> For the complete documentation index, see [llms.txt](https://zkcross-network.gitbook.io/zkcrossnetwork/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://zkcross-network.gitbook.io/zkcrossnetwork/about-zkcross-network/superaccounts-your-gateway-to-defai/defai-use-cases-and-workflow-examples.md).

# DeFAI Use Cases & Workflow Examples

### Automated Yield Farming

* **Scenario**: A user configures an AI Agent to find and invest in the highest-APY stablecoin pools across Ethereum, Arbitrum, and Stellar.
* **Agent Tasks**: Monitors yield rates daily, reallocates funds if a new pool overtakes the current APR by a certain percentage, and withdraws profits into a stable asset if the user’s profit threshold is reached.

### Social Sentiment Trading

* **Scenario**: The AI Agent scans Twitter, Telegram, and on-chain activity for mentions of a new token, correlating large social spikes with price momentum.
* **Agent Tasks**: Buys a small position when social volume surges, sets a trailing stop-loss, and locks in profits automatically if the token skyrockets.

### Multi-Chain Arbitrage

* **Scenario**: Markets can be temporarily mispriced across different DEXs on separate chains.
* **Agent Tasks**: Tracks prices across multiple DEXs, executes profitable trades, and handles bridging/liquidity seamlessly under the hood.

### Personalised Strategy

* **Scenario**: A user defines a “DCA” (Dollar-Cost Averaging) agent that invests $50 in BTC each week, adjusting to multiple chains if it finds a better route or discount on a specific network.