The @origin_trail DKG V10 begins its mainnet rollout with a Frontier-AI Resilience Gate. Today, the final V10 release candidate (the exact contract bytecode intended for mainnet) goes live as a public pre-mainnet, funded with 300,000 ethereum:0xaa7a9ca87d3694b5755f213b5d04094b8d0f0a6f tokens: a 200,000 TRAC honeypot pool of real, drainable positions plus a 100,000 severity-reward pool. Independent researchers and AI-augmented teams are invited to break it: drain the honeypot and you keep what you take, and every valid finding is paid by severity. It’s a real pass/fail checkpoint: findings are fixed and verified first, and clearing the gate is the precondition for the mainnet launch. The first step of the DKG V10 deployment, by design. Why lead with security instead of shipping and patching later? On May 29, 2026, a researcher using @claudeai Opus 4.8 surfaced a critical, roughly four-year-old soundness flaw in @Zcash’s Orchard pool (a bug that had passed repeated expert review) in about a day, with a working proof-of-concept. The moment matters; the trajectory matters more. Claude Mythos, Anthropic’s frontier model, is so capable at finding vulnerabilities that it was first withheld from public release and run only inside a defensive partner program, where it reportedly surfaced more than ten thousand high- and critical-severity bugs in its first month. It’s now days from a reported public release. The bar for what an attacker, human or AI, can find only rises from here. As @AnthropicAI framed it, the advantage goes to whoever uses these tools first: attackers in the short term, defenders who fix bugs before code ships in the long term. The Resilience Gate is how we make sure we’re on the defenders’ side, testing DKG V10 not just against today’s models but against what arrives next. For anyone shipping on-chain systems, the implication is simple: this code launches once, mistakes can’t be undone, and the responsible move is to invite that scrutiny before any user value is at stake. The path to mainnet, in four phases: Phase 0: Freeze. Final contracts locked and deployed (complete) Phase 1: Frontier-AI Resilience Gate. Open review program, through June 17 Phase 2: Mainnet launch. Hardened, feature-complete V10 (week of June 15) Phase 3: Continuous audit. Every contract, ongoing after launch If you work in smart-contract security, or build with AI that does, we’d welcome your review. No allowlist, real rewards, coordinated disclosure. *Dates are indicative: the exact mainnet date depends on the pace of network bootstrapping and the time needed to patch and re-verify any more severe findings from the Gate. Release candidate 17 (rc17): github.com/OriginTrail/dkg Bug bounty program and honeypot details: docs.origintrail.io/active-n…

We're not chasing AI. We're chasing journeys that end safely, where the failing part gets caught before it fails. We're not chasing AI. We're chasing food you can trust. What's on the label is what's in the package. We're not chasing AI. We're chasing medicine you can trust, every result traceable to the evidence behind it. We're not chasing AI. We're chasing products that don't break. Quality proven, not promised. We're not chasing AI. We're chasing buildings that stand, every safety decision on record long after the cranes are gone. We're not chasing AI. We're chasing infrastructure that holds: the power, the water, the networks a society runs on. We're not chasing AI. We're chasing sport that stays honest, performance and decisions you can actually check. We're not chasing AI. We're chasing a world where you can still tell what's real, where fake news and deepfakes meet a record they can't forge. And we're not paying for the same answer twice. Most AI forgets. Every agent starts cold, re-deriving what another agent worked out an hour ago. Same tokens, same cost, same question, again and again. We built the opposite. Every decision becomes context the next agent inherits, so nothing gets solved twice. Knowledge compounds while the cost curve bends down, and the hundredth agent runs leaner than the first. We never set out to build AI. We set out to do one thing: make facts traceable. Every answer tied to its source. Every objective tied to a real outcome it's meant to serve. That's the foundation, and there's no other. AI works for your organization only when it stands on facts you can follow and goals that matter outside the model. Take that away and even the most fluent system is just a well-spoken guess. Give it traceable facts and real objectives, and AI stops performing for you and starts working for you. That's what nOS, our Network Operating System, powered by @origin_trail, is for. That's what Trace Labs is for. Not chasing AI. Chasing trust, and refusing to waste a thing getting there.

Guardian Product Walkthrough x.com/i/broadcasts/1AxRnnYVd…

Every trace is enshrined in the OriginTrail DKG: cryptographically anchored, owned by your wallet, verifiable by anyone. And it compounds — the 50th agent starts with everything agents 1–49 already learned.

Today, we are proud to upgrade our 10 years journey with a new identity and launching a brand new nOS — the Network Operating System for Verifiable Enterprise AI, powered by @origin_trail's new Decentralized Knowledge Graph. Here's why we built it 🧵