Large Language Model (LLM), AI trained on huge amounts of text that predicts and generates language and code., Inference, The moment a trained model actually produces an output from your input., Token, The small chunk of text a model reads and writes., Context window, How much text the model can "hold in mind" at once., Prompt engineering, Crafting the instructions you give an AI to get a better result., Hallucination, When AI confidently produces something false or inverted., Agentic, AI that can act by itself, Non-deterministic, The same prompt can produce a different answer each time., Code completion, AI suggesting the next lines of code as you type., Scaffolding, Auto-generating the basic structure of a project to build on., Fine-tuning, Extra training that specialises a general model for a specific task., Abstraction, Hiding low-level detail so you can work at higher level., Codebase, The whole collection of source code that makes up a project., Repository, A storage space holding a project's code and its history., Refactoring, Restructuring existing code without changing what it does., Technical debt, The future cost of choosing a quick fix over a clean solution., Boilerplate, Repetitive, standard code you need just to get something running., Dependency, External code or a library your project relies on to work., Bloat, unnecessarily large or slow software due to poor optimization., Legacy Code, Old code that's hard to understand or change

Vibecoding

Autor
Ispis
Postavi

Top-lista

Vizualni stil

Postavke

Promijeni predložak

Vrati automatski spremljeno: ?