Expired50% confidenceOpinionExact time
For complex applications requiring databases, network communication, or multi-file architectures, AI currently still struggles to generate complete, ready-to-use code in one shot, and typically requires human intervention for debugging and integration.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
7/2/2026
First Seen
This claim has expired. It is kept for the record and no longer describes the current state.
Valid until: 9/30/2026(expired)
Sources
Five AI Models Tested for Game Development: Which Is Best for Zero-Experience Coding?
bilibiliso-PHI-a_903/1/2025
Related Claims
UnverifiedAI tends to generate correct but inefficient code, and large-scale data processing scenarios require manual optimization intervention.82% similarUnverifiedAI辅助开发中代码生成变得高效,但环境配置、文件管理等部署细节仍需人工介入80% similarUnverifiedThe vast gap between the surface-level completion and actual usability of large-scale AI-generated code is a core challenge that urgently needs to be addressed in the field of AI-assisted software engineering.79% similarVerifiedThe systemic limitation of current AI code generation tools is that their optimization target is 'making the code run' rather than 'making the code easy to maintain'.78% similarUnverifiedAI-generated code often inadvertently introduces security vulnerabilities such as SQL injection, XSS, and permission bypasses, and the lack of consistent architectural design leads to high long-term maintenance costs.77% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/60459API
curl https://kongchang.com/api/v1/knowledge/claims/60459MCP
get_claim(id=60459)