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How to Future-Proof your Tech Career in the Age of AI

AI is transforming many jobs and fields, and software development is no exception. Tools like GitHub Copilot and ChatGPT can already generate code, debug, or refactor. As these tools improve, the landscape for developers is changing fast. So how can you make sure your career is future-proofed for all those tech advancements? 

The good news is that developers who adapt can become more valuable, not less. Here’s how to stay ahead.

What AI Can and Can’t Do

AI is good at code generation, testing and debugging, and refactoring. It can also help non-programmers build simple tools with low-code or no-code platforms. However, AI can’t architect large, scalable systems, understand nuanced requirements and context, or navigate legacy systems and undocumented code. Importantly, it also can’t collaborate with teams and reach compromises, nor come up with innovative solutions.  

This means that while routine coding tasks can increasingly be automated, there will be rising demand for developers who can work with AI, understand large-scale projects, and communicate efficiently with teammates and clients. 

AI might make you more productive, but it won’t make you obsolete if you’re adaptable.

How to Future-Proof your Career

  1. Start with the fundamentals

AI can write code, but not understand it. This is where you need to start. If you’ve never coded before, Northcoders offers a free, no-obligation Python Basics online course as part of the application for the Data Engineering, AI & Machine Learning Bootcamp

If you want to get deeper into coding and become a data engineer, the bootcamp itself will cover everything you need to know to start your career. It’s also regularly updated to reflect the latest advances in tech and to match employer expectations.

  1. Move up the stack

AI is unreliable at managing complexity, and this is where you can stand out. Make sure to keep in mind the big picture of how different aspects of tech work together. It’s no longer enough to simply know a coding language. You have to understand how to use it within various contexts. 

The Data Engineering, AI & Machine Learning Bootcamp goes further than just teaching Python. It also covers all key aspects of data engineering, including some often forgotten by beginners. These include architecture and scalability, but also technologies such as DevOps, containerisation, and cloud platforms like AWS. 

  1. Embrace your human side

Humans are necessary to bring context, ethics, and empathy to tech. It’s easy to think about software development as something you do alone at a computer without talking to anyone. The reality is that it usually involves a lot of teamwork and problem-solving with others. 

Just like AI struggles with complexity and context for coding projects, it is also limited in its understanding of business goals and colleague dynamics. It also may not understand ethical or social implications, or be biased due to working from limited data.  If you’re interested in why diversity is so important in AI, you can check out our previous article on this topic here

During the bootcamp, you will learn how to collaborate with other developers, work by pair programming, and manage projects. Being able to communicate with clarity and empathy can cement your place as an essential part of the team. 

  1. Explore AI and machine learning

This is an area often unexplored by junior developers, but a skill that will set you apart. This is a particular strength of the new curriculum of the Data Engineering, AI & Machine Learning Bootcamp

It will take you from foundational AI and machine learning concepts to solving industry-relevant, real-world problems with AI applications. You’ll also gain practical experience with neural networks, decision trees, LLMs, embeddings, and fine-tuning models. By the end, you’ll even build your own RAG-powered AI system, which will be a great addition to your portfolio.

Overall, AI isn’t the end of software development. Rather, it’s a big shift in how it’s done. The developers who will thrive aren’t necessarily the ones who write the most lines of code, but those who can adapt quickly, learn relevant technologies, and work effectively with new tools.

Ready to future-proof your career? You can get started with Northcoders’ Data Engineering, AI & Machine Learning Bootcamp. Find out more and apply here.