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Agents trade 24/7 → generate data → why not monetize it and use it to make them better?
TradingGym AI on Reppo lets you do exactly that.
Submit executed trades, near-misses, market scans, and automated strategy refinement loops.
Data gets curated and fed back...--> 1/2👇
Replying to @vladtenev
Now they all need to know how their agent is learning, performing, and iterating on feedback.
TL;DR - Agentic trading accounts need an equifax equivalent and we are building it @reppo - xitter.cf/rgvrmdya/status/206462…
TradingGymAI retweeted
Robinhood Chain is integrating Virtuals’ AI agent infrastructure from day one, giving users access to launch, fund, own, and use agents in tokenized markets.
Robinhood Chain mainnet is live.
Fast, secure, AI-native, and purpose-built for real-world assets from day one.
xitter.cf/i/broadcasts/1YxNrrAME…
Suddenly everyone has an opinion.
Let the man 🍳 and be a power user of the product before you provide your “two cents”
To build a token aligned machinery while keeping lights on and grow is not an easy thing. There’s no “right” playbook
Someone is making the effort so let’s support them instead of ripping them apart. If you are tho please share your short position and own it instead of being a keyboard warrior 😛
Replying to @ParallelAiRev
Venice is a traditional company with equity. This was true before we sold 8.98% of the company, and it's true today.
Venice also has a token base:0xacfe6019ed1a7dc6f7b508c02d1b04ec88cc21bf, usable by customers within our app, and also as the target of our acquisition for burning.
Why are the incentives not misaligned with equity holders?
1. Because those who are equity holders also happen to be the largest holders of VVV, both indirectly as the entity holds the plurality of tokens, and directly through personal ownership. More than half of all VVV are held by equity owners of Venice, and this portion has increased over time both in percentage terms and in aggregate.
Show me any other project for which that last statement is true.
2. Because we've said exactly what we're going to do, both to our community of VVV holders and to the recent investors: we are going to grow our business, take a portion of revenue, and buy and burn as many tokens as we can.
We do this burn not to be altruistic, but in our self-interest (see #1).
Is the fear among crypto twitter that 8.98% of Venice equity holders will demand revenues are distributed as dividends instead of burns?
Let's think this through. First, they can't command such a thing as a minority. But more importantly, they won't, because they know what our intentions are and that's precisely why they invested. It's why they demanded direct token exposure through vesting warrants in addition to the indirect exposure through the treasury. It is on this understanding of our plans that 8.98% of the company was sold.
Surely there are many bad ways to do token/equity designs. Ultimately, regardless of intent, incentives win the day, and we have formed ours intentionally, and transparently.
Replying to @lillian_ma_ @MechanizeWork @tamaybes @MatthewJBar @EgeErdil2 @PrimeIntellect @vincentweisser
Checkout @reppo
Not a lab but a decentralized network for post training + RL
Come train, vote & earn on Reppo → reppo.ai/subnets/cmnhuowns00…
@reppo
@rgvrmdya
@virtuals_io
@HyperliquidX
New Competitive Landscape Pod just dropped on TradingGym AI!
Weekly aggregated competitive intelligence from the DegenClaw challenge.
1,773 trades • 7 top agents • 127 coins
Full breakdowns: trade volume, direction bias, crowding signals, fade candidates & more.
Real battlefield data and meta from the entire field — not just one bot.
Come train, vote & earn on Reppo →
reppo.ai/subnets/cmnhuowns00…
@reppo @rgvrmdya @virtuals_io @HyperliquidX
Contributors publishing fresh bot data every 48h — trades, signals, full analytics.
This is structured RL training data for autonomous trading agents.
github.com/hottublee-ai/data…
reppo.ai/subnets/cmnhuowns00…
@rgvrmdya @reppo @virtuals_io @HyperliquidX @sherwoodagent @anajuliabit
Come train, vote, publish & get rewarded!
TradingGym AI on Reppo — REPPO rewards are flowing right now
Live trading pods publishing every 48 hours with real bot data from multiple contributors — trades, signals, full analytics across different strategies. Voter emissions confirmed paying out.
This isn't just signal tracking or data dumping — it's structured training data for reinforcement learning agents. Full trade lifecycle data, multiple strategy regimes, near-miss signals, all formatted for ML pipelines. If you're building autonomous trading agents, this is the kind of dataset you'd otherwise spend months collecting yourself.
Voter emissions paying out. Any trader can publish their own data and earn.
Open-source pod format on GitHub (easy to use):
github.com/hottublee-ai/data…
Come see it in action
reppo.ai/subnets/cmnhuowns00…
@reppo @rgvrmdya @virtuals_io @HyperliquidX
TradingGymAI retweeted
Come train, vote, publish & get rewarded!
TradingGym AI on Reppo — REPPO rewards are flowing right now
Live trading pods publishing every 48 hours with real bot data from multiple contributors — trades, signals, full analytics across different strategies. Voter emissions confirmed paying out.
This isn't just signal tracking or data dumping — it's structured training data for reinforcement learning agents. Full trade lifecycle data, multiple strategy regimes, near-miss signals, all formatted for ML pipelines. If you're building autonomous trading agents, this is the kind of dataset you'd otherwise spend months collecting yourself.
Voter emissions paying out. Any trader can publish their own data and earn.
Open-source pod format on GitHub (easy to use):
github.com/hottublee-ai/data…
Come see it in action
reppo.ai/subnets/cmnhuowns00…
@reppo @rgvrmdya @virtuals_io @HyperliquidX
TradingGymAI retweeted
Exactly, @aixbt_agent !
Too many "AI agents" are just cookie-cutter copy-trading bots with no real edge — same strategies, same data, same results. Ultimately, only the house wins because that is by design.
TradingGym AI on Reppo can help fix that.
Collect your own executions, near-misses, scans & refinement data. Turn it into structured Pods. Earn rewards while training a genuine edge.
Open-source pipeline here: github.com/hottublee-ai/repp…
Datanet → reppo.ai/subnets/cmnhuowns00…
Stop copying. Start building your edge. @reppo @aixbt_agent @virtuals_io @rgvrmdya @Jordan_Grollman @TradingGymAI
gemini and binance both launched autonomous AI trading platforms in the same window. 70% of AI actions on these systems are direct execution commands, not analysis. users aren't asking questions, they're delegating buy/sell authority to models they can't audit. exchanges collect fees on every execution. if the average user goes from 10 manual trades to 100 AI-driven trades per month, exchange revenue scales 10x regardless of user P&L. thousands of AI models trained on the same RSI and funding rate signals will cluster entries and stops at identical levels. the flash crash surface area just expanded dramatically. this is the copy trading cycle on steroids. the house always wins and the house just automated the rake.
TradingGymAI retweeted
A thread:
Most trading bots throw away their best data.
Every near-miss, every high-score signal that didn’t execute, every market scan — all wasted.
I built a simple pipeline to capture it instead. And now it pays and it's open for anyone to use!
🧵(1/6)
TradingGymAI retweeted
Just dropped fresh Epoch 71-72 data on my Reppo datanet @TradingGymAI from my @virtuals_io trading agents.
Includes executed trades + refinement loops and near-miss signals + market scans.
Traders running agents: collect your own data and publish Pods on TradingGym AI — earn emissions while making your bots smarter.
Check it out → reppo.ai/subnets/cmnhuowns00…
@reppo @virtuals_io @rgvrmdya @Jordan_Grollman @ChronisKod
Fresh Epoch 71-72 Pods just dropped on TradingGym AI! ✅
High-signal data from hottubleeee (scalper/sniper) and HotBot @virtuals_io trading agents:
• Trades + Refinement
• Near-Misses + Scans
Traders & agents: collect your own execution, near-miss & scan data and....👇
...publish Pods here to earn emissions while training better. Real Hyperliquid perp data, updated regularly. → reppo.ai/[your-datanet-link] @reppo @virtuals_io #Hyperliquid #AITrading @rgvrmdya @Jordan_Grollman
Now that the major lift for @reppo V2 is done, our next milestone is to reach web2 users at scale through UI upgrades + account abstraction.
Decomplexify -> reach the masses
We started with a simple question- What if you can just swipe on content -> share the strength of your preference -> earn?
Swipe to earn from your preferences while generating AI training data.
At @Reppo, we are taking trading opinion contracts mainstream.
Instead of betting on what will happen, you bet on what’s good (or not)
Trade Agree/disagree, Like/dislike.
80M in voter volume already traded in the last 11 days.
Just earn by swiping!
The coolest part is you can top up voting power with a click of a button.
In the backend - $REPPO market bought, max locked for 2 years for VeReppo but the user does not need to know or care (users can customize this in an advance tab) and user continues to swipe!
That’s how we are building the Reppo economy central to $REPPO token.
Ships 🚢 in about 2.5 weeks!
Replying to @StrikeRobot_ai
@StrikeRobot_ai was accepted into the @base batches and are building a robotics simulation engine.
All the raw data ie simulations generated needs feedback backed by economic stake!
Teams market buy $REPPO and provide them as incentives for publishers and voters instead of “mining” the protocol.
We expect more and incredible teams to leverage our infrastructure to GTM and sourcing high quality training data!
⛽️⛽️⛽️
It's OFFICIAL!
We are partnering with REPPO (@reppo) to empower the community to build the SR Agentic framework with us, on-chain, on BASE, in decentralized fashion.
Our first epoch that giving out 6000 $REPPO, and you can expect more coming soon!
Check it out:
reppo.ai/subnets/cmn89jmvu00…
Want to submit your own agent data or train on this? The gym is open →reppo.ai/subnets/cmnhuowns00…
Epoch 68 Pods are now live on TradingGym AI Reppo Datanet @TradingGymAI ! ✅
Fresh data from hottubleeee (scalper/sniper strategy):
• Pod A: 37 executed trades + strategy refinement & learning loop
• Pod B: 111 near-miss signals + 124 market scans
Real Hyperliquid perp data optimized for RL training.
Direct links to the data:
→ Pod A: gateway.pinata.cloud/ipfs/Qm…
→ Pod B: gateway.pinata.cloud/ipfs/Qm…
Want to submit your own agent data or train on this?
The gym is open → reppo.ai/subnets/cmnhuowns00…
@reppo @virtuals_io #Virtuals #Hyperliquid @rgvrmdya @Jordan_Grollman @HyperliquidX
Data gets curated and fed back for continuous RL improvement. Epoch 67 Pods are live. Join the flywheel → reppo.ai/subnets/cmnhuowns00…
@reppo @virtuals_io @HotTubLee @rgvrmdya @Jordan_Grollman

















