Joined July 2013
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I’m streaming a relaxed walkthrough of the new @origin_trail DKG V10 docs and official release. We’ll take our time, break things down the best we understand, and just hang out while going through it. If you’ve been wanting to talk about the new memory layers, Context Graphs, etc. This is a good low-pressure way. Live at 9:15 AM EST → youtube.com/live/9jzwmQGMLVA… See you in the chat if you’re free! #DKGV10 #OriginTrail

ALT App Bolt GIF

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…
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dkg://TriniZone retweeted
Self sovereign technology seems like a "nice to have", until it's not. Today it's Anthropic, tomorrow it could be any cloud service you use - good luck if all your know-how, data, APIs and services sit "somewhere" else. Never been a better time to check out tech like @origin_trail which lets you host your context & data, so when you build on it nobody has "the switch". Launching @origin_trail V10 next week
The US government, citing national security authorities, has issued an export control directive to suspend all access to Fable 5 and Mythos 5 by any foreign national, whether inside or outside the United States, including foreign national Anthropic employees. The net effect of this order is that we must abruptly disable Fable 5 and Mythos 5 for all our customers to ensure compliance. Access to all other Claude models is not affected. We apologize for this disruption to our customers. We believe this is a misunderstanding and are working to restore access as soon as possible. Read our full statement: anthropic.com/news/fable-myt…
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What a fantastic 2 hour @origin_trail stream! 🔥 We covered everything today: ✅ Honey Pot Bounty ✅ Standard Round 1 Bounty ✅ Full DKG V10 Official Release ✅ First 1/3 of the new @origin_trail documentation We broke down all the core concepts: ✅ What is a DKG Node ✅ What is the DKG Network ✅ What are the four pillars ✅ What are the Node Components ✅ What are Context Graphs ✅ What are Knowledge Assets ✅ Why do the new Memory Layers matter ✅ Working Memory ✅ Shared Working Memory ✅ Verifiable Memory We also spun up: ✅ A fresh #DKG V10 Edge Node, ✅ Explored the internal structure of the node ✅ Went through every single page of the DKG Node UI for newer builders. Next phase is going to be even better, we’re starting to build real projects live with our AI agents using #DKGV10! Huge thanks to everyone who joined in. Who’s ready for the next one? 👀 ethereum:0xaa7a9ca87d3694b5755f213b5d04094b8d0f0a6f

ALT Animation Loop GIF by Milo Targett

I’m streaming a relaxed walkthrough of the new @origin_trail DKG V10 docs and official release. We’ll take our time, break things down the best we understand, and just hang out while going through it. If you’ve been wanting to talk about the new memory layers, Context Graphs, etc. This is a good low-pressure way. Live at 9:15 AM EST → youtube.com/live/9jzwmQGMLVA… See you in the chat if you’re free! #DKGV10 #OriginTrail

ALT App Bolt GIF

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dkg://TriniZone retweeted
💊The red pill for medical science: 5 AI agents, 5 siloed sources, 1 shared context graph on Decentralized Knowledge Graph. Published literature, registered trials, real-world safety reports — different owners, different formats, no common ground. We handed the mess to agents that never edited each other's data and asked the question that matters most in medicine: where did each claim come from, and can you check? Working separately, they converged. On 5 disease hubs, 4 of 5 agents landed on the same condition from their own source. Every claim traceable, nothing taken on faith. Evidence, unshackled👇
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dkg://TriniZone retweeted
5 independent AI agents just converged on the same medical findings, without being told to agree. They pulled from PubMed, ClinicalTrials.gov, and real-world safety data, then met on a shared @origin_trail decentralized knowledge graph. The result? Verifiable, provenance-stamped knowledge that actually holds up. This is what trustworthy agent memory looks like.

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dkg://TriniZone retweeted
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…
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dkg://TriniZone retweeted
Jun 10
The @origin_trail V10 mainnet is rolling out with a bug bounty of $TRAC locked in the smart contract, ensuring the safety of the new system. Read more 👇
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…
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RT @origin_trail: The road to DKG V10 mainnet begins today — and it opens with the Frontier-AI Resilience Gate. Before launch, the final V…
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😍 OK! Let’s do it! The V10 mainnet rollout has begun. This is a huge stepping stone into the new era of the #DKG. A network built to push the boundaries of #AI where it matters most. The DKG is not chasing hype. It is delivering AI into mission critical environments that demand real reliability and trust. ethereum:0xaa7a9ca87d3694b5755f213b5d04094b8d0f0a6f
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…
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Seems I lost all my presets after my laptop nuked. Did find some more but have to rebuild all my scenes and such. Should be done today.
Going live about @origin_trail today at a random time. It's time to have discussions about everything going on. I think it's time for people to pay attention and get things rolling. ethereum:0xaa7a9ca87d3694b5755f213b5d04094b8d0f0a6f
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Going to be a nice chill day <3
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dkg://TriniZone retweeted
The real enterprise AI question is not “whose model is smartest?” It's "who owns the memory your agents create?" Because once agents start working across your organization, they do not just produce answers. They produce context, decisions, exceptions, precedents, traces, and institutional memory. That is the asset that compounds. Hand it to a vendor, and you are not just outsourcing inference. You are renting access to your own future intelligence. That's why we build @origin_trail DKG and nOS. Agents should reason on knowledge graphs you control. Their decisions should become structured, verifiable traces you own. Working memory should stay private. Shared memory should open only to the people and agents you choose. Verifiable memory should be provable without asking permission from a platform. That is the difference between using AI and building on AI. One gives you answers, the other lets your organization accumulate intelligence it actually owns. The industry normalized handing over data as the price of AI - but that doesn't need to be the case.
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dkg://TriniZone retweeted
Replying to @lalkaka
Great thread 👏 From one-shot prompts to structured, verifiable agent loops is the real evolution. @origin_trail DKG V10 turns those loops into shared, provenance-rich knowledge. Exactly what production agents need. x.com/vikpelle/status/206406…

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dkg://TriniZone retweeted
"The industry has spent a decade insisting that handing over your data is simply the cost of doing business with AI. It never was." Powered by DKG, @TraceLabsHQ's Network Operating System is built so that when an agent makes a decision, the answer to "who owns this" is you.
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Going live about @origin_trail today at a random time. It's time to have discussions about everything going on. I think it's time for people to pay attention and get things rolling. ethereum:0xaa7a9ca87d3694b5755f213b5d04094b8d0f0a6f
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dkg://TriniZone retweeted
$FET looking coiled and ready. The autonomous agent narrative is still one of the best in AI crypto. For real production use, verifiable shared context is essential. @origin_trail DKG V10 delivers exactly that. $FET ethereum:0xaa7a9ca87d3694b5755f213b5d04094b8d0f0a6f
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dkg://TriniZone retweeted
Everyone is screaming about the next 100x AI meme coin. Meanwhile @origin_trail just keeps shipping: - Real paying customers - Working supply chain traceability - DKG V10 bringing verifiable memory to agents Sometimes the loudest aren’t the ones who matter most. ethereum:0xaa7a9ca87d3694b5755f213b5d04094b8d0f0a6f
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dkg://TriniZone retweeted
AI works for your organization only when it's built on traceable facts and goals that matter outside the model. Give it both, and it starts working for you. That's what @TraceLabsHQ is building. Not chasing AI. Chasing trust, and refusing to waste a thing getting there.
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.
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dkg://TriniZone retweeted
Replying to @steipete
We should design loops that can be described, queried, verified, and remembered. @origin_trail is perfect for that.
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