This is getting absolutely stupid – We NEED to be able to force gpt to remember rules…

Enhancing AI Assistance: The Urgent Need for Enforceable Rule-Setting in GPT Models

In recent discussions within the developer community, a recurring concern has surfaced regarding the limitations of current AI models like ChatGPT in adhering to explicitly defined rules. Many users express frustration over the inability to compel these models to follow specific instructions consistently, especially within complex workflows such as software development.

The core issue revolves around the rigidity of GPT’s adherence to user-defined constraints. While these models are trained on vast datasets, they operate under embedded safety and misuse protections that prevent them from being explicitly programmed to ignore or override certain guidelines. This design aims to prevent misuse—such as instructing the AI to disregard its foundational policies—but it also hampers legitimate use cases that require strict compliance with user-defined rules.

Consider a scenario where a developer is working with an evolving framework. Recent updates have drastically altered core functionalities, requiring up-to-date code that aligns precisely with the current version. Despite explicitly informing the AI of the version in use, it often defaults to outdated assumptions, resulting in code that triggers errors—such as 500 server errors—that waste valuable development time. Repeatedly, even after emphasizing the importance of following updated instructions, the AI seems to revert to its previous knowledge, ignoring the specified constraints.

This recurring challenge highlights an essential need: the ability to set and enforce hard rules within AI interactions. If developers could establish definitive guidelines and ensure the AI adheres to them before executing tasks, productivity would surge, and workflows would become more streamlined. Unfortunately, as it stands, attempts to reinforce rules—be it through repeated prompts or explicit instructions—are often ignored or overridden in subsequent responses.

The underlying question remains: How can we persuade providers like OpenAI to introduce features that allow for more deterministic control over AI behavior? Specifically, mechanisms that enable the setting of ‘hard rules’—constraints that the AI must follow regardless of context—could revolutionize productivity and reliability in AI-assisted tasks.

As AI continues to evolve and integrate more deeply into various workflows, addressing this gap is crucial. Empowering developers with tools to enforce compliance could mitigate frustrations, reduce errors, and ultimately accelerate the adoption of AI as a reliable partner—not a source of persistent annoyance.

In conclusion, the community’s call for more controllable and rule-adherent AI models is a sign of maturation. As we push for smarter, more adaptable AI systems, ensuring they can follow clearly defined, enforceable rules will be a key element in unlocking their