The True Impact Of AI On Software Engineering

Summary

In 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

00:00

🤖 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.

05:00

📈 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.

10:01

🚀 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.

Keywords

💡AI

AI, or Artificial Intelligence, refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. In the context of the video, AI is highlighted as a transformative tool in software engineering, particularly in automating tedious tasks such as codebase migrations and upgrades, which traditionally consume significant developer time and resources.

💡Software Engineering

Software Engineering is the application of engineering principles to software design, development, and maintenance. The video emphasizes the impact of AI on this field, suggesting that AI can alleviate the burden of routine, non-creative tasks, allowing software engineers to focus more on innovative and customer-facing work.

💡Codebase Migration

Codebase Migration is the process of transferring a software application from one platform, framework, or version to another. The script describes this as a tedious but critical task for software development teams. The video uses the example of migrating the Google Cloud platform UI from JavaScript to TypeScript to illustrate the time-consuming nature of such tasks.

💡Frameworks and Languages

Frameworks and programming languages are foundational tools in software development. The video discusses the necessity of updating these foundational software components, such as migrating to newer versions of Java or upgrading Angular versions, which are essential for maintaining the security and efficiency of software applications.

💡Developer Years

Developer Years is a measure of the amount of work done by a developer over a period of time, typically one year. In the video, the concept is used to quantify the significant savings in labor hours achieved through AI-assisted software upgrades, with Amazon estimating savings equivalent to 4,500 developer years of work.

💡Efficiency Gains

Efficiency Gains refer to improvements in the performance or productivity of a process. The video highlights how AI has led to annualized efficiency gains of approximately $260 million for Amazon, by reducing the time and effort required for software upgrades and migrations.

💡Amazon Q

Amazon Q, mentioned in the video, is an AI assistant for software development within Amazon. It is portrayed as a game-changer that has significantly reduced the workload for developers by automating the process of upgrading and transforming code, leading to more efficient and error-free code reviews.

💡TypeScript

TypeScript is a superset of JavaScript that adds static types to the language. The video discusses the migration from JavaScript to TypeScript as part of the necessary but tedious updates that software engineers must perform. This migration is used to exemplify the kind of work that AI can now assist with, streamlining the process and saving developer time.

💡Angular

Angular is a platform for building mobile and desktop web applications. The video references the effort required to upgrade from Angular 1 or 1.5 to Angular 2 as an example of the kind of foundational software updates that are critical but not directly related to feature development, which AI can help automate.

💡Infrastructure Costs

Infrastructure Costs refer to the expenses associated with the underlying technology and systems that support software applications. The video suggests that by using AI to streamline software updates, companies like Amazon can reduce these costs, as more efficient code can lead to better use of resources and potentially lower maintenance expenses.

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

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resources for all specializations ml

front end systems design iOS you name it

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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

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