Recently, two engineers involved in the OpenClaw project issued a warning, pointing out that humans are generating a large amount of low-quality code, which may even pose safety hazards. Although AI shows some advantages in handling simple programming tasks, the root of the problem is not the tools themselves, but the excessive reliance of developers on them.

As more and more developers get used to using AI tools, many people directly publish the generated results without carefully reviewing them based on vague prompts. In such cases, the generated code may seem fully functional on the surface, but its underlying structure is often very messy. Such code is not only more prone to errors, but also has lower running efficiency, consuming much more computing power, memory, and bandwidth than traditional code.

The engineers warned that the potential risks of this low-quality code are not only in functional errors, but also in the rising computational costs, which could lead to significant financial pressure for startups. Therefore, developers should be more cautious when using AI tools, should not completely rely on these technologies, but should conduct strict reviews and tests after generating the code to ensure its quality and safety.

Key Points:

🌟 The quality of AI-generated code varies greatly and may cause safety hazards.

🛠️ Over-reliance on AI tools is the root of the problem.

💰 Poor-quality code may bring significant financial pressure to startups.