quite disappointed with latest chatgpt model and coding

Evaluating Recent Challenges with ChatGPT’s Performance in Coding and Problem Solving

As an experienced user of ChatGPT spanning several years, I have relied on this AI language model primarily for research, technical advice, and software development tasks. Over time, I have seen ChatGPT evolve and assist in creating scripts and developing complex applications. However, recent experiences have raised concerns about its current reliability and effectiveness when tackling programming problems.

One persistent issue I’ve noticed is that ChatGPT tends to generate solutions that are unexpectedly complex and sometimes disorganized for problems that should be straightforward. This often results in a significant investment of time—sometimes exceeding an hour—to identify issues, iterate on solutions, and resolve inconsistencies. Such inefficiencies hinder productivity and diminish confidence in the tool’s problem-solving capabilities.

By contrast, other AI solutions like Gemini appear to approach similar problems with greater clarity and conciseness. They typically produce clean, effective solutions with minimal iterations, as if guided by an experienced developer who knows precisely what is necessary. This stark difference suggests that ChatGPT’s recent outputs may be overcomplicated or less streamlined than before.

This leads to a broader question: Is this behavior an inherent aspect of ChatGPT’s current design, or could it be a matter of optimizing prompting strategies? Alternatively, might there be underlying changes in the model’s training or deployment that influence its problem-solving style?

In conclusion, while ChatGPT remains a valuable resource, its evolving performance in coding and technical contexts warrants critical assessment. Users should consider how they formulate prompts and set expectations, as well as explore complementary tools for more efficient development workflows. Continuous feedback on AI behavior is essential for improving these models and ensuring they serve developers effectively in their evolving needs.