Why AI coding agents aren’t production-ready: Brittle context windows, broken refactors, missing operational awareness

Remember this Quora comment (which also became a meme)?

(Source: Quora)

In the pre-large language model (LLM) Stack Overflow era, the challenge was discerning which code snippets to adopt and adapt effectively. Now, while generating code has become trivially easy, the more profound challenge lies in reliably identifying and integrating high-quality, enterprise-grade code into production environments.

This article will examine the practical pitfalls and limitations observed when engineers use modern coding agents for real enterprise work, addressing the more complex issues around integration, scalability, accessibility, evolving security practices, data privacy and maintainability in live operational settings. We hope to balance out the hype and provide a more technically-grounded view of the capabilities of AI coding agents.

Limited domain understanding and service limits

AI agents struggle significantly with designing scalable systems due to the sheer explosion of choices and a critical lack of enterprise-specific context. To describe the problem in broad ...