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Exploring AI: From Prompt Engineering to Context Engineering

This entry is part 1 of 4 in the series AI Leveling

🚀 Starting a New Python AI Project with OpenAI

Recently, I shared an idea for a new Python/AI project: creating an app that leverages the OpenAI API to interact with and analyze written stories.

This project will not only highlight my existing Python skills but also serve as an entry point into the fast-evolving world of artificial intelligence and large language models (LLMs).


🧠 Learning AI Through Practical Application

Before diving too deep, I’m focusing on practical AI use — not the underlying theory or machine learning science. My goal is to become fluent in using tools like ChatGPT, OpenAI’s API, and AI frameworks, rather than studying the internal workings of transformers and model architectures.

A family member who’s ahead of me in AI suggested a helpful video on understanding foundational concepts. It was a spark that has definitely jumpstarted my creativity.


🧪 Experimenting Before Building

Before I start writing code, I want to experiment with AI interactions, prompt strategies, and context flow. This is a big shift from traditional software development, where problems are solved deterministically with clearly defined logic.

In contrast, working with AI feels more like shaping probability with strategic context and prompt design.


🔍 From Prompt Engineering to Context Engineering

I’m especially fascinated by the shift from prompt engineering (crafting input instructions) to context engineering (structuring surrounding data for better AI performance).

Here are some of the questions I’m exploring:

  • How can I build a board of AI advisors with specialized tasks?
  • How do I maintain state across multiple AI interactions?
  • Can I chain AI outputs — feeding the results of one model into another?
  • What workflows will help me scale these experiments?

💡 What’s Next?

This phase is all about learning by doing. As I get more comfortable with AI tools, I’ll begin designing the architecture for the actual Python app — one that brings AI storytelling, context chaining, and modular prompt logic together.


Stay tuned — I’ll be sharing more as the project evolves.

ChatGPT Free took the rough draft of this article and polished it up for WordPress and a software engineering audience

CR Johnson

As a software engineer with over a decade of experience working for Fortune 50 companies developing software for Windows, the web, and a few interplanetary spacecraft, she's programmed in a plethora of languages including the C#/ASP.NET stack and, recently, Rails. She has tweaked more CSS files than she can count and geeks out a little on data and SQL databases. In her spare time she works on her first novel and enjoys bicycling and dark chocolate.