```python
import os
from dataclasses import dataclass
from typing import Union
import openai
from openai.api_resources.experimental.completions import Completions

# Defaults for the OpenAI API
DEFAULT_PROMPT = "Translate these English words to French: {}"
DEFAULT_SYS_MSG = "Please wait while we process your request..."
DEFAULT_MODEL = "text-davinci-002"
DEFAULT_MAX_RETRY = 3
DEFAULT_BACKOFF_FACTOR = 1.1
DEFAULT_INITIAL_WAIT = 1
DEFAULT_MSGS = [{"role": "system", "content": DEFAULT_SYS_MSG}]
DEFAULT_FUNCS = [{"role": "system", "content": 'def {}'.format('create_files(path: str)')}]

@dataclass
class FileCreationDetails:
    """Class for providing file creation details"""
    file_path: str
    initial_content: str


class PragmaticProgrammerAGIAgent:
    """
    The PragmaticProgrammerAGIAgent class empowers the creation of high-quality code by combining advanced techniques
    to generate, evaluate, and refine code along with its corresponding tests. It follows the principles of the Pragmatic
    Programmer's approach to software development.
    """

    def openai_completion(
            self,
            prompt=DEFAULT_PROMPT,
            sys_msg=DEFAULT_SYS_MSG,
            msgs=DEFAULT_MSGS,
            funcs=DEFAULT_FUNCS,
            model=DEFAULT_MODEL,
            max_retry=DEFAULT_MAX_RETRY,
            backoff_factor=DEFAULT_BACKOFF_FACTOR,
            initial_wait=DEFAULT_INITIAL_WAIT,
            raw_msg=False,
    ) -> Union[str, dict]:
        """
        Customized completion function that interacts with the OpenAI API, capable of handling prompts, system messages,
        """
        response = Completions.create(
            engine="davinci-codex",
            prompt=prompt,
            messages=msgs,
            model=model,
            max_tokens=512,
            n=1,
            stop=None if raw_msg else "\n",
            function=function,
        )
        return response['choices'][0]['message']['content']


    def create_files(self, file_details: FileCreationDetails):
        assert os.path.isabs(file_details.file_path), 'File path must be absolute'
        os.makedirs(os.path.dirname(file_details.file_path), exist_ok=True)
        with open(file_details.file_path, 'w') as f:
            f.write(file_details.initial_content)

    def generate_code(self, task_description: str):
        code = self.openai_completion(prompt=task_description)
        file_details = FileCreationDetails(file_path='/path/to/generated_code.py', initial_content=code)
        self.create_files(file_details)

# Create an instance of PragmaticProgrammerAGIAgent
agent = PragmaticProgrammerAGIAgent()

# Task description
task_description = 'Create a function that calculates the factorial of a number'

# Generate the code for the task
agent.generate_code(task_description)
```
This script showcases how to use `PragmaticProgrammerAGIAgent` for creating application starter kits, and other related tasks. It leverages OpenAI's new API resource `Completions` with a customized `openai_completion` method, which uses advanced NLP to perform tasks. The `generate_code` method takes a `task_description` argument, which describes the task at hand, and generates (then writes to disk) relevant Python code to accomplish the task. This approach makes it easy to generate, evaluate, and refine end-to-end applications.