Software Engineer jobs (Mid-Senior) can NEVER be replaced by a Coding "AI" like Devin

Summary

The video script discusses the limitations of code generation AI in replacing software engineers. It emphasizes that software engineering is more about managing people and balancing business, technical, and financial requirements than just writing code. The role of a Prompt Engineer is introduced, who would direct the AI, but the complexities of system integration and performance tuning still rely on human expertise. The video argues that unless there's a revolutionary change that makes code generation irrelevant, AI will remain a tool for software engineers rather than a replacement.

Takeaways

• 🤖 The core argument is that code generation AI will not replace software engineers due to the human-centric aspects of the job.
• 🧠 The future vision of software development includes a Prompt Engineer who communicates with AI to generate code, but this is not yet feasible.
• 🔄 The current state involves software engineers acting as the intelligence behind code generation, with product owners providing direction.
• 👥 A multitude of roles and stakeholders contribute to the software development process, not just engineers and product owners.
• 🔧 Software engineers often deal with technical details and integrations that product owners may not fully understand or engage with.
• 💡 The real challenge in software engineering is balancing business, technical, and financial requirements, not just writing code.
• 🚀 The role of the software engineer extends beyond coding to include handling requests from various departments and team members.
• 🌟 The complexity of software engineering lies in people management and communication, rather than technical skills alone.
• 📈 The quality of software is influenced by the effectiveness of communication and management within the organization, not just the technology used.
• 🌐 Unless there is a revolutionary change that makes code generation irrelevant, AI will remain a tool for software engineers rather than a replacement.

Q & A

What is the main argument presented in the video script against the idea of a code generation AI replacing software engineers?

The main argument is that the job of a software engineer is more about people, integration, and balancing various requirements than just writing code, which a code generation AI cannot effectively do.

What role does the Product Owner play in the current software development process?

The Product Owner is the person who tells the Software Engineer what to do, focusing on what the product is supposed to be and how users will use it, rather than getting involved in technical details.

What are some of the other roles involved in a software development department?

Other roles include stakeholders, scrum masters, integrators, DevOps folks, operations folks, UI/UX designers, subject matter experts, QA, and QC testers.

What is the role of the Prompt Engineer as described in the script?

The Prompt Engineer is a separate role that would communicate with the AI code generator, telling it what code to generate based on the requirements provided by various stakeholders.

Why might a Prompt Engineer struggle with certain aspects of software engineering?

A Prompt Engineer might struggle because they may not understand the technical details, such as system performance and integration with other systems, which are crucial for effective software engineering.

What is the main challenge for software engineers in balancing business, technical, and financial requirements?

The main challenge is synthesizing all the information from various stakeholders and requirements to build a product that satisfies all those needs while dealing with the complexities of people and communication.

How does the script suggest improving the software development process?

The script suggests teaching software engineers how to do Prompt Engineering, making AI a tool for them to use, rather than replacing them.

What are some potential revolutionary changes that could make code generation irrelevant?

Revolutionary changes could include brain implants or uploading that allow for direct balancing of requirements without communication, or AI becoming so smart that it understands our needs better than we do ourselves.

Why does the script argue that the quality of software is not improving?

The script argues that despite the use of agile methodologies and project management, the complexity of balancing various requirements and the inherent challenges in communication among people lead to software quality issues.

What is the ultimate conclusion the script reaches about the role of AI in software engineering?

The script concludes that unless there is a completely revolutionary change that makes code generation irrelevant, an AI code generator will never be able to replace the nuanced and people-centric role of a software engineer.

Outlines

00:00

🤖 The Role of AI in Software Engineering

This paragraph discusses the limitations of code generation AI in replacing the role of a software engineer. It explains the current state of software development, where the software engineer acts as the intelligence behind code generation, while the product owner represents the stakeholder's interests. The complexity of integrating with other teams and systems, as well as the need for human understanding in balancing business, technical, and financial requirements, are highlighted. The paragraph emphasizes that software engineering is more about managing people and their requirements than it is about writing code.

05:01

🛠️ AI as a Tool for Software Engineers

The second paragraph focuses on the idea that AI will serve as a tool for software engineers rather than replacing them. It argues that the real challenge in software engineering lies in balancing business, technical, and financial requirements, which involves understanding and managing people. The paragraph suggests that even if AI becomes more advanced, as long as human communication and understanding remain the limiting factors, AI will not be able to replace the nuanced human aspects of software engineering. It concludes by contemplating revolutionary changes that could make code generation obsolete, but asserts that until such a development occurs, AI will remain an辅助 tool rather than a replacement for software engineers.

Keywords

💡Code Generation AI

Code Generation AI refers to artificial intelligence systems designed to automatically create and output computer code. In the context of the video, it is posited that such AI will not replace software engineers because the human element of understanding and balancing various requirements is crucial. The video argues that despite advancements, the AI's role will remain as a tool for software engineers rather than a replacement.

💡Software Engineer

A software engineer is a professional who applies engineering principles to the design, development, maintenance, and testing of software systems. In the video, it is emphasized that the role of a software engineer extends beyond coding to include understanding and integrating with various aspects of a company's operations, dealing with stakeholders, and balancing technical with business requirements.

💡Prompt Engineer

The term 'Prompt Engineer' is used in the video to describe a hypothetical role where a person would instruct an AI on what code to generate. This role is suggested as a middleman between stakeholders and the AI, tasked with translating business needs into specific instructions for the AI to follow.

💡Agile Roles

Agile roles refer to the various positions and responsibilities within an agile software development team. These roles are designed to support the agile methodology, which emphasizes flexibility, collaboration, and rapid response to changes. The video mentions some of these roles, such as Scrum Masters and Product Owners, to illustrate the complexity of software development beyond just coding.

💡Product Owner

A product owner is a role in agile software development who is responsible for defining and prioritizing features to be developed based on market research, customer needs, and business goals. They act as a proxy for the end-users and ensure that the product delivers value. The video argues that while product owners focus on the 'what' and 'how' of the product, they are not deeply involved in the technical details, which remain a significant part of the software engineer's job.

💡Integration

Integration in the context of software development refers to the process of bringing together different software components or systems to work as a unified whole. This is a complex task that requires understanding how various parts of a system interact and may involve coordinating with different teams and technologies.

💡DevOps

DevOps is a set of practices that combines software development (Dev) and information technology (IT) operations. The goal is to shorten the system development life cycle and provide continuous delivery of high-quality software by improving collaboration and communication between developers and IT teams.

💡Stakeholders

Stakeholders are individuals or groups that have an interest or concern in a project or organization. In software development, stakeholders can include executives, project managers, legal teams, and end-users, all of whom may have specific requirements or expectations that influence the development process.

💡Scrum Master

A Scrum Master is a role in Scrum, an agile framework for managing and completing complex projects. The Scrum Master ensures that the Scrum process is understood and enacted correctly by the development team and helps to facilitate the Scrum events and meetings.

💡Technical Requirements

Technical requirements are the specific, detailed needs that must be met for a software system to function properly. These can include performance metrics, system integration, scalability, and security considerations, among others.

💡Business Requirements

Business requirements are the goals and needs that a software system must satisfy to be considered successful. They are often defined from a perspective of business objectives, user needs, and market strategies.

Highlights

The future vision of a Prompt Engineer directing an AI to code is discussed, emphasizing the theoretical shift in software development roles.

The current state of software engineering is contrasted with the future vision, highlighting the role of the Software Engineer as the primary intelligence behind code generation.

Agile roles within a company are outlined, including the Product Owner and Scrum Master, and their importance in the software development process.

The role of integrators is explained, focusing on their responsibility for coordinating team outputs and ensuring seamless integration.

DevOps and operations teams are discussed as crucial supports for deployed software, managing cloud accounts and system performance.

UI/UX designers and subject matter experts are identified as key contributors to the software development process, though their roles may be undervalued.

QA and QC testers are acknowledged as essential in ensuring software quality, despite the complexity of their tasks.

The concept of stakeholders is expanded upon, including executives, project management, and other departments that influence software development.

The limitations of the Product Owner role are discussed, noting their focus on product vision rather than technical or integration details.

The idea of a separate Prompt Engineer is introduced, meant to communicate with the AI code generator and handle requests from various company roles.

The potential lack of understanding from a Prompt Engineer regarding system performance and integration is highlighted.

The necessity of human oversight and tuning in software development is emphasized, despite AI advancements.

The core argument is presented that software engineering is more about people and balancing requirements than code writing.

A potential future scenario is considered where AI surpasses human intelligence, which could revolutionize the need for code generation.

The conclusion is drawn that AI code generators will not replace Software Engineers, as the human element is central to the role.

The transcript suggests that the quality of software is not improving and may be deteriorating, despite various management strategies.

The necessity of teaching Software Engineers to perform Prompt Engineering is proposed, positioning AI as a tool rather than a replacement.

The idea of a revolutionary change that makes code generation irrelevant is considered, questioning the fundamental nature of software development.

Transcripts

Welcome to the Internet of Bugs.

My name's Carl and today we're

going to talk about why it is

that a code generation AI is never

going to be able

to take the job of a software

engineer.

Let's start off by talking about

the world

as they tell us it's going to be.

So they tell us there's going to be

a Prompt Engineer,

that Prompt Engineer is going to

tell the AI

what the AI is supposed to code

and then that code is going to get

spit out

and then it's going to get deployed

and it's going to be stuck on the

system

that actually the offering lives on.

Okay, before we go there,

let's talk about where we are now

and if we're actually going to get

to that world ever,

how that might happen.

What we'll do is we'll talk about

the current state

which is the Software Engineer does

what they say

the AI is going to do.

The Software Engineer is the

intelligence

that currently generates the code

that goes and gets deployed

and the Product Owner is the person

that tells the Software Engineer

what to do.

So roughly the Software Engineer is

equivalent to the AI

and the Product Owner is equivalent

to the Prompt Engineer.

Big animal pictures, just go with

it for now, okay?

Except this isn't the whole

organization, right?

You've got more stuff.

This is a very incomplete list of

agile roles, right?

You've got your stakeholders.

You've got your scrum master

'cause we have to have a scrum

master

'cause everybody has to do scrum

these days.

That's a whole other problem

but we'll talk about that in a

different video.

You've got your integrators

which basically are the people

under agile terminology.

These are the people that are

responsible

for coordinating the output of your

team

with the output of other teams

and make sure they all hook

together.

You've got the DevOps folks

that support the software once it

gets deployed.

You've got the operations folks

which are cloud accounts and all

that kind of stuff.

You've got UI designers, you've got

UX designers,

you've got your subject matter

experts

which less said about that the

better

and then you've got your QA, QC, your

testers.

And again, this is a very

incomplete list

of the roles that happen in a real

company

when you're actually in a software

development department.

This stakeholders thing is kind of

fuzzy.

So let's break that out.

So among other things,

you've got your Executive Sponsor

and really the rest of the

executives too.

You've got your Project Management

Office,

theoretically, Compliance, Legal,

Marketing, Finance, Budget.

The number of times I've heard,

"Hey, we need to change the software

so that our cloud bill stops going

up

or our cloud bill goes down.""

I don't even want to talk about

that.

You've got other tribes.

So for those of you that haven't

done the Spotify model,

basically, well, it's complicated.

You can look it up.

But it's other groups in the

company

that are doing the same kind of

thing that you do

that kind of have a say in what you're

doing

because they want it all to be the

same.

You've got your business analysts.

You've got your content strategy

folks.

And again, this is a very

incomplete list, right?

Problem is, this isn't really what

happens

because most of those folks, right?

So like the integrators, the DevOps

folks,

the operations folks,

the Product Owner doesn't

understand

any of the stuff that they're

saying.

The Product Owner is supposed to

understand

what it is the product's supposed

to be.

But they might get involved in like

UI UX maybe,

but they don't get involved in DevOps.

They don't want to know about that.

They don't want to get involved in

organizing scrum stuff.

They don't want to get involved in

how this project

integrates in a technical way

with the other projects in the

company.

All those people end up talking to

the Software Engineer,

not the Product Owner.

And then you realize that actually,

all the people in the top part of

that list

are capable of throwing

requirements in.

And sometimes those go to the

Product Owner,

but a lot of times they don't.

And you get business analysts or

content strategy people

or marketing people that just open

tickets

that you're supposed to go in and

deal with.

And that's life as a Software

Engineer.

This kind of thing happens all the

time.

And the Product Owner just isn't

the kind of person

that's going to be able to handle

all those requests

'cause that's not their job.

Their job is to focus on what the

product is supposed to be

and how users are gonna use it,

not all the technical details

of how the thing is supposed to

work.

So tell you what, what we'll do is

we'll pull the Product Owner out

and we won't make the Product Owner,

the Prompt Engineer will make the

Prompt Engineer

a separate person.

So we've got the Product Owner,

the Product Owner is gonna talk to

the Prompt Engineer,

everybody else is gonna talk to the

Prompt Engineer.

And the Prompt Engineer is gonna

talk to the AI code generator

and the AI code generator is gonna

generate the stuff

that goes into the system.

Thing is, a Prompt Engineer doesn't

know about how

the integration with the software

is gonna work

with all the other integration

stuff.

They understand how to tell

an AI what to do

is not the kind of thing where you

understand

what the performance of the system

is necessarily going to be.

Once the code gets generated, if

the code is slow

and we need to reduce the cloud

costs,

we're gonna have to go tune that by

hand.

The AI may or may not be able to do

that.

And if it does, it's gonna need

very specific instructions

about how to do that,

that a Prompt Engineer may or may

or may not understand

like the algorithms involved.

So a lot of what's happening here

is Software Engineering,

figuring out how to make the thing

run faster,

figuring out how to integrate your

technical part

of the offering with the rest of

the offering

with the other teams.

That stuff is what software

engineering really is

in a big company.

So now you've got the Software

Engineer whose job basically

is to handle all of these requests

from everybody.

You've got a Prompt Engineer that's

talking to the AI code

and you've got your offering system.

Now when you think about the fact

that the vast majority

of what's happening here is the

Software Engineering part,

right?

It's dealing with Finance.

It's dealing with the Scrum Master.

It's dealing with Operations.

It's deciding how are we gonna make

this cheaper?

How are we gonna make this faster?

How are we gonna make this scale?

That's all Software Engineering

stuff.

And so all we really need to do is

teach the Software Engineer

how to do Prompt Engineering.

And then we're back to this.

So now AI is basically just another

tool

that the Software Engineer uses.

See, the hard part of Software

Engineering

is not the code writing.

The hard part of Software

Engineering

is balancing all of the business

requirements

with all the technical requirements,

with all the finance requirements,

and figuring out what it is that we

need to build

in order to be able to get all of

those requirements satisfied.

Those are really tricky problems,

but those problems are all about

the people.

If the Product Owner was capable

of taking all of that information

and synthesizing all of it and just

telling you,

okay, this is what we need to get

built

and this is how it needs to get

built,

and you don't need to talk to

anybody else in the organization,

we wouldn't need agile

and we wouldn't need project

management

and we wouldn't need project

management offices.

But we need all of that and even

with all of that,

the quality of software is still

arguably abysmal.

It's certainly not getting any

better

and it's apparently getting worse,

or at least by some measures, it's

objectively getting worse.

So here's the thing.

It doesn't matter how much better

the AI gets.

As long as the people are the

limiting factor

and as long as the people don't get

that much smarter,

then the AI isn't gonna be able to

help.

Now, there are a couple of things

that might happen.

One is that we might get some kind

of a brain implant thing

or brain uploading thing

that lets all of those requirements

get balanced

without having to do all of the

communication,

which is the thing that takes all

the time.

It's also possible that maybe the

AI

is gonna get so smart that it's

smarter than us

and it knows what we want better

than we do.

But if either of those things

happen,

we're not gonna be bothering with

Python code anymore.

It's not gonna be the AI is gonna

spit out code

and then the code's gonna get

deployed.

The AI is just gonna do stuff.

And there's not gonna need to be

this intermediate step

of, okay, we're gonna generate this

code

and then someone's gonna have to go

stick that on a server.

So failing something completely

revolutionary

that makes code generation

irrelevant,

it's just not the case and will

never be the case

that an AI code generator is gonna

do the job

of a Software Engineer because the

job of a Software Engineer

is more about people than it is

about code.