Imagine a world where AI not only writes code but also double-checks its work for security flaws. That's the promise of a new framework called INDICT, which stands for Internal Dialogues of Critiques. Researchers have found that large language models (LLMs), while impressive at generating code, can sometimes produce insecure outputs or even be tricked into writing malicious code. INDICT addresses this by creating a system of AI critics that analyze code for both safety and helpfulness. These critics aren’t just passive observers. They engage in a dynamic dialogue, challenging each other's assessments and using external resources like web searches and code interpreters to back up their arguments. This process helps the LLM refine its code, making it more robust and secure. Think of it like a team of expert code reviewers working together to ensure the highest quality. What sets INDICT apart is its proactive approach. It examines code during both the initial generation phase and after execution, providing preemptive and post-hoc feedback. This two-stage process is crucial for preventing potentially harmful actions. The research shows promising results. Across various coding tasks and programming languages, INDICT consistently improved the safety and helpfulness of LLM-generated code. For example, in tests involving security attacks, INDICT significantly increased the percentage of benign or harmless outputs. This suggests that AI critics can play a vital role in making LLMs more reliable and responsible code generators. While INDICT shows great potential, there are still challenges to overcome. The framework currently relies heavily on well-crafted prompts to guide the AI critics. Additionally, it's computationally more expensive than simply generating code without these extra checks. However, the researchers believe the added safety benefits outweigh the costs, especially for sensitive applications. INDICT is not just limited to code generation. It could also be applied to other AI domains, helping to create more responsible and secure AI systems overall.