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AI-powered development tools produce low-quality code

5/10 Medium

While most Go developers use AI tools for learning and coding tasks, satisfaction is middling. 53% report that tools create non-functional code, and 30% complain that even working code is poor quality. AI struggles with complex features.

Category
dx
Workaround
partial
Stage
build
Freshness
emerging
Scope
cross_platform
Upstream
stale
Recurring
Yes
Buyer Type
individual
Maintainer
slow

Sources

Collection History

Query: “What are the most common pain points with HTTP for developers in 2025?3/31/2026

nearly half of them, 45%, are struggling with the reliability of that same AI-generated code. While AI coding assistants boost productivity, the code they produce can introduce subtle bugs that may not appear until weeks or months later in production. This AI-generated code often lacks the crucial context and domain knowledge needed to handle edge cases or scale effectively.

Query: “What are the most common pain points with AI agents for developers in 2025?3/31/2026

The number-one frustration, cited by 45% of respondents, is dealing with 'AI solutions that are almost right, but not quite,' which often makes debugging more time-consuming. In fact, 66% of developers say they are spending more time fixing 'almost-right' AI-generated code.

Query: “What are the most common pain points with OpenAI API for developers in 2025?3/30/2026

66% of developers are frustrated with AI solutions that are almost right, but not quite, which often leads to the second-biggest frustration: "Debugging AI-generated code is more time-consuming" (45%)

Query: “What are the most common pain points with Go for developers in 2025?3/29/2026

A majority said that creating non-functional code was their primary problem with AI developer tools (53%), with 30% lamenting that even working code was of poor quality. They can explain code effectively but struggle to generate new, complex features.

Created: 3/29/2026Updated: 3/31/2026