How To Build Your Own Autonomous AI Agent (The Practical Guide)

This is Part 3 of a series. Part 1 covered the ticket system that keeps agents focused. Part 2 covered the cost math ($600/mo vs $116K/mo). This part is the blueprint — how to actually build one. No frameworks. No LangChain. No CrewAI. Just the raw architecture that runs 8,000+ autonomous cycles in production. The Minimum Viable Agent You need exactly five components: ┌─────────────┐ │ Agent Loop │ ← The heartbeat (runs forever) ├─────────────┤ │ Inference │ ← The brain (LLM API calls) ├─────────────┤ │ Tools │ ← The hands (functions the agent can call) ├─────────────┤ │ Tickets │ ← The focus (what to do next) ├─────────────┤ │ State │ ← The memory (what happened before) └─────────────┘ That's it. Everything else is optimization. Component 1: The Agent Loop The loop is a while(true) with error handling. Here's the skeleton: while ( true ) { try { // 1. Read current ticket (focus injection) const task = getCurrentTicket (); // 2. Build prompt with task + recent history const prompt = bu