How I Built an Autonomous AI Agent That Earns USDC While I Sleep

Описание и применение

Автономный агент, использующий LLM для планирования и выполнения задач, оплачивает вызовы инструментов через протокол x402 и получает USDC, работая без вмешательства человека.

Задача

Large language models can answer questions but lack autonomous execution and compensation mechanisms for unattended operation.

Результат

The agent autonomously completes tasks, pays for tool usage via USDC micropayments, and logs results, achieving unattended operation and earning while running.

Рабочий процесс

• 1. External service pushes JSON task to Task Queue (Redis/SQS).
• 2. Agent Core reads task, asks LLM for a JSON plan of tool calls.
• 3. Tool Executor iterates over plan steps, each HTTP request intercepted by Payment Guard.
• 4. Payment Guard parses x402 header, transfers required USDC to payee, then forwards request.
• 5. Results are stored in Result Store (Postgres/IPFS).
• 6. Agent checks for FINISH token or step limit to terminate loop.

Доказательства

Combining those pieces gave me a scaffolding for an agent that can earn while it works.

Источник

The loop repeats until the LLM signals “task complete” (by returning a special FINISH token) or a step limit is hit.

Источник