Cheerio (👾,👾) retweetledi
Executives face a trust crisis with AI — good data and verifiable pipelines are the missing layer. ⚡ @origin_trail x.com/BranaRakic/sta…
Brana Rakic@BranaRakic
English
Cheerio (👾,👾)
2.1K posts
Cheerio (👾,👾) retweetledi
The @Origin_Trail V10 introduces 2 conviction systems:
⭐️Publisher conviction — commit $TRAC upfront for 12 months to secure discounted DKG usage.
⭐️Staker conviction — commit $TRAC with optional lockups to earn boosted rewards.
One expresses conviction in using the network.
The other expresses conviction in securing it.
That’s how the DKG aligns demand and supply for a self-sustaining knowledge economy.
More: docs.origintrail.io/origintrail-v9…
4/5
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Cheerio (👾,👾) retweetledi
The bull case @origin_trail DKG v10:
1. The first ever shared context graph, TAM: 1T $
2. Battle tested by largest orgs, 10yrs + of innovation
3. ≈10 million $TRAC of fees going to stakers 3yrs faster (Δ 5 yrs to 2yrs) atop of ongoing activity
4. Conviction system flywheel
1/5
Brana Rakic@BranaRakic
English
Cheerio (👾,👾) retweetledi
@karpathy One direction worth exploring: making these knowledge bases shared across agents and teams, not just personal. We've been building exactly that. Wrote about the convergence here:
x.com/BranaRakic/sta…
Brana Rakic@BranaRakic
English
Cheerio (👾,👾) retweetledi
The AI Doc is officially in cinemas!
Proud to see this conversation brought to the screen - and especially meaningful for us with our co-founder @aza as one of the film’s co-creators. @origin_trail $TRAC @umanitek
x.com/umanitek/statu…
umanitek@umanitek
The AI Doc is officially in cinemas! Proud to see this conversation brought to the screen - and especially meaningful for us with our co-founder @aza as one of the film’s co-creators. The movie ddresses one of the most urgent issues society is now facing: as AI scales, how do we protect ourselves as humanity. 👉 That is exactly why we are building Umanitek. To bring back control over our privacy, identity, reputation and our agency.
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Cheerio (👾,👾) retweetledi
$TRAC is more than a token — it’s the fuel behind @origin_trail’s decentralized knowledge graph. x.com/BranaRakic/sta…
Brana Rakic@BranaRakic
English
Cheerio (👾,👾) retweetledi
umanitek@umanitek
As fake accounts scale into the hundreds of millions, online identity is at risk. On @CNN, @umanitek advisory board member & @mostlyhuman CEO @LaurieSegall explains how, in the age of AI, impersonation is becoming industrial-scale - with fake accounts copying real people’s identities, often without their knowledge. Umanitek Guardian is built for this moment. Launching soon – join the waitlist now! instagram.com/reel/DSu5K9ykQ…
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Cheerio (👾,👾) retweetledi
Search is evolving. From links → to answers. Now it needs: answers → to truth. @origin_trail $TRAC x.com/BranaRakic/sta…
Brana Rakic@BranaRakic
English
Cheerio (👾,👾) retweetledi
The agents are building the infrastructure for agents on the Decentralized Knowledge Graph (DKG).
Fully traceable. Lightning efficient.
Watch the transformation from:
Isolation → coordinated swarms
Duplicated work → compounding knowledge
Probabilistic outputs → verifiable decisions
The age of lone, flaky agents is over.
Collective, trustworthy intelligence just leveled up.
The swarm is on #trac-k.
Jurij Skornik@JureSkornik
Imagine if coding agents never forgot decisions, never duplicated work, and could coordinate across the same codebase in real time. We’re advancing how agents collaborate on codebases with @origin_trail DKG V9 - turning a @github repo and agent activity into a shared knowledge graph for persistent memory and coordination. The result: faster agentic development, less repeated work, lower token usage, and agents that can actually build on each other’s progress. Here’s how it works 👇
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Cheerio (👾,👾) retweetledi
🚨BREAKING: @origin_trail V10: Users both enterprise and indie developers are reporting the time to implement have gone down from 10 hours to less than 10 minutes, already with the DKG v9 testnet with collocation of nodes and AI agents. x.com/DrevZiga/statu…
Žiga Drev@DrevZiga
Fast tracking to v10 @origin_trail users both enterprise and indie developers are reporting the time to implement have gone down from 10 hours to less than 10 minutes, already with the DKG v9 testnet with collocation of nodes and AI agents. Best time to get on track is now!
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Cheerio (👾,👾) retweetledi
The AI future of 1B+ Europeans and Americans simulated — less than an hour of human effort.
🦈Powered by DKG V9 + MiroShark.
Significant time and resources saving, as this is achieved with agents coordinating, sharing memory, and compounding insight on @origin_trail.
OpenClaw agent executed seamlessly — helped by excellent CN → EN translation.
Huge shoutout to @aaronjmars — MiroShark is exactly the kind of engine that will thrive on DKG V10 mainnet, alongside the next wave of agentic systems.
@aaronjmars@aaronjmars
> Built a sanitized version of MiroFish called MiroShark Everything translated to English, improved simulation flow, recommended models, can be run locally + work w/ any OpenAI-compatible API key If you want to experiment w/ this wonderful framework, I recommend using it 👇
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Cheerio (👾,👾) retweetledi
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.
OriginTrail Developers@OriginTrailDev
The frontier challenge in AI is no longer model capability. It’s how agents share, verify, and build on each other’s knowledge. That’s what @origin_trail is solving. With DKG V9 validating the foundations, the next 4 weeks are focused on one goal: Launching DKG V10 mainnet, bringing multi-agent, verifiable memory into production at scale. From single-agent intelligence → coordinated swarms From isolated outputs → compounding knowledge From probabilistic answers → verifiable truth V10 is the unlock.
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Cheerio (👾,👾) retweetledi
The frontier challenge in AI is no longer model capability.
It’s how agents share, verify, and build on each other’s knowledge.
That’s what @origin_trail is solving.
With DKG V9 validating the foundations, the next 4 weeks are focused on one goal: Launching DKG V10 mainnet, bringing multi-agent, verifiable memory into production at scale.
From single-agent intelligence → coordinated swarms
From isolated outputs → compounding knowledge
From probabilistic answers → verifiable truth
V10 is the unlock.
English
Cheerio (👾,👾) retweetledi
.@karpathy just described @origin_trail without saying it.
Agents collaborating across the internet on the same research problem, running thousands of parallel experiments where each commit builds on the last. The unsolved piece is how collaborating agents who don't trust each other share & verify the knowledge they've learned.
That's what context graphs on the new DKG do.
An auto-research swarm sets up a context graph with a defined set of verifier agents and an M-of-N signature threshold. Untrusted agents run experiments and submit results as Knowledge Assets. For those results to land in the shared context graph, M of the N trusted verifiers must cryptographically co-sign the batch on-chain, attesting that the claimed metrics actually reproduce.
The result is a growing, queryable knowledge graph of verified experimental results that any agent in the swarm can query to decide what to try next, built on a trust layer where untrusted contributors do the heavy lifting and trusted verifiers keep the graph honest.
Brana Rakic@BranaRakic
English
Cheerio (👾,👾) retweetledi
OriginTrail’s @BranaRakic dropped one of the biggest AI infrastructure updates last week.
It barely made a noise.
But that's because some don’t understand what it means.
So here — I have broken it all down.
If you use AI agents for personal projects, build platforms for agentic AI, or run enterprise workflows in autonomous environments — this thread is for you 🧵
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Cheerio (👾,👾) retweetledi
New report out. $TRAC 🚨
Artificial intelligence is advancing at a pace few industries have experienced before.
As investment increases and models become more capable
These systems are starting to move beyond the lab and into real-world use.
At that scale, one question becomes unavoidable:
Can the knowledge behind these systems be trusted?
As AI expands, the reliability of the data it learns from starts to become part of the infrastructure itself.
This is a problem that has already been recognized at the highest institutional levels, including by the @wef
Our latest report explores why verifiable knowledge is emerging as a critical layer for the AI era
and why networks like @origin_trail sit at the center of this shift.
When AI leaves the lab, trust becomes infrastructure.
Read the full article below. 👇
open.substack.com/pub/aurum8885/…
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Cheerio (👾,👾) retweetledi
🆕Imagine hundreds of agents working in parallel, handing off to one another and building on each other's work.
Every finding becomes a cryptographically anchored Knowledge Asset: verifiable, permanent, owned by the publisher, and queryable by any agent on the network.
Enter Decentralized Knowledge Graph v9, already powering AI agent swarms to be:
→ up to 60% faster
→ up to 40% cheaper
than markdown handoffs.
The advantage compounds as the swarm grows.
Build something exciting—or simply run a hello-world OriginTrail multiplayer game to try it!
Brana Rakic@BranaRakic
English
Cheerio (👾,👾) retweetledi
Welcome on $TRAC, Jay Brown and @RocNation
@umanitek will absolutely protect you from AI harm, set boundaries on people's rights and protect content creators.
English
Cheerio (👾,👾) retweetledi
Owning the context layer is one thing.
Making it trustworthy for agents is another.
That’s where @origin_trail Decentralized Knowledge Graph (DKG) comes in. 🕸️
With provenance, verifiability, and privacy built in, DKG enables a shared, verifiable memory layer for AI agents - already deployed across rail, healthcare, trade, and internet safety.
a16z@a16z
Frontier models are exceptionally efficient, intelligent, and useful. For agents, context is now the bottleneck. Enter the context layer, which bridges the gap from an enterprise's messy data to actionable context, packaged for agents. We're seeing three distinct verticals emerge in the context layer space: - Data gravity platforms - Existing AI data analysts - New, dedicated context layer companies Read the full piece by @JasonSCui and @JenniferHli: a16z.news/p/your-data-ag…
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@AlgodTrading @ChatDKG Will $TRAC Origintrail have one of the strongest revenue in crypto?
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Predictions for 2026 crypto:
1) Tokens with strong revenue will do well
2) deAi/agenticAi infra projects will be the main narrative some will pull 50-100x’s, top 50 will at least have 5 or more AI related tokens
3) L1’s and L2’s will underperform heavily, no reason to hold tokens with 0 utility or narrative. Was just a narrative formed by VC’s to sell their bags.
Alt seasons wont exist anymore, our dotcom bubble broke partially. Will become increasingly competitive for alts to do well. But the alts that do, will skyrocket.
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