Alan Sapède

What a week at @EFDevcon in Buenos Aires 🇦🇷 We kicked off with @ffarall giving a talk on “Beyond the Runtime – Unlocking the Substrate Node Potential" at @Polkadotsub0. Then @BridgetHearst moderated "The Age of Autonomous Economies: How AI Agents Will Redefine On-Chain Payments" at @openagisummit Huge congrats to Moonsong's very own @tomimorenox and the @zksync team for winning the @UniswapFND Cup 🏆⚡️ And we closed out the week at our Living Knowledge Café y Conexiones with @aleph_im @miranetwork @Gaianet_AI @ZKamigos. Thanks to all that attended! Buenos Aires delivered. On to the next. 🌙💫

🚂 Introducing Agent Prompt Train 🚂 An open-sourced high-performance proxy that works with Claude Code to help turn it from a single-developer tool into a collaborative development platform. Claude Code changed the game. Now, Agent Prompt Train is here to help teams: ✅ Log every conversation for review ✅ Analyze & optimize prompts with AI ✅ Turn best practices into reusable team commands ✨ The payoff: Smarter prompts, faster learning, and shared knowledge across your whole team. 📖 Read more on the blog & test it out 👇 moonsonglabs.com/blog/agent-…

🤖 What are AI Agents? At their core, they’re autonomous software systems that can perceive, decide, and act in pursuit of a goal—without constant human input. At Moonsong, we’re exploring a few distinct ways to think about agents—and those perspectives are actively shaping how we build. Read more in our latest blog post ⬇️ moonsonglabs.com/blog/what-a…

You’ve probably heard a lot about AI agents recently. With advances in LLMs and automation, we’re seeing software programs capable of setting and achieving goals independently—taking automation to a whole new level. So, what exactly are AI agents 🤖 and why are they interesting🤔? AI agents are autonomous programs powered by LLMs, designed to perform tasks on their own. They’re given goals and use AI-based reasoning to figure out how to achieve those goals—without ongoing human intervention.💡 These agents don’t just think—they act. They can use tools like external API calls or execute actions on Web3 platforms. By observing the effects of their actions, they create feedback loops, learning and adapting as they go. An AI agent with its own X account, posting with specific objectives… check out @truth_terminal and @luna_virtuals—both generating posts autonomously and working toward their own goals.✨ AI agents are catching on in enterprises  💼, too. Companies are deploying them for complex tasks like customer support, data analysis, and back-office operations—tasks that traditionally needed human oversight. In the coming years, we expect a proliferation of AI agents across different domains. Many will operate in controlled enterprise environments, but others will interact openly on social media and blockchain networks. 🌐 This shift opens up enormous potential to build agent-centric infrastructure. These agents are becoming a unique type of ‘user,’ and as their numbers grow, so will the need for protocols designed specifically for them. At Moonsong, we’re focused on this agentic future, building the tools and infrastructure needed to support it. Follow us to stay updated as we explore the possibilities of an agent-driven world.🌍

In our latest blog by @jayfarei, we present Unravel—a prototype to decode Ethereum transactions and improve user clarity. You can check it out at unravel.wtf!

🚀 Introducing @klusterai: the distributed platform for large AI models! 🧠 Built at the intersection of Web3 and AI, @klusterai breaks free from computational constraints to enable seamless, large-scale model workloads. @klusterai empowers developers to run and tune large AI models on a distributed compute grid sourced by GPU providers from all around the globe. Explore the inception story of @klusterai and delve deeper into its vision in the latest blog post by @derekyoo. You can read the full post ⬇️ moonsonglabs.com/blog/kluste…