Dmitry (Charts never lie)

@origin_trail $TRAC is top 10 with a small team, but huge ambition and potential with DKG V10 coming.

@Blockchain1013 @origin_trail see here - origintrail.io/solutions

@dmitry_charts @origin_trail who are the customers?

Epoch 15 $TRAC @origin_trail network earnings are 1.46M TRAC (~$442k), +44% over previous epoch. All of that comes from customers who use the network and it will be distributed to stakers in the coming epochs. 530k TRAC ($160k) were sent to stakers yesterday. No inflation, 100% supply in circulation. stats - othub.io/preview.html

The month of Mar is over, 1.3M $TRAC (~$410k) was spent by customers on @origin_trail network, +37% MoM. With network earnings split 2:1 between @gnosis_ and @base. All that TRAC will be distributed among delegators in the coming epochs. source - othub.io

For those who missed the AMA, this strikes me as the best part for DKG V10: @BranaRakic was explaining how using x402 protocol for agentic payments make the whole process of buying trac, spending trac to pub knowledge assets, etc., super easy to integrate with users' productivity tools. Users will just allocate like $200/mo (or whatever amount they need/want) to their agent, much like how users pay for LLMs already, and then the DKG v10 runs in the background creating context graphs (new word for parachain) to supercharge the users' AI agents. Everything will be smooth and seamless for best user experience. And while on the call, Brana's DKG agent swarm were literally coding for him live on the call in the background. He reiterated that his agents are ~60% more efficient with the DKG context graphs and cost about 40% less when using it. And this is why @DrevZiga added if your business is not using the DKG its going to become obsolete. Context graphs are the future of agentic AI and the DKG V10 is sitting right on top of it. Market seems to be waking up to this. Are you getting on $TRAC yet?

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.

Epoch 14 $TRAC @origin_trail network earnings are above 1M TRAC (~$334k), nice! All of that comes from customers who use the network and it will be distributed to stakers in the coming epochs. 651k TRAC ($200k) were sent to stakers yesterday. No inflation, 100% supply in circulation. stats - othub.io

Epoch 14 is over in the $TRAC @origin_trail world, 651k TRAC ($200k) have been distributed to stakers. Top nodes made 13%-15% APR, all are available to stake on. No inflation, 100% supply in circulation. How? Yep, revenue comes from customers who use the service. othub.io/preview.html

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!

Join @ChrisRynning and @TomazOt for a live walkthrough of the Umanitek Guardian Agent, using the recent wave of fake airline support accounts targeting stranded GCC travellers as a real-world use case. See how impersonating accounts are identified, evidence is captured, and takedowns can be initiated directly from the platform. - Link in reply.

@NearKatToken @General_Illia @AlexAuroraDev $NEAR revenue last 365d is 2.9M and expenses 82.4M. I'll update my table but still puts it 4th place. Source: tokenterminal.com/explorer/proje… $TRAC is still king of earnings Source othub.io

The @origin_trail DKG just ended the month of February 2026 with a boom💥 Best month in terms of network use in terms of $TRAC Source: othub.io

"The most urgent film of our time." THE AI DOC: OR HOW I BECAME AN APOCALOPTIMIST is only in theaters March 27. Watch the trailer now.

You know why it’s HARD to “buy the dip” when an asset is down 97% from its highs? Because if an asset has zero fundamental value and is only surviving on attention, then it is a very real possibility that it may never recover and in effect, become worthless. You know what makes it EASY to “buy the dip” when an asset is down 97% from its highs? When you know that it CAN’T go down to zero because token holders get paid out with real revenue day after day and there is zero dilution from token inflation. Soon people will wake up to projects like $TRAC that are tired to real, profitable businesses and that pass these profits directly on to token holders. An asset that “can’t” go to zero because it produces real yield for token holders, which is always worth something. Yes price can go lower, but that simply increases the APR for token holders because the annual revenue is independent of token price. This means that as price falls and APR increases, it simply becomes an even more attractive asset for investors. When you understand all this, your view on dips and depressed prices changes from a curse to a blessing, because you get time to accumulate these assets at a discount when most aren’t paying attention.

AI is blurring the line between real & fake identity online. Join @ChrisRynning & @TomazOT as they demo the @umanitek Guardian – a privacy-preserving early warning system that monitors content, flags AI-driven threats, and helps act before harm spreads.

@CredibleCrypto @origin_trail And since we are talking numbers, Epoch 13 ended the other day, 637k TRAC were distributed to stakers, same as usual no inflation and 100% supply in circulation. x.com/dmitry_charts/…

$TRAC is objectively undervalued vs its "AI" peers when comparing revenue to current marketcap. All revenue generated by @origin_trail is passed on to $TRAC stakers and node operators, and the token has ZERO inflation (fully circulating). If $TRAC was trading at the same MC/Rev ratios as it's peers, it would be priced at: ICP- $1.32 FET- $1.92 FIL- $2 NEAR- $3.26 TAO- $3.70 RNDR- $3.56 GRT- $5.75 It currently trades at .32.

Epoch 13 is over in the $TRAC @origin_trail world, 637k TRAC ($212k) have been distributed to stakers. Top node made 21% APR, others are in 3%-18% range. No inflation, 100% supply in circulation. How? Yep, revenue comes from customers who use the service. othub.io/preview.html