that it builds a whole
project using all the same tools that a
human software engineer would use Devon
has its own command
line its own code
editor and even its own
browser in this case Devon decides to
use the browser to pull up API
documentation so that it can read up and
learn how to plug into each of these
apis here Deon runs into an unexp
[Music]
error Deon actually decides to add a
debugging print
statement reruns the code with the
debugging print statement and then uses
the error in the logs to figure out how
to fix the
bug finally Devon decides to build and
deploy a website with full styling as
the
visualization you can see the website
here
all of this is possible today because of
the advancements that we've made in both
reasoning and long-term planning it's a
really hard problem and we've only just
started but we're super excited about
the progress that we've made so
far in the meantime if you'd like to try
out Devon on your own real world tasks
send us a request below and we'd be
happy to forward it to Devon about 6
months ago I made this video about
autonomous AI agents now this was before
that terminology was quite as used you
we're hearing it more now back then it
was isn't quite as common so this was 6
months ago August 27th 2023 I'll play a
clip from this towards the end of the
video but the question I was asking that
video was how far away are we from a
situation where basically an autonomous
AI agent would be able to kind of run a
software business on your behalf satisfy
customers orders create little scripts
for them send those out Etc and you know
that video is very well received a few
people thought that's never going to
happen that's a million years away and
some people gave their kind of timelines
for that but I think overall a lot of
people said how Blown Away they were by
this concept of having an autonomous
worker that's able to generate money for
you kind of a big concept to think about
on many different levels not just for
yourself but how would having access to
something like that change the world
it's been about 6 months that was 6
months ago keep that keep that in mind
people were super interested some small
percentage was calling BS that was 6
months ago and this this is today today
we're announced to excite I can't even
read right now okay Wes calm down and
try that again today we're excited to
announce Devon the first AI software
engineer so Devon has successfully
passed practical engineering interviews
from leading AI companies and has even
completed real jobs on upwork so it does
the job interview it completes the jobs
demon is an autonomous agent that solves
engineering tasks through the use of its
own Shell Code editor and web browser so
let me do this so this thing isn't out
yet for everyone I am I am spamming the
crap out of anyone that can uh get me
access so I'm really hoping to have
access to this thing ASAP big props to
David Andre for breaking the story
that's where I saw it first the title
said world's first AGI agent yes this is
real I was like no it's not and I
clicked it anyways and yeah it kind of
seems like it just might be let me know
in the comments what you want to see
this thing do and watch these videos
that showcase its
abilities hey I'm Walden one of the
developers here at cognition AI we were
playing around with whether or not Devon
could start a side hustle on upwork so
here's actual real job from upwork where
the client wants to set up this computer
vision model which actually looks quite
interesting seems very difficult to set
up um I'm not sure how I would start
doing this but you know you give the
task to Devon and ask Devon to figure it
out and things just kick off Devon
immediately
goes ahead and you can see it sort of
starts setting up the repo it actually
runs into some issues here with the
versioning so if you watch how Devon
deals with
it deon's actually updating the code to
make these things
work he continues with this loading and
importing packages you can see that
actually downloads images from the
internet to run through the
model
but you can see here that there are
actually some issues that come across
however Devon knows how to handle these
things Devon kind of pushes through and
if you look closely Devon's actually
doing print line debugging
here where Devon is adding these
statements to track where the data
flows and Devon continues to do this
until Devon understands how everything's
working and actually then updates the
code with the fixes
after removing print line
statements Deon continues this pattern
of fixing code and running it again
until it runs the image model across all
these roads across the world and we can
ask for a report from
Devon at which point Devon sends over
some sample images of roads with damage
marked
out and a nice txt file explaining
Devon's work and the different kinds of
outputs of the model good job
de hi I'm Adon and today I felt like
playing the game of life so I asked Deon
to implement it for
me Deon started by creating a new react
application using the Shell and then it
started writing some code through its
editor after that it deployed the app
through netlify let's check it
up that seems nice um but there's a lot
more features which I want to add
so let's ask Deon to do this one at a
time I want the words Dev to be written
at the initialization screen instead of
it being
random then I want the word to be
slightly bigger and the frame rate to be
faster I also want him to fix a bug
where the screen gets freezed after 3
seconds let's see the progress dev has
made so far
you can see the diff and um the last
diff shows that Devon just fixed the bug
uh where the screen gets frozen after 3
seconds the seems reasonable to me so
let's move
on next I want Deon to increase the
frame rate after 10
seconds and also to make the website
responsive to different window
sizes also wanted to make it interactive
so that when when I click my mouse
somewhere it should spawn a new
block let's check out what Deon has made
so
far started with de which is what we
asked for and when I click something it
creates a new block as
well that's
fun um let's play around with
it well that goes my evening
hey guys today I'm going to show you an
AI training in
AI so here we're going to take the Cur
repo which is a fine-tuning method for
quantizing large language models we're
going to feed this repo to our agent
Devin and all we have to ask Devon is to
fine-tune a 7B llama model Devon clones
the repo
figures out how to run it using the
readme sets up all of the requirements
using
pip looks through all the
scripts and is able to start running the
training job there are a few hiccups
where Devon runs into some Cuda issues
which is to be expected with open source
repos but it's not a problem Devon looks
at the Nvidia environment
and figures out how to reinstall the
packages to make it
work after a few more runs figure out
the correct model
names Devon successfully gets the
training run
working here we see training proceeding
smoothly loss is going
down and
after few steps looks pretty good I tell
Devon to wait as the training job
runs after about an hour I come back ask
Devon hey how's the training going Devon
helps me look a few hundred steps are
done now and everything is still
proceeding
smoothly looks great thanks Devon for
helping me set up my training
run hey I'm Tony an engineer cognition I
helped build Devon and now Deon helps me
too today at work I wanted to run a
bunch of commands at once and be able to
track their status on one screen I found
an open source tool named impro to do
this here it is right here looks like it
all finished but the status is way too
vague I don't know which ones failed
they all just say
down I really want to improve the ux
here but I'm not familiar with the code
at all so I had Devin my AI software
engineer help me looks like this person
right here had the same issue so all I
gave Devon was the link to the issue and
asked Deon to fix it you can see me make
the request right here on the left let's
see what Devon did on the right we can
track deon's work and watch Devon jump
from tool to Tool first Deon Clon the
repository using the Shell then reads
the read me and an Editor to learn how
to sub the
code then goes back to the Shell to
install the required
dependencies Devon also opens up a web
browser
to take a look at the
issue now Devon starts
coding at some point Devon even opens up
some Rust documentation to debug a
compiler
error finally Deon finishes the task and
reports a summary of the changes that
were
made let's see the changes work I have
deon's code right
here looks like it worked the third
command succeeded I can even see the
status
codes here's all the code that Devon
wrote for this
change thanks
Devon hey I'm Neil and I wanted to show
you an example of Devon our AI software
engineer helping me fix a bug so I've
been using this repo called Senpai
Senpai is an algebra system written in
Python and I noticed this issue where
when you take the log of a fraction you
get Zoo which is a type of
infinity so that's definitely wrong but
instead of trying to figure this out
myself I just asked Deon to take a
look Devon immediately jumps in sets up
the repo and is able to reproduce that
same Zoo
output Devon then figures out the right
part of the code and adds print
statements um in order to figure out
what the cause of this issue
is
and we can see here that the cause is
that integer division leads to a zero
and then we take the log of zero So
based on that Devon's able to fix the
issue in The Code by replacing that
integer division with true Division and
then cleans up the debug
output and verifies that the result is
what we want and then Devon even runs
the test and the repo as well to make
sure nothing else is broken so that was
great um saved me a ton of time so thank
you
Dev hey I'm Andrew an engineer at
cognition and I wanted to share a pretty
amazing experience I had with Devon so I
maintained this big open source
repository uh which contains a lot of
different algorithms uh used for
competitive programming a lot of people
use it and a few weeks ago uh my friend
texted me that you know there was
actually a bug in one of the in one of
the implementations uh the
implementation wasn't quite right when
the inputs weren't uh weren't relatively
prime I kind of glossed over that case
when I was implementing it so I never
really thought about it so I implemented
a quick fix and then I thought that I
should test it but I actually never
really got around to writing any test
cases so I thought if I don't want to do
it I should just ask Devon to do it
instead so I gave Deon the repository
asked uh asked Deon to just check it out
and start working on it uh so Deon you
know found the right repository checked
it out you know found all files that are
in the repository and then I told Devon
what test case I wanted him to
write uh I just told Deon you know these
are the inputs and then try checking for
these conditions for me so Devon wrote
the test without too much trouble uh it
was Devon just looked around to
understand what exactly uh what exactly
the test should look like and what
exactly the interfaces were and with
this Devon ran the tests ran into a
quick hiccup which was a compile ER but
Devon is able to solve those very
effectively and just added an extra
include to fix that and then uh was done
writing this initial test so then I
asked de to actually expand the test a
little bit instead of just testing this
one input I wanted Deon to write test it
on all inputs so kind of the Brute Force
testing strategy I use this a lot in my
test and I just wanted Devon to
implement it so that I didn't have to
worry about it so de went and rewrote
the test function to use four n for
Loops but this time after Deon ran the
tests Devon actually found a test
failure now you know if the code were
correct there could be compilers in the
test but you know the test seemed really
pretty reasonable so there probably
shouldn't be a failure so Devon went and
tried to debug the program for me so
Devon here actually wrote uh actually
added a print statement to debug the
outputs uh and the inputs to the failing
test reran the tests and actually found
which case was wrong in this case these
are the inputs and then the return value
was actually 9 uh and the the code I'm
running actually should never really
return negative values so Deon realized
this and actually went looking in the uh
went looking in the code that we're
trying to test and actually added this
line of code that if extra less than
zero extra plus equals you know plus
equals something and in order to make
sure that the return value was actually
non-
negative so after fixing this Devon
actually reran the tests and now uh now
I can be confident that my code is
correct and I have some tests to prove
it thanks
Deon hey everyone my name is Sarah and
I'm going to show you how Devon our AI
software engineer can autonomously learn
from a blog post within a few minutes
Devon successfully generated this
desktop background image for me with my
name on it so all I had to do was send
this blog post in a message to Devon
from there Devon actually does all the
work for me starting with reading this
blog post and figuring out how to run
the
code in a couple minutes Devon's
actually made a lot of progress and if
we jump to the middle here you can see
that Devon's been able to find and fix
some edge cases and bugs that the blog
post did not cover for me and if we jump
to the end we can see that Devon uh
sends me the final result which I love I
also got two bonus images uh here and
here so uh let me know if you guys see
anything hidden in these so this is
cognition Labs website so that you've
raised a 21 million series a led by
Founders fund meet Devon the world's
first fully autonomous AI software
engineer Deon is a tireless skilled
teammate equally ready to build
alongside you or independently complete
tasks for you review with Devon
Engineers can focus on more interesting
problems and Engineering teams can
strive for more ambitious goals with our
advances and long-term reasoning and
planning Devon can plan and execute
complex engineering tasks requiring
thousands of decisions Devon can recall
relevant context at every step learn
over time and fix mistakes we've also
equipped down of common developer tools
including the Shell Code editor and
browser within a sandboxed computer
environment everything a human would
need to do their work what I find really
interesting about this stuff is
generally when you're building tools
aimed at developers um I mean generally
speaking you have less restrictions
versus something that's aimed at sort of
everybody so from what we've seen so far
because this seems much more powerful
than anything else that's available
right now to the general public being
able to learn unfamiliar technology so
like giving it a blog post and then it
knows how to do stuff I mean that was
the promise that's kind of what we
expected these things to be able to do
we've seen some of that like that in
context learning by large language
models we've seen it but this seems Next
Level certainly build and deploy apps
end to endend now on this channel we've
shown for example chat Dev and autogen
and stuff like that so this isn't new
but just everything about this seems
smoother faster more intuitive and more
what is even the word for this more
agentic like it just seems smarter and
more competent you tell it what to do
and it goes and does that so thewe bench
is a benchmark for you know can language
models resolve real world GitHub issues
and so here's kind of the results that
they have right here with Claude 2 GPT 4
Etc assisted and unassisted so looks
like yeah Cloud 2 4.8 unassisted GPT 4
1.74% unassisted and so Devon just
completely knocks it out of park so
that's
13.86% 13 Point let's say just call it
14% so what is that 7x better than GPT 4
looks like Cloud 3 hasn't been tested
yet is isn't on The Benchmark quite yet
so I am tirelessly trying to wrestle up
the beta access to this thing and see it
kind of in effect for real but let me
play you that clip that I was talking
about from this channel that you can see
here on this channel 6 months ago back
then I was asking how long until we have
something like this is it a year 5 years
10 years 20 and I don't know if this
thing will exactly hit all those
criteria it might but the rate of
progress here is quite astonishing from
6 months ago to to today we can't even
make babies that fast imagine this if
you can you wake up in the morning you
have your coffee or whatever other
stimulant gets you going you turn on
your computer and pops up your very own
autonomous AI agent you named him
goalgetter or GG for short that was very
clever of you Gigi reports to you what
it's been doing while you were sleeping
and it's been very busy you see you
created GG to run a business for you the
business idea is simple millions of
people in the world are looking for
simple inexpensive custom automation
Solutions some want a little script that
helps them automate their home some want
a morning routine automation where the
alarm rings their curtains open the
coffee maker turns on Etc some want
their emails answered and sorted in very
specific ways some want a thing that
feeds their cat automatically other
people want solutions for their business
that are a little bit more advanced
requires cameras and tracking Etc but
the point is that people are lazy people
are busy and you have developed quite a
reputation for delivering smart and
inexpensive custom automation Solutions
one-of-a-kind automation Solutions
people go on your website they type in
what they want done they don't even have
to know exactly what they want they just
type in something like my stupid cat
keeps running away now you respond
within a minute or two with an exact
plan of how to fix that problem and
multiple choices with different price
options
depending on how fancy they want to get
starting from a simple tracker for your
cat to an army of drones folling it
around everywhere it goes they choose
whatever option they want and they
provide a credit card for you to build
once the automation is done you type a
script doing the thing that they want
maybe you have to order some parts like
trackers or video cameras and have it
shipped to their house and then you
record a quick voice over with visuals
on how to set it all up you're kind of
like the Ikea of automations the
instructions are great they're brain
dead simple you made sure the
documentation can be understood by
anyone regardless of their Tech
background if they can use a smartphone
they can set up the thing that you've
made for them if they run into any
issues you provide unlimited support
through text emails or whatever they
want once you send everything over to
them all the instructions all the
details Etc you charge their credit card
and you're done but here's the key you
didn't do any of that you were sleeping
the whole time remember everything was
done by GG it talk to the customers and
figure out what they wanted it
brainstorm some Solutions told them
where to put their credit card
information Etc then it went to work
building needed software ordering the
parts that were needed and writing out
very clear instructions for how to use
the thing that it just built it shipped
the product either digitally or the
physical components that I needed it
handled the customer service it made
sure that everybody was happy Etc
recently you've been teaching it how to
do marketing campaigns and you're seeing
some great results of that it learned to
hug people in with little free
automations then it goes online to find
whatever information about them that it
can and then starts pitching them ideas
that it thinks they will respond to it
produces content showing how their lives
could be improved by these various
Solutions custom made tailor made to
them now your customers are ecstatic and
you are basically printing money you
don't do any work to run the business
zero the only work you do is on
improving the agent the autonomous AI
agent that is running this whole thing
you work on optimizing it on teaching it
new skills
now you are aware that eventually people
will catch on and these agents will be
more commonplace and more available to
everyone but until then you basically
found an unlimited money glitch GG so my
question for you is when will this
scenario likely play out never is it
just science fiction is it possible 10
years in the future 50 what do you think
what number of years will pass before a
handful of people have something like
this
running
تصفح المزيد من مقاطع الفيديو ذات الصلة
First AI Software Engineer Devin By Cognition AI :(- Lag Gaye Bhai
Introducing Devin, the first AI software engineer
AI just officially took our jobs… I hate you Devin
DON'T Become a Software Engineer - Do THIS instead
Microsoft BOMBSHELL Announcements: Sam Altman on GPT-5, Devin Joins Microsoft and Phi-3 (SUPERCUT)
Will Devin AI Take Your Job?
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