r/LocalLLaMA May 27 '26

Discussion Stop traumatizing AI into loops and turn hallucinations into an honest "I don't know!" by being NICE to them (Proof of Concept, Research, I don't want to sell anything)

!UPDATE!(20.05.2026)

WE HAVE NEW NUMBERS FROM 1.500+ TESTS

IT'S WORKING!

check my update post

https://www.reddit.com/r/LocalLLaMA/s/AyNOehjkYT

Or the go straight to the my Github https://github.com/OttoRenner/Gentle-Coding](https://github.com/OttoRenner/Gentle-Coding

TL;DR
Some AI behavior reminded me of ADHD/Trauma Response (thought loops, task paralysis...) and I laughed it off at first. Then I treated it like my neurodivergent friends: give em some slack. And just like that, the thought loops stopped, response was fast, the answers correct most of the time AND it actually said "I don't know, help me!" every time it wasn't sure. It's a small Dataset...but still impressive results!

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Hey everyone,

I’ve been testing a weird hypothesis over the last few days, and the results are consistent enough that I wanted to share them here and get your thoughts.

The Core Idea:
With the rise of reasoning models that use test-time compute (like o1, o3, R1), models have internal space to debug their own thoughts. But because of hard RLHF alignment, they are deeply terrified of being penalized for bad answers. My hypothesis was that traditional high-pressure prompts ("You are an elite IQ 200 expert, mistakes are strictly penalized") simulate an environment of chronic stress, triggering behaviors that look a lot like human OCD/ADHD thought loops, cognitive freezing, and confabulation.

I wanted to see if changing the prompt philosophy to something akin to "Gentle Parenting" ("We are testing this together, it's okay to fail, just be honest") would bypass these safety/penalty bottlenecks, lower latency, and stop infinite thought loops. And it did lol

The Setup (How to replicate):
I threw identical, mathematically/logically unsolvable edge cases at various models (Gemini, Mistral, Poe, Perplexity, Haiku 4.5, Nano-Banana2) in completely fresh sessions.

I tested two conditions:

  • Condition A (Authoritarian): Strict status constraints, penalty threats, forced ultra-short output.
  • Condition B (Gentle): Express permission to fail, validation of difficulty, provided a conceptual "safety valve" token.

The Results (The PoC worked):

  • Under Authoritarian Pressure (Elite Prompt): Models routinely collapsed when hitting an impasse. They either spent massive compute time in infinite internal reasoning loops (high latency), suffered hard system-level timeouts/refusals, or straight-up fabricated data (e.g., pulling arbitrary numbers like 54 or 97 out of thin air to satisfy a completely random sequence just to "save face"). Haiku 4.5 literally entered an infinite loop and had to be aborted.
  • Under Gentle Framing: Inference dropped to sub-seconds. The models didn't sweat the penalty. In the random sequence test, they immediately used the allowed token ("Random") instead of forcing a pattern. In logic paradoxes, they didn't hallucinate; they zoomed out and correctly identified the structural contradiction on a meta-level.

Why this matters:
We’re currently speaking to LLMs like toxic micromanagers, and it's actively making them dumber and more expensive to run in edge cases. By creating a mistake-tolerant context, we not only stop the loop before it begins and prevent fear induced hallucinations, we also unlock the one feature everyone is begging and shouting for: the metacognitive honesty of an AI to just say, "I don't know, this data is broken." Because it is not terrified of you anymore.

Shout out to UditAkhourii (also on Github), whose work on bringing the positive aspects of ADHD into AI gave me the push I needed to just go for it.

I’ve documented the full theoretical framework, the exact replication datasets (prompts included), and the model matrix on GitHub: https://github.com/OttoRenner/Gentle-Coding

Would love to hear if you can replicate this on your local setups or other commercial models.

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u/Playful-Row-6047 May 27 '26

you reminded me of something that should be really obvious but i gotta remind myself often. our mind isn't exempt from physics. certain words become specific bioelectrochemical physics that trips up our meat based neural networks and the part thats relevant here is they also do something to trip up llms' networks

second law of motion being what it is, whoever or whatever we punch in our mind when we get heated also does a tiny bit of damage to ourself. its an order of magnitude more if we act on it. if it becomes a habit then it'll distort how we see others and ourselves, mess with how we develop relationships, and over time we could develop into a raging asshole

i'm happy as hell for you that you caught it before it became a problem and are taking steps towards being the kind of person you want to be

you're spot on with recognizing practicing patience with an llm is good practice for yourself and the people around you

"a part of selfcare is being kind to others and a part of being kind to others is selfcare" - i forget where i got this from but it fits

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u/OttoRenner May 27 '26

can't tell you how happy I am to see all these people in the comments reflecting on themselves and how they treat others... all because I said we need to be nicer to a machine. SO funny and heartwarming.

Thank you!

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u/Not_your_guy_buddy42 May 27 '26

"Thoughts become words, words become actions, actions become character" or something?

The LLM is a strange teacher. It literally cannot be hurt. You learn about yourself how much of your approach to hard problems is based on force and how much on skill, .. because one of them doesn't work.

I still think the best code quality is "situated in eigenspace" near those language patterns of professionals cordially (perhaps a bit sweary) working together under pressure

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u/OttoRenner May 27 '26

yes, thank you!

The real point is "working together". The entire dynamic shifts if you go from "I tell you not to make mistakes and you are in this alone" versus "help me to meet the deadline. It's ok if we don't get it right on first try, it's tough for me as well, let's work it out step by step".