The 80% of agent development nobody demos — and how we solved it
Posted by Intelligent_Hand_196@reddit | LocalLLaMA | View on Reddit | 2 comments
Everyone shows the agent making decisions. Nobody shows what happens when it forgets everything on session restart.
AIBrain is the persistent memory layer for any AI agent framework (LangChain, LlamaIndex, CrewAI, raw API calls). Dual-system memory — fast episodic for recent context, slow semantic for long-term learning. Nightly consolidation (we call it "dream mode") compresses and strengthens key memories.
Local-first. Your data never leaves your machine.
audioen@reddit
What is the name of this LLM that writes this 'blablabla that nobody does' stuff. It is insultingly and laughably false for in all the claims being made, and there's like 5 of these posts here every day containing these same sentences in roughly the same order.
Intelligent_Hand_196@reddit (OP)
I guess if it’s all blah blah blah blah to you then maybe you don’t use it…. But I do and it’s not laughably false it’s what I’m running my agents on and using to produce results I’m not seeing anywhere else I agree though that there are many false claims being made in the realm of agentic memory Atm but I have plenty of science backed research powering what I’m doing on the backend, https//:arxiv.org/pdf/2604.02431 is the paper I wrote on selective routing for information retrieval that showed my model out scores every other model that’s ever tested on the known benchmarks one of those being contriever which was the Meta teams information retrieval system… but is the post doesnt make sense to you then the paper certainly won’t either… I wish the best for you in all your endeavours and hope you find value in the information.