🤖 AI Summary
After two years of using AI for coding tasks, a developer has returned to traditional hand coding due to frustrations with the limitations of AI models. Initially impressed by AI's ability to assist with increasingly complex tasks, the developer soon encountered issues with inaccurate outputs and a dependency on overly precise specifications. This disillusionment revealed that while AI can generate seemingly sound code, it often lacks coherence and structural integrity when viewed in the context of the entire codebase, leading to messy and untrustworthy results.
The significance of this shift highlights a critical reflection within the AI/ML community on the reliability of AI-generated code. Many developers have faced similar challenges, recognizing that AI agents tend to produce solutions that fail to align with broader design goals. The author concluded that traditional hand coding not only proved to be more efficient and creative but also carried a higher assurance of quality and user trust. This return to manual coding emphasizes the ongoing need for human oversight in software development, especially when delivering products that require high levels of accuracy and reliability.
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