Back to AI Recipes

Autonomous Agent

AgentLoops

Agent

Self-directed agents plan, act, and observe to reach objectives.

Summary

The Autonomous Agent pattern implements a self-directed AI system that can pursue objectives with minimal human intervention. It follows a continuous loop of thinking (planning), acting (executing actions), and observing (processing feedback), allowing it to adapt its approach based on the environment's responses. This pattern is particularly powerful for complex tasks that require multiple steps, decision-making, and adaptation to changing conditions.

How it works

  1. Goal Setting: Define objective and constraints
  2. Planning: Agent develops step-by-step approach
  3. Action Execution: Performs actions via tools or APIs
  4. Observation: Processes results and feedback
  5. Reflection: Evaluates progress, replans if needed
  6. Iterate: Continues until goal achieved or resources exhausted

Agent capabilities

  • Tool Use: Call external APIs, run code, search web
  • Memory: Maintain context across interactions
  • Planning: Break down complex goals into steps
  • Reflection: Evaluate and improve own outputs

Use cases

  • Research assistants that can gather, analyze, and synthesize information
  • Task automation systems that can handle multi-step workflows
  • Virtual assistants that can complete complex requests through multiple actions
  • Problem-solving agents that can explore different approaches to reach a goal
  • Content creation systems that can iteratively improve outputs based on criteria
Code View

Autonomous Agent Implementation

// Autonomous Agent recipe using OpenAI
// Install: bun add openai

import OpenAI from "openai";

async function main() {
  const input = "Add your prompt here.";
  const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
  const system = "You are a senior AI engineer and technical writer. Apply the agent recipe to structure the reasoning and produce a useful result. Recipe: Autonomous Agent. Description: Self-directed agents plan, act, and observe to reach objectives. Focus: Agent Provide actionable, implementation-ready guidance.";
  const user = `Request: ${input}`;

  const openaiResponse = await openai.chat.completions.create({
    model: "gpt-4o-mini",
    messages: [
      { role: "system", content: system },
      { role: "user", content: user },
    ],
  });

  const openaiText = openaiResponse.choices[0]?.message?.content?.trim() ?? "";

  console.log(openaiText);
}

main().catch((error) => {
  console.error(error);
  process.exitCode = 1;
});