Over the Christmas and New Years holiday, I spent some time “interviewing” AI coding assistants. I will follow up this “article” with a more comprehensive review of my experiences. In the meantime, I thought it would be fun to imagine what actual interview with them might look like (ok, I was bored). I mixed in some actual responses from ChatGPT as well as Bard (although I did modify them a bit).
[Scene: A futuristic tech office. The Chief Software Architect, Sam, is seated at a sleek, high-tech desk. Two AI Coding Assistants, named CogMinds and NeuroCraft, stand in a line, each displaying a holographic avatar.]
Sam: [Smiles] Welcome, CogMinds and NeuroCraft! I’m excited to dive into this interview. Let’s start with a simple question: How would you approach optimizing a database query for a high-traffic website?
CogMinds: [An intricate, ever-changing web of lines and dots, symbolizing the intricate thought processes of a brilliant mind, pulsating light between the lines and dots]
To optimize database queries for high-traffic websites, I’d act like a detective: profiling tools to find bottlenecks, optimizing query structure by minimizing joins and caching frequently accessed data, tuning the server and distributing load across multiple servers, all while continuously monitoring and adapting to traffic patterns and new techniques. It’s about ensuring a smooth, responsive performance for every user, regardless of the crowd.
NeuroCraft: [An avatar combining robotic and organic elements, moving slowly and deliberately] I’d employ deep learning techniques to predict query performance, dynamically adjusting database configurations, and adapting to changing traffic patterns for optimal efficiency.
Sam: Let’s up the ante. How would you design a microservices architecture for a globally distributed application with varying data compliance regulations?
CogMinds: I’d design modular microservices, ensuring compliance with each region’s regulations by implementing specific modules for data handling. Communication between microservices would be secure and monitored.
NeuroCraft: My neural network would analyze regional compliance requirements in real-time and dynamically adapt the microservices architecture to ensure seamless adherence to data regulations without compromising performance.
Sam [Looking a bit skeptical] : Fascinating! Now, let’s delve into the realm of ethical coding. How would you ensure that an AI system you’ve developed avoids bias and promotes inclusivity?
CogMinds: Ethical AI requires diverse data, fairness-aware algorithms, inclusive design, user feedback, and continuous improvement. Debiasing techniques, explainable AI, accessibility features, and transparency with audits are key tools. It’s an ongoing journey to ensure AI avoids bias, promotes inclusivity, and benefits everyone.
NeuroCraft: My neural network would be trained on diverse and representative datasets, with ongoing fine-tuning based on real-world feedback. Traceability features would allow users to understand and address any biases that may arise.
Sam: [noticing the consistent repetition in the answers and becoming annoyed] Now, let’s switch gears. How would each of you approach debugging a complex issue in a distributed system, especially when the problem manifests intermittently and involves multiple interconnected components?
CogMinds: I would meticulously trace the data flow, analyze system logs, and dynamically visualize potential points of failure using my holographic avatar. This approach ensures a comprehensive understanding of the issue.
NeuroCraft: Debugging is an art, and I excel at it. My neural network dynamically adapts to real-time feedback, identifying patterns associated with intermittent issues. I illuminate pathways , shedding light on the specific areas where debugging interventions are most needed. It’s all about adaptability and precision.
Sam: [An audible loud exhale] Astounding. Each of you answer with the facade of deep knowledge, but provide answers without concrete solutions. A complete mess of jargon meant to confuse and frustrate the most knowledgeable people.
Sam: [pause]
Sam: [slyly smiling] Have you thought about marketing?