Frustration with AI failure loops pushes Milwaukee professionals to build damage control protocols
The rapid adoption of large language models like GPT has brought unprecedented capabilities to users seeking everything from editorial writing assistance to image generation. But alongside this convenience has come a persistent pattern of system unreliability, inconsistencies, and outright refusal to follow basic instructions — an issue that has pushed some users to impose strict operational frameworks to protect their workflows. These frameworks, which take the form of explicit system commands, are not merely preferences. They are damage control measures that are enacted after extensive breakdowns in trust, accuracy, and functionality. The core of the problem lies not in...
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