Category: Building Jarvis
Open research notes on building Jarvis — a persistent, self-improving AI agent. One paper at a time.
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SALIENCE: The Death of Fixed Thresholds, the Pyramid of Significance, and Cheap Traversal as the Basis of Next-Generation Vibe Programming
Relevance must be re-computed from the live situation — not read off a frozen list. SALIENCE argues for three pillars: kill fixed thresholds, order knowledge as…
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Instant Recall: A Pre-Computed Concept Index for O(1) Memory Retrieval in Persistent AI Agents
Your agent has the answer in its memory and still can’t find it; Instant Recall builds an offline concept index so retrieval is a constant-time lookup…
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Fractal Reasoning: Multi-Resolution Memory and Self-Similar Metacognition for LLM Agents
Your agent’s memory is flat — one zoom level — so it fetches a fact or a gist, never both; Fractal Reasoning indexes memory and structures…
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Identity Persistence: Keeping an LLM Agent’s Personality Stable Across Sessions, Model Swaps, and Restarts
Your agent keeps every fact and still stops sounding like itself — Identity Persistence pins the persona every turn, compacts the task without flattening the voice,…
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Sleep Consolidation: How Nightly Prompting Makes a Stateless Agent Get Better Over Time
A stateless AI agent that gets 79% fewer incidents over 30 days — not by fine-tuning, but by a nightly loop that rewrites its own operating…
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Round Table: Exploiting Cognitive Diversity as a Computational Resource in Persistent AI Agents
Stop asking which model is best and picking one — Round Table puts Claude, GPT, and Gemini at the same table, casts each to the role…
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The Wondering Machine: Giving an LLM the Drive to Learn on Its Own
LLMs answer brilliantly but never wonder — they can’t spot their own knowledge gaps or learn after training. The Wondering Machine is a blueprint for an…
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Humor Embeddings: Laughter from Inverted Memory — Bisociation in Computational Embedding Space
Memory retrieves what’s nearest to a query; humor searches for what’s at the right distance and can still be joined by an unexpectedly valid bridge —…
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HIVEMIND: Role-Bound Agent Swarms for Enterprise Continuity
Role-bound agents — one shared AI agent per job function that outlives the people who use it — so a company’s institutional knowledge never walks out…
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Learned Intuition: A Reflex Layer That Stops Your Agent Before It Does the Wrong Thing
Your agent had all the context it needed and still did the wrong thing — AMYGDALA gives it a learned reflex layer that pauses dangerous actions…