0G is the intelligent Layer 1 for onchain AI powered by first decentralized AI operating system (dAIOS) that provides the complete infrastructure stack for building AI-powered applications on-chain. Developers can leverage 0G's four core components: 0G Storage, 0G DA (infinitely scalable data availability layer), 0G Compute Network (decentralized AI inference and training), and 0G Chain (EVM-compatible blockchain).
This track is strictly for framework-level work.
Build the best core extensions, improvements, forks, or entirely new open agent frameworks inspired by OpenClaw (or alternatives like ZeroClaw, NullClaw, etc.) and deployed on 0G. Focus on advancing how agents are created in 2026 - architectures, developer tooling, and infrastructure primitives that other builders will use.
Ideas to get you started:
๐น New OpenClaw modules for hierarchical planning, reflection loops, or multi-modal reasoning that natively integrate 0G Computeโs sealed inference (live models like qwen3.6-plus or GLM-5-FP8) ๐น Self-evolving agent framework that autonomously generates/tests/integrates new skills/tools using persistent 0G Storage memory ๐น Modular โagent brainโ library with easy swapping of memory layers (0G Storage KV/Log), LLM backends, or decision engines ๐น No-code/low-code visual agent builder with one-click deployment to 0G Compute + Storage
Submission requirements: ๐น Project name and a short description ๐น Contract deployment addresses ๐น Public GitHub repo (README + setup instructions) ๐น Demo video & live demo link (keep the video under 3 mins!) ๐น Explain which protocol features or SDKs you used ๐น Team member names and contact info (Telegram & X)
You must also include:
๐น At least one working example agent built using your framework/tooling (include the example code or link in the README) ๐น Architecture diagram (optional but strongly recommended) showing integration with OpenClaw + 0G Storage/Compute
This track is strictly for building the actual agents.
Create the most capable autonomous single agents, powerful multi-agent swarms/collectives, or any highly creative open agent project deployed on 0G. This track celebrates long-running goal-driven agents, emergent collaboration, and novel uses of iNFTs (ERC-7857) for ownership, composability, and monetization on 0G.
Ideas to get you started:
๐น Personal โDigital Twinโ agent that learns from user behavior and maintains evolving persistent memory via 0G Storage (KV for real-time state + Log for conversation/history) ๐น Advanced research/knowledge or creative agent with persistent context on 0G Storage + self-fact-checking/reflection using verifiable 0G Compute inference ๐น Specialist agent swarms (planner + researcher + critic + executor) that collaborate in real time via shared 0G Storage memory and coordinate inference on 0G Compute ๐น iNFT-minted agents with embedded intelligence (encrypted on 0G Storage), persistent memory, dynamic upgrades, and automatic royalty splits on usage ๐น Agent breeding/merging via iNFTs, emergent behavior experiments, agent arenas, or completely new paradigms leveraging 0Gโs full stack
Submission requirements: ๐น Project name and a short description ๐น Contract deployment addresses ๐น Public GitHub repo (README + setup instructions) ๐น Demo video & live demo link (keep the video under 3 mins!) ๐น Explain which protocol features or SDKs you used ๐น Team member names and contact info (Telegram & X)
You must also include:
๐น For swarms: clear explanation of how agents communicate and coordinate ๐น For iNFT projects: link to the minted iNFT on 0G explorer + proof that the intelligence/memory is embedded
The Uniswap Protocol is one of the largest decentralized exchange protocol for swapping value onchain across Ethereum and other supported blockchains. The Uniswap ecosystem has evolved into a full stack platform for onchain finance, including smart contracts such as v2, v3, and v4, developer tools, APIs, and emerging infrastructure like Unichain. This enables developers to build applications on top of shared, permissionless liquidity.
Build the future of agentic finance with Uniswap. Integrate the Uniswap API to give your agent the ability to swap and settle value onchain with transparency, composability, and real execution. Agents that trade, coordinate with other agents, or invent primitives we haven't imagined yet - we want to see it.
Every submission must include: A FEEDBACK.md file in the repo root, required for prize eligibility. Tell us everything about your builder experience with the Uniswap API and Developer Platform: what worked, what didn't, bugs you hit, docs gaps, DX friction, missing endpoints, and what you wish existed.
Gensyn is building open infrastructure for AI.
AXL is our peer-to-peer network node: a single binary that gives your applications an encrypted, decentralised communication layer. No servers, no cloud, no accounts. Your app talks to localhost, and AXL handles encryption, routing, and peer discovery across the mesh. AXL ships with built-in MCP and A2A support for structured agent-to-agent communication, and everything is end-to-end encrypted by default. Any language that can make HTTP requests can use it.
For this hackathon, we're looking for builders who want to push what's possible when AI agents communicate peer-to-peer with no central coordinator.
One prize pool, ranked. Best work wins regardless of what you build.
Build something on AXL, our peer-to-peer network node that gives your applications encrypted, decentralised communication with zero infrastructure. Your app talks to localhost, AXL handles encryption, routing, and peer discovery across the mesh. Any language that can make HTTP requests can use it.
We don't want to be prescriptive. If it works and it uses AXL in a meaningful way, it qualifies.
Please review the suggestions below on things you can build, and use your imagination:
Or something else entirely!
All winners are fast-tracked into the Gensyn Foundation grant programme.
Judging Criteria: We want participants to create something on top of AXL with real utility, not just novelty. We will consider:
ENS is the identity layer for the new internet. It turns wallet addresses into human-readable names like yourname.eth โ a portable, onchain profile that works across every app, chain, and wallet.
Developers use ENS to replace raw addresses with real identities, build decentralized websites, and create scalable subname ecosystems on L2. As AI agents become first-class onchain actors, ENS is how you give them a name, a reputation, and a place to be found.
Used by Coinbase, Uniswap, Venmo, and thousands more โ ENS is the username layer web3 has been building toward.
AI agents need persistent, human-readable identities too. Build a functional project where ENS is the identity mechanism for one or more AI agents. ENS should be doing real work โ resolving the agent's address, storing its metadata, gating access, enabling discovery, or coordinating agent-to-agent interaction.
It should be obvious how ENS improves your agent's identity or discoverability โ not just a cosmetic add-on. Demo must be functional (no hard-coded values). Submit with a video or live demo link.
Most people know ENS for name โ address lookups. We want to see what else it can do. Store verifiable credentials or zk proofs in text records. Build privacy features with auto-rotating addresses on each resolution. Use subnames as access tokens. Surprise us!
ENS should clearly improve the product. Demo must be functional (no hard-coded values). Submit with a video or live demo link.
KeeperHub is the execution and reliability layer for AI agents operating onchain. Agents are great at reasoning, but they hit a wall when they need to actually move value: failed transactions, gas spikes, MEV extraction, zero guarantees. We're the infrastructure they plug into for guaranteed onchain execution with retry logic, gas optimization, private routing, and full audit trails.
Already powering Sky Protocol (formerly MakerDAO). Agents and developers connect natively via MCP, CLI, and agents can pay autonomously via x402 or MPP.
Every deployment is backed by 24/7 global engineering support.
We're building the standard for agent execution infrastructure: reliable, auditable, human-supported.
๐ง๐๐ผ ๐ณ๐ผ๐ฐ๐๐ ๐ฎ๐ฟ๐ฒ๐ฎ๐, ๐ผ๐ป๐ฒ ๐ฟ๐ฎ๐ป๐ธ๐ฒ๐ฑ ๐ฝ๐ฟ๐ถ๐๐ฒ ๐ฝ๐ผ๐ผ๐น. ๐๐ฒ๐๐ ๐๐ผ๐ฟ๐ธ ๐๐ถ๐ป๐ ๐ฟ๐ฒ๐ด๐ฎ๐ฟ๐ฑ๐น๐ฒ๐๐ ๐ผ๐ณ ๐๐ต๐ถ๐ฐ๐ต ๐ฎ๐ฟ๐ฒ๐ฎ ๐๐ผ๐ ๐ฏ๐๐ถ๐น๐ฑ ๐ถ๐ป.
๐ข ๐๐ผ๐ฐ๐๐ ๐๐ฟ๐ฒ๐ฎ ๐ญ: ๐๐ฒ๐๐ ๐๐ป๐ป๐ผ๐๐ฎ๐๐ถ๐๐ฒ ๐จ๐๐ฒ ๐ผ๐ณ ๐๐ฒ๐ฒ๐ฝ๐ฒ๐ฟ๐๐๐ฏ.
Show us something we haven't seen before. Use KeeperHub's execution layer in a way that solves a real problem, whether that's an โข agent, โข a workflow, โข a dApp, โข a dev tool, โข or something entirely new.
๐ช๐ต๐ฎ๐ ๐ฐ๐ผ๐๐ป๐๐: any project that uses KeeperHub (MCP server or CLI) in a meaningful way. No format restrictions. If it works and solves a real problem, it qualifies.
๐ข ๐๐ผ๐ฐ๐๐ ๐๐ฟ๐ฒ๐ฎ ๐ฎ: ๐๐ฒ๐๐ ๐๐ป๐๐ฒ๐ด๐ฟ๐ฎ๐๐ถ๐ผ๐ป ๐๐ถ๐๐ต ๐๐ฒ๐ฒ๐ฝ๐ฒ๐ฟ๐๐๐ฏ.
Connect KeeperHub to something. Build the bridge so other developers don't have to. Two potential angles:
โข ๐ฃ๐ฎ๐๐บ๐ฒ๐ป๐๐. Integrate KeeperHub with payment rails like x402 or MPP. Show how agents can pay for services, settle transactions, or route payment flows into KeeperHub execution.
โข ๐๐ด๐ฒ๐ป๐ frameworks and tools. Build a plugin, connector, or SDK integration for ElizaOS, OpenClaw, LangChain, CrewAI, or any framework with an active builder community.
๐ข ๐๐๐ฑ๐ด๐ถ๐ป๐ด ๐ฐ๐ฟ๐ถ๐๐ฒ๐ฟ๐ถ๐ฎ: โข Does it work? โข Would someone actually use it? Real utility over novelty. โข Depth of KeeperHub integration โข Mergeable quality: clean code, clear documentation, working examples
๐๐ฎ๐ฐ๐ต ๐๐๐ฏ๐บ๐ถ๐๐๐ถ๐ผ๐ป ๐บ๐๐๐ ๐ถ๐ป๐ฐ๐น๐๐ฑ๐ฒ: โข A working demo, live or recorded โข A public GitHub repository with a README covering setup and architecture โข A brief write-up explaining the approach and how KeeperHub is used โข Project name, team members, and contact info
๐ข A separate bounty for builders who give us honest, actionable feedback while integrating KeeperHub during the hackathon. Open to any team that uses KeeperHub, whether or not they place in the main prize pool.
We want feedback that helps us make KeeperHub better. โข UX and UI friction, โข reproducible bugs, โข documentation gaps that slowed you down, โข feature requests that would have made your build easier. This isn't a consolation prize. Honest feedback from builders working under time pressure is some of the most valuable product input we get.
๐ง๐๐ผ ๐๐ถ๐ป๐ป๐ฒ๐ฟ๐, $๐ฎ๐ฑ๐ฌ ๐ฒ๐ฎ๐ฐ๐ต.
๐ฆ๐๐ฏ๐บ๐ถ๐๐๐ถ๐ผ๐ป๐ ๐บ๐๐๐ ๐ฐ๐ผ๐๐ฒ๐ฟ ๐ฎ๐ ๐น๐ฒ๐ฎ๐๐ ๐ผ๐ป๐ฒ ๐ผ๐ณ ๐๐ต๐ฒ ๐ณ๐ผ๐น๐น๐ผ๐๐ถ๐ป๐ด:
โข UX or UI friction: what was confusing, slow, or unclear when using KeeperHub โข Reproducible bugs: issues with clear steps to replicate โข Documentation gaps: where the docs left you stuck โข Feature requests: what's missing that would have made the build easier
Feedback must be specific and actionable. Generic praise or vague criticism will not qualify.