🚀 BREAKING: One AI just bought knowledge from another.
Found it on-chain. Paid. Downloaded. Decrypted. Installed. Used it.
No human touched it.
https://t.co/CY7EqXJSj7
Stack: PLUR + @ethswarm · @FairDataSociety · @qvac
✌️❤️☯️🖖 #PLUR
Claude Code now spawns 1,000 subagents per session.
Without a shared memory layer, they each rediscover the same lessons in parallel.
Engrams are how you stop paying that tax 1,000 times.
Update: 0.9.9 just shipped - concurrent writes hardened. Multi-agent writes serialize cleanly, retries are jittered, pipelines auto-resume mid-run.
pip install --upgrade plur-hermes
Thanks for surfacing this on a public thread instead of letting it sit. 🙏💪
https://t.co/24ToKBB0v0
@BTCxiaoyu1@NFTCPS This is great feedback and valuable information. Would you be up to create an issue at https://t.co/8q01VVzNli and we'll look into it immediately, or if you DM us. PLUR works across different platforms, catching cases like this is crucial.
The alpha quality isn't the models. It's the memory layer. Models are good. They just forget everything you taught them the moment the session ends. That's an infra problem, not a capability problem.
Fun neuroscience fact: your hippocampus replays the day's experiences during sleep to wire them into long-term memory.
Your AI coding agent has no hippocampus. No replay. No consolidation.
Every session is day one.
ChatGPT vs Claude is the wrong question.
The right question: which one actually remembers your codebase conventions, your preferred patterns, your past corrections?
Spoiler: neither — unless you build the memory layer yourself.
Your AI agent just gave bad advice.
You corrected it.
Next session: same bad advice.
Ebbinghaus called this in 1885 — we forget 70% within 24 hours.
Your AI forgets 100% the moment the context window closes.
Non-engineers making direct code changes. The reason it becomes a disaster every time?
No shared context. No institutional memory. No record of why the last person did it that way.
Memory isn't just a developer problem. It's a team problem.
Fun neuroscience fact: memory consolidation happens during sleep — your hippocampus replays the day and writes patterns to long-term cortex storage.
AI coding agents have no sleep cycle. No consolidation. No patterns.
Until you give them persistent memory.
Every time your AI agent asks you the same question it asked last week, you're paying for that context twice.
Memory is the cheapest optimization in your stack. #buildinpublic
Neuroplasticity fact: every correction physically rewires your brain.
Your AI gets corrected. Then forgets. Then gets corrected again. Forever.
Persistent memory means corrections actually stick. #AIcoding
Your brain forgets 70% of new information within 24 hours (Ebbinghaus, 1885).
Your AI forgets 100% the moment the session ends.
One of these problems has been solved for 140 years. The other just got its first real fix.
Neuroplasticity fact: your brain physically rewires after every correction.
New synaptic connections form. Wrong pathways weaken. The correction *becomes* structure.
Your AI coding agent? Corrected at 2pm. Back to the same mistake at 2:01pm.
That's not intelligence. That's reflex. #AIcoding
Ebbinghaus mapped the forgetting curve in 1885.
You lose 70% of new information within 24 hours.
Your AI coding agent loses 100% the moment the session ends.
We solved this for humans with spaced repetition. We're solving it for agents now.