About CodeKing
A working notebook documenting methods and code for building software with AI.
What is the history of CodeKing?
CodeKing operated as a studio from 2006 to 2014. During those years the team delivered web design projects and built mobile applications for a range of clients. The work involved assembling digital products, integrating third‑party systems, and writing custom scripts to meet specific requirements. All effort was focused on delivering functional, client‑oriented solutions rather than experimental research.
After 2014 the studio stopped offering services. The domain now hosts a technical notebook that records observations made while applying artificial intelligence to software development. The shift moves the content from a service‑based model to a personal archive of experiments, measurements, and code that can be reused by other developers.
How does the working notebook differ from a marketing site?
The site is deliberately built as a notebook, not a brochure. It stores concrete measurements, code fragments, and step‑by‑step methods that were actually executed. Every entry reflects a real experiment, including failures, so readers can see what succeeded and what did not when AI was introduced into a development pipeline.
The organization avoids abstract theory. Instead each note describes a specific prompt, the model’s response, and the adjustments made to integrate the output into existing tooling. This practical focus gives developers a reproducible reference they can copy, adapt, or extend without wading through promotional language.
Who should read this notebook?
The material targets developers who regularly ship code and need actionable insight. It assumes familiarity with standard software engineering practices and a willingness to dive into low‑level details. The tone stays factual, skipping hype in favor of clear explanations that help solve immediate programming problems.
Readers will find concrete implementation notes, such as how a particular model was called from a CI pipeline or how generated tests were filtered for relevance. The notebook serves as a bridge for engineers moving from purely manual coding toward workflows that incorporate AI assistance, offering a realistic picture of current capabilities.
How is the content structured?
Entries are grouped into three main areas: notes that capture high‑level observations, coding sections that contain full snippets and configuration files, and AI‑focused pages that detail prompt engineering and model integration. This taxonomy lets users jump directly to the depth of detail they need.
Older experiments live in an archive that provides historical context for how techniques have evolved. Newer notes appear at the top of each category, making it easy to locate the latest findings. The consistent layout across sections helps readers compare approaches and track progress over time.
Where can I find practical AI integration examples?
The AI section presents step‑by‑step guides for embedding language models into build scripts, IDE extensions, and test generators. Each guide records the exact command line used, the environment variables set, and the observed latency or error rates during execution.
Measurements are presented alongside the code so developers can gauge performance trade‑offs. When a model produced unexpected output, the notebook records the debugging steps taken, including prompt tweaks and post‑processing filters. This level of detail enables reproducibility without guessing which configuration led to success.
What resources support deeper exploration?
Cross‑links point to related notes, coding examples, and archived entries that expand on a given technique. For instance, a note on prompt tuning may reference a coding page that shows the surrounding script and an archive entry that documents an earlier version of the same experiment.
The site also includes references to external tools and libraries used in the experiments, but only as they appear in the actual code. This approach keeps the focus on what was tried and measured, allowing developers to replicate the environment with minimal extra research.
Questions
Is CodeKing still a web design agency?
No, the studio operated from 2006 to 2014 and is no longer providing design services.
What is the purpose of this website?
It is a working notebook documenting the use of AI in software development.