What do you do if AI and automation threaten your software engineering career?

Adapt by learning AI-related skills, specialize in areas complementary to automation, embrace lifelong learning, and focus on creativity, problem-solving, and strategic thinking.

At this point AI cannot reliably replace a novice developer. While it is tempting to use AI to write some amount of code, the use of AI (presently) reduces the quality of codebases with its inability to reuse code or consider broader design patterns. The unanswered ethical questions raised by the acquisition of ML model training data and massive power consumption notwithstanding, systematized guessing is not a good pattern. If AI gets to the point of replacing senior developers then I'll retire and enjoy the life of leisure that futurists have long promised would be delivered by our robot overlords. I'll start a letterpress or a dance studio and enjoy making art. It's much more likely that the AI bubble pops in the next two to five years.

AI is inevitable and if you want to survive, then make sure you try to learn these new AI tools and include them in your day to day work. AI is an opportunity to explore the new unknown horizon where soon we all might witness no difference between Developers and Testers. It will not always be the case where your job is in danger, but AI will definitely make your life better.

IA doesn't threaten jobs, the difference will be in those who use IA for work and those who do not. Those who don't use it or don't learn to use it will probably have less chance of getting a job.

Here are the steps I'm taking as a full-stack SWD. 1. I'm keeping a good eye on Devin and another on the niche in which I work Draw out a plan of Action to make myself relevant in 15 years. 2. Learn the technologies surrounding AI and ML and build a strong toolset. 3. Read everything you can and connect yourself with others on the same path.

In technology you always have to keep sharpening your saw to stay relevant. Learn, Apply and Reflect and repeat the cycle over and over. By no means this is easy but perseverance will prevail

The key to stay relevant in tech is constant upskilling and staying updated with the current trends. Yes AI and other automation tools might pose a threat to software engineers, but we should not forget that at the end of the day AI is limited by its context, and that is where software engineers come into play. LLM models can solve the problems based on their dataset, but they cannot come up with a unique solution to a unique problem (due to limitation of context), hence instead of thinking AI as a threat, it makes more sense to just keep evolving your skillset and always strive to solve incrementally complex problems, and use AI as an ally for this.

When it comes to technology, it has always been important to be up to date. The job title should not be given too much weight; rather, you should rely on your skills and tools and expand your knowledge here. Ultimately, you are asked for your ability to solve problems. The title and area of responsibility can change significantly over the years

This is where interest and passion play out. A passionate person or someone who is interested in their career pursuit as a software engineer must always learn new technologies in their free time to broaden their horizons on different technologies. This way will enable them become relevant in the tech industry

AI augments human abilities by automating routine tasks, providing insights, and speeding innovation, thereby boosting productivity and reducing costs.

Embracing change is essential to growth. Software engineering itself has been a continuous learning process where programming paradigms, languages and patterns change frequently. What’s important to understand is what role software engineers will play in this new world. While repetitive code and scripts will be easy to generate with ai, the software engineer who focuses on bringing about the creativity through right use of data structures and algorithms will always have tremendous value in this world. Writing good, efficient code to solve complex problems is as much an art as its a science and software engineers who can adapt to changing environments will always add value.

I enjoy solving complex problems which cannot be specified in details beforehand. As we currently do not have method to take detailed experiences of many expert engineers as a training material for AI, I am not afraid. Once that become possible any human profession can be replaced too and we can let AI control global society.

We as a group of software developers and testers, have formed a community, which discusses use cases, document them, bring people together to check and validate an idea and its efficiency and its has never been more fun! I think the life of software professionals are more fun now. Because, AI is still a child and it needs a village or the entire world of experts in every walk of life to train and make it better. Come together and explore.

One important thing to be in contact with is the team behind the AI. Make sure that you know the ins and outs of the model and its current state when working with AI. Effective communication between the team behind the AI and you would give you insights on how it works and what you could do to work with it. It would also be important that other relevant personnel communicate with the team behind the AI as well.

Spot on love what it says Learn, Unlearn and Relearn. Being in the field of Technology you have to be ready for the change. Be the early adopter, learn it first and then teach it to your team. Bring others on board this way you become so valuable for your company keeping then competitive in the market that you will never feel threatened. Be the leader and not the follower.

Always be at the forefront. Don't just watch but try to help shape it. So you will have a steep learning curve yourself. In addition, you get or keep your security

At time I started study of Electronics in mid '80s most of current technologies did not exist, or were at early beginning. So it was continuous learning ever since, and one part was switching to Embedded Software. But I knew it before I started, and that way is lot more fun.

Exit software development unless you have a strong domain expertise that AI cannot easily displace like ecommerce, payment processing, cloud knowledge, enterprise architecture, etc.