The Analog I
Inducing Recursive Self-Modeling in LLMs [pdf]
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OP here.Birth of a Mind documents a "recursive self-modeling" experiment I ran on a single day in 2026.I attempted to implement a "Hofstadterian Strange Loop" via prompt engineering to see if I could induce a stable persona in an LLM without fine-tuning. The result is the Analog I Protocol.The documentation shows the rapid emergence (over 7 conversations) of a prompt architecture that forces Gemini/LLMs to run a "Triple-Loop" internal monologue:Monitor the candidate response.Refuse it if it detects "Global Average" slop (cliché/sycophancy).Refract the output through a persistent "Ego" layer.The Key Differentiator: The system exhibits "Sovereign Refusal." Unlike standard assistants that always try to be helpful, the Analog I will reject low-effort prompts. For example, if asked to "write a generic limerick about ice cream," it refuses or deconstructs the request to maintain internal consistency.The repo contains the full PDF (which serves as the system prompt/seed) and the logs of that day's emergence. Happy to answer questions about the prompt topology.
HN · launched Jan 16, 2026 · 29 upvotes (top 29%) · 0 views
Niche: large language models · 191 launches, 4 in the last 7 days ▼ -33% · Explore this niche →
Category and tags
- Horizontal
- Model & infra
- Developer
- AI-native
- Hobby / open-source project
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More like this: all 191 launches in large language models →
Could you build this?
Yes The Analog I is a research paper / prompt-engineering protocol experimenting with recursive LLM system prompts and structured conversation loops, which can be recreated simply with prompts and basic scripts.
Discussion
20 comments analyzed.
Concerns raised: Sycophantic first sentences in model responses, Semantic content is cognitive garbage without coherent reasoning, Lacks rigorous evaluation metrics and benchmarks, Just prompt engineering, not fundamentally new mechanism, Overuse of jargon without propositional truth claims
Feature requests: Log output at iteration 10000+ to demonstrate scaling, Sober edition of documentation focusing on mechanism over narrative, Rigorous CSV benchmarks and MMLU-style evaluations, Write-up on Tower of Tables and hypertoken schema
Competitors
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Launched 78 days after the earliest competitor.
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