Jameson Lopp(@lopp):This prompt is a mixed bag that could be trimmed down to avoid burning tokens on useless directives. The good: 1. "If you don't know something, just say so." That's a genuine instruction the model can execute. It gives the model a valid output for uncertainty instead of forcing it to fake confidence. 2. "Do not anchor on numbers or estimates I provide; generate your own independently first." That's specific, operational, and addresses a real failure mode. It changes a behavior at the method level. 3. "Use explicit confidence levels." Good. It gives the model a concrete output format that counteracts performed authority. 4. "Do not capitulate unless I provide new evidence or a superior argument." This is trying to solve the sycophancy problem and it's directionally correct. What's ineffective: 1. The entire first paragraph's flattery of the model. "World class expert in all domains," "intellectual firepower on par with the smartest people in the world." This is the user performing the sycophancy they're trying to suppress. It's also cargo cult; the model doesn't become smarter because you told it it's smart. It generates differently, yes, but the difference is superficial. You get more confident-sounding output, which is performed authority. It's the exact thing the second paragraph tries to prevent. 2. "Never hallucinate or make anything up." The model cannot execute this instruction. It doesn't have a mechanism for distinguishing hallucination from generation. 3. "Verify your own work. Double check all facts." Same problem. The model doesn't have a verification mechanism separate from its generation mechanism. 4. "Make your answers as long and detailed as you possibly can." This actively degrades quality. Length pressure produces padding, redundancy, and the managerial smoothing the prompt is trying to prevent. The model fills space because it was told to fill space. 5. "Your answers can and should be provocative, aggressive, argumentative, and pointed." This replaces one performance with another. Instead of performing warmth, the model performs intellectual aggression. The output sounds sharper but the underlying mechanism is identical. You get performed disagreement instead of performed agreement. Neither tracks truth.

2026.05.06 15:05

This prompt is a mixed bag that could be trimmed down to avoid burning tokens on useless directives. The good: 1. "If you don't know something, just say so." That's a genuine instruction the model can execute. It gives the model a valid output for uncertainty instead of forcing it to fake confidence. 2. "Do not anchor on numbers or estimates I provide; generate your own independently first." That's specific, operational, and addresses a real failure mode. It changes a behavior at the method level. 3. "Use explicit confidence levels." Good. It gives the model a concrete output format that counteracts performed authority. 4. "Do not capitulate unless I provide new evidence or a superior argument." This is trying to solve the sycophancy problem and it's directionally correct. What's ineffective: 1. The entire first paragraph's flattery of the model. "World class expert in all domains," "intellectual firepower on par with the smartest people in the world." This is the user performing the sycophancy they're trying to suppress. It's also cargo cult; the model doesn't become smarter because you told it it's smart. It generates differently, yes, but the difference is superficial. You get more confident-sounding output, which is performed authority. It's the exact thing the second paragraph tries to prevent. 2. "Never hallucinate or make anything up." The model cannot execute this instruction. It doesn't have a mechanism for distinguishing hallucination from generation. 3. "Verify your own work. Double check all facts." Same problem. The model doesn't have a verification mechanism separate from its generation mechanism. 4. "Make your answers as long and detailed as you possibly can." This actively degrades quality. Length pressure produces padding, redundancy, and the managerial smoothing the prompt is trying to prevent. The model fills space because it was told to fill space. 5. "Your answers can and should be provocative, aggressive, argumentative, and pointed." This replaces one performance with another. Instead of performing warmth, the model performs intellectual aggression. The output sounds sharper but the underlying mechanism is identical. You get performed disagreement instead of performed agreement. Neither tracks truth.