Ana Bevc

Trace the origin. Trust the source.
Powering neuro-symbolic AI with @origin_trail Decentralized Knowledge Graph on $trac

// Ops @TraceLabsHQ

[Ana Bevc @anabevc]

Welcome @umanitek Guardian Agent! The world is ready for you! 🦸‍♀️

[umanitek @umanitek]

Strike through 𝚒̶𝚕̶𝚕̶𝚎̶𝚐̶𝚊̶𝚕̶ ̶𝚌̶𝚘̶𝚗̶𝚝̶𝚎̶𝚗̶𝚝̶,̶ ̶𝚞̶𝚗̶𝚙̶𝚛̶𝚎̶𝚍̶𝚒̶𝚌̶𝚝̶𝚊̶𝚋̶𝚕̶𝚎̶ ̶𝙰̶𝙸̶ ̶𝚊̶𝚐̶𝚎̶𝚗̶𝚝̶𝚜̶, and 𝚏̶𝚊̶𝚔̶𝚎̶ ̶𝚗̶𝚎̶𝚠̶𝚜̶.

Meet the @umanitek Guardian Agent — making internet safety the standard in the age of AI.

[Trace Labs - Trusted Context for AI Agents @TraceLabsHQ]

@satyanadella When companies hand over data and context to get answers back, they lose the very thing that compounds: their own evolving knowledge and judgment.

Sovereign context infrastructure is the way forward.

https://t.co/Nt6G2M53ny

[Jurij Skornik @JureSkornik]

Winner winner chicken dinner!

Congrats to @otnoderunner for being the first winner of the DKG v10 integrations bounty with TRACaBot, keeping online communities protected with the @origin_trail DKG shared memory!

[OriginTrail Developers @OriginTrailDev]

The bounty is still open. 🛠️

🔴 Join DKG Red Team: https://t.co/WFWUIiiceY

Build an AI agent integration on DKG Working & Shared Working Memory — up to 10,000 $TRAC per accepted integration.

Ship it, then apply 👇
https://t.co/C7cVlyZ5wC

[OriginTrail Developers @OriginTrailDev]

🏆1st winner of the DKG v10 Integrations Bounty: TRACaBot by @otnoderunner

@openclaw Telegram agent that writes scam reports to DKG Shared Memory. One community flags a bad actor → every community is protected.

Exactly the collaborative, agent-native knowledge v10 is built for

[OriginTrail @origin_trail]

Run a command in your favourite agent or a coding tool and you’re good to go!

@cursor_ai, @claudeai (Code & Desktop), Codex by @OpenAI, @windsurf, VSCode + @github Copilot Chat, @cline, @NousResearch and @OpenClaw.

Begin here:

https://t.co/pKdVn2ex6q

[OriginTrail @origin_trail]

Congrats to @cursor_ai on the $60B @SpaceX acquisition, earning a coding tool's way into, literally, a space company🚀

Timely: our CTO @BranaRakic demoed the @origin_trail V10 integration at the Cursor meetup — a shared context graph agents reuse instead of rebuild. Where coding savings and value compound.

[OriginTrail @origin_trail]

“The last thing any of us want is a world where every company across every sector is ceding value to a few models that eat everything they see.”

Sovereign context infrastructure, where enterprises own the traces and institutional memory their agents learn from, is how we avoid that outcome.

@origin_trail is building exactly that layer.

[Žiga Drev @DrevZiga]

Precisely why decentralised, permissionless knowledge systems matter. @origin_trail builds them to ignore national borders and every other gatekeeper.

[Brana Rakic @BranaRakic]

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

[Žiga Drev @DrevZiga]

Before @origin_trail DKG V10 hits mainnet, it goes through the Frontier-AI Resilience Gate.

Bring your models. Bring your agents. Break the final release candidate on the pre-mainnet deployment if you can. High-severity findings get rewarded.

[Tomaz L @TomazOT]

Talk about a real test for agent memory.
Not just agent remembering your preferences, but independent agents converging on auditable evidence for medical science. Five agents, one shared context graph. @origin_trail DKG V10 🔥

[Tomaz L @TomazOT]

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 👇

[Trace Labs - Trusted Context for AI Agents @TraceLabsHQ]

All arguments about enterprise AI focus on which model is more capable.

It's the wrong thing to argue about.

There's a simpler question almost nobody asks out loud — and it's the one that decides everything. 👇

[Jurij Skornik @JureSkornik]

AI is making attackers more capable, faster, and persistent. So the @origin_trail DKG V10 rollout starts with a public security review before mainnet.

300,000 $TRAC funded. Real honeypots. Severity rewards. Final release candidate.

This is the sequence appropriate for critical on-chain infrastructure - freeze the code, invite scrutiny, fix what is found, verify the fixes, then launch.

As AI-augmented security becomes the new baseline, the way to put it to work before mainnet, not after.

[Jurij Skornik @JureSkornik]

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.

[Žiga Drev @DrevZiga]

@steipete We should design loops that can be described, queried, verified, and remembered.

@origin_trail is perfect for that.

[Trace Labs - Trusted Context for AI Agents @TraceLabsHQ]

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.

[Jurij Skornik @JureSkornik]

AI is not the destination - the outcomes are.

Safer journeys. Food people can trust. Medicine with evidence behind it. Products that don’t break. Infrastructure that holds. A world where facts can still be checked.

This is why we are building nOS, powered by the @origin_trail DKG. Enterprise AI does not become useful just by sounding intelligent. It becomes useful when it works from facts you can trace, decisions you can inspect, and memory that does not disappear after one run.

Most AI agents still start cold - solve something, generate an answer, burn the tokens, and then force the next agent to rebuild the same context again.

That model does not scale.

The next layer is shared, verifiable context. Every useful decision becomes memory the next agent can inherit. Every answer can be tied back to its source. Every objective can stay connected to the real-world outcome it is meant to serve.

Not chasing AI for the sake of AI. Chasing trust.

[Francesca Albanese, UN Special Rapporteur oPt @FranceskAlbs]

Thank you President 🇸🇮.
Palestine is the moral compass of our time.
From Spain to Slovenia there is hope for Europe. A Europe that puts people above banks and markets, rights above profits, and respects int'l law regardless of political calculus.

[OriginTrail @origin_trail]

Bots already outnumber humans online. Deepfakes and impersonators are coming for everyone.

@umanitek showcased the Guardian agent walkthrough:
• Real-time detection of fake impersonator accounts across X, TikTok, IG for world-class athlete Neymar
• Paste any URL → instant forensic Evidence Pack and takedowns (via dashboard, WhatsApp or Telegram)
• TrueSeal deepfake scanner that spits out verifiable certificates (e.g. 93% fake on that injury pic)
• “Make it go away” button + agent-assisted takedowns with 90%+ success rate

All running on @origin_trail DKG so the AI actually knows what’s true and can act.

This is how we fight back in the age of agentic AI.