The True Impact Of AI On Software Engineering
Summary
TLDRIn this insightful video, the host discusses a LinkedIn post by Andy Jassy, CEO of Amazon, highlighting the transformative impact of AI on software engineering. The post details how Amazon's AI tool has significantly reduced the time and effort required for software upgrades, saving an estimated 4,500 developer years of work. This not only improves efficiency and security but also enhances developers' job satisfaction by eliminating tedious tasks, allowing them to focus on more meaningful work. The host emphasizes the potential of AI to revolutionize the industry, making developers' lives better and more productive.
Takeaways
- 😀 Andy Jassy, CEO of Amazon, shared insights on AI's impact on software engineering, emphasizing its role in reducing tedious tasks.
- 🛠️ AI has significantly reduced the time required for software updates, saving Amazon the equivalent of 4,500 developer years of work.
- 🚀 The integration of AI in software development has accelerated tasks like upgrading Java applications, cutting what used to take 50 developer days to just a few hours.
- 💼 AI's efficiency in software updates has not only saved time but also improved security and reduced infrastructure costs, leading to an estimated $260 million in annualized efficiency gains.
- 🔄 AI's assistance in software engineering is expected to expand, with Amazon planning to add more transformations for developers to leverage.
- 💡 The script suggests that AI will take over monotonous tasks, allowing software engineers to focus on more exciting and customer-facing work.
- 🎯 AI's potential to enhance software engineering productivity is highlighted, with an Amazon engineer anecdotally reporting a 30% reduction in workload.
- 📈 The narrative supports the optimistic view of AI, where it complements and augments software engineers' capabilities rather than replacing them.
- 💼 The script encourages software engineers to embrace AI, learn to use AI tools, and leverage them to increase productivity and job satisfaction.
- 📝 The post underscores the importance of foundational software hygiene work and how AI can be a game changer in this area for large enterprises.
Q & A
What does the speaker estimate as the time saved due to AI in the context of software development?
-The speaker estimates that AI has saved the equivalent of 4,500 developer years of work.
What is one of the most tedious tasks for software development teams according to the script?
-Updating foundational software is considered one of the most tedious tasks for software development teams.
What was the speaker's experience with migrating the Google Cloud platform UI?
-The speaker had to migrate the Google Cloud platform UI from JavaScript to TypeScript and upgrade Angular, which was a tedious and time-consuming process.
What is the name of the company the speaker mentions that provides software engineering interview preparation resources?
-The speaker mentions Algo Expert as the company that provides software engineering interview preparation resources.
What is the promotional code provided for a discount on Algo Expert's platform?
-The promotional code provided for a discount on Algo Expert's platform is 'clam CM'.
What is the average time to upgrade an application to Java 17 according to the AI integration mentioned in the script?
-After integrating the AI tool, the average time to upgrade an application to Java 17 plummeted to just a few hours.
What percentage of autogenerated code reviews were shipped without any additional changes according to the script?
-79% of the autogenerated code reviews were shipped without any additional changes.
What are the estimated annualized efficiency gains due to the AI tool as mentioned in the script?
-The estimated annualized efficiency gains due to the AI tool are 260 million dollars.
What does the speaker suggest about the impact of AI on software engineering jobs?
-The speaker suggests that AI will replace the tedious work that software engineers currently do, allowing them to focus on more exciting and customer-facing tasks.
What advice does the speaker give to software engineers who might be worried about AI?
-The speaker advises software engineers to learn about AI and how to use AI tools to be more productive and to rid themselves of tedious work.
How much workload reduction has an Amazon engineer reported due to the internal AI tools, according to a Twitter post mentioned in the script?
-An Amazon engineer reported a 30% reduction in workload due to the internal AI tools.
Outlines
🤖 AI's Impact on Software Engineering Efficiency
This paragraph discusses the transformative effect of AI on software engineering, as illustrated by Andy Jassy, CEO of Amazon. The narrative begins with the mundane yet crucial task of updating foundational software, which is often tedious and time-consuming. The speaker shares personal experiences from their time at Google, where they spent a significant portion of their time on such migrations, like upgrading to TypeScript from JavaScript. The introduction of Amazon's AI tool, which drastically reduced the time to upgrade Java applications from 50 developer days to just a few hours, is highlighted. This tool is estimated to have saved the equivalent of 4,500 developer years of work, underscoring the potential of AI to revolutionize the industry.
📈 AI-Driven Efficiency and Cost Savings in Software Upgrades
The second paragraph delves into the specifics of how AI can handle repetitive and monotonous tasks in software development, such as codebase migrations and upgrades. It references Andy Jassy's LinkedIn post, which details the impressive statistics of Amazon's AI tool's impact: upgrading more than 50% of their Java systems in under six months with minimal time and effort. The tool's ability to generate code that requires minimal review is also noted, emphasizing the efficiency gains and the potential for AI to take on an even broader range of tasks in the future. The financial benefits, including enhanced security and reduced infrastructure costs, leading to an estimated $260 million in annualized efficiency gains, are highlighted, showcasing the significant advantages of leveraging AI in software development.
🚀 Embracing AI to Enhance Software Engineering Productivity
In the final paragraph, the speaker reflects on the personal implications of AI's role in software engineering, suggesting that AI could alleviate the burden of tedious tasks, allowing engineers to focus on more fulfilling and innovative work. The potential for AI to improve feature work speed and reduce the drudgery of routine coding tasks is explored. The paragraph also touches on the anecdotal evidence from an Amazon engineer who claims a 30% reduction in workload due to AI tools, hinting at a broader industry trend. The speaker encourages software engineers to view AI as an opportunity rather than a threat, to learn and adapt to these tools to enhance productivity and job satisfaction.
Mindmap
Keywords
💡AI
💡Software Engineering
💡Codebase Migration
💡Frameworks and Languages
💡Developer Years
💡Efficiency Gains
💡Amazon Q
💡TypeScript
💡Angular
💡Infrastructure Costs
Highlights
AI has saved the equivalent of 4,500 developer years of work by streamlining the process of updating foundational software.
Software development teams often dread the tedious task of migrating codebases to new frameworks or language versions.
Andy Jassy, CEO of Amazon, shared insights on AI's impact on software engineering in a LinkedIn post.
AI has significantly reduced the time to upgrade applications to Java 17, from 50 developer days to just a few hours.
Amazon's internal AI tool has enabled the upgrade of over 50% of their production Java systems within 6 months.
Developers at Amazon have shipped 79% of the autogenerated code reviews without any additional changes.
AI's role in software engineering is to automate the tedious and repetitive tasks, allowing engineers to focus on more exciting work.
The AI tool has potentially saved Amazon an estimated 260 million in annualized efficiency gains.
AI is expected to replace much of the invisible work in software engineering, such as codebase migrations and updates.
Software engineers should embrace AI and learn to use AI tools to increase productivity and eliminate mundane tasks.
Anecdotal evidence from an Amazon engineer supports the claim that AI has reduced their workload by 30%.
AI's impact on software engineering is not just about time and cost savings but also about improving the quality of life for engineers.
The speaker's personal experience at Google involved spending a significant amount of time on codebase migrations.
At Algo Expert, the company had to migrate the entire front-end codebase to TypeScript and React with functional components.
The speaker suggests that AI will continue to improve and take over more complex tasks in software engineering.
The video discusses the current state of the software engineering industry and the potential of AI to transform it.
The video concludes by encouraging software engineers to adapt to AI and leverage it for personal and professional growth.
Transcripts
we estimate that this has saved us the
equivalent of
4,500 developer
years of work what's up everybody how's
it going this past weekend I came across
a post on LinkedIn about AI from none
other than Andy jasse he's the current
CEO of Amazon he replaced Chad Bezos a
few years ago and in this video I want
to share this post because I think that
it really captures the true impact of AI
on software engineering the impact that
it's having right now and that it's
going to continue having on this
industry so I'll just read through the
post and give my comments it starts out
with one of the most tedious but
critical tasks for software development
teams is updating foundational software
very true if you've been in software
engineering for even just one year
you've likely experienced a migration
you have to migrate an entire codebase
to a new framework or you have to
upgrade an entire code based to uh the
latest version of the language and it's
very very tedious it's not new feature
workor no it's not and it doesn't feel
like you're moving the experience
forward as a result this work is either
dreaded or put off for more exciting
work or both so I can totally relate and
I'm sure that many of you can totally
relate to this during the two years and
2 months and 8 days if I remember
correctly that I was at Google as a
software engineer I remember I had to
take part in many of these migrations
namely the the big one that we had to do
was we had to migrate the entire Google
Cloud platform UI uh to typescript from
JavaScript to typescript and I think
that we had to upgrade angular from like
angular one or 1.5 whatever whatever it
was called to angular 2 and uh that was
a lot of work like by my rough estimate
I probably spent about 20% of my
software engineering time at Google
working on these migrations and I
remember like I really disliked it it
was like really boring really tedious
like he said it didn't feel like new
feature work it didn't really feel like
the kind of work that would you know
help me get promoted or teach me new
stuff about engineering it wasn't
exciting and the exact same thing
happened at algo expert my company we
had to migrate the entire codebase uh
the front end code base to typescript uh
we had to migrate the entire front end
code base to the version of react with
like functional components we also had
to upgrade many times like the actual
coding solutions to our algorithm style
coding interview problems in certain
languages like upgrad it to the new
version of C++ and I remember like that
was super tedious it was a lot of work
it was really taking away from like our
ability to launch new features which was
what was really important you know for
for us as a company and for our
customers but this was kind of necessary
work you know that necessary invisible
work by the way if you're a software
engineer preparing for technical
interviews definitely check out my
company algo expert we've got the best
software engineering interview prep
resources for all specializations ml
front end systems design iOS you name it
coding interviews of course check it out
at algoexpert.io and use a promo code
clam CM for Discount of the platform so
back to the post Amazon Q are gen AI
assistant for software development so
probably some sort of internal AI tool
is trying to bring some light to this
heaviness we have a new code
transformation capability and here's
what we found when we integrated it into
our internal systems and applied it to
our needed Java upgrades brace yourself
you might want to be sitting down when
you hear this the average time to
upgrade an application to Java 17
plummeted from what's typically 50
developer days so 50 developer days
that's you know almost two months of a
software engineer working exclusively on
you know upgrading a single single
application at Amazon to Java
17 it plummeted to just a few hours
almost two months of work for a software
engineer to Just 2 hours okay or a few
hours we estimate that this has saved us
the equivalent of
4,500 developer
years of work 4,500 developer years of
work do you guys hear me
years of work yes that number is crazy
but real I don't think that the CEO of
Amazon like one of the largest companies
in the world would publicly say on
LinkedIn an outrageous number like that
that it has saved them the equivalent of
4,500 developer years and then like
acknowledge that that number is crazy
but say that it's real but be lying in
other words I think he's telling the
truth and I believe it I believe believe
that this is the kind of work that AI
can do like the sort of like very
repeatable or repetitive no repeatable
this is like the kind of work that is
repeatable and like always the same but
extremely tedious like still requires
effort to do but it's very monotonous
right and AI can do it like this now I
would do some back of the napkin math
estimations to see how much money this
might have saved them but luckily for me
Andy jasse has already done the work for
us so let's continue in under 6 months
we've been able to upgrade more than 50%
of our production Java systems to
modernized Java versions at a fraction
of the usual time and effort and our
developers have shipped 79% of the
autogenerated code reviews without any
additional changes and again this is
something that I can definitely believe
because I look back at the times that I
did these migrations at Google and on
algo expert and all the time like the
the reviews you know when you're
reviewing the other Engineers work where
they migrated the the
application there isn't much to review
because like if the pull request or the
change list passes all the internal
tests all you have to do is kind of like
skim through it make sure like yeah they
clearly didn't tweak any you know major
other things in the system and you know
it should be good and all the time or
most of the time it is good in other
words like I don't it usually doesn't
require that much review it's very quick
to review but it requires a lot of work
to do you know it's the kind of work
where the review is simple but the
actual work is a lot is complicated and
not complicated again but tedious
dreaded it's not exciting you're you're
not going to get promoted for it or it
doesn't feel like you're going to get
promoted for it you're not going to
learn much you're not developing stuff
that customers care about even though
you care about as a developer because
it's going to make you faster and the
business cares about it because
ultimately like without it they can't
really survive but as far as like actual
end customers they don't care about it
so then let's go into the math the
benefits go beyond how much effort we've
saved developers the upgrades have
enhanced security okay because probably
you're on newer versions of Java or you
know you're on better you know you're on
typescript so it's a bit more
secure and reduced infrastructure costs
providing an estimated
260 million in annualized efficiency
gains 260 million ion in annualized
efficiency gains and that makes sense if
you look at it like 4 4,500 developer
years which by the way that figure was
likely gotten by the fact that like you
know if it saves about two months of
developer days two months of developer
work for one application and you think
that Amazon has like thousands maybe
more than you know dozens of thousands
of applications to upgrade then yeah you
get to the 4,500 figure in in developer
years of work saved and you you look at
the cost that's like 4,000 500
engineering salaries saved you get to
260 million in annualized efficiency
gains that is huge just to have like
this AI tool that probably costs them
very little to use now that they
actually have it especially if it's like
an internal tool developed by Amazon
itself so he goes on to say this is a
great example of how large scale
Enterprises can gain significant
efficiencies in foundational software
hygiene work by leveraging Amazon Q it's
been a game changer for us and not only
do our Amazon teams plan to use it or
use this transformation capability more
but our Q teams plan to add more
Transformations for developers to
leverage in other words he's hinting at
you know this AI is going to be able to
do more stuff maybe more complicated
migrations more complicated upgrades so
to me this post is really wonderful
first of all like it is insanely
impressive um like I don't think you can
look at this and not be impressed just
the sheer amount of time and therefore
money saved is incredible but but I
think that this really speaks to the
true impact of AI on software
engineering my most recent video was uh
you know I shared my honest thoughts
about the current state of the industry
and how you know right now the industry
software engineering is not doing great
at all it's really rough to get a job
and I talked about AI you know how some
people are doomers about AI they think
that AI is going to completely replace
software engineers and other people
which is likely the camp that I fall
into are more optimistic about Ai and I
think this post supports that optimism
AI is going to replace all of the
tedious work that software Engineers
have to do all these migrations these
upgrades these internal like updates
that are super boring not exciting
you're not doing Feature work they're
invisible to the End customer you really
feel like a cog in the machine when
you're doing them well guess what you're
no longer going to have to do them
because AI is going to do them for you I
can only imagine that if I were back at
Google where I had spent let's say about
20% of my time working on Migra a
codebase to angular 2 from angular and
to typescript from JavaScript if I had
been able to spend that 20% time doing
just more Feature work I would have been
way more happy upper management would
have been thrilled I remember there was
so much work on Google Cloud platform
that we needed to do and that you know
we we were just never able to do it's
like this infinite race like we're never
able to complete all the work it would
have been incredible and if you can
imagine that AI is just going to keep
getting better right so it might allow
you to make some of your Feature work
faster right some of the tedious things
for Feature work is going to be faster
all the let's say like you know
generating skeletal you know skeleton
files like all the all the crap that you
just hate doing as a software engineer
AI is going to do it or is already doing
it and so I think that like if you're a
software engineer who's kind of scared
right now worried about AI this should
do the opposite it should it should give
you motivation like learn AI start to
work or not learn AI start learn how to
use the tools these AI tools to better
you you know uh leverage them to be more
productive and to be able to rid
yourself of all this garbage work that's
super annoying and be able to do just
way more stuff than you would have been
able to do even just a year ago and just
on top of this uh on Twitter I came
across a post that talked about this
this um LinkedIn post from Andy jasse
and someone responded Amazon engineer
here Q which is the the internal tool
and other internal gen tools have
reduced my workload easily by 30% which
is kind of matches my 20% from Google in
terms of random engineering or business
admin type of work docs mrbs Etc not
sure what mrbs are mbrs are maybe um
like design docks or feature requirement
docs I'm not sure off the top of my head
but so this Amazon engineer here can
attest to this post from Andy ji just
like anecdotally right and presumably
like this is the kind of work that he
you know random engineering or business
admin type of work nobody likes to write
docs so not only does this save time and
and money for the company and and
increases the security and the the sort
of uh robustness of their applications
but it makes the engineers lives better
because no one wants to be writing docs
no one wants to be writing for the 10th
billionth time like some typescript
class or typescript type in their code
base that's all I've got for you guys
let me know what you think in the
comments below like I'm sure many of you
have your own horror stories about
migrations and and things like that like
me know what you think about this maybe
some of you are at Amazon and you and
you've actually worked with this don't
forget to smash the like button if you
enjoy the video subscribe to the channel
if you haven't already follow me on all
my other social media platforms if you
like those platforms and I will see you
in the next video
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