The Rise of AI in Tech
AI has been a popular topic for a while now and is especially transforming the tech industry. Changing the way, we work as developers, that is, if we allow it. As someone in tech, it’s important to get on board with AI and learn how to utilize it effectively before it’s too late. As AI evolves, knowing how to use it well will become a core skill in the industry.
AI is Powerful – But Not Perfect
AI is amazing and has come a long way. However, it’s not perfect, and there are important considerations to keep in mind when using it, to unlock its full potential without introducing unnecessary complexity.
This Risk of Developer Complacency
AI can make us humans lazy. With it being built into almost all search engines and social media platforms, we tend to ask AI instead of browsing through articles and doing our own research. Yes, it can save you a lot of time and probably get you the answer you’re looking for, but we need to be cognisant of AI hallucinations.
Understanding AI Hallucinations
What is an AI hallucination? It’s a phenomenon where AI perceives patterns or objects that don’t exist, producing outputs that are nonsensical or inaccurate. So, it’s always good to fact-check AI results or ask follow-up questions to get closer to the truth.
This is especially important for junior developers, who might not know what further questions to ask or may not recognise when AI suggestions are inaccurate. For them, it’s best to consult Google alongside AI. We must not be lazy and blindly accept what AI tells us.
Context Is Key When Using AI
Context, context, context. The more context you give AI, the better it performs. It tends to make assumptions, so when working on a new feature or bug, make sure to provide as much context as possible. You can feed it context gradually as it responds, but junior developers might struggle to notice when AI goes off course. If you’re new to using AI or still developing your skills, giving more context upfront helps.
I also find that being able to describe the issue or feature you’re working on in detail brings you closer to solving it. If you’re struggling, it likely means you need to revisit the code or spec to ensure you fully understand what’s needed.
AI-Generated Code Can Be Overcomplicated
AI tends to make code more complex than necessary. If you ask AI to generate a piece of code, I often find it overcomplicates the implementation. AI performs best when you ask it to implement specific functions and provide documentation for reference.
Another useful way to use AI while coding is through tools built into your IDE that suggest the next block of code as you type. Sometimes it misses the mark, but often you can tab through the rest of the line and make minor adjustments.
Use AI Strategically – Not Passively
Use AI to your advantage, strategically and thoughtfully. One of the most impactful ways to do this is by identifying parts of your workflow that can be streamlined through automation. Tools like Node-based automation frameworks and workflow orchestrators have become more powerful and accessible, especially with the rise of AI. These tools can integrate seamlessly with AI services to handle repetitive tasks, trigger actions based on events, or even assist in deployment pipelines. As AI continues to evolve, so too will the tools that support it, so staying informed and experimenting with these integrations can give you a real edge in your development journey.
Embracing AI doesn’t mean replacing your skills, it means enhancing them. The key is finding the right balance: learning to collaborate with AI, leveraging its strengths, and questioning its outputs, without becoming overly dependent on it. While AI can accelerate your workflow and boost productivity, relying on it too heavily can lead to complacency and missed learning opportunities. Use AI to amplify your capabilities, not to replace your critical thinking. The future of tech is being written now. Make sure you’re actively shaping it, not just passively following along.
