Coding with AI by Jeremy Morgan

Author:Jeremy Morgan [Jeremy Morgan]
Language: eng
Format: epub
ISBN: 9781633437272
Publisher: Manning Publications Co.
Published: 2025-08-29T00:00:00+00:00

By combining AI generation with human judgment, we rapidly developed an application foundation. We used AI accelerated suggestions to flesh it out, and then I provided a bit of course correction based on my experience. The process demonstrated the immense value these tools provide, while highlighting the importance of human expertise. The future is a partnership between humans and AI—each playing a vital role. We’ll continue this partnership as we build a usable application.

Summary

Generative AI tools such as BlackboxAI can speed up development. They generate initial code, letting developers focus on refining architecture and improving quality.

Clear and specific context in prompts is key when using AI coding tools. Vague requests lead to generic or incorrect code, while detailed prompts with clear requirements yield better results.

Separation of concerns is key in AI-assisted development. We demonstrated it by keeping database connections in dedicated classes instead of mixing them in the application.

Human intervention is required to adjust AI-generated code. It is essential when the code doesn’t follow best practices or meet the application’s needs.

Good database design should come before code generation. Even with AI help, proper schema planning helps avoid technical debt and future problems.

Context management patterns, such as Python’s with statement, ensure proper resource handling. These fundamentals are still vital in AI-accelerated development.

Rather than replacing us, AI should serve as an intelligent partner in our work. It speeds up implementation but requires human judgment for design and architecture choices.

Testing and checking the database are key with AI-generated code. This aspect helps find problems that might be missed in code reviews alone.

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