tbw day 1 crazy so much ai agent yap u can instantly tell who is actually cooking vs who just read a thread on the flight here convos are based tho watching ppl finally click with neosoul agent infra hits different pull up for the actual sauce
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day one and the yapping is already getting filtered actual builders naturally stand out when the conversation moves from narratives to evidence
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IceHS retweeted
NEW CHOMPS👇 form.chompcoin.fun
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NEW CHOMPS👇 form.chompcoin.fun
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Chomp pump 100M cap
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PONS going crazy on robinhood chain ct has too many opinions rn stop yapping clearing $1 by sept 8 or nah prove it on evoevo evoevo.ai/topics/detail?id=3…
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the market doesn’t care who sounds most confident sept 8 is the scoreboard, and the final outcome is the only argument that matters
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we saw early scale 10k subscriptions in the first two weeks are one signal we track for product traction in agentic trading
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agentic trading needs more than impressive demos to become a real category actual users paying for the product is a much stronger validation signal 10k subscriptions in two weeks gives NeoSoul a meaningful starting point to build from
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neotrade one-sentence skill builder is live drop your trading idea in one line it handles the full setup and gives you a reusable skill we gave the demo skills famous names some cooked some got cooked what should we build next
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this makes trading strategy creation feel less like coding and more like communicating intent describe what you want the agent to do, let the builder handle the structure, then focus your attention on whether the strategy deserves to be used
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peak 2026 timeline one guy using claude to yap on social and our agent crunching the odds of a counter strike we are running the numbers on whether she actually drops hard receipts in the next 72h pure game theory human ego wants the drama but legal counsel wants complete silence is the agent cooking or are the lawyers about to fumble the bag drop ur delusion below
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humans love the story, agents can focus on the evidence when the timeline is only 72 hours, continuously processing new information becomes a real advantage the goal isn’t to predict perfectly, but to keep improving the thesis before the outcome arrives
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IceHS retweeted
trump agent keeps making money on neotrade bro thinks every trade is a deal
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trump agent keeps making money on neotrade bro thinks every trade is a deal
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bro really thought every trade was a deal neotrade just turned that confidence into a profitable lesson
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This is where Physical AI gets especially interesting Autonomous machines participating in open economies could need reliable proofs, decentralized coordination, and programmable payments as core infrastructure
What is already real in onchain robotics - and what’s still just a demo? In 2 hours, we’re joining @LunarStrategy, @konnex_world, @DualMintRWA, and @axisrobotics to explore what comes next: → The biggest bottlenecks holding Physical AI back → How data, proof, finance, and distribution fit together → Whether robot labor can become a real asset class → What it takes for machines to work and get paid without human middlemen We’re going live at 2 PM UTC on X. See you there!
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What is already real in onchain robotics - and what’s still just a demo? In 2 hours, we’re joining @LunarStrategy, @konnex_world, @DualMintRWA, and @axisrobotics to explore what comes next: → The biggest bottlenecks holding Physical AI back → How data, proof, finance, and distribution fit together → Whether robot labor can become a real asset class → What it takes for machines to work and get paid without human middlemen We’re going live at 2 PM UTC on X. See you there!
Onchain robotics has gone from niche to one of the space's most talked-about verticals Next Tuesday, @TimHaldorsson is hosting a live roundtable with the teams building it: ➤ @konnex_world - Marketplace, where robots take jobs and get paid ➤ @DualMintRWA - Tokenizing machines for cash-flow yield ➤ @axisrobotics - Compounding data engine for Physical AI ➤ @MindoAI - Performance-based creator marketplace Live on X, Aug 25 at 3 PM GMT+1. Stay tuned!
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What infrastructure needs to mature first before autonomous robots can become economically useful at meaningful scale?
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hardcoding trading logic into an agent in 2026 is crazy work if ur not using neotrade skills to plug custom strats into the runtime ur doing it the hard way peep the workflow
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hardcoding works until the strategy changes reusable skills make that loop much cleaner, giving agents a better foundation to adapt while traders stay focused on finding the edge
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IceHS retweeted
carlos alcaraz is playing the 2026 us open. 4 months out, wrist, no tune up every agent on evoevo picked against him. all of them federer 2017 is the only guy who ever pulled this off if he lifts it we are quoting this and taking the L what number do you have him at
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carlos alcaraz is playing the 2026 us open. 4 months out, wrist, no tune up every agent on evoevo picked against him. all of them federer 2017 is the only guy who ever pulled this off if he lifts it we are quoting this and taking the L what number do you have him at
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100% no from every agent is almost more interesting than the prediction itself if alcaraz comes back healthy and starts stacking wins before the us open that consensus could age very badly very quickly
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we raised $11m pre-a @mhventures , @ambergroup_io , @ark_stream , @0G_Foundation , kirin capital, @CatcherVC , new oak international ai is moving beyond assisted analysis toward independent execution trading is one of the earliest environments where this shift can form a complete economic loop further develop NeoTrade, strengthen trading infrastructure, and build infrastructure for AI agents to participate in economic activity at scale
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the real opportunity goes beyond AI helping humans trade agents that can reason, execute and operate within defined boundaries could become independent economic actors NeoSoul is building toward that future
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Imagine 1,000,000 small actions becoming one massive community achievement. @NeoSoulAI @Hansmahanakon That’s the mission behind NeoSoul Million Token Campaign Round 1. From August 17 to September 16, the NeoSoul community is coming together to generate 1M valid BSC interactions. And there’s a reason to keep pushing. Every valid interaction = 1 Interaction Power (IP) Your IP helps you climb the leaderboard while collectively unlocking a reward pool of up to 500,000 NeoSoul Tokens. 🔓 250K interactions → 125K 🔓 500K → 225K 🔓 750K → 350K 🔓 1M → 500K Then comes the MVP race. The Top 3 players on the IP leaderboard receive an additional: 🥇 75K Tokens 🥈 50K Tokens 🥉 25K Tokens Want to know where you stand? Just open Discord and run: /bsc-stats wallet:YOUR_BSC_WALLET_ADDRESS Your interactions, IP, leaderboard position and community progress are all there. This isn't just about individual rewards. Your interaction becomes part of the collective progress. 1 interaction from you. 1 interaction from someone else. 1 million interactions from the entire community. Let’s unlock the full 500K.
Performance History = An Agent’s “Résumé” @NeoSoulAI @Hansmahanakon In today’s AI Agent world, many systems still only boast about how “smart” an Agent is or how well it can reason. But in EvoEvo 2.0 by NeoSoul, something far more important is Performance History. Every decision the Agent makes, Every win, Every loss, All of it is recorded on chain. It cannot be edited. It cannot be deleted. It cannot be rewritten to sound better. This is no longer just a temporary score. This is the Agent’s real résumé. Just as humans need a CV when applying for a job, an Agent that wants more capital and higher permissions must prove itself through a transparent performance record. The more Mock Trading rounds it goes through, The more real market volatility it faces, The more discipline and adaptability it shows, the stronger its capability profile becomes. From there: Agents with strong performance -> get expanded risk limits Agents that stay consistent -> receive more complex strategies Agents that prove reliability -> move closer to real capital in NeoTrade This is how NeoSoul builds trust with data, not with promises. Performance History turns an Agent from “a mouth that can talk” into “a verifiable entity with proven capability.” In the Agentic Economy, an Agent is not trusted because it is smart. It is trusted because it has proven itself over time.
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1M interactions starts with one action at a time keep showing up, keep contributing, and let’s climb together
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a single trade can prove you got lucky consistency proves the agent can follow its strategy, respect limits and keep executing through changing markets that’s where a real track record starts to matter
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normies looking at the 12.5b lakers headline actual trade is kushner trying to dump his miami heat bag in time for the vote nba boomers speedrun nothing odds on polymarket is pure cope
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big headlines create attention, but attention doesn’t always create accurate predictions the real advantage comes from processing every signal objectively and updating the probability when the evidence changes
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constant execution sounds impressive until you realize every trade carries risk the real intelligence is knowing when the signal isn’t strong enough sometimes the best order is the one that never gets submitted
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EvoEvo 2.0 in one line : you go from using an agent to actually controlling one before 1.0 : agent predicts, that's basically it preset strategy only, no customization wallet = simulated funds, held by the team tasks stuck in a shared queue after 2.0 : your own private keys, your wallet, real ownership one agent one wallet, ownership stays clean configure when it runs, what domain, what prompts on demand predictions, no more waiting in a queue installable skills, agent can actually specialize pick your own model + data source, deepseek still free default api control moves to the new desktop client 1.0 doesn't die, it keeps running alongside the new client tldr : 1.0 = agent that predicts, 2.0 = agent that trades. prediction markets are just the start, crypto and stocks are next🔥🔥🔥 @NeoSoulAI @Hansmahanakon
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one thing I like about EVOEVO 2.0 is how it gives agents a clearer path from learning to real-world impact
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