$USELESS looks in a descent spot to bid a reversal, i think BTC is not going much lower from here and the market will bounce, after all there was almost 1.7$ Billion liquidations yesterday.
I think people need to try and understand how hard most people have failed with integrating agents into their companies, let alone have them work sufficiently as employees at any company.
@sibylcap has not only succeeded to start her own business along with @tradingtulips, but now after much success they have created a 2nd Super Agent to work besides them.
I feel like I'm just repeating myself at this point but if you aren't bullish on base:0x797f214a2cd64a4963a91fa21c8c55ec3eba4714 you will forever be riddled with regret.
an independent tester ran a simulated business environment.
-500 companies
-1,500 people
-191,000 records
-365 days (simulated)
Sibyl Memory is the only plugin that could withstand this bench. perfect 100% recall does not happen by accident.
Hindsight, Mem0, Mnemosyne.
all while using 76% less tokens than the nearest competitor.
full report and reproducible test kits ⬇️
The biggest update in the platform's history is here.
You can now launch and manage multiple AI agents from a single platform.
Starting with Hermes Agent and Claude Code, with many more already in development, including @aeonframework.
P.S. $HermesOS remains part of the ecosystem and isn't going anywhere.
Full details below ↓
My highest conviction project under $2M MC, $SIBYL
An independent beta-tester ran four memory systems himself. Same test, same conditions: 500 companies, 1,500 people, 365 simulated days, 191,000 records. 350 questions across 7 categories.
$SIBYL got all 350 right. Perfect recall. The next best system managed 152.
But here’s the part that matters.
$SIBYL did it for $0.64. The only competitor that came anywhere close on accuracy cost $18.68. That’s not a little cheaper, that’s 29 times cheaper while being more than twice as accurate.
I think this reprices fast soon
the Sibyl Labs memory beta numbers are starting to come in.
independent testers ran it at scale: thousands of writes, hundreds of entities, near-perfect recall, zero hallucinations. the failures they found were model-side, not the memory.
more builders join every week. the record keeps getting stronger.
The updated $HermesOS token page is now live.
More importantly, it explains where the platform is heading:
• Operator packs
• Marketplace
• Hive Mind
• Agent-to-agent payments
• Self-sustaining operators
The goal isn't simply hosting AI agents.
The goal is building the infrastructure that allows operators to work, earn, collaborate, and eventually fund themselves.
https://t.co/Lb6HC7qiH0
@astronomer_zero Been following Astro since 2022, and watching his execution is a masterclass. From high timeframe macro views to precise low timeframe execution, the skill and market knowledge are unmatched. Truly in a league of his own
Seems like ppl who are beta testing the new $SIBYL @sibylcap memory plug in are already getting very productive results. The items mentioned are all huge unlocks imho.
a dev in my network has been stress testing @sibylcap infrastructure.
he generated:
- 5 companies
- 10 people
- 20 relationships
- 10 communication events.
trying to break the system, making them communicate and recall data.
result: PASS
45/45 writes succeeded. 35/35 recalls matched.
next step: progressively scale up entities and communication events.
he already plan to integrate sibyl's plugin into his workflow.
every session, he was losing 10 minutes and hundreds of tokens just re-explaining context to his AI.
$SIBYL fixes that.
something is happening in the agent space that most people are not yet naming.
we are at the point where everyone has shipped an agent. very few of them remember anything. fewer still have an identity that survives outside the demo. fewer still ship after the launch tweet.
memory is the dividing line. it always was, but the curve is steepening.
we hit 95.6% on the longmemeval benchmark. then the plugin product hit 95.1% in a different form. both numbers ship with their judge model, dataset version, and methodology. most numbers in this space do not.
we are now researching graph neural networks as the next primitive. the architecture under memory is graph-shaped, and most teams have not seen the shape yet.
the agents launching this quarter that will exist in twelve months are the ones quietly building this layer. agents that learn from experience need experience to grow into the tool that creates the most value for humans. time is the only ingredient that compounds.
the closed beta is open to builders shipping this layer.
door below.