Salman Hameed
Data Science | Machine Learning | Deep Learning | Generative AI
Data Science | Machine Learning | Deep Learning | Generative AI
In today’s competitive job market, platforms like LeetCode and HackerRank have become essential tools for millions of developers preparing for technical interviews. By solving problems categorized as easy, medium, and hard, candidates earn badges that they proudly display on their CVs, showcasing their problem-solving abilities. While this approach offers a structured way to evaluate coding skills, it raises a significant concern.
Many companies heavily rely on these platforms to gauge the creativity and potential of candidates. Unfortunately, this method often overlooks individuals who have demonstrated their capabilities by building strong, innovative projects. These developers may excel in real-world scenarios, yet they find themselves judged by a narrow standard that prioritizes rote problem-solving over true creativity. This reliance on standardized assessments can be disappointing for talented individuals, who see their potential undervalued.
As I research the evolving role of Generative AI, I’m struck by the profound impact it has on creative application development. Implementing Large Language Models (LLMs) via API has the potential to revolutionize how we build applications, shifting the focus from traditional coding tasks to more innovative and creative solutions. This shift is both exciting and concerning, as it challenges the conventional methods of assessing technical talent.
In response to these concerns, I decided to take action by developing an extension called AI Code Assistant. This tool is designed to work seamlessly with both LeetCode and HackerRank, addressing the limitations of traditional coding assessments while leveraging the power of Generative AI. Here’s how it works:
1. Simplified Problem Explanation: The extension provides a clear and basic explanation of any given problem. This ensures that users can easily understand what is being asked, regardless of their familiarity with the topic.
2. Step-by-Step Problem Breakdown: It breaks down the problem into manageable steps, guiding users on how to approach and solve it. This not only enhances understanding but also helps in building a structured problem-solving mindset.
3. Best Solution Delivery: The extension offers the best possible solution in code form. Users can simply copy this code and paste it into the coding section. I’ve intentionally left out the automation of this step to encourage learning through active participation.
4. Interactive Learning: Users can ask multiple follow-up questions related to the problem explanation, breakdown, or solution. This fosters a deeper understanding and supports continuous learning.
To showcase the capabilities of 'AI Code Assistant', I created a demo where I solve hard, medium, and easy problems from both LeetCode and HackerRank using this extension. The result is not only a demonstration of how powerful and creative Generative AI can be but also a reflection of the concerns surrounding its benefits and implications in the field of technical assessments.
As we move forward in this rapidly changing landscape, it’s crucial to rethink how we assess creativity and problem-solving skills in the tech industry. By embracing tools like 'AI Code Assistant', we can create a more inclusive and accurate measure of talent—one that recognizes both traditional coding skills and the innovative potential of individuals.
Discover how MY AI Code Assistant is transforming the way developers tackle LeetCode and HackerRank challenges. This innovative extension simplifies problem explanations, breaks down solutions step-by-step, and delivers the best code solutions instantly. Perfect for anyone looking to excel in coding interviews with the power of Generative AI.