A working notebook for AI-assisted development
The core concept
This site functions as a working notebook, documenting the practical application of large language models throughout the software development lifecycle. Instead of theory, the entries focus on concrete code, precise prompts, and the outputs generated by various AI assistants during real development tasks.
The goal is a repository of technical observations. Readers find detailed accounts of how AI speeds coding, catches errors, and shapes architecture. Every entry rests on code that has been executed and tested locally, guaranteeing practical relevance.
Methods and measurements
Documentation follows a strict input‑output pattern. When a problem is solved with an AI assistant, the process is recorded: the initial statement, the iterative prompting, and the final implementation. This provides a transparent view of the reasoning behind the code.
Measurements evaluate the effectiveness of different AI‑driven workflows. They track how much manual intervention is needed to fix hallucinations or logic errors. By logging these friction points, the notebook shows exactly where AI excels and where human oversight is critical for shipping stable software.
Target audience
The entries are written for professional developers who already understand programming concepts, version control, and deployment pipelines. No introductory material for beginners is included; the focus stays on optimizing existing workflows and integrating new AI capabilities into production environments.
The tone is direct and technical, avoiding marketing hype. AI is treated as another assistant in the developer's stack, like a compiler or debugger, emphasizing utility, reliability, and the reality of building software today.
Navigating the notebook
The site is organized into logical sections. Notes offer quick observations, the AI section explores practical applications, and the coding section dives into implementation details. These categories let readers locate information that matches their current technical challenges or interests.
The archive holds older entries that provide historical context for the evolving field of AI development. To see methods applied to real‑world scenarios, visit the reference projects section.
Questions
Is this a tutorial site?
No, it is a working notebook documenting actual development processes and experiments.
Who is the intended reader?
Developers who are already shipping software and want to integrate AI into their workflow.
Rebuilt from the archive of codeking.eu. Last reviewed 2026-10-27.