AI Ethics · ARTICLEMEMBERS
How a small team trials AI, compares it with a non-AI baseline, and actually stops after a poor result
AI Ethics · ARTICLEMEMBERS
A comparison is a test design, not a vote on truth
AI Project Management · ARTICLEMEMBERS
Safety rules, evaluation logic and process boundaries
AI Project Management · ARTICLEMEMBERS
Hallucinations, subtle errors and quality control
AI Data Engineering · AGENTIC PACKAGEFREE
A portable operating system for traceable AI data work — canonical core, Obsidian vault, auditable workflows, skills, harness and adapters.
AI Data Engineering · ARTICLEMEMBERS
A rule that merely sounds good does not govern a system. It must be discoverable, applicable and testable.
AI Data Engineering · ARTICLEMEMBERS
Documented knowledge explains what to do. Executable knowledge also defines when, with which tools, inside which limits and with what quality evidence it may be done.
AI Data Engineering · ARTICLEMEMBERS
An answer is the end of a processing chain. Evidence exists only when that chain can be inspected in reverse all the way to a valid source.
AI Data Engineering · ARTICLEMEMBERS
A strong idea may exist between two dense topics. The same space may also contain a data error, poor segmentation or simply no defensible relationship.
AI Data Engineering · ARTICLEMEMBERS
Good search need not hit one perfect sentence immediately. It can first identify the region of knowledge where a defensible answer is likely to exist.
AI Data Engineering · ARTICLEMEMBERS
A vector database can find similar passages. It does not know which source is authoritative, which version applies or which result actually answers the question.
AI Data Engineering · ARTICLEMEMBERS
A chunk is not merely a piece of text. It is a unit of meaning with provenance, neighbourhood and a role in the document.
AI Data Engineering · ARTICLEMEMBERS
Uploading files creates access. A RAG system creates a controlled path from a question through selected evidence to a verifiable answer.
AI Data Engineering · ARTICLEMEMBERS
The CE marking says that conformity is declared for a specific system against the applicable requirements. It does not say that the system is the best, error-free or endorsed by an authority.
AI Data Engineering · ARTICLEMEMBERS
Once real people, decisions or consequences are involved, the word "pilot" is no longer a safety architecture.
AI Data Engineering · ARTICLEMEMBERS
A team is created not by adding voices, but by combining complementary capabilities, clear ownership and verifiable integration.
AI Data Engineering · ARTICLEMEMBERS
A prompt describes one request. A skill describes how a class of requests is handled repeatedly, verifiably and safely under defined conditions.
AI Data Engineering · ARTICLEMEMBERS
A language model does not become truthful merely because documents are placed in its context. It only gains a better opportunity to ground its answer in inspectable evidence.
AI Data Engineering · ARTICLEFREE
Data is not abstractly good or bad. Its quality depends on whether it can support a concrete task at an acceptable level of risk.
Prompt & Context Engineering · ARTICLEMEMBERS
The best choice does not begin with a model name. It begins with an honest description of the task, the data and the environment you actually have.