3 new obstacles for aspiring coders in the age of AI
I’m Fahim, a software developer turned tech founder. This article is part of my series: The Developer’s Launchpad. I’ll share my top lessons, hacks, and best practices for learning how to code and launching a new career — things I wish I would’ve known earlier in my journey. If you’re starting out your own coding journey, this series is for you.
When you start a new endeavor, the particular time in which you’re learning— and the factors that come with it — will undoubtedly influence the journey ahead.
I was learning to code in the early 00’s. Distributed systems and cloud computing were poised to sprawl across the industry. They impacted both my career and the evolution of tech till this day. In due time, I became a systems engineer, and was part of the first generation of engineers designing the distributed systems that we still rely on today.
Of course, if you’re learning to code today, you’ll be facing unique challenges and circumstances that will shape your learning and career goals.
To help you plan for success, I want to talk about 3 obstacles facing those learning to code today (and some guidance on overcoming them):
3 new obstacles for aspiring coders in the age of AI#
1. The concern that AI will make devs obsolete.#
AI is changing so many of our services and workplace norms right now. With AI tools capable of doing certain tasks like writing code, there’s a lot of concern about whether AI will impact the demand for developers… and the rampant layoffs of late don’t help soothe concerns.
Regardless, the layoffs are not a result of AI taking over jobs. The idea that AI will replace software engineers is an exaggeration. AI tools are mostly useful for writing code right now, but writing code is just a small subset of the tasks that software engineers take on to ship production-grade software.
In fact, AI is going to create more jobs for developers. Customers are now expecting AI in every application and every domain. That means almost all software in the world has to be re-imagined. Once it’s re-imagined, the task of translating that imagination into a great user experience falls squarely on the shoulders of software engineers.
Imagine if every bridge in the world had been built with wood and humans invented steel. Now, every bridge has to be reconstructed using steel. In our case today, AI is that invention.
As software companies need to re-imagine and re-write almost all software applications, the demand for engineers will skyrocket.
Ignore the naysayers and learn to code. The AI era will not make developer jobs obsolete. In fact, I’d encourage you to embrace Generative AI tools like ChatGPT and Copilot to streamline your learning and coding journey.
2. AI idling.#
AI can’t replace human developers… but human developers will need to learn AI skills eventually to stay in-demand. While you shouldn’t jump into AI too early as a learning coder, be sure to learn AI skills at some point instead of idling for too long.
The advent of AI means that expectations for developers are changing. Developers need to know how to leverage AI tools like LLMs to streamline their work.
At minimum, developers need to learn prompt engineering. Prompt engineering means writing effective prompts that get the outputs you need out of Generative AI tools like CoPilot and ChatGPT. Learning prompt engineering will help you streamline your work by leveraging (rather than struggling with) Generative AI to write code, debug, and more.
At most, you might learn machine learning and data science to work directly with and improve AI models. If this is the case, you have a long journey ahead. But not every developer needs to go this far to stay competitive.
Again, if you’re just getting started with learning coding, you shouldn’t fret too much about AI skills yet. Learning how to leverage AI will be most relevant once you’ve mastered programming itself. However, you can certainly learn prompt engineering now to leverage Generative AI as a learning assistant.
3. Information overload.#
From video tutorials to online courses, the internet is absolutely saturated with learning resources today. Whether you’re self-taught or going to school for a computer science degree, these resources can all help supplement your learning.
But the prospect of abundant resources also comes with a risk.
Namely, you can suffer from information overload, or exposing yourself to too much information at once. Information overload can harm your learning by impacting your memory retention, and causing undue stress if you’re not ready to absorb all the information you’re learning.
It can also be easy to get lost and lose focus. If you keep exploring tutorials on different topics, you can get stuck in a rabbit-hole instead of moving forward.
If your journey is fully self-taught, you’re at greatest risk of information overload. The best way to protect yourself from information overload is to have a structured learning plan for the topics you’ll learn, and in what order.
Learn the fundamentals and code as you learn in the language of your choice. Educative’s Learn to Code resources include 50+ courses and projects curated for beginners. You can try them for free here.
There’s never been a better time to learn to code.#
With all the resources and programs out there, learning to code has never been more accessible. Meanwhile, the introduction of AI is poised to help developers solve even bigger problems than ever before.
It’s certainly an exciting time to learn to code.
Whichever method or resources you use to learn coding, make sure you take your time on mastering the fundamentals, and get hands-on with your learning as you go.
To help you build confidently with fundamental coding skills, we curated 50+ courses and projects specifically for beginners at Educative: the Learn to Code Starter Pack.
You can get started with it today with a low-cost subscription or a free trial — and no setup is required, you can practice coding right in your browser.
Start strong today and Learn to Code with Educative.
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