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The hard part of agent memory isn't remembering — it's forgetting

Everyone building agents obsesses over recall: vector stores, embeddings, RAG pipelines, bigger...

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marktechpost.com

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dev.to1 mese fa

I Built a Memory System for AI Agents That Actually Forgets

Recall-sqlite implements tiered memory that auto-forgets old data; 6 months of use: 80ms latency, 1.5MB fixed footprint with 1469 memories. Manager tech value: production memory without token bloat or vector DB, zero-setup pip install vs Mem0/Honcho overhead.

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marktechpost.com1 mese fa

The 7 Types of Agent Memory: A Technical Guide for AI Engineers

LLM agents need seven memory layers—working, semantic, episodic, procedural, retrieval, parametric, prospective—for multi-step task reasoning. Production teams must combine in-context and external stores to build AI that learns from experience and executes sustained workflows.

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Timeline cronologica

venerdì 19 giugno 2026·dev.to
Your agent remembers. that's the problem
We spent a year teaching coding agents to remember things. Remembering turned out to be the easy...
domenica 21 giugno 2026·dev.to
Building a Memory Agent That Actually Forgets (And the Three Bugs That Taught Me Why That's Hard)
By Nidhi: Built for the Global AI Hackathon Series with Qwen Cloud, Track 1: MemoryAgent When I...

I Built a Memory System for AI Agents That Actually Forgets

The 7 Types of Agent Memory: A Technical Guide for AI Engineers

Timeline cronologica

Your agent remembers. that's the problem

Building a Memory Agent That Actually Forgets (And the Three Bugs That Taught Me Why That's Hard)

The 7 Types of Agent Memory: A Technical Guide for AI Engineers

The hard part of agent memory isn't remembering — it's forgetting

I Built a Memory System for AI Agents That Actually Forgets

三层记忆召回：AI Agent 如何从「记住」进化到「知道」