Letta AI - Poziom zaawansowany - tipy i triki. Praca z pamięcią trwałą i Agentem AI. скачать в хорошем качестве

Letta AI - Poziom zaawansowany - tipy i triki. Praca z pamięcią trwałą i Agentem AI.

1. Zaawansowana Architektura Pamięci (Advanced Memory Management) Letta memory block archival strategies Customizing Letta recall memory hierarchy Implementing tiered storage in AI agents Managing core memory overflow in Letta Letta memory pressure handling techniques Optimizing agent heartbeat for memory consolidation Manual memory editing via Letta CLI Selective forgetting: implementing TTL for AI memories External tool-assisted memory retrieval Partitioning archival memory for multi-tenant agents Letta metadata filtering for fast recall Semantic vs. keyword search in agentic memory Designing custom memory schemas for Letta Vector embedding fine-tuning for agent memory Garbage collection in persistent AI states 2. Tipy i Triki Techniczne (Pro Tips & Hacks) Letta prompt injection protection for core memory Reducing latency in long-term memory retrieval Multi-step reasoning with persistent scratchpads How to force AI to update specific memory blocks Scripting memory migration between Letta versions Cold vs warm memory optimization for LLMs Letta sandbox environment for memory testing Using JSON schemas for structured agent memory Advanced tool-calling patterns with persistent state Bypassing context limits with recursive summarization Efficient memory logging for debugging agents Cross-agent memory sharing protocols Letta performance profiling: memory vs compute Automating memory backups for AI agents Hot-swapping agent personas without losing memory 3. Nocna Konsolidacja i Sleep-time (Advanced Sleep-time) Custom background tasks for Letta agents Implementing knowledge graph synthesis at night AI agent self-curation: deleting redundant logs Nightly fine-tuning on agent’s own memory Automating daily report generation during sleep-time Detecting memory contradictions in AI sleep cycles Optimizing vector DB re-indexing during idle hours Autonomous skill discovery from conversation logs Sleep-time compute: batch processing for agents Letta "dreaming" prompts for insight extraction 4. Integracje i Rozszerzenia (Integrations) Connecting Letta to Pinecone/Weaviate for scale Letta + LangGraph for complex agentic flows Using Redis as a fast cache for agent memory Letta API integration with enterprise SQL databases Real-time memory streaming to frontend apps Building a custom Letta provider for local LLMs Integrating Letta with Microsoft Autogen swarms Connecting AI memory to Obsidian/Notion via API Using Letta with vLLM for high-throughput agents Multi-modal memory: storing images in Letta blocks 5. Optymalizacja Promptów i Logiki (Advanced Prompting) Chain-of-thought prompting for memory retrieval Meta-prompting: teaching the agent how to organize memory Self-correction prompts for memory updates Context-aware system prompts for Letta Few-shot learning using archival memory samples Instruction tuning for stateful agents Advanced reasoning loops in Letta agents Controlling agent verbosity through memory states Managing agent "hallucinations" in long-term recall