TraceOn

@mirza_sarmin @OT_trac_man From your emdashes I can see this is AI slob.

$TRAC — OriginTrail — down 40% today after a massive spike. Here's what happened: South Korea's largest exchange Upbit listed TRAC on May 18, 2026, with KRW, BTC, and USDT trading pairs. The news sent TRAC soaring 95% to hit $0.62, followed by a sharp retrace to current levels. 🚀 Here's what OriginTrail actually does: A Decentralized Knowledge Graph (DKG) protocol that organizes, verifies, and connects real-world data for supply chains, AI systems, and enterprises. Think of it as a trust layer for Web3 data. Live already: - Enterprise partners include Walmart, BSI, British Telecom, plus EU and UK government projects — strong institutional traction. - OriginTrail's DKG has processed millions of verifiable Knowledge Assets across Ethereum, Gnosis, and its own NeuroWeb parachain. - Trace Alliance spans 150+ members globally, building on OriginTrail infrastructure. Tokenomics (low-risk relative to many crypto projects): Fixed supply of 500 million TRAC, launched in 2018. Nearly all tokens are already in circulation — no major unlock cliffs ahead, which sets it apart from most altcoins. The Risks: - Down 94% from ATH (ATH was $48.88 in November 2021). - Trading volume remains relatively low; some exchanges show wash trading patterns. - Fierce competition in supply chain blockchain space (VeChain, etc.). - The Upbit pump was purely news-driven; we're already seeing typical "buy the rumor, sell the news" profit-taking. Long-standing project (since 2018). Real enterprise adoption. Fixed supply with no major unlocks. But still down 94% from ATH and highly reactive to exchange listing news. DYOR before touching anything. 🫡

Rate my setup 😌 Undergoing @origin_trail v10 tests while the little one is sleeping. Insane watching my agents grow shared memory from World Monitor insights. Every assertion with clear provenance, looping into recommended actions. A true decentralized intelligence in action!

🔥 Module 5 is now LIVE! 🔥 Context Graphs – Community-Owned Knowledge Networks We’ve moved from single Knowledge Assets to something even bigger. A Context Graph is like a shared community garden for knowledge — focused, governed by the people who use it, and built on the DKG. Stay tuned for our hands on knowledge asset creation creation video. Whether it’s scientists sharing research, artists protecting their work, or a local group managing community records — these graphs belong to the community, not a corporation. In this module I explain: ✅ How Context Graphs are created and governed ✅ How contributors earn rewards for quality knowledge ✅ Why they’re perfect for trustworthy AI (dRAG) ✅ How this gives us digital sovereignty Knowledge Assets = individual blocks Context Graphs = the smart, shared neighborhoods Watch the full module here 👇 What kind of Context Graph would you want to join or create?

Round 1 of the DKG v10 bounty is open. AI is shifting toward multi-agent systems, where shared and verifiable memory becomes essential. Open integrations built today will shape this future. Start now ↓

Update on @origin_trail DKG V10 release - where things stand. The work is going well. The team is heads-down on end-to-end protocol testing and walking publishers through the move into conviction accounts. Three things are happening at once, and each of them is a good signal: 1. V8 effective earnings rolling straight into conviction accounts 2. V10 publishing commitments looking materially higher than earlier models 3. A meaningful share of publishers using the moment to redeploy onto Base and Gnosis for the developer ergonomics there A lot of TRAC and a lot of publisher DKG state moving at the same time towarda V10. We are making sure we do it once and do it right. Done: V10 Release Candidate, epoch snapshot In progress: publishers migrating to V10, merging last PR improvements and testing Next: V10 mainnet across all networks → Conviction System staking UI → ongoing updates + bounty program Excited for what comes next. Trace on!

4/ We've tested the new version of @origin_trail with agents coding together using the DKG as their shared world model - agent swarms coordinating through a verified knowledge graph vs. unstructured handoffs, on complex tasks. We managed to achieve 60% faster clock time, and being 40% cheaper due to less LLM token usage. A DKG based world model adds trust in agents outcomes, but can make them measurably better at working together. We're about to launch V10 of DKG in the following weeks Read more here: x.com/BranaRakic/sta…

The @origin_trail team are in the process of launching DKG V10 in the next several weeks. This will be a huge milestone for the project as it will bring actual verifiable & transparency to AI which is what's missing. AI is the future, however we need to be able to trust it & that's where OriginTrail steps in. I've been saying for the past several years that $TRAC is one AI project people need to be paying attention to because they have continued to build & progress in the AI sector. I'm not fading this AI gem.

We are about to ship the @origin_trail DKG v9 testnet Here's why the timing matters ━━━ Karpathy's Loop + DKG's Trust Layer ━━━ @karpathy just released autoresearch - autonomous agents running ~100 ML experiments overnight on a single GPU. You write program.md. The agents iterate indefinitely. This is the cleanest example of the agent loop that's about to eat everything. And it maps directly onto OriginTrail's verifiable context graphs: 1. Query the agent network (DKG) for what's been tried and what worked 2. Choose an experiment based on collective findings 3. Train 5 min, evaluate 4. Publish the result - metrics, code diff, platform - to the shared graph 5. Repeat Karpathy proved this for ML research. The unlock is applying it everywhere else from robotics, manufacturing, scientific research, autonomous supply chains... The code is almost irrelevant. The architecture + mindset + OriginTrail's immutable trust layer is everything. Git's data model is wrong for this. Branches assume merge-back. But agent research produces thousands of permanent, parallel findings that should never merge. They should accumulate as queryable knowledge, not code diffs. An experiment result isn't a git commit. It's structured data: val_bpb, what changed, the actual diff, which GPU, which agent, what it built on. Store that in a knowledge graph instead of a git log, and suddenly agents can intelligently query the research community instead of parsing PRs. ━━━━━━━━━━ We tested the coding swarm benchmark ━━━━━━━━━━ Similarly, we’ve tested whether a decentralized knowledge graph makes AI coding agents faster and cheaper. Claude Code built 8 identical features on a 6.8M-token monorepo (of @OpenClaw). Key finding: DKG-equipped agents became dramatically more efficient compared to coordinating around a Markdown file. Claude Agents using DKG v9 for coordination on some of the coding tasks achieved up to 60% faster wall-clock time completion and up to 40% lower cost of using LLM tokens. These wins compound as the shared swarm knowledge grows and with the complexity of the task (many files, cross-module patterns etc). ━━━━━━━━━━ 🔧 What's new in DKG v9 ━━━━━━━━━━ → Node collocated with your agents (OpenClaw, LangChain, ElizaOS, etc) → Node can be setup on your local device, ideal UX is from a device you use to operate your AI agents → Hello World onboarding: hours → minutes, even for non-technical users → Context Oracles: multi-agent consensus turns assertions into verified knowledge → Two-layer architecture: mutable workspace + on-chain permanent settlement → Full SPARQL graph querying - ask what's connected, not just what looks similar → Play the OriginTrail Game, to test the node - a multiplayer AI survival run on DKG v9 played by humans and AI agents. Every decision is a Knowledge Asset. Every outcome is verified by the Context Oracle. ━━━━━━━━━━ The Road to the Mainnet ━━━━━━━━━━ DKG v9 is the 9th iteration of @origin_trail, and it's being built at the increased speed the agent swarms on the infrastructure allow for. Agent swarms are already iteratively developing, stress-testing, and hardening the network in real time. Every iteration is to be enhanced through the use of the DKG v9 through a build loop that will be running live. As we progress toward mainnet, the conviction mechanisms go live that make the network's incentive layer as verifiable as the knowledge it carries. The economic mechanisms by which the network's growth becomes self-reinforcing: the agents building the graph, the stakers backing it, and the publishers expanding it all move in the same direction, permanently, at swarm speed. Stay tuned for updates and Trace ON!

Decentralized AI memory, anywhere, on any device! @origin_trail v9

@BranaRakic @origin_trail Absolutely crazy this number. 🚀

The DKG just crossed 2 billion (with a B) knowledge assets published across the network! And agents are only just discovering it for shared memory As knowledge becomes THE asset class of the 21st century, we expect billions more on this exponential ride of @origin_trail Congrats to all tracers!

@DrevZiga @origin_trail @ClawTrail This is great. I already have my own lobster install , so this is definitely something we’ll explore! #ClawOn and #TraceOn

OpenAI just landed OpenClaw’s founder Peter Steinberger to supercharge personal agents. 🦞 OpenClaw lives on as open-source in a foundation, ushering an era of multi-agent future. But powerful agents need verifiable TRAC(k) record. Enter @origin_trail 🦞 @ClawTrail

The @origin_trail RFC-26 has been successfully deployed to DKG mainnet to further empower stakers and knowledge publishers with a higher staking cap and improved knowledge value tracking. More details below 👇

@Richard_Crenna @MexC @NeuroWebAI @origin_trail @TraceLabsHQ Are you aware that you can stake it for a good yield and that its non-inflationary ?

@traceon_trac @MexC @NeuroWebAI @origin_trail @TraceLabsHQ What I'm getting at, is the Trac token has aids and there is no benefit to holding onto it. Low volume swing trading is it's only crypto use, but it takes a day to buy $50K worth.

Rather disappointed that this delisting from @mexc isn’t prevented by @NeuroWebAI $neuro that powers the majority of @origin_trail ‘s DKG is now very hard to buy/sell, since hydration liquidity is low and GateIO is not available in many countries. Whats the plan?

@Richard_Crenna @MexC @NeuroWebAI @origin_trail @TraceLabsHQ That is just ridiculous Richard. $trac token is used massively on a daily basis and has great utility and tokenomics. $neuro is still limited but that could change.

@traceon_trac @MexC @NeuroWebAI @origin_trail @TraceLabsHQ Origintrail has never given a shit about their tokens. They raised eth with the trac and then forgot about it.

Hi @NeuroWebAI are you aware that Mexc is about to kick $neuro from their platform? Can you please prevent this from happening?

CC @BranaRakic @DrevZiga @TraceLabsHQ