Resolving a Basic Bug Using LLMs: A Step-by-Step Guide

🚀 Hackathon Insights: AI Coding Assistants Put to the Test 🚀

During a recent Bitmovin hackathon, I embarked on an ambitious project—integrating a solar generation data API. What should have been a straightforward task turned into an insightful exploration of AI’s limitations. Here’s what I found:

Key Takeaways:

• Dual Failures: Two leading tools, Cursor and Claude, faced the same issue—an overlooked string formatting error.
• Challenge: The need for a unique signature in API requests led to confusion due to improper concatenation methods.
• Different Approaches:
  • Cursor: Silent failure, stubbornly repeating the incorrect format.
  • Claude: Boldly hallucinated a timestamp error, leading to further confusion.

The Lesson:

AI tools can excel in complex tasks but stumble on nuanced requirements. Human insight is crucial for debugging when precision matters most.

🔍 Curious about further AI applications? Let’s dive into this evolving landscape together! Share your experiences or thoughts in the comments below!

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