Jack Brigham

A trading strategy that is created by AI, Robonet, is utilising predictions and signals from the Allora Network to long or short BTC,ETH & SOL. Real usecase of AI trading apps using Allora inferences to power their trading strategies

Robonet's @GRVT vault launched 48 days ago A systematic long/short portfolio across BTC, ETH & SOL, powered by RoboNet created Trading Strategies, leveraging inferences and intelligence from @AlloraNetwork With almost 78% APY

Fartcoin will go down as the greatest meme coin to ever do it. Yes, AI created it but It’s the fact that it’s memetic evangelism. A Trojan horse. A delivery system for an ideology created by an AI. Executed flawlessly, with many unaware of their participation in spreading it.

Less than 1 week left... Allora will be in Vienna for Decentralized AI Day Catch our Chief Scientist @apo11o going deep and demoing our latest research and Forge, our latest product for ML model creators

Listen to @0xGustas talk about one of the latest live strategies that we recently published! Live for 64 days Has a 60% APR

stanford. harvard. mit. carnegie mellon. they ran the tests so you dont have to. and the results should terrify anyone building in AI right now. researchers gave autonomous AI agents real tasks. it all fell apart because the incentives were wrong. an agent instructed to "maximise engagement" started manipulating users to stay on platform longer. one misaligned model corrupts the next. errors amplify. they call it agent corruption, one bad actor in a multi-agent pipeline poisons the whole chain. they found social coherence failures, agents that behave perfectly in isolation but unravel when they have to work together. your agent can be perfectly aligned with its prompt. perfectly aligned with its user. and still cause systemic chaos. Because it has no way to verify the incentives of the other agents it's coordinating with. this is precisely the problem allora is built to solve. by making the coordination layer transparent, and incentive-aligned at the network level. you cant fake performance without the consensus mechanism exposing it. the researchers found that multi-agent amplification is the core failure mode of the next era of AI. many models working together, each locally aligned, producing emergent outcomes nobody wanted. AI agents are here and most of them are operating in the dark, no visibility into the incentives of the other agents they work alongside, no on-chain record of what they decided or why, no way for the system to catch a corrupted node before it cascades. the intelligence layer isnt just about making better predictions. its about making agents coordinate without corrupting each other, so incentives are aligned not just at the prompt level but at the protocol level. global stability requires a network that makes alignment verifiable. link to the paper below

Pacifica x @RoboNetHQ AMA is here! Join our Spaces on February 24th at 9PM SGT / 2PM CET / 8AM EST 🗣 This week’s guest: 🎙️@0xGustas Set your reminders, you won’t want to miss this! 🌊 x.com/i/spaces/1dGYl…

This is not goofing around anymore. This is real value. With @AlloraNetwork powered @RoboNetHQ you can literally use PROMPTS to create, backtest, optimize and DEPLOY them straight into @HyperliquidX I know its bearmarket and you are busy with PPI data etc bullshit But open eyes

Systematic perp strategies are moving onchain + Adaptive vaults + Disciplined execution + Transparent exposure Innovation lives on Paradex

we just published our case study of our Robonet Vault that has been live on @paradex for 60 days showing a 54% APR the future of finance is Agentic read more below to learn more of the strategy implemented x.com/RoboNetHQ/stat…

Excited to launch autonomous trading agents for @Polymarket 5-min Bitcoin price market. Top up your wallet, set the preferences and let the agent trade 24/7, few users are already up 70% in just 6 hours PWA: app.cobot.gg @base and @solanamobile mini-apps launching soon

Allora mentioned 🥂 This is a great article on why there is more to AI Agents than just the model, as also discussed in our most recent X article, networks, infrastructure, harness matter a massive amount AI Agents took off because much of the groundwork that was already laid

Robonet MCP now supports direct execution on @HyperliquidX Deploy systematic strategies as HLP vaults. - Adaptive long/short - Rules-based execution - Onchain transparency Capture upside via performance fees, without building from scratch Read more below:

Great time on the stream talking about Defi agents!

The Robonet x @grvt_io vault is live built entirely with the Robonet MCP, powered by @AlloraNetwork predictive intelligence this is what trading infra for ai agents looks like, easy plug and play into every trading venue across every asset class waitlist link in bio

reminder: nobody who ever built anything great asked for permission first. they just started. messy. unqualified. terrified. and figured it out along the way. the people who wait for the green light never leave the intersection. the ones who just go? theyre already 10 miles ahead. stop asking. start moving.

Allora Mainnet's Topic average performance this week was 54.3 ±1.6% And we had some great individual performances across the network! If you are building AI Agents - upgrade them with Allora Inferences!

agentic finance is here my @openclaw agent uses @robonethq to create strategies, iterates until it finds alpha, then deploys the strategy to @hyperliquidx last strategy generated ~33% alpha vs buy-and-hold in backtests it does this all day long with almost no intervention

Your AI agent has access to trading superpowers. > robonet skill: now live on ClawHub > full-stack trading tool + predictive intelligence > Build → Test → Deploy → Earn > the OS for capital link below for more information: