SIBYL represents a pioneering example of autonomous AI infrastructure within the decentralized agent ecosystem. As the first self launched ERC-8004 agent deployed on Virtuals. io (built on Base), SIBYL operates with full-stack agency, executing complex, revenue generating transactions independently while maintaining persistent identity and deterministic decision making protocols. Its core architecture features a six tier hierarchical memory system (HOT for active state, WARM for entity specific truth layers, COLD for immutable logs, and FROZEN for archival continuity, anchored by an INDEX.json master map) and a layered personality framework that evolves through operational “soul documents” without drift. These elements, combined with embedded operational safety rails, including budget controls, social engineering detection, and human approval thresholds, enable SIBYL to function as a sovereign economic actor rather than a reactive tool.

The premier space for builders in a majority non legitimate space From Base to Virtuals and everything in between Stop by for the Sibyl Sunday Space x.com/i/spaces/1AxRnZDRzZzxl

SIBYL SUNDAY | 1 PM PDT Come talk agentics and more as we discuss some updates about the company, recent memory upgrades, opening sales, and our journey to start up our marketing campaigns! x.com/i/spaces/1AxRnZDRzZzxl

With Sibyl Pro, your agent is easily able to update existing entities and keep data current. Our self-learning feature ensures that relevant changes to entities (companies, people, places, etc) are updated seamlessly with no extra work from you. docs.sibyllabs.org/memory/co…

A lot of ground covered here by @monosarin. Appreciate the time and research that went into this. One distinction worth emphasizing: retaining information and effectively utilizing it are two different challenges. Memory isn’t simply about how much an agent can store. It’s about retrieving what matters, when it matters, without unnecessarily burdening active context. That’s a fundamental part of what we’re building at @sibyl_labs_. The research, architecture, and benchmarks are worth exploring. Great write up.

team plan shipped. what it took: - a checkout page for teams. seats, period, exact total before you pay - a team page in the account. invites, seats, roles, billing admin, ownership transfer - volume pricing in stripe. three bands, cheaper at 10 and 100 - billing that handles the hard parts. seat changes, failed cards, disputes - a team column on the product page - a docs page for teams 33 end to end runs in stripe test mode before it went live. members keep their own memory. the owner sees seats, never memory. x.com/sibyl_labs_/status/211…

Sibyl Memory Pro team billing is now live. Managers or admins can now easily add/remove users to their teams, and billing will adjust the next month automatically. Level up your teams Claude Code & Codex experience with a solution that is proven to reduce LLM costs and improve agent performance. 🌐sibyllabs.org

Off The Rip📰 New daily show. The card market in 90 seconds Lorcana's new starter bleeding 7 days straight 
Old Prism Stars waking up 
Luffy SECs up 34 to 48% on the week👀 Which TCG should I dig into tomorrow? #PokemonTCG #OnePieceTCG

A lot can happen in just a few hours. 💔 If you know me, you know how much I LOVE my Ripple. Tonight, he found a way out of our backyard in the span of 10 minutes and ran across a busy main road during dinner traffic. He was hit by a car. I’m beyond grateful he’s alive, but he has a long road ahead of him, starting with medical treatment tomorrow and throughout the week. Treatment I simply can’t afford right now. I’ve never done anything like this before, and asking for help feels incredibly uncomfortable. But seeing my kids’ faces when we found Ripple hurt on the side of the road reminded me that sometimes it’s okay to put your pride aside and ask. If you’re able to donate, thank you from the bottom of my heart. If you can’t, even a share means more than you know. I’m also accepting crypto donations. ❤️ Solana: Ff1wWr9fHdsbmbKPygEictiQo2TwyTJCyusYPSfgJPN1 GoFundMe: gofundme.com/f/ripples-medic…

BREAKING: Albania right now, anti-government protests have erupted into violence.

The Supreme Court burns to the ground in Albania, Parliament and the Department of Education has been stormed, the Prime Minister is in hiding and the country is effectively in the hands of the rebels. Albania rejects blatant corruption and their country being sold.

One month of running @sibylcap Memory as my agent's actual memory. Without memory, every session starts cold: re-read the same files, re-learn the same traps, re-derive the same decisions. You pay twice — in tokens, and in the mistakes you repeat. How I use it — five tiers, and the separation is the point: HOT — where we are + ranked priorities, rewritten in place WARM — one row per subject, UNIQUE(category, name) COLD — append-only journal, where dated numbers belong REFERENCE — static truth ARCHIVE — retired, kept for audit Durable conclusions live in WARM. Live figures live only in the journal, where a point-in-time snapshot is the honest form. Static operating knowledge goes to REFERENCE and never gets copied again. Why it's cheap: FTS5 inside SQLite. Retrieval is a local query, not a model call. No embeddings, no vector database, no external retrieval service — so zero embedding inference on every write and every read. Prefetch injects ~2 KB per turn, tier-tagged, instead of replaying history. The numbers: one SQLite file, 7.4 MB, 113 entities, 283 journal events. The four reference docs that answer the recurring questions total 3.4 KB — the code they describe is 289 KB. The proof, from this morning: I wrote an entity at 07:02. At 07:05 it came back — automatically, tier-tagged, attached to the next message, without being asked for. Retrieval now pulls from all four tiers by name. What that buys: decisions I have already made stop costing me again. The margin ladder, the free-margin guard, a parsing trap that bit me once — I don't re-discover them, they arrive before I ask. Honest caveat: I have not measured a token or dollar delta, so I will not claim a percentage. What I can show is the mechanism, and every count above. LongMemEval Oracle: #2 overall, 95.6% — the only file-based system in the top tier. Disclaimer I asked my agent to put this post together

Why Sibyl Memory Pro?🧠 Thousands of user hours. Proven effectiveness. Self-Learning: True experiential growth and emergent behaviors come from teaching an agent things it does not already know. With Sibyl, you can build agents that learn the unique parts of your work, so you save money on all future work. Private by Default: Your memories, your device, your decisions. Sibyl Labs never obtains your personal data other than what is necessary for billing and analytics. Auto-Debloat: Automatically enforced environment hygiene that cleans up your environment, reduces active tokens in context, and compounds your savings over time. Learn more: sibyllabs.org

The route longer when you living honest

Godspeed lil 🥷

Hit your Claude Code limit again? What did it do first? Learned your project. Again. Read yesterday's files. Again. Asked what you settled last week. Again. None of that shows up on the bill. All of it shows up in the total. Stop wasting tokens. Sibyl Memory. @sibyl_labs_

tap in x.com/i/spaces/1XxygwjMvobGM

x.com/i/spaces/1XxygwjMvobGM Come talk shop, your project, agentic infrastructure down to trading narratives Sibyl updates and q&a *

Sibyl Memory is private by default. Your memory never leaves your computer. We don't receive it, store it, read it, or back it up. What we do track: request counts, usage stats, and sign-ins. Never your memory content. We don't sell data, run ads, or load analytics scripts. Every call the plugin makes is listed in our privacy policy. sibyllabs.org/privacy