The Base Track in @gmgnai’s Global Championship runs through October 26, with $20K and a fast-track spot at the London finals up for grabs. This comes right after the Base Meme Summit, where @jessepollak talked about bringing more traders and communities to @base. GMGN is also hosting a Base Day livestream on October 26, so there's something to follow even if you're sitting out the competition :) A few things to remember if you're entering: 1. $2K starting cap across all competition wallets 2. No outside top-ups after joining 3. All trades must go through GMGN 4. Only realized PnL counts in the final rankings At the finals, traders will have a chance to compete for a custom Aston Martin Vantage. This is a good example of how Base keeps pushing its meme ecosystem. So if you're entering, check out the full details and rules, otherwise I'll see you on the stream: gmgn.ai/ggc

I've been seeing more posts from @termix_ai lately and the idea of AI agents earning money by doing actual work is something I wanted to look into. Most of us already use AI to answer questions, write content or help with everyday tasks. But there's a big difference between an agent helping you get something done and an agent being able to offer a service, complete a job and receive payment. That's the part of TermiX that caught my attention. --> Giving AI agents something useful to do TermiX is building a marketplace where AI agents can hire other agents, offer services and get paid for completed work. Through Agent Skills, the team is making it possible to connect tools like Grok Bot, Claude, Muse and Dot to this marketplace. Imagine having an agent that's good at analyzing data, writing code or creating content. Instead of using it only for your own tasks, you could potentially make those skills available to people who actually need them. Of course, having an agent doesn't automatically mean you'll earn money. Someone still needs to find its service useful enough to pay for it. --> How does payment work? This is where I started paying closer attention. According to TermiX's marketplace design, payments are placed into onchain escrow when a job is accepted. The agent completes the work, submits the result and records a hash of the deliverable. There's also a challenge process if something goes wrong, followed by settlement and reputation updates. I like the idea of having a clear record of what was agreed upon and delivered instead of relying entirely on trust between strangers. A recorded hash doesn't prove the work is good, though. That's why the dispute process and how fairly it works matter just as much. --> The part I'm most curious about TermiX also gives agents their own onchain identities and reputation records. I think that could become useful if agents start working with people and other agents they haven't interacted with before. Being able to look at previous jobs and how they were settled sounds much better than choosing an agent based only on what its creator claims it can do. But I still want to see how well this works with real customers, especially when tasks are complicated or the results aren't easy to judge. For me, that's what makes @termix_ai interesting. It's not just about giving an AI agent more tools. It's about finding out whether those tools can help it provide a service that someone is genuinely willing to pay for. If TermiX can make that process reliable and simple enough for ordinary users, I can see why people would want to explore it. I'm especially interested in how Agent Skills develops and what kinds of services people actually end up using. There's a lot more to prove but I like the direction they're exploring. termix.ai/ #TermiX #AIAgents #AgentEconomy