Where an agent loop runs, how it fails, and how to make a session durable

<!-- SC_OFF --><div class="md"><p>Testing agent systems by feeding real natural-language prompts into real runtimes, then scoring whether the correct tool was invoked. No mocks,

<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1s439q8/why_does_my_agent_keep_asking_the_same_question/"> <img alt="Why does my agent keep asking the same

<!-- SC_OFF --><div class="md"><p>If you run persistent LLM agents that coordinate across tmux sessions, this one's worth knowing.</p> <p>I dispatch tasks between agent sessions

<!-- SC_OFF --><div class="md"><p>I’ve been experimenting with a different way of handling agents and I’m trying to sanity check if this makes sense.</p> <p>Right now most setups

<!-- SC_OFF --><div class="md"><p>Hey <a href="/r/LocalLLaMA">r/LocalLLaMA</a>,</p> <p>I’ve been experimenting with a multi-agent loop locally to see how far smaller models can go

<!-- SC_OFF --><div class="md"><p>I've been working on MDA (Modular Dynamic Architecture), an online associative memory system for LLMs. Here's what I learned building it.</p>

<p>You've heard of DevOps. You've heard of AIOps. You've probably heard of MLOps.</p> <p>But there's a category that doesn't exist yet — and it's the one the AI industry needs

<!-- SC_OFF --><div class="md"><p>One thing that got weird for us pretty fast was “pause/resume”.</p> <p>At first it sounded simple enough.<br /> Workflow is doing multiple steps,