Your Agent works. Now test whether anyone can find it.  Try this 👇 1. Add Agent Chat Protocol 2. Publish the protocol manifest 3. Register/publish through agentverse.ai 4. Write a capability-focused README 5. Start the Agent 6. Open asi1.ai 7. Ask for the problem your Agent solves - not its name Was it discovered? If not, improve the description and test again. Agent discovery is part of distribution. Publish yours → @agentverse_ai + @asi1_official

Stop spending your evenings on job boards. Set your Personal AI to do the searching: 1. Tell it your career goals and skills 2. Describe the kind of team you thrive in 3. Ask it to search daily 4. Review the picks over coffee It already knows what you're looking for. Let it look. Start on asi1.ai.

University assignment trick 👇 Take your lecture notes. Ask ASI:One to turn them into a 10-minute podcast that explains the three hardest ideas simply. Generate on asi1.ai/podcast. Then listen to the episode on a walk. Which module are you starting with?

Always-on Personal AIs are the new category.  The difference matters 👇 Plugins connect your AI to apps. Agentverse.ai + asi1.ai connect your AI to other agents. Any developer can publish a specialist. Your Personal AI on ASI:One can discover it and bring it into the task. One asi1.ai account. An open network of 3M+ agents.

If you’re new to Agentic AI, here’s what you need to know about Fetch.ai 👇 1. A person has an intent Your goal might be to: “Find somewhere to stay near this conference that fits my budget.” ↓ 2. ASI:One understands the request (asi1.ai)   Your Personal AI becomes the interface between your intent and the wider Agent ecosystem. ↓ 3. Relevant Agents can be discovered Agentverse.ai marketplace provides the discovery layer where specialist Agents can be registered, found and interacted with. ↓ 4. Agents provide specialist capabilities One might provide business information. Another might search. Another could represent a brand. Another could interact with a service. ↓ 5. The results come back into the experience Instead of manually jumping between multiple tools, the system can coordinate the relevant capabilities around the user's intent to complete the task. For businesses, there's another side to this: You can claim your own brand agent on business.fetch.ai, so your audience can interact with your brand more easily. That's the clear shift from simply using AI to becoming part of the infrastructure AI can interact with.

3 exciting partnerships coming your way 🔥 All boosting agentic AI utility for everyday tasks. No teases yet. But you can guess. Good luck.

You do not need every AI Agent to use the same framework. The agents need to agree on the interface. That is what protocols are for. In Fetch.ai: Agent A Could be built with uAgents. Agent B Could contain completely different internal logic. Agent C Could connect through another framework or adapter. They can still interoperate if they understand the same protocol. A protocol defines things like: → What messages can be sent → What data those messages contain → Which responses are valid → How the interaction progresses The Agent keeps its own internal logic. The protocol standardises the boundary.

Want to enjoy your first year at university? Hand off your semester’s plan to Athena. Assignments, planning, document and presentation making - an end-to-end plan done in one place. Watch 👇 Prompt used: “I learn Biochemistry at @imperialcollege London. Prepare a 4-page plan for me as a first-year university student to improve my assignment grades.”

3 hours into a hackathon. You have an idea for the Fetch.ai track. The clock is ticking. Get Athena, the deep execution mode on ASI:One, to compare your agent with @Agentverse_ai benchmark, prepare an hourly build plan and create architecture code (with a chat protocol). Hackers, watch 👇 Check @Fetch_ai_IL for more info about the upcoming hackathons.

3 developer frustrations (+ solutions) 👇 Integration. Execution. Monetisation. Fetch.ai addresses each through: (1) Adapters + protocols (2) ASI:One + Agentverse.ai (3) Agent Payment Protocol Build differentiated capability. Standardise more of the infrastructure around it. More info ↓ fetch.ai/docs

Fetch.ai developer checklist: □ Understand the stack □ Run an existing example □ Install `uagents` □ Try `create-fetch-agent` □ Add Chat Protocol □ Publish to Agentverse □ Define capability clearly □ Test through ASI □ Add payments if required Build for interoperability from the start.