"There is a plague in software development as of today, and it has become something we are gradually beginning to accept. It goes something like this: you're stuck on some code, so you deliver a code snippet to your favorite AI tool, hoping to debug it. You might get a solution, but then your AI tool introduces a new bug, which you suddenly have to spend time debugging."
"Think of your conversation as an article that is read from the beginning every single time you send a new message. To figure out what to say next, the AI looks at everything you must have discussed so far. The context window is the maximum length of the article that the AI can read at one time. This is relevant depending on the length of the conversation you're having:"
"The truth is, if you vibe code, you will probably end up fixing more bugs than you would if you self-code. I've seen it firsthand: In this article, we will help developers recognize that AI coding tools could create more problems than they solve when used carelessly, and provide practical strategies to work with AI more effectively. The real problem: AI's finite context window"
AI-assisted debugging often produces new bugs when developers paste code into tools and accept suggestions without full verification. Relying on AI output rather than writing code oneself commonly results in more time spent fixing AI-introduced errors. Developer trust in AI accuracy dropped from 43% in 2024 to 33% in 2025, driven largely by AI failures to maintain context. AI models operate with a finite context window and process each new message by rereading the conversation up to that limit. Long or complex code interactions can exceed that window, causing the model to lose relevant information and produce incorrect or inconsistent responses.
Read at LogRocket Blog
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