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How to build a coding agent with Claude

Q: How to build a coding agent with Claude

Use the anthropic Python SDK with the claude-3-5-sonnet-20241022 model to build a coding agent by sending coding tasks as prompts and parsing the responses. The agent can generate, explain, or debug code by leveraging Claude's advanced coding capabilities.

Quick answer

Use the anthropic Python SDK with the claude-3-5-sonnet-20241022 model to build a coding agent by sending coding tasks as prompts and parsing the responses. The agent can generate, explain, or debug code by leveraging Claude's advanced coding capabilities.

PREREQUISITES

Python 3.8+
Anthropic API key (free tier works)
pip install anthropic>=0.20

Setup

Install the anthropic Python SDK and set your API key as an environment variable for secure access.

bash

pip install anthropic>=0.20

Step by step

This example shows how to create a simple coding agent that asks Claude to write a Python function to reverse a string and prints the output.

python

import os
import anthropic

client = anthropic.Anthropic(api_key=os.environ["ANTHROPIC_API_KEY"])

system_prompt = "You are a helpful coding assistant. Write clear, correct Python code."
user_prompt = "Write a Python function that reverses a string and demonstrate it with 'hello'."

response = client.messages.create(
    model="claude-3-5-sonnet-20241022",
    max_tokens=300,
    system=system_prompt,
    messages=[{"role": "user", "content": user_prompt}]
)

print(response.content[0].text)

output

def reverse_string(s):
    return s[::-1]

print(reverse_string('hello'))  # Output: 'olleh'

Common variations

Use max_tokens to control response length.
Switch to claude-3-opus-20240229 for faster but less detailed code.
Implement async calls with asyncio and anthropic for concurrency.
Stream responses for real-time code generation feedback.

python

import asyncio
import anthropic

async def async_coding_agent():
    client = anthropic.Anthropic(api_key=os.environ["ANTHROPIC_API_KEY"])
    response = await client.messages.acreate(
        model="claude-3-5-sonnet-20241022",
        max_tokens=300,
        system="You are a helpful coding assistant.",
        messages=[{"role": "user", "content": "Write a Python function to check if a number is prime."}]
    )
    print(response.content[0].text)

asyncio.run(async_coding_agent())

output

def is_prime(n):
    if n <= 1:
        return False
    for i in range(2, int(n**0.5) + 1):
        if n % i == 0:
            return False
    return True

Troubleshooting

If you get authentication errors, verify your ANTHROPIC_API_KEY environment variable is set correctly.
For incomplete code responses, increase max_tokens.
If the model outputs irrelevant text, refine the system prompt to be more specific about coding tasks.

✅

Key Takeaways

Use the anthropic SDK with claude-3-5-sonnet-20241022 for best coding agent performance.
Set clear system prompts to guide Claude’s coding behavior effectively.
Adjust max_tokens and model choice based on task complexity and speed needs.
Async and streaming calls improve responsiveness for interactive coding agents.
Always secure your API key via environment variables to avoid leaks.

Verified 2026-04 · claude-3-5-sonnet-20241022, claude-3-opus-20240229

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