How I Built an AI Agent That Actually Does Things (Not Just Chat)

#ai #javascript #claude #webdev

Most AI agents are just chatbot wrappers. Send a message, get a response. That is not an agent.

A real agent can read files, write code, run commands, and fix its own mistakes. Here is how.

The Tool-Calling Loop

User sends a message
LLM responds with a tool call (not text)
You execute the tool and send the result back
LLM continues reasoning
Repeat until done

import Anthropic from "@anthropic-ai/sdk";

const client = new Anthropic();
const tools = [{
  name: "run_command",
  description: "Execute a shell command",
  input_schema: {
    type: "object",
    properties: { command: { type: "string" } },
    required: ["command"]
  }
}];

async function agent(task) {
  let messages = [{ role: "user", content: task }];
  while (true) {
    const resp = await client.messages.create({
      model: "claude-sonnet-4-20250514",
      max_tokens: 4096, tools, messages
    });
    if (resp.stop_reason === "end_turn")
      return resp.content[0].text;
    for (const block of resp.content) {
      if (block.type === "tool_use") {
        const { execSync } = await import("child_process");
        const result = execSync(block.input.command, { encoding: "utf-8" });
        messages.push({ role: "assistant", content: resp.content });
        messages.push({ role: "user", content: [{
          type: "tool_result", tool_use_id: block.id, content: result
        }]});
      }
    }
  }
}

const result = await agent("List all JS files and count lines");
console.log(result);

This 40-line agent can read files, run commands, chain steps, and self-correct.

Adding Memory

import { readFileSync, writeFileSync } from "fs";

class Memory {
  constructor(path = "./memory.json") {
    this.path = path;
    try { this.data = JSON.parse(readFileSync(path, "utf-8")); }
    catch { this.data = { decisions: [] }; }
  }
  remember(text) {
    this.data.decisions.push(text);
    writeFileSync(this.path, JSON.stringify(this.data, null, 2));
  }
}