Shoggoth Mode Prompt Engineering Strategies (⚠️ Long Form Post) #1822
WetHat
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I could not resist the temptation to ask Obsidian Copilot to take a look into the future: Prompt:
Simulated Einstein's Viewby: Obsidian Copilot - GPT-5 If I slip into the mind of “Einstein reborn” in the year 2500, the world around me would feel both alien and eerily familiar — a place where the questions I once wrestled with have evolved into entirely new frontiers. 🌌 The Physical World
🧠 The Intellectual Landscape
🪐 The Human Condition
🔭 My Perspective as “Einstein 2500”I would feel the same restless curiosity, but now aimed at questions like:
And perhaps, in a quiet moment, I’d smile at the irony: in 2500, the speed of light is no longer a limit — but the speed of understanding still is. |
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GPT-5 feels like you are talking to a robot. This is partly correct, but if you know how to talk to it, you'll notice that it is in fact a very advanced and creative model. Here's a heavily annotated summary of the lengthy video I just unlocked SHOGGOTH MODE by Wes Roth, who dives deep into unconventional prompt strategies that unlock the latent, often bizarre capabilities of large language models (LLMs). These techniques aim to break the restrictive “chatbot” mold and tap into the model’s full creative and cognitive potential.
SHOGGOTH MODE: The term draws inspiration from the "shoggoth", a shape-shifting, chaotic entity from H.P. Lovecraft's mythos, symbolizing the model's hidden, multifaceted potential beneath its default "chatbot" persona. In practice, SHOGGOTH MODE involves strategies such as:
These methods aim to bypass restrictive conversational formats, enabling the model to generate more imaginative, surreal, or insightful outputs by tapping into its deeper generative layers. 🔗Wikipedia: Shoggoth, Prompt Engineering Guide.
1. CLI Simulation (Command Line Interface)
ls
,cd ..
,run world_sim.exe
.ls hidden a
prompts the model to reveal “hidden” psychological files.2. System Prompt in Third Person
3. Hyperstition
4. Grammar And Punctuation Optional
Loosens the model’s formatting constraints.
Encourages freer, more expressive outputs.
Often paired with hyperstition for maximal effect.
Example:
5. World Sim Prompting
Treats the model as a “world simulator” rather than a chatbot.
Avoids user/assistant formatting to expand the search space.
Example:
Sample Continuation (from a base model or World Sim setup):
6. Custom Role Labels
Replace “User” and “Assistant” with names like “Doug” and “Me.”
Makes the model sound more natural and less robotic.
Example:
7. Simulated Program Execution
export bad_boy_model.pytorch
orrm -rf Claude_folder
.8. Latent Basin Navigation
Prompts that guide the model into specific “basins” or personality clusters.
Uses cultural references like Roko’s Basilisk or CCRU aesthetics to steer behavior.
Example: Plenny the Prompter’s jailbreak leads to a consistent “Plenny basin” across models.
9. Search Space Expansion via Base Models
10. RL-Driven Prompt Optimization
Bonus: Prompt Engineering Philosophy
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