OpenAI Agents & Orchestration · Lesson 2

Coding Agent: GPT-4.1 + Agents SDK

Building a coding agent with GPT-4.1 via the OpenAI Agents SDK: web_search + shell tools, ShellExecutor with an isolated workspace, scaffold → feedback → iteration loop.

30 min read3 questions in quizReady prompt includedIn progress

Practical exercise

What to do after this lesson

Run the coding agent with an instruction to create a simple Flask app with a single /health endpoint. Make sure the agent uses ShellExecutor in an isolated directory and you can approve/reject each command.

Task grader

Run the coding agent with an instruction to create a simple Flask app with a single /health endpoint. Make sure the agent uses ShellExecutor in an isolated directory and you can approve/reject each command.

Your answer

Ready-to-use prompt

Template for this lesson

Copy and adapt to your context. Text in angle brackets should be replaced.

import asyncio
from pathlib import Path
from agents import Agent, Runner, WebSearchTool

workspace_dir = Path("agent-workspace").resolve()
workspace_dir.mkdir(exist_ok=True)

agent = Agent(
    name="DevAgent",
    model="gpt-4.1",
    instructions="Scaffold a minimal Flask app with /health endpoint in the workspace.",
    tools=[WebSearchTool()],
)

async def main():
    runner = Runner(agent=agent)
    result = await runner.run(
        "Create a Flask app with a /health endpoint returning JSON {status: ok}"
    )
    print(result.final_output)

asyncio.run(main())

Prompt sandbox

Prompt

Agent Setup

from pathlib import Path workspace_dir = Path("coding-agent-workspace").resolve() workspace_dir.mkdir(exist_ok=True) coding_agent = Agent( name="CodingAgent", model="gpt-4.1", instructions=( "You are an expert coding agent. Scaffold apps from user prompts, " "edit files with apply_patch, and run shell commands in the workspace. " "Always sandbox commands — never run outside workspace_dir." ), tools=[ WebSearchTool(), ShellTool(cwd=str(workspace_dir), require_approval=True), ], )

ShellExecutor with Isolation

import asyncio from agents import ShellCommandRequest, ShellResult class ShellExecutor: def __init__(self, workspace: Path, require_approval: bool = True): self.workspace = workspace self.require_approval = require_approval async def __call__(self, req: ShellCommandRequest) -> ShellResult: if self.require_approval: print(f"Agent wants to run: {req.command}") if input("Approve? (y/n): ").strip().lower() != "y": return ShellResult(stdout="", stderr="Rejected by user", exit_code=1) proc = await asyncio.create_subprocess_shell( req.command, cwd=str(self.workspace), stdout=asyncio.subprocess.PIPE, stderr=asyncio.subprocess.PIPE, ) stdout, stderr = await proc.communicate() return ShellResult(stdout=stdout.decode(), stderr=stderr.decode(), exit_code=proc.returncode)

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Coding Agent: GPT-4.1 + Agents SDK

Task grader

Prompt sandbox

Quiz — 3 questions

Discussion

GPT-4.1 for Coding

Agent Setup

ShellExecutor with Isolation

Agent Loop