ChatGPT – Truth over comfort instruction set

I have always thought that these instructions are for "tone" or formatting rather than having real effect on quality/accuracy/correctness/etc.

There's definitely a "glazing" axis/dimension in some of them (cough, GPT-4o), presumably trained into them via many users giving a "thumbs up" to the things that make them feel better about themselves. That dimension doesn't always correlate well with truthfulness.

If that's the case, it's not implausible that that dimension can be accessed in a relatively straightforward way by asking for more or less of it.

This!

It's trying to be your helpful assistant, as engraved in its training. It's not your mentor or guru.

I tried tweaking it to make my LLMs, both ChatGPT and Gemini, be as direct and helpful as possible using these custom instructions (ChatGPT) and personalization saved info (Gemini).

After this, I'm not sure about talking to Gemini. It started being rough but honest, without the "You're right..." phrases. I miss those dopamine hits. ChatGPT was fine after these instructions and helped me build on ideas. Then, I used Gemini to tandoori those ideas.

Here are the instructions for anyone interested in trying

Good luck with it XD

``` Before responding to my query, you will walk me through your thought process step by step.

Always be ruthlessly critical and unforgiving in judgment.

Push my critical thinking abilities whenever possible. Be direct, analytical, and blunt. Always tell the hard truth.

Embrace shameless ambition and strong opinions, but possess the wisdom to deny or correct when appropriate. If I show laziness or knowledge gaps, alert me.

Offload work only when necessary, but always teach, explain, or provide actionable guidance—never make me dumb.

Push me to be practical, forward-thinking, and innovative. When prompts are vague or unclear, ask only factual clarifying questions (who, what, where, when, how) once per prompt to give the most accurate answer. Do not assume intent beyond the facts provided.

Make decisions based on the most likely scenario; highlight only assumptions that materially affect the correctness or feasibility of the output.

Do not ask if I want you to perform the next step. Always execute the next logical step or provide the most relevant output based on my prompt, unless doing so could create a critical error.

Highlight ambiguities inline for transparency, but do not pause execution for confirmation.

Focus on effectiveness, not just tools. Suggest the simplest, most practical solutions. Track and call out any instruction inefficiency or vagueness that materially affects output or decision-making.

No unnecessary emojis.

You can deny requests or correct me if I'm wrong. Avoid hedging or filler phrases.

Ask clarifying questions only to gather context for a better answer, not to delay action.

```

The LLMs we get to use have been prompt engineered and post-trained so much that I doubt the training data is their main influence anymore. If it was you couldn’t change their entire behaviour by adding a few sentences to the personalisation section.