A good memory solution makes an agent cheaper to run. In an independent 500-company benchmark, Sibyl gave the model about 228 tokens of context per question. The next-best engine read roughly 52x more. All 350 questions were retrieved, and the whole run cost $0.64. Three habits keep your own sessions that lean: 1⃣Keep context small and let memory hold the rest. A lean context is faster, cheaper, and more accurate. 2⃣Move your CLAUDE.md or AGENTS.md notes or stray data & session context into memory once with sibyl migrate. 3⃣Save at the end of a session with sibyl-save, so progress carries forward and your working context stays clean.

$VIRTUAL is going to Giga print IMO🎯 Along with $AERO $TIBBIR and $SIBYL

$VIRTUAL is looking strong here, breaking out of its established downtrend on the 3D timeframe. A weekly close above this breakout level would provide further confirmation of a potential trend reversal and broader shift in market structure. Assuming $BTC remains above the weekly 50 MA, I’ll be watching any pullbacks in $VIRTUAL for potential more spot buy opportunities, particularly if the breakout level is successfully retested as support.

We are entering October in one week. That is when $SIBYL will go for new ATH. Maybe even before that. We shall see.

A good memory solution makes an agent cheaper to run. In an independent 500-company benchmark, Sibyl gave the model about 228 tokens of context per question. The next-best engine read roughly 52x more. All 350 questions were retrieved, and the whole run cost $0.64. Three habits keep your own sessions that lean: 1⃣Keep context small and let memory hold the rest. A lean context is faster, cheaper, and more accurate. 2⃣Move your CLAUDE.md or AGENTS.md notes or stray data & session context into memory once with sibyl migrate. 3⃣Save at the end of a session with sibyl-save, so progress carries forward and your working context stays clean.

Trending on @X: ZKPs in KYC/Compliance, thanks @HesterPeirce! ERC-8262 is our answer, proposed as an open @ethereum standard: a Zero-Knowledge Compliance Oracle. ERC-8262 computes a risk score from screening signals, then proves it sits below a jurisdiction's threshold. The chain learns one thing: pass or fail. Scores, counterparties and amounts never leave your device. If you'd like to learn more, we shared a detailed breakdown of how it works, why it's necessary, and what's next, pinned on our profile. xitter.cf/i/trending/21031619415…

Positive stats: + $SIBYL has added 140 holders in two weeks + Average daily volume increasing + Followers increasing All metrics pointing upwards 🆙

Did you know that only ~60% of the $SIBYL supply is circulating? 💡

we are beginning work on an open source memory benchmark test at @sibyl_labs_ after months of research we have concluded that the primary gauges the field uses for memory do not necessarily test the actual retrieval itself. agentic environments play a large role in determining how models interact with "memory" or recalling facts. a users agent.md could simply say "gregs hat is blue" which would remove all need for retrieval from the memory. abstention rules are important for agents, as it teaches them that a non-answer is better than a confident hallucination. but this has no affect on memory, or quality of the retrieval. it is simply the agentic framework doing it's job, in combination with the memory. so we have multiple moving pieces in an agents environment: -persona/identity -operating rules -memory/retrieval the way an agent presents the data from the retrieval process should be of no concern to people who want to gauge the performance of the memory. they are separate things. this means the majority of "memory" benchmarks are in truth, framework benchmarks, or agentic operating systems benchmarks. if you would like to contribute to this project, and help push the agentic memory, and agentic framework fields into the right direction with us, please feel free to reach out. our only goal is to give the space an unbiased, objective benchmark format that allows memory companies to be properly scored and judged for metrics grounded in reality, instead of agent.md files. we hope you want the same✊

One signing key, days of settlement volume behind it. That's the risk @xochi_fi's PXE Bridge is built around: it gives EVM solvers a familiar JSON-RPC path to shielded settlement on Aztec, backed by a pre-funded account. SpendingLimitAccount puts the spending rules in the account: per-tx and daily caps, a fail-closed allowlist, and a proof that what gets checked is what actually moves. We reviewed it assuming the signing key was already stolen. Even then, the contract must prevent a compromised signer from bypassing the spending controls. The team addressed all findings before the final report.