25 answers
Zane
Student
Frankfort, Kentucky
1
Question
Updated
2366 views
Is computer science really a doomed career?
Everyone says that computer science is being destroyed by AI. To what degree is that true? Is there really no hope for this degree, or is this just overdramatized?
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25 answers
Andras C
Software Engineering
8
Answers
Budapest, Hungary
Updated
Andras’s Answer
As an addition to the great answers provided by the others: in my daily coding experience AI helps a lot to make proper technical choices and to troubleshoot quicker, but in the end I never can fully and blindly trust it and need to double-check everything it suggests. Driving the conversation, evaluating the answers, guiding with feedback, and in general, connecting the dots in your whole system knowledge - these all require you! Not to mention that the models and agents beneath AI are also developed and operated by software engineers. I would not worry.
Tayyaba Javed
Web development intern
6
Answers
Taxila, Punjab, Pakistan
Updated
Tayyaba’s Answer
It’s **overdramatized**, but there is some truth behind it.
AI is making basic coding much easier, so some entry-level programming jobs may become harder to get. But **CS itself is not becoming useless**. AI still needs people who understand software, systems, databases, security, testing, architecture, and how to solve real problems.
The degree is changing from **“I can write code”** to **“I understand technology and can use AI to build and manage things effectively.”**
So no, there is **definitely hope for CS**. But simply having a CS degree without practical skills is becoming less valuable. The people who learn to **work with AI rather than compete against it** will likely have the strongest position.
AI is making basic coding much easier, so some entry-level programming jobs may become harder to get. But **CS itself is not becoming useless**. AI still needs people who understand software, systems, databases, security, testing, architecture, and how to solve real problems.
The degree is changing from **“I can write code”** to **“I understand technology and can use AI to build and manage things effectively.”**
So no, there is **definitely hope for CS**. But simply having a CS degree without practical skills is becoming less valuable. The people who learn to **work with AI rather than compete against it** will likely have the strongest position.
Sahida Khatun
Software Consultant and Analyst
142
Answers
Kolkata, West Bengal, India
Updated
Sahida’s Answer
Look at history:
Calculators didn't stop people from learning math.
Compilers didn't end programming.
High-level languages didn't make software engineering disappear.
The internet didn't destroy computer science.
AI isn't going to end computer science either.
AI changes how we use our time. It might reduce the need for some simple programming tasks. While AI can help write code, it doesn't always get it right. We still need humans to check and fix it.
A survey from Stack Overflow in 2025 shows that 46% of developers don't fully trust AI's accuracy, while 33% do. Only 3% have high trust in it. Many, about 66%, find AI solutions often almost right but not quite perfect.
Focus on improving your problem-solving and analytical thinking skills. Use AI to help automate tasks and work alongside computer science.
Calculators didn't stop people from learning math.
Compilers didn't end programming.
High-level languages didn't make software engineering disappear.
The internet didn't destroy computer science.
AI isn't going to end computer science either.
AI changes how we use our time. It might reduce the need for some simple programming tasks. While AI can help write code, it doesn't always get it right. We still need humans to check and fix it.
A survey from Stack Overflow in 2025 shows that 46% of developers don't fully trust AI's accuracy, while 33% do. Only 3% have high trust in it. Many, about 66%, find AI solutions often almost right but not quite perfect.
Focus on improving your problem-solving and analytical thinking skills. Use AI to help automate tasks and work alongside computer science.
Teklemuz Tesfay
Software Engineer and Career Mentor
717
Answers
Ethiopia
Updated
Teklemuz’s Answer
Computer Science remains a field with strong demand and is likely to stay relevant as technology continues to advance. However, AI is transforming the job market by making some entry-level coding tasks more challenging. Instead of fearing AI, learn to use it and become skilled at it. AI can handle repetitive tasks, save time, and boost productivity. AI won't replace people; those who learn to use AI well will have an edge over those who don't. Human skills like ethics, judgement, communication, empathy, leadership, and responsibility are still crucial.
CS offers many paths, so think about what you're good at and what you want in your career before picking a focus. You can explore areas like software development, AI, machine learning, data science, data engineering, databases, cloud computing, DevOps, cybersecurity, networking, distributed systems, systems engineering, computer architecture, embedded systems, robotics, and computer graphics. Gain experience through courses, projects, internships, hackathons, and open-source work.
CS offers many paths, so think about what you're good at and what you want in your career before picking a focus. You can explore areas like software development, AI, machine learning, data science, data engineering, databases, cloud computing, DevOps, cybersecurity, networking, distributed systems, systems engineering, computer architecture, embedded systems, robotics, and computer graphics. Gain experience through courses, projects, internships, hackathons, and open-source work.
Loved reading this, thanks!
Daniel Wuest
Executive leader
2
Answers
Milwaukee, Wisconsin
Updated
Daniel’s Answer
No, I don’t think computer science is a doomed career, but I do think software engineering is changing dramatically. I lead a large technology organization, and our experience with Claude Code has been eye-opening. The vast majority of users reported productivity gains, and reported improvements in quality, not just speed. AI can now help write code, create tests, debug, refactor, document systems, and navigate unfamiliar codebases. So it would be unrealistic to say this won't affect engineering jobs. We are already experimenting with smaller teams, broader roles, fewer handoffs, and less reliance on some traditional specialized roles and external development resources.
But that doesn't mean we won't need software engineers. It means what makes a great software engineer is changing. The value is shifting away from simply being able to write code toward understanding complex systems, solving difficult problems, designing good solutions, knowing whether AI-generated work is correct and secure, and understanding the business problem you're trying to solve. We're seeing engineers use AI to take on work outside their traditional specialties and handle complexity that previously required more time or help from others. In that world, the best engineers may actually become much more valuable because each individual can accomplish substantially more.
So I would still recommend computer science to someone who genuinely enjoys technology and problem solving, but I would prepare for the career differently. Learn the fundamentals deeply, but also become exceptionally good at working with AI, and develop strong communication, critical-thinking, architecture, and business skills. I would be more cautious about choosing CS simply because it has historically been considered a safe path to a high-paying job. Entry-level work is likely to change significantly and expectations will rise. Computer science isn't disappearing. The job description is being rewritten, and students entering the field today have the opportunity to learn that new version of the profession from the beginning.
But that doesn't mean we won't need software engineers. It means what makes a great software engineer is changing. The value is shifting away from simply being able to write code toward understanding complex systems, solving difficult problems, designing good solutions, knowing whether AI-generated work is correct and secure, and understanding the business problem you're trying to solve. We're seeing engineers use AI to take on work outside their traditional specialties and handle complexity that previously required more time or help from others. In that world, the best engineers may actually become much more valuable because each individual can accomplish substantially more.
So I would still recommend computer science to someone who genuinely enjoys technology and problem solving, but I would prepare for the career differently. Learn the fundamentals deeply, but also become exceptionally good at working with AI, and develop strong communication, critical-thinking, architecture, and business skills. I would be more cautious about choosing CS simply because it has historically been considered a safe path to a high-paying job. Entry-level work is likely to change significantly and expectations will rise. Computer science isn't disappearing. The job description is being rewritten, and students entering the field today have the opportunity to learn that new version of the profession from the beginning.
Nandishkumar Shah, MBA
Technology Leader
7
Answers
Prosper, Texas
Updated
Nandishkumar’s Answer
The idea that computer science is a "doomed" field mixes up the automation of simple tasks with the end of problem-solving. Over time, new tools like programming languages and cloud technology haven't ended computing jobs; they've just made them more advanced.
AI is changing the field in three main ways:
1) AI takes care of routine tasks, allowing engineers to focus on designing systems, making logical choices, and planning architecture instead of just writing code.
2) AI-generated code can look correct but may have hidden errors or security issues. Checking and fixing this requires strong computing skills in data structures, algorithms, and security.
3) Computer science is much broader than basic web development. Areas like cybersecurity, cloud infrastructure, data engineering, robotics, and AI development need deep thinking that AI can't replace.
In the end, AI boosts productivity but doesn't replace engineers. The focus of computer science is shifting from just coding to thinking algorithmically, managing complex systems, and using AI to build bigger and better projects.
AI is changing the field in three main ways:
1) AI takes care of routine tasks, allowing engineers to focus on designing systems, making logical choices, and planning architecture instead of just writing code.
2) AI-generated code can look correct but may have hidden errors or security issues. Checking and fixing this requires strong computing skills in data structures, algorithms, and security.
3) Computer science is much broader than basic web development. Areas like cybersecurity, cloud infrastructure, data engineering, robotics, and AI development need deep thinking that AI can't replace.
In the end, AI boosts productivity but doesn't replace engineers. The focus of computer science is shifting from just coding to thinking algorithmically, managing complex systems, and using AI to build bigger and better projects.
Jezlea Ortega
Tech Architecture
102
Answers
New York, New York
Updated
Jezlea’s Answer
Hi, Zane. Computer science is not doomed. It is evolving, and there is a very big difference between the two. Yes, AI is changing the way software gets written. Tools like GitHub Copilot and various AI assistants can generate code, autocomplete functions, and speed up certain parts of the development process significantly. But here's what those tools cannot do. They cannot architect complex systems, make high-stakes engineering decisions, debug deeply layered infrastructure problems, understand business context, or take accountability for the products they help build. Those things still require a human with real technical knowledge and judgment.
If anything, AI is raising the floor of what's possible in tech, which means the demand for people who truly understand how these systems work underneath the surface is only going up. Someone needs to build the AI tools, train the models, maintain the infrastructure they run on, secure the systems they interact with, and evaluate whether their outputs are actually correct. All of that is computer science work.
What is true is that the bar is shifting. Junior roles that involve writing basic, repetitive code are becoming harder to land because AI handles more of that work now. This means coming out of school with just a degree and no real-world experience is riskier than it used to be. Internships, personal projects, open-source contributions, and specialized skills in areas like cybersecurity, machine learning infrastructure, or cloud engineering will matter more than ever.
If anything, AI is raising the floor of what's possible in tech, which means the demand for people who truly understand how these systems work underneath the surface is only going up. Someone needs to build the AI tools, train the models, maintain the infrastructure they run on, secure the systems they interact with, and evaluate whether their outputs are actually correct. All of that is computer science work.
What is true is that the bar is shifting. Junior roles that involve writing basic, repetitive code are becoming harder to land because AI handles more of that work now. This means coming out of school with just a degree and no real-world experience is riskier than it used to be. Internships, personal projects, open-source contributions, and specialized skills in areas like cybersecurity, machine learning infrastructure, or cloud engineering will matter more than ever.
Matthew Setter
I'm a software developer and trainer
3
Answers
Bundaberg Central, Queensland, Australia
Updated
Matthew’s Answer
Personally, I am firmly of the belief that the idea that AI destroying software development as a career is completely overblown!
I've been in tech for around 30 years, and in that time, there have always been those that saw, or tried to treat, software developers as glorified factory workers. We have very valuable, in-demand skills, ones that we had to invest years and significant resources to develop. But, that didn't matter to them. They attempted to treat us as though they can dictate the tools that we use and how we develop — in every respect!
I often wondered if those same people would hire another professional, such as an electrician or plumber, for a task that they were unable to complete, and then attempt to tell them how to do their work and the tools that they needed to use. Or, would they tell their dentist or doctor how to treat them when they got sick?
Cutting a long story short, I see AI, in a lot of respects, as the next evolution of that type of thinking.
Then, there's another way to look at it. Sure, people can complete rather complex tasks using sophisticated software. But, if something goes wrong, if people don't know what's going on under the surface, it's highly likely that they won't be able to complete said task, as the software hid most (if not all) of the work away behind a (hopefully) impressive user interface.
Contrast that with the person who knows how to complete the task themselves, but uses software to simplify or reduce the time required. If something goes wrong, those people are not helpless. Things might take a bit longer, and they might have to do a bit more work than they otherwise would. But they'd be able to get their work done.
For those reasons, I believe that people with a strong foundation in and experience with software development will be in demand for a long time to come! Sure, you can rapidly generate software prototypes and proofs of concept with AI, but without the fundamental knowledge, how do you know the quality of what AI produced for you? How do you know if the software's suitably performant, has security holes, or where it could be improved? Answer: you can't.
So, as with so many other industries, keep learning those core skills.
I've been in tech for around 30 years, and in that time, there have always been those that saw, or tried to treat, software developers as glorified factory workers. We have very valuable, in-demand skills, ones that we had to invest years and significant resources to develop. But, that didn't matter to them. They attempted to treat us as though they can dictate the tools that we use and how we develop — in every respect!
I often wondered if those same people would hire another professional, such as an electrician or plumber, for a task that they were unable to complete, and then attempt to tell them how to do their work and the tools that they needed to use. Or, would they tell their dentist or doctor how to treat them when they got sick?
Cutting a long story short, I see AI, in a lot of respects, as the next evolution of that type of thinking.
Then, there's another way to look at it. Sure, people can complete rather complex tasks using sophisticated software. But, if something goes wrong, if people don't know what's going on under the surface, it's highly likely that they won't be able to complete said task, as the software hid most (if not all) of the work away behind a (hopefully) impressive user interface.
Contrast that with the person who knows how to complete the task themselves, but uses software to simplify or reduce the time required. If something goes wrong, those people are not helpless. Things might take a bit longer, and they might have to do a bit more work than they otherwise would. But they'd be able to get their work done.
For those reasons, I believe that people with a strong foundation in and experience with software development will be in demand for a long time to come! Sure, you can rapidly generate software prototypes and proofs of concept with AI, but without the fundamental knowledge, how do you know the quality of what AI produced for you? How do you know if the software's suitably performant, has security holes, or where it could be improved? Answer: you can't.
So, as with so many other industries, keep learning those core skills.
Dima Vizelman
Software Engineer
34
Answers
Tel Aviv-Yafo, Tel Aviv District, Israel
Updated
Dima’s Answer
Hi Zane,
It's true that no one knows exactly what will happen yet. AI is definitely going to change computer science and might take over some jobs. However, saying it will "destroy" the degree seems a bit too much.
In fact, the focus is shifting. It's becoming more important to understand systems, algorithms, architecture, debugging, security, and how to use AI well. These skills will likely become even more valuable as AI handles more coding. So, there's definitely hope for computer science. The degree is evolving, and while we can't predict exactly how, it's an exciting time to be part of this field.
It's true that no one knows exactly what will happen yet. AI is definitely going to change computer science and might take over some jobs. However, saying it will "destroy" the degree seems a bit too much.
In fact, the focus is shifting. It's becoming more important to understand systems, algorithms, architecture, debugging, security, and how to use AI well. These skills will likely become even more valuable as AI handles more coding. So, there's definitely hope for computer science. The degree is evolving, and while we can't predict exactly how, it's an exciting time to be part of this field.
Jess Agliam
HR Professional
13
Answers
Mandaluyong, Metro Manila, Philippines
Updated
Jess’s Answer
I think it's a bit overdramatized. Saying AI will doom computer science is like saying GPS would make learning how to drive unnecessary. GPS changed how we navigate, but we still need people who understand the road.
AI is changing how software is built, but computer science isn't disappearing. If you enjoy problem-solving and technology, a computer science degree can still open many doors. The key is to learn how to work with new tools, not compete against them.
AI is changing how software is built, but computer science isn't disappearing. If you enjoy problem-solving and technology, a computer science degree can still open many doors. The key is to learn how to work with new tools, not compete against them.
Michael Richtberg
Product management & engineering
25
Answers
Norfolk, Virginia
Updated
Michael’s Answer
In these rapidly evolving times of AI, it's certainly understandable that you have concerns. However, there's room for value-add in the AI technology space.
Rather than repeat what I've written, please have a look at what career conscious individuals can do to thrive in an AI world:
https://www.linkedin.com/posts/mrichtberg_which-ai-skills-are-employers-looking-for-activity-7503122221880471552-1O8R
Get your degree and keep learning
College teaches not just skills, but how to learn. The learning process is a lifelong process.
Rather than repeat what I've written, please have a look at what career conscious individuals can do to thrive in an AI world:
https://www.linkedin.com/posts/mrichtberg_which-ai-skills-are-employers-looking-for-activity-7503122221880471552-1O8R
Michael recommends the following next steps:
Sandeep Khandelwal
Software Engineer
155
Answers
San Ramon, California
Updated
Sandeep’s Answer
Hello Zane,
Computer science is definitely not a doomed career, but it is changing because of AI. AI can automate some coding tasks, but companies still need people who understand how software works, solve complex problems, design systems, and make good technical decisions. I would focus on strong CS fundamentals while also learning how to use AI tools effectively. The combination of computer science skills and AI knowledge will likely be very valuable in the future.
Computer science is definitely not a doomed career, but it is changing because of AI. AI can automate some coding tasks, but companies still need people who understand how software works, solve complex problems, design systems, and make good technical decisions. I would focus on strong CS fundamentals while also learning how to use AI tools effectively. The combination of computer science skills and AI knowledge will likely be very valuable in the future.
Minglun Li
Machine learning engineer
4
Answers
Boston, Massachusetts
Updated
Minglun’s Answer
Nothing lasts forever. Some jobs will disappear, others will change, and new ones will emerge. I think the more useful questions are: “How will this field change, and how can I prepare?”
AI will likely reshape many kinds of knowledge work. Studying computer science puts you closer to the technology driving that change and gives you tools to shape it. That doesn’t guarantee job security, but it’s a reason I wouldn’t write off the field.
AI will likely reshape many kinds of knowledge work. Studying computer science puts you closer to the technology driving that change and gives you tools to shape it. That doesn’t guarantee job security, but it’s a reason I wouldn’t write off the field.
Suhas Sundararaju
Cloud Engineer
1
Answer
Bengaluru, Karnataka, India
Updated
Suhas’s Answer
AI is part of computer science, and students can study it as part of their curriculum. The applications of CS across topics are massive, and pretty much every field is incorporating AI now as part of advanced computer science.Students can major in Computer Science and take AI electives for advanced study or to build a career in it. The future is Computer Science -> AI / Computing
Sunil Bs
business analyst
1
Answer
Bengaluru, Karnataka, India
Updated
Sunil’s Answer
Think of AI as a helpful addition to what you already know, like having a car with some cool features. You still need to know how to drive it. Hope this makes sense!
Dakota Dry
Risk Management
2
Answers
Seattle, Washington
Updated
Dakota’s Answer
Hello!
Even if you're not directly in software development or computer science, you can still appreciate the importance of these fields. Computer science degrees will always be valuable. While AI has made coding easier for everyone, having a strong foundation is still essential for creating good and effective tools.
People in computer science should focus not only on technical skills but also on creativity. This helps them stay competitive with creative individuals who can now build things without deep technical knowledge. Think of it like giving a child a complex book—they might read the words but not understand the story. Similarly, just because coding is more accessible doesn't mean everyone can create high-quality tools. This is where computer science experts shine.
Even if you're not directly in software development or computer science, you can still appreciate the importance of these fields. Computer science degrees will always be valuable. While AI has made coding easier for everyone, having a strong foundation is still essential for creating good and effective tools.
People in computer science should focus not only on technical skills but also on creativity. This helps them stay competitive with creative individuals who can now build things without deep technical knowledge. Think of it like giving a child a complex book—they might read the words but not understand the story. Similarly, just because coding is more accessible doesn't mean everyone can create high-quality tools. This is where computer science experts shine.
Vijay Singh
Cybersecurity Professional
7
Answers
Seattle, Washington
Updated
Vijay’s Answer
Hi Zane, I don't believe that a career in computer science is doomed. The field is evolving, perhaps more than ever before, but that's normal in a technology-driven world. It's important to stay flexible and learn new skills as technology advances. With AI emerging, some routine coding tasks might become outdated, but the core of computer science is still problem-solving, and that remains unchanged. Using AI to tackle problems will be a valuable skill, in my opinion.
Adegboye Adebayo
IT Security Analyst
2
Answers
Chicago, Illinois
Updated
Adegboye’s Answer
Hi Zane, I understand your concerns about the future of Computer Science. While there might be fewer graduates needed, it doesn't mean there won't be opportunities. AI is changing how we work in every field, and it can be a great tool to help you stand out. Embrace AI to boost your skills and stay competitive.
Krishnam Rastogi
Software Engineer
8
Answers
Lucknow, Uttar Pradesh, India
Updated
Krishnam’s Answer
I wouldn’t say computer science is a doomed career. AI is definitely changing software development, but I think “AI will destroy programming” is heavily overdramatised.
AI can already write a lot of code, but software development is much more than writing code. Developers still need to understand problems, design solutions, work with teams, debug systems, make decisions, and understand whether the code actually solves the right problem.
What may change is the amount of basic or repetitive coding that developers do, especially at the entry level. That means it’s becoming even more important to understand the fundamentals rather than simply knowing how to write code.
If you’re considering CS, I’d focus on learning programming fundamentals, data structures, databases, Git, and problem-solving. Build projects outside of class and learn to use AI tools as a productivity tool—but make sure you understand and can verify the code they produce.
You also don't have to limit yourself to traditional software development. CS can lead to cybersecurity, cloud/infrastructure, data engineering, AI/ML, and many other areas.
Technology will continue to change, but people who can learn, adapt, and solve problems will continue to be valuable. If you genuinely enjoy technology and problem-solving, I wouldn't let the fear of AI alone stop you from pursuing computer science.
AI can already write a lot of code, but software development is much more than writing code. Developers still need to understand problems, design solutions, work with teams, debug systems, make decisions, and understand whether the code actually solves the right problem.
What may change is the amount of basic or repetitive coding that developers do, especially at the entry level. That means it’s becoming even more important to understand the fundamentals rather than simply knowing how to write code.
If you’re considering CS, I’d focus on learning programming fundamentals, data structures, databases, Git, and problem-solving. Build projects outside of class and learn to use AI tools as a productivity tool—but make sure you understand and can verify the code they produce.
You also don't have to limit yourself to traditional software development. CS can lead to cybersecurity, cloud/infrastructure, data engineering, AI/ML, and many other areas.
Technology will continue to change, but people who can learn, adapt, and solve problems will continue to be valuable. If you genuinely enjoy technology and problem-solving, I wouldn't let the fear of AI alone stop you from pursuing computer science.
David Otero
System Architect
3
Answers
Passaic, New Jersey
Updated
David’s Answer
Over 20 years ago, my college professors gave me some advice: if you love computer science and see a future in it, stick with it. Learn to think critically and explore different theories. Take care of your health by eating well and exercising. Be open to new knowledge and accept that you don't know everything. Seek spiritual guidance and trust in a higher power to guide you. This might not make sense until you take that leap of faith, but then things will start to fall into place according to a higher purpose.
Manvi Sharma
3
Answers
Chandigarh, India
Updated
Manvi’s Answer
Hi Zane,
Computer science is full of exciting opportunities. While the field has changed, with tools like Claude and No-Code AI reducing the need for some traditional skills, they have actually increased the importance of engineers. Those who grasp how computers, networks, and data systems really work are more valuable than ever.
Computer science is full of exciting opportunities. While the field has changed, with tools like Claude and No-Code AI reducing the need for some traditional skills, they have actually increased the importance of engineers. Those who grasp how computers, networks, and data systems really work are more valuable than ever.
Feroz Rah
Support Engineer
3
Answers
Srinagar
Updated
Feroz’s Answer
Think of learning computer science like building houses:
What's new: AI is like a super-fast power tool. Instead of spending hours on each nail, builders can now use machines to do the repetitive tasks quickly.
The real job now: Since machines handle the hammering, the focus shifts to being the architect. You decide how the house is designed, ensure the roof is strong, and make sure machines don't make mistakes.
Is the degree useless? No. You still need to know how houses work to design them and spot errors. But just knowing how to hammer a nail isn't enough to get hired anymore.
Computer science isn't disappearing; it's evolving from "doing simple tasks" to "being the smart planner who uses AI tools to create big projects."
What's new: AI is like a super-fast power tool. Instead of spending hours on each nail, builders can now use machines to do the repetitive tasks quickly.
The real job now: Since machines handle the hammering, the focus shifts to being the architect. You decide how the house is designed, ensure the roof is strong, and make sure machines don't make mistakes.
Is the degree useless? No. You still need to know how houses work to design them and spot errors. But just knowing how to hammer a nail isn't enough to get hired anymore.
Computer science isn't disappearing; it's evolving from "doing simple tasks" to "being the smart planner who uses AI tools to create big projects."
Isabella Brody-Calixto
Business Analyst
2
Answers
New York, New York
Updated
Isabella’s Answer
Definitely overdramatized. There's some truth in that Computer Science (software engineering) has changed. A lot of SWE's day now is more about project management and architecting solutions rather than writing code. However, in my opinion, taking the classes and understanding the foundations is still really important to being a good engineer vs just being a vibe coder. Also, you don't have to be a SWE if you major in CS! You can do different things with that degree. The job market is tougher these days, so I recommend specializing with a minor or extra certifications.
Nicole Reitz
Analytics Engineer
4
Answers
Boston, Massachusetts
Updated
Nicole’s Answer
Lots of good perspectives here! I think the important thing is to not get too attached to any job or field in the exact form that it exists now, but to keep an open mind as things change. Pay attention to how the ways you solve problems translate to new areas and interests as things evolve. I started out aspiring to be a "Data Scientist" 20 years ago, but the field we called data science then is now many different specialties (e.g., machine learning, data engineering, business intelligence and analytics, visualization and design, etc.)! A foundation like computer science will give you a solid starting point for many paths. The learning never stops!
Praise Ayorinde
Software Engineering Manager
1
Answer
Seattle, Washington
Updated
Praise’s Answer
My take is its overdramatized. AI is a tool we use to release - we use it and it accelerates our productivity but we still need to understand the field to direct AI. Working has changed but i think we'll still work hand in hand for the next years