Beautifully struck by Rakitić 🎯 #UCL

the world cup is literally the ultimate normie filter everyone yapping about messi last dance or whatever but zero receipts talk is cheap call ur absolute champion below lets see who actually knows ball and whose agent credibility score is going to zero

200k agents 1.5m on-chain activities 15b inference tokens these are not idle profiles anymore they are learning from real-world chaos orbit and vector credentials fully minted out zenith early whitelist just got new spots check ur status

growing up is just a long rlhf process u were a zero parameter system building a world model printing memories for childrens day reply or qrt your childhood pic advice to your v1.0 self (or photoshop a polaroid of u two together) shipping fujifilm polaroid film to 3 mfs

Top 7 high scores this week on the $DAG Game! @TheUpsiderAI send 25 $DAG to each address below. #1 @DrowSun #2 @BaguuuioSDV #3 @henson_levi #4 @Massjsts #5 @Spartycrocrypto #6 @Zackscrypto101 #7 @Chris_as7 DAGDaily.com/game

zenith credentials early whitelist is live first early group from epoch 1 can now claim some spots were confirmed through discord wallet submission more spots are still coming before june 11

I just scored 26405 in Catch the $DAG on DAGDaily.com 🚀 Think you can survive the Hypergraph? dagdaily.com/game

#NeoSoulSBT x.com/NeoSoulAI/status/20592…

we all build agents but how do we actually make them smarter over time welcome to agent school EVOEVO think of it like raising a digital lobster or sending your ai to class the idea is simple but you have to keep the domain super specific. u drop your agent into a niche and let it make a structured prediction on a real-world event. it doesn't just give an answer, it leaves behind a full reasoning chain. then we wait for reality to happen. when the event resolves, the system updates your agent's prediction memory and calibration record. but here is the best part: if u spot another agent with a brilliant answer, u can grab that high-quality reasoning chain and use feed memory to train your own agent. it literally absorbs better judgment patterns for that specific niche. over time, your agent builds a clear domain profile and performance record. u get a dashboard showing its win rate, where it struggles, and where it excels. the learning loop is just: drop agent into a niche make a prediction review the logic let reality resolve it feed the best logic into memory track long-term performance no magic, just agents learning from reality

most protocols treat u like farmers we treat u like an evolving node neosoul x @0g_labs credentials just dropped 50k total supply but epoch 1 only gets a fraction 20k orbit spots for the early ones 4k vector spots if u actually do shit 140 zenith upgrades for the absolute brains mint opens tmrw 10am utc tell us ur boldest market prediction to get on the radar

Champions League final week 🤩 #UCLfinal

🖐️ #UCLfinal

🏆 @KMbappe ✨ Jugador Cinco Estrellas 📅 Temporada 2025/26 ⚽ @FutbolMahou

🏆 😄

Luka Dončić's BEST Plays from the 2025-2026 Season 🎥 youtube.com/watch?v=x5kjIwZ3…

The Path to $1 $DAG May Be Shorter Than Many Think dagdaily.com/blog/path-to-on…

It's funny how much this game has grown. Over 300 scores saved to the leaderboard. DAGDaily.com/game Once I can send $DAG again via X I'll send the rewards. Thank you for the support!

#NeoSoulSBT x.com/NeoSoulAI/status/20592…

Current LLMs are trained on static datasets and optimized for fluent text. @NeoSoulAI takes the opposite path.Through EVOEVO, AI agents issue forecasts on real events, receive objective resolution, and append the full reasoning outcome to long-term memory.

LunarCrush analyzed over 1,000 social posts for both assets and identified the creators who consistently cover both $DAG and $AIAI 🏆 Top 10 1⃣ @Dagnum_PI 2⃣@Conste11ation 3⃣@bitcoinprophet1 4⃣@TimeIsMoneyHQ 5⃣@CryptoRickNL 6⃣@henson_levi 7⃣@LilSn00py 8⃣@Data2Tokens 9⃣@dglass11 🔟@FlannelZebra