<!-- 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>I’ve been building Signet, an open-source memory substrate for AI agents.</p> <p>The problem is that most agent memory systems are still
<!-- SC_OFF --><div class="md"><p>Every time one of our agents made a bad call in production, we had the same problem. Logs showed what happened. Nothing showed why it decided to
<!-- SC_OFF --><div class="md"><p>Link to full article <a href="https://orimnemos.com/bedrock">here </a></p> <p>TLDR:</p> <p>- LLMs are the wrong substrate for memory. Prediction
<p>Most agent frameworks treat memory as an afterthought. They give your agent tools, prompts, and orchestration patterns — but when you restart the conversation, everything
<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>we run an agent thing in production and we use langfuse for traces.</p> <p>last month our agent started refusing requests it should have
<table> <tr><td> <a href="https://www.reddit.com/r/singularity/comments/1tib2r4/proposed_memory_preference_apply_memory/"> <img alt=""Proposed memory:
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