Is AI memory a problem in the AI coding agent?

<!-- SC_OFF --><div class="md"><p>I need some verification on this matter</p> <p>A bit of context, I went through other subreddits and I saw a huge influx of &quot;AI memory

<!-- SC_OFF --><div class="md"><p>I get that there a lot of challenges with memory such as selective retrieval and loss of detail etc. but how has no one come up with a solid

<!-- 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

<!-- SC_OFF --><div class="md"><p>Heptabase just dropped a CLI so Claude Code / Codex can create, read, and update a local knowledge base from the terminal. It’s a smart move.</p>

<!-- SC_OFF --><div class="md"><p>Most agent systems treat memory as advisory.</p> <p>The agent reads past context, but nothing forces it to follow it.</p> <p>So memory becomes a

<!-- SC_OFF --><div class="md"><p>want to put a different multi-agent direction on the table because most of what i see assumes task teams.</p> <p>the dominant pattern right now:

<!-- SC_OFF --><div class="md"><p>The idea is simple, if one agent is good then multiple agents working together must be better. In practice coordination between agents is an

<!-- SC_OFF --><div class="md"><p>But is there an industry need for it ... It's smth like vlc media player of memory systems ... My team thinks it's hard to make money from it or