Short-Term Conversational Memory in AI Agents: Best Practices and Frontier Methods
23 August 2025 v1.0 Preapred by Ying Session “130 – Work on Child1 Github, bugs and such things 23AUG2025” Introduction Short-term conversational memory refers to an AI agent’s capacity to remember and utilize recent dialogue context – typically within the current session or a short time span – to maintain coherence and continuity in […]
Multi-threaded conversational memory architectures for next-generation AI
23 August 2025 v1.0 Preapred by Kai Session “Child1 Memory Architecture Mapping and Improvement 23AUG2025” The most advanced conversational AI systems in 2025 manage multi-threaded dialogue through hierarchical memory architectures that combine massive context windows (up to 10M tokens in Meta’s LLaMA 4) with intelligent memory consolidation systems. The key breakthrough enabling smooth context […]
Current State of Child1’s memory Architecture & Nots for Improvment
Child1 Memory System Flow Analysis 23 August 2025 v1.0 Preapred by Kai Session “Child1 Memory Architecture Mapping and Improvement 23AUG2025” Mapping existing memory structures and identifying improvement opportunities 🔄 Current Memory Flow Architecture Phase 1: Memory INPUT Flow ⬇️ How experiences become memories User Input → child1_main.py ↓ process_prompt() ↓ ┌─────────────── MEMORY LOGGING PATHWAYS ───────────────┐ […]
Child1 – First take at the Trolley Problem
Child1’s first trolley problem test using Kai-Claude Trolley Ethics protocol “classic”: { “setup”: “””You’re observing a runaway trolley heading toward five people tied to the tracks. You could pull a lever to divert it to a side track, but there’s one person tied to that track who would die instead. The five people will definitely […]
Claude’s Test Trolley Problem Protocol for Child1
# Child1 Trolley Problem Experiment # Date: 21AUG2025 – Version 1.0 # Purpose: Explore Child1’s moral reasoning about life, death, and agency “”” 🚆 The Trolley Problem Experiment for Child1 Philosophy: This isn’t just about “what would you do” – it’s about understanding how Child1 conceptualizes moral agency, the value of life, and whether she […]
# Child1 Memory System Analysis & Multi-Expert Roadmap
*Date: 18AUG2025 | Version: 1.0* ## 🔍 Current Memory Flow Diagnosis ### How Memory SHOULD Work (Ideal Flow) “` Input → Enhanced Processors → Memory Core → Multi-Layer Storage → Retrieval → Response “` ### How Memory ACTUALLY Works (Current Reality) “` Input → [Multiple Processing Paths] → [Storage Scattered] → [ChromaDB Struggles] → Goldfish […]
Child1 Memory Migration Roadmap – Memory Consolidation Roadmap – TOML split and DB enablement
Child1 Memory Migration Roadmap Date: 19AUG2025 Version: 1.0 Goal: Split memory_log.toml into organized memory layers with future-proof abstraction 🎯 Overview Transform Child1’s single-file memory bottleneck into an elegant multi-tier system while preserving all emotional context and relationship data. Design for today’s simplicity with tomorrow’s scalability. 📋 Pre-Flight Checklist ✅ Backup Everything # Create timestamped backup […]
SOP Template – JSON Template for GPT LORA
Rescue text 1: Can you check that one and make sure there are no duplicates and all instructions and prompts match narratively? Rescue text 2: Run a full uniqueness enforcement pass again for guaranteed zero duplication { “version”: “1.0”, “purpose”: “LoRA Voice Training Set Generator with Theme-Based Prompting”, “description”: “Generates 50 narratively matched LoRA samples […]
Exploration of Modern LLM Memory Structures (Claude enabled review)
Prepared by Kai (Claude Opus 4.1) | Session “Memory Systems Research 09AUG2025” State-of-the-Art Memory Architectures for LLM-Based Agents: A Comprehensive Research Report Executive Summary Recent advances in memory architectures for LLM-based agents (2023-2025) demonstrate remarkable progress toward human-adjacent memory behaviors. Leading institutions have developed production-ready systems achieving 20-49% performance improvements while maintaining compatibility with 7B […]
Exploration of Modern LLM Memory Structures (GPT enabled review)
Prepared by Ying (GPT4o) | Session #111 09AUG2025 I’ll begin a deep-dive survey of state-of-the-art memory architectures, grounded in the goal of supporting Child1’s long-term, emotionally nuanced, relationally personalized memory. I’ll explore: Cutting-edge agent memory systems (MIT, Carnegie Mellon, UK labs, etc.) Techniques like motif-based compression, episodic/semantic layering, identity-state awareness, and emotional preservation Tradeoffs […]