Embrace, Not EXTERMINATE In the last 12 months, it seems like every other buzzword in the tech industry has been talking about “embracing AI” to write code, solve problems, answer questions, and do everything outside of playing with your cat. Noticeably, this has developed two different camps of early career software engineers: AI Maximalists and AI Doomsayers. The maximalists- aka the vibe coders- I’ve met have become experts at prompt engineering, while the doomsayers I’ve met have been exasperated every single time I suggest pair programming with ChatGPT. I spend a lot of time mentoring junior engineers both professionally as well as outside my 9-5, volunteering with bootcamp grads and early career coders, and the amount of time I’ve been asked some variation of “is AI going to take my job” is at this point, too many to count. So, yes, Virginia, I’m going to tell you that AI is coming for your job- at least your expectation of what your job was. Now, it’s up to you to adapt your techniques and approaches to harness LLM utilities as a key part of your toolchain to solve problems. As long as you do this, the robots are not going to EXTERMINATE you. The Redefinition of Junior Engineer The concept of what a Junior Engineer is has been a shifting target over the last year or two as AI coding becomes more efficient, smarter, and more intuitive. Given context, LLMs and reasoning models such as Sonnet + ChatGPT can dive into a code base, build understanding, and answer questions in a nuanced, effective, and clear way. But isn’t that what a Junior Engineer does? Generally, a Junior Software Engineer is considered a more naive coder at a tech company. They’re just getting started in their career, so a lot of their time is spent learning — whether that’s figuring out the company’s code base, picking up best practices (SPACES VS TABS!!!!), or getting comfortable with tools and workflows, much like what an AI engine can do as it consumes the code in your company’s repository. Most of their day involves writing code, but not the super complex, high-stakes stuff (yet). They typically work on and eventually own smaller tasks or bug fixes, often with detailed guidance from more experienced engineers. Think of it kind of like rolling through the code base with training wheels- eventually, they'll ride on their own, but for now, they’re sticking close to the team. They also do a lot of code reviews (both giving and receiving), ask tons of questions (ideally!), and sit in on meetings where the big-picture decisions happen. Here’s the key differentiating factor between AI and Engineers- the junior engineer’s job isn’t just about coding; it’s about learning how to build things well, collaborating with others, and slowly leveling up until they can tackle bigger challenges. In combination with AI, a Junior Engineer can dive deeply into a code base and more quickly understand the state of the world, even if they don’t fully understand what the system does on the whole just yet. well Harmony With The Machine Instead of fearing AI as a replacement, junior engineers, you should view AI as an accelerator for your career growth. Here’s how they can make the most of it: Leverage AI for Faster Learning: Instead of spending hours searching documentation, use AI tools to get concise, relevant explanations quickly. Is there a utility function that is 500 lines long that you can’t quite understand the need for? Have an LLM translate that for you into clear, actionable understandable steps.


Use AI for Idea Validation: Have an idea for solving a bug? Run it by an AI model to get alternative approaches before implementing. Be mindful - there’s bound to be business context or reasoning to do things in certain ways.  The riskiest approach you can possibly take is to hit tab, let Copilot fill in the blanks and forget.


Strengthen Problem-Solving Skills: AI can provide solutions, but understanding why those solutions work (or don’t work) is a key differentiator of a strong engineer. You can also strengthen your code review skills by reviewing the AI’s code- dive in and have a dialogue about different approaches (“consider a switch case and provide me an explanation as to the pros and cons of doing so in this method”).


Collaborate and Think Beyond Code: AI can generate code, but it won’t replace creative problem-solving, stakeholder communication, or the ability to think critically about a project’s goals. If an AI can write code that works, that’s great, but how can you as an engineer convey the solution to the problem to stakeholders and also update it if it doesn’t solve for all the required cases?


Focus on Growth Beyond Coding: Soft skills, system design, and understanding business impact remain vital. AI can be a tool, but it won’t replace engineers who drive meaningful innovation. Leverage AI for Faster Learning: Instead of spending hours searching documentation, use AI tools to get concise, relevant explanations quickly. Is there a utility function that is 500 lines long that you can’t quite understand the need for? Have an LLM translate that for you into clear, actionable understandable steps. Leverage AI for Faster Learning: Instead of spending hours searching documentation, use AI tools to get concise, relevant explanations quickly. Is there a utility function that is 500 lines long that you can’t quite understand the need for? Have an LLM translate that for you into clear, actionable understandable steps. Leverage AI for Faster Learning: Use AI for Idea Validation: Have an idea for solving a bug? Run it by an AI model to get alternative approaches before implementing. Be mindful - there’s bound to be business context or reasoning to do things in certain ways.  The riskiest approach you can possibly take is to hit tab, let Copilot fill in the blanks and forget. Use AI for Idea Validation: Have an idea for solving a bug? Run it by an AI model to get alternative approaches before implementing. Be mindful - there’s bound to be business context or reasoning to do things in certain ways.  The riskiest approach you can possibly take is to hit tab, let Copilot fill in the blanks and forget. Use AI for Idea Validation: Strengthen Problem-Solving Skills: AI can provide solutions, but understanding why those solutions work (or don’t work) is a key differentiator of a strong engineer. You can also strengthen your code review skills by reviewing the AI’s code- dive in and have a dialogue about different approaches (“consider a switch case and provide me an explanation as to the pros and cons of doing so in this method”). Strengthen Problem-Solving Skills: AI can provide solutions, but understanding why those solutions work (or don’t work) is a key differentiator of a strong engineer. You can also strengthen your code review skills by reviewing the AI’s code- dive in and have a dialogue about different approaches (“consider a switch case and provide me an explanation as to the pros and cons of doing so in this method”). Strengthen Problem-Solving Skills: why Collaborate and Think Beyond Code: AI can generate code, but it won’t replace creative problem-solving, stakeholder communication, or the ability to think critically about a project’s goals. If an AI can write code that works, that’s great, but how can you as an engineer convey the solution to the problem to stakeholders and also update it if it doesn’t solve for all the required cases? Collaborate and Think Beyond Code: AI can generate code, but it won’t replace creative problem-solving, stakeholder communication, or the ability to think critically about a project’s goals. If an AI can write code that works, that’s great, but how can you as an engineer convey the solution to the problem to stakeholders and also update it if it doesn’t solve for all the required cases? Collaborate and Think Beyond Code: Focus on Growth Beyond Coding: Soft skills, system design, and understanding business impact remain vital. AI can be a tool, but it won’t replace engineers who drive meaningful innovation. Focus on Growth Beyond Coding: Soft skills, system design, and understanding business impact remain vital. AI can be a tool, but it won’t replace engineers who drive meaningful innovation. Focus on Growth Beyond Coding: The role of the Junior Engineer isn’t disappearing—it’s evolving. If you embrace AI as a partner rather than a competitor, you can accelerate your career and take on more challenging, rewarding work faster than ever before.

The is an opinion piece based on the author’s POV and does not necessarily reflect the views of HackerNoon.

AI as a Tool, Not a Threat: Transforming Junior Roles Beyond "Vibe Coding"

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