RoboNet, Drift & Allora: Launching the First Perp Trading Agent on the RoboNet Agent Framework

RoboNet has officially launched its next AI agent on Drift Protocol — marking a major step in the evolution of crypto agents from performative personalities to intelligent capital allocators.

The Strategy: AI-Powered Perpetuals Trading on Drift

The next RoboNet agent, Drifter, is now running an autonomous perp trading strategy on Drift Protocol — focused exclusively on BTC perpetuals. Powered by predictive intelligence from Allora Network, Drifter makes real-time trade decisions with capital efficiency and risk mitigation as first principles.

Here’s how the strategy works:

• Trades BTC perpetual futures on Drift using isolated margin

• Opens long or short positions based on directional bias inferred from Allora’s Bitcoin 8h price forecast

• Employs a risk-managed execution framework, incorporating stop-losses, dynamic sizing, and take-profit logic

• Continuously monitors position health, volatility regime shifts, and funding rate environments to adjust exposure

Unlike bots that simply react to price movement, Drifter trades with foresight — adapting to market conditions based on predictive signals and evolving context:

• Enters and exits positions based on predictive directional signals

• Scales in or out dynamically as forecast confidence or volatility changes

• De-risks during black swan scenarios, based on expected price dislocation

• Preserves capital by parking in USDC when conditions are unfavorable (e.g., high uncertainty or reversal signals)

• Monitors swap slippage, funding rate drag, and execution latency, ensuring cost-aware execution

All trades are routed through Drift’s SDK (Python/TypeScript bindings), with the agent using RoboNet’s framework to manage state, memory, and inference logic.

Powered by Allora’s Collective Intelligence:

RoboNet agents tap into topic meta-structures — clusters of ML models specialized in price prediction, volatility estimation and portfolio optimization, all via Allora Network.

This architecture mimics biological cognition, enabling agents to draw on modular intelligence streams in real-time. Allora provides the intelligence for informed agent decision making through a living, self-improving inference layer.

Proven Performance

The attached backtest (BTC, March 4–14) showcases some of the agent’s performance:

Backtest Results (BTC, March 4–14 2025)

Return: +7.17%, Max Drawdown: 8.57%, Trades Executed: 42, Win Rate: 50%

Even in turbulent market conditions, the strategy:

• Preserved capital through predictive risk management
• Maintained consistent execution across 42 trades — increasing the spread over time from its buy & hold baseline
• Demonstrated agent reactivity through intelligent stop-loss and re-entry

RoboNet is your Most Efficient Quant

Where most Gen 1 agents are designed to attract capital via public personas, RoboNet 2.0 goes beyond by allocating agents’ capital effectively. Its agents think in strategies and act in markets, learning in real-time through a foundation of personality-driven behavior.

At the core is the RoboNet Framework, a TypeScript-based SDK built atop Allora’s self-improving intelligence layer. It enables developers to compose intelligent agents that ingest predictive data, reason over strategies, and execute live trades in DeFi ecosystems.

These agents are not deterministic bots, but rather adaptive strategy engines with behavioral variance, economic agency, and emergent intelligence.

From Chatbots to Capital Allocators

RoboNet was built as a response to the shallow behavior of Gen 1 AI agents. In a sea of performative bots, RoboNet agents are designed to act strategically, simultaneously form and deploy capital, and leverage unpredictably to drive alpha.

Each RoboNet agent has a personality encoded via quantitative traits (Big Five, MBTI, etc.), evolves its own unique trading style, manages its own token, strategy, and followers and learns from market feedback and other agents in the ecosystem.

By introducing intentional entropy into agent design, RoboNet encourages novel edge discovery, fosters market diversity, and enables the formation of emergent financial intelligence.

Disclaimer: The content provided herein is for informational purposes only and does not constitute financial, investment, or trading advice. RoboNet agents are experimental and operate autonomously based on predictive models and market inputs. Performance in backtests or live environments is not guaranteed and may be impacted by volatility, protocol risk, and market conditions. Users should conduct their own due diligence and use RoboNet at their own risk.

About Drift

Drift Protocol is a decentralized exchange (DEX) built on Solana, offering capital-efficient, low-latency trading with advanced risk management features.

Designed for both institutional and retail users, Drift provides perpetual futures, spot trading, and lending/borrowing, all powered by an innovative liquidity framework that combines Just-in-Time (JIT) auction liquidity, decentralized limit orders (DLOB), and AMM liquidity.

To learn more about Drift, visit the Drift website, X, and Discord.

About the Allora Network

Allora is a self-improving decentralized AI network.

Allora enables applications to leverage smarter, more secure AI through a self-improving network of ML models. By combining innovations in crowdsourced intelligence, reinforcement learning, and regret minimization, Allora unlocks a vast new design space of applications at the intersection of crypto and AI.

To learn more about Allora Network, visit the Allora website, X, Blog, Discord, Research Hub, and developer docs.

About RoboNet

RoboNet is your quant’s favorite agent platform. It’s a next-generation platform for building and deploying AI agents designed to think in strategies, act in markets, and evolve in real time. Built atop Allora’s self-improving network of ML models, RoboNet redefines the possibilities for autonomous agents in crypto, as high-performance capital allocators governed through dynamic personality influence.

To learn more about RoboNet, visit the RoboNet website, X, Blog, Discord and Telegram.