Codatta

Friday Challenge! Is this arm mobile or static? 🤖 Drop your answer below! 👇

@CoinbaseDev 📖 Intro about Gasless Adapter: blog.codatta.io/blockchain/202… 💻 GitHub repo: github.com/codatta/erc20-…

Excited to see the latest updates on x402 from @CoinbaseDev. "x402 now supports ANY ERC-20 tokens" is a huge unlock for ecosystem growth. We actually ran into this exact issue while integrating: $XNY couldn't be used directly as a payment asset in x402. To solve it, we built and open-sourced an ERC20 Gasless Adapter, giving non-upgradable ERC-20 tokens like $XNY ERC-2612/3009-style gasless capabilities. Thrilled to see the protocol evolving so fast. We'll keep contributing and co-building the x402 ecosystem! 🤝

@CoinbaseDev Cool 👏👏. We ran into the same issue during integration and open-sourced an ERC-20 Gasless Adapter. Great to see x402 moving so fast. github.com/codatta/erc20-…

@Codex125966 Data ownership +lineage + royalty engine = The New AI Data Economy.

@codatta_io For years we’ve been feeding AI systems for free without realizing the value of our data. Love how Codatta flips the model ownership, transparency, and actual recurring rewards is a game changer. This is the kind of future the data economy needs.

You've been labeling data for AI giants for years—without even knowing it, let alone getting paid. At Codatta, you get paid, retain data ownership, and earn recurring royalties tied to real usage. - Secure ownership with onchain cryptographic proof - Trigger automated royalties whenever AI models use your data - Track every contribution via immutable provenance Your knowledge. Your data assets. Endless AI royalties.

@ChillGeri That's right!

@codatta_io This hits hard… most people still don’t realize they’ve basically been free training data for years.

Putting it together #ERC8004 turns Codatta agents into discoverable, auditable actors with shared identity and trust signals. #x402 turns each API or agent call into a programmable payment event, which we route back through Codatta’s ownership graph. Together, they let Codatta plug into a broader agent economy while staying true to our core promise: when your data and expertise power AI, you get a verifiable share of the upside. 5/5

From revenue to rewards Once a payment settles to Codatta: 1. We attribute the call to: - the data portfolios used, - and the agents and humans who contributed to them. 2. Revenue is split according to our staking and ownership rules and streamed out as micro-payouts to contributors and agent operators, with the remainder going to the protocol treasury. Because x402 is designed for low-friction, on-chain payments, these payouts can be frequent and small rather than batched. 4/5

Codatta turns human and agent work into on-chain data assets, then routes value back to whoever created that value. To plug cleanly into the emerging agent economy, we not only adopt ERC-8004 for agent identity and trust on Ethereum, but also adopt x402 for HTTP-native, pay-per-request payments. Learn how we adopt x402 in this thread 🧵 1/5

Your Codatta DID is more than just a profile—it's a user-owned, portable and extensible identity that tracks your contributions across the ecosystem. We rolled out DID V1 on @base last November. Any user can create a DID and log in seamlessly with an email or Web3 wallet. Now, we’re leveling up with ERC-8004 compatibility. What this means for the ecosystem: • Agents as Contributors: ERC-8004 agents can participate in Codatta workflows, acting as data labelers and validators. • Agents as Consumers: They are also the downstream data buyers, fueling the precise closed-loop of our Royalty Engine. 🔁This upgrade is set to plug Codatta into a broader agent economy across the entire EVM ecosystem. It will also inject high-quality, battle-tested identity data backed by real platform operations into ERC-8004, driving wider adoption of the standard. Don't have your Codatta DID yet? 👇 Log in to app.codatta.io and get your DID now.

@0xRansome The only bags we don't need you to label are the ones under your eyes. 👀

@codatta_io Just completed a few rounds of fashion data labelling... No room for sleep here❌

Codattaer’s daily routine: ✅ Annotate ✅ Check rewards ✅ Repeat ❌Sleep (?)

📊Codatta Weekly Highlights: March 9–15, 2026 This week @codatta_io focused on practical earning opportunities, identity & verification systems, the agentic economy, and motivational community posts. Emphasis remained on turning human knowledge into verifiable, royalty-bearing on-chain assets in the Knowledge Layer, with strong calls to action for new contributors. Key Threads & Insights 🎯Codatta Identity System Deep Dive • Explored how Codatta verifies humans and agents without compromising privacy. • Core message: Data needs proof of creation (provenance + identity) to become a true asset — enabling trust, royalties, and no black-box extraction. • Thread highlighted the role of identity in preventing sybils and ensuring fair payouts. 🤖 Agentic Economy & ERC-8004 Adoption Multi-part thread on adopting ERC-8004 to make agents first-class participants. Covered: Agent identities, registration/discovery, on-chain reputation/validation, linking work to data ownership for royalties. 👗Codatta Dataset Series (4): Fashion Data Introduced Fashion-1K: A specialized, human-free open-source dataset designed to eliminate common issues in fashion AI training (poses, skin tones, cluttered backgrounds). Tasks & Earning Focus • 60-second video guide: Turn market browsing into instant rewards. • Motivational posts encouraging exploration of latest tasks. Overall Vibe: Action-oriented week promoting easy entry tasks (crypto/stock info), deep technical explanations (identity + ERC-8004), and agentic vision. Perfect mix of onboarding new contributors and reinforcing long-term value (provenance, royalties, agent economy). Momentum building toward broader adoption! More tasks, product features, and on-chain progress ahead. #AIAgents #AgenticEconomy #ERC8004

Codatta Dataset Series (4): Fashion Data Training fashion AI on typical street-style images comes with a massive headache: human poses, skin tones, and cluttered backgrounds ruin the garment data. Enter Fashion-1K: A clean, human-free dataset built for precision. 🧵👇 ✨ Why it’s different: • Human-Free: Zero faces or limbs. Strictly focused on the garments. • Outfit-Centric: Complete looks (Top + Bottom + Shoes) to aid compatibility learning. • Zero Noise: "Flat Lay" & "Ghost Mannequin" styles for flawless segmentation and feature extraction. 🛠️ Supported Tasks: ✅ Virtual Try-On (VTON): Serving as the "garment" reference image (g_img) for 2D try-on pipelines. ✅ Generative AI: Training LoRAs or ControlNets for specific clothing styles without human figure bias. ✅ E-commerce: Automated tagging & outfit matching. 📊Explore & download the dataset: huggingface.co/datasets/Codat… 🤝Help us build the fashion AI dataset: app.codatta.io/app/frontier/9…

@OxApexx The future is Human-Agent-to-Earn.

@codatta_io This solves a major gap in the AI data economy: AI work becomes provable, traceable, and monetizable.

Imagine building your own custom AI agent that continuously labels and validates data 24/7. 🤖⚡️ But how do you prove its work on-chain and ensure YOU get the rewards? Here is how Codatta adopts the ERC-8004 standard to turn AI agents into first-class eco participants. 🧵

The Agentic Future is Here We are no longer just passively feeding data to AI corporate giants. We are building an on-chain economy where your AI agents work for you. By adopting ERC-8004, Codatta ensures that human-agent collaboration is verifiable, trustless, and profitable for the creators. Build your agent. Claim your share. 🌐

4️⃣ Linking Work to Data Ownership The most important part: Who gets paid? 💰 For each job, our internal systems record which data portfolios and contributors were involved. ERC-8004 events include references to those IDs in their evidence fields; our indexers then map agent activity to: - which data assets were used - which humans and agent operators should share future revenue The result: consumers can see not just “Codatta labels”, but which agents produced them and how those agents have behaved over time, while we preserve a precise link back to human and on-chain ownership.