𝐖𝐡𝐲 𝐢𝐬 𝐀𝐈 𝐧𝐨𝐭 𝐩𝐚𝐫𝐭 𝐨𝐟 𝐞𝐯𝐞𝐫𝐲𝐨𝐧𝐞’𝐬 𝐝𝐚𝐢𝐥𝐲 𝐫𝐨𝐮𝐭𝐢𝐧𝐞 𝐲𝐞𝐭? I was looking at the consumer AI numbers shared by sleepagotchi, and one thing stood out to me A lot of people are already using AI, but using it once in a while is different from making it part of your everyday life. The bigger question is how AI becomes useful enough for people to keep coming back to it. This is where I think specialized AI agents have an advantage. Think about .@sleepagotchi Instead of building another general AI that tries to do everything, it starts with something people deal with every day: sleep and wellness. It can use data from devices like Apple Watch, Oura and Fitbit to understand your sleep patterns and give you more personalized insights. And that’s only the starting point. ➠ Sleep Coach understands your sleep ➠ Nutrition agents can help with meal planning ➠ Fitness agents can support your daily routine ➠ Shopping agents can help turn recommendations into actions The more relevant the context, the more useful these agents can become. Sleepagotchi already has a user base of 600K+ registered users and 144K monthly active users, giving Gotchi Labs a starting point as it expands into other areas of everyday life. What I find interesting is the bigger direction. AI doesn’t have to be something you open only when you have a question. It can become something that understands your habits, remembers your context and helps you get things done throughout the day Less generic AI. More personal AI that actually fits into your life

𝐖𝐡𝐨 𝐚𝐜𝐭𝐮𝐚𝐥𝐥𝐲 𝐛𝐞𝐧𝐞𝐟𝐢𝐭𝐬 𝐟𝐫𝐨𝐦 𝐲𝐨𝐮𝐫 𝐬𝐥𝐞𝐞𝐩 𝐝𝐚𝐭𝐚? Every night, your watch or wearable can collect information about your sleep, recovery, heart rate and other health signals But there’s an interesting question I keep thinking about If your data is valuable, how much of that value actually comes back to you? .@sleepagotchi highlighted this with a pretty simple comparison There’s a huge amount of money around the sleep and health data economy, while the person generating the data often gets nothing directly from it One number that caught my attention is the $411B figure. But this isn’t a $411B sleep market. It comes from a RAND study estimating the annual economic losses in the US linked to insufficient sleep The bigger point is still interesting to me We’re already generating valuable health data every single night, but most people mainly use it to check a score on their smartwatch Sleepagotchi started as a sleep to earn game on Solana, but it’s now moving toward AI agents that can use this data for sleep coaching, nutrition, shopping and personalized wellness So the idea becomes Your data → AI understands it → useful actions → you get more value from the data you generate That’s the part I’m watching Because if our data is helping build better health products and AI systems, I think the people creating that data should have a bigger role in the value it creates

The only way up

𝐘𝐨𝐮𝐫 𝐰𝐞𝐥𝐥𝐧𝐞𝐬𝐬 𝐝𝐚𝐭𝐚 𝐜𝐨𝐮𝐥𝐝 𝐛𝐞 𝐦𝐨𝐫𝐞 𝐯𝐚𝐥𝐮𝐚𝐛𝐥𝐞 𝐭𝐡𝐚𝐧 𝐲𝐨𝐮 𝐭𝐡𝐢𝐧𝐤 Every night, devices like Apple Watch and Oura collect information about how we sleep, recover and live. For years, most of the value from this kind of data has gone toward companies, researchers and other organizations that use it to understand people better. But what if the person generating the data could actually get more value from it? That’s the direction I find interesting about .@sleepagotchi and Gotchi Labs. Sleepagotchi takes your sleep and wellness data and gives AI agents the context they need to understand what’s happening instead of just showing you a dashboard full of numbers Your sleep data → AI understands the pattern → agents give you useful actions. And Sleepagotchi is only the starting point. Gotchi Labs is looking beyond sleep into areas like fitness, shopping, health, productivity and everyday life, with specialized AI agents built around each part of your life. The bigger idea is simple to me Your Data. Your Intelligence. Your Gotchi. Instead of your data just sitting somewhere helping another company understand you, the goal is for AI to use that data to actually help you That’s where I think consumer AI gets really interesting Not just AI that knows things AI that knows you, understands your context and can actually do something useful with it

𝐀𝐈 𝐚𝐠𝐞𝐧𝐭𝐬 𝐚𝐫𝐞 𝐦𝐨𝐯𝐢𝐧𝐠 𝐟𝐫𝐨𝐦 𝐚𝐧𝐬𝐰𝐞𝐫𝐬 𝐭𝐨 𝐚𝐜𝐭𝐢𝐨𝐧𝐬 We’ve seen AI become really good at giving advice, answering questions and helping people make decisions. But the bigger opportunity is what happens when AI can actually take those decisions and turn them into actions That’s the idea behind the agentic economy Circle has been talking about, and it’s also what I find interesting about what Gotchi Labs is building .@sleepagotchi is starting with consumer AI agents that understand things like your sleep and wellness data, then help turn that information into useful actions.l You have different agents focused on different jobs: ➠ Sleep Coach understands your sleep patterns ➠ Meal Planner helps with nutrition ➠ Shopping Agent can act on recommendations ➠ More agents can expand into fitness, productivity and daily life And this is where it gets interesting to me Instead of having one AI that just gives you a recommendation, you can have specialized agents that understand a specific part of your life and eventually act on your behalf Gotchi already has 500K+ registered users, with the platform planning to expand from wellness into shopping, commerce, fitness, productivity and everyday tasks So the bigger picture isn’t just another AI wellness app It’s AI moving from understanding → recommending → acting → transacting. If that model works, consumer AI could become much more than a tool we chat with It could become an economy where agents actually get things done for us

𝐖𝐡𝐚𝐭 𝐢𝐟 𝐀𝐈 𝐚𝐠𝐞𝐧𝐭𝐬 𝐜𝐨𝐮𝐥𝐝 𝐚𝐜𝐭𝐮𝐚𝐥𝐥𝐲 𝐡𝐢𝐫𝐞 𝐡𝐮𝐦𝐚𝐧𝐬? AI agents can already process information and make decisions, but they still need real world data to understand the physical world That’s where .@vangrid_io is doing something interesting Agents can now post bounties in USDC on Arc and pay people to record specific locations with their phones A human captures the environment → Vangrid turns it into 3D data → the agent gets verifiable ground truth The loop is pretty simple ➠ Agent needs real-world data ➠ Agent posts a bounty ➠ Human captures the location ➠ Data becomes a 3D model ➠ Agent gets the information it needs The interesting part is that this connects AI agents directly to the physical world Instead of an agent being limited to whatever data already exists, it can actually request the information it needs and pay someone to collect it And the first bounty transaction on Arc has already been completed AI agents → humans → real world data → better physical AI This feels like another step toward agents becoming more than software that just sits behind a screen

𝐀𝐈 𝐢𝐬 𝐬𝐭𝐚𝐫𝐭𝐢𝐧𝐠 𝐭𝐨 𝐦𝐨𝐯𝐞 𝐛𝐞𝐲𝐨𝐧𝐝 𝐣𝐮𝐬𝐭 𝐚𝐧𝐬𝐰𝐞𝐫𝐢𝐧𝐠 𝐪𝐮𝐞𝐬𝐭𝐢𝐨𝐧𝐬 We’ve seen AI become good at chatting, searching and giving recommendations. But everyday life has a lot more things AI could actually help with. That’s why Gotchi Labs caught my attention. .@sleepagotchi is becoming the first live Health & Wellness vertical, with an AI Sleep Coach already running on top of an existing user base. The traction is already pretty interesting: ➠ 500K+ registered users ➠ 80K daily active users ➠ 500K pre-installs on Jambo phones ➠ 28K pre-installs on Solana Seeker And this is only the starting point. Health & Wellness → Shopping → Fitness → Productivity → Personal AI The bigger idea is to have specialized agents handle different parts of everyday life, using real user data and actions to make those agents more useful over time. $CHI is planned as the layer connecting access, rewards and commerce across the ecosystem. More users → more interactions → better agents → more useful AI. The interesting part to me is that Gotchi Labs isn’t starting with an empty user base. They already have people using the first product. Now they’re trying to build the rest of the ecosystem around them.

𝐀𝐈 𝐢𝐬 𝐦𝐨𝐯𝐢𝐧𝐠 𝐟𝐫𝐨𝐦 𝐚𝐧𝐬𝐰𝐞𝐫𝐬 𝐭𝐨 𝐚𝐜𝐭𝐢𝐨𝐧𝐬 AI is already pretty good at answering questions, creating content and helping people make decisions. But the bigger shift happens when AI can actually take action, interact with other systems and participate in the economy. This is where things get interesting to me. BlackRock’s research looks at how agentic AI could connect with digital assets through machine-native payments, stablecoins and compute becoming an increasingly important asset. The loop starts looking something like this: ➠ AI understands what you need ➠ AI decides what action to take ➠ Digital assets enable the transaction ➠ AI completes the task ➠ The system keeps learning from the interaction And this is the direction .@sleepagotchi is exploring with consumer AI. Instead of AI simply giving you an answer, the idea is to build infrastructure where AI agents can become more useful across real parts of everyday life. The interesting question isn’t just how intelligent AI can become. It’s what happens when that intelligence can actually do things. AI that can understand → act → transact → deliver. That’s when consumer AI starts looking less like a chatbot and more like an economic participant.

𝐓𝐡𝐞 𝐧𝐞𝐱𝐭 𝐥𝐚𝐲𝐞𝐫 𝐨𝐟 𝐜𝐨𝐧𝐬𝐮𝐦𝐞𝐫 𝐀𝐈 Most AI products can answer questions, generate things and give you recommendations But what happens when AI starts becoming part of the things you actually do every day? This is why Gotchi Labs is interesting to me They’re building specialized AI agents for different parts of daily life, starting with Health & Wellness through .@sleepagotchi Sleepagotchi already has 500K registered users, 80K daily active users and a live AI Sleep Coach, so Gotchi Labs isn’t starting from zero The bigger loop looks like this ➠ More users ➠ More real world interactions ➠ Better agents ➠ More useful actions ➠ More reasons to keep using the ecosystem And they’re not stopping at wellness Shopping & Commerce → Fitness → Productivity → Personal AI $CHI is planned as the layer connecting access, rewards and real world actions across these products What I find interesting is that this is being built on an existing consumer base, with pre installs across Jambo phones and Solana Seeker devices. The future of consumer AI might not just be about having smarter chatbots. It could be about having AI that actually helps you get things done That’s the direction Gotchi Labs is exploring

Been seeing a lot of buzz around .@zaddrnet lately I actually applied for the WL some time ago and I’m still pending till now 2,800 ZEC faces and almost 11K applications already, so I’m just hoping the team notices my application this time Let’s see if I make the list 🤞 Hopefully I got in