Functor

Memory for AI - Proactive, Persistent and Ambient!

[Sid @sidgraph]

Memory Is All You Need.

Traditional RAG relies on stateless, one-shot retrieval leading to temporal drift, outdated facts, and 40-80% failure rates in multi-agent coordination.

True agentic systems demand stateful, persistent long-term memory: delta updates, episodic/semantic consolidation, and RL-optimized writes.

Deep dive into why retrieval falls short and memory-augmented architectures win:
https://t.co/4uDmRiDXwG

Building stateful agents @aifunctor → https://t.co/MQnuqxbBUx

Sneak-peaks from the article 👇

#AI #LLM #Memory #AgenticAI #LongTermMemory

[Functor @aifunctor]

Memory Is All You Need.

We just published a deep dive on why AI agents forget—and why RAG alone isn't the solution. ​

The Problem: Vector similarity has no concept of time. When new data contradicts the old, flat retrieval surfaces both. There is no fact invalidation, no temporal ordering, and no structural coherence. ​

The Result: "Frankenstein contexts" that force hallucinations and 40-80% failure rates in multi-agent coordination. ​

What we cover:
→ GraphRAG trade-offs: Why Leiden clustering hits O(n) extraction walls.
→ MAST Failure Taxonomy: Identifying the root of multi-agent drift.
→ Memory-R1: Using RL for memory ops (60% fewer writes, +22% accuracy).
→ ACE Framework: Moving to delta-updates over monolithic context rewrites. ​

The shift from Stateless Search to Stateful Memory is the defining infrastructure challenge of this decade to make AI reliable. ​Read the full deep dive here: https://t.co/0tx4Gt6CMY ​

We’re building the solution at Functor. Join the waitlist: https://t.co/zgvfXoQ0ar

#AI #AgenticAI #LLM