What is prompt engineering?
Prompt engineering is crafting the input to a model to get a better output — choosing wording, structure, examples, and constraints. For image and vector generation it is how you steer subject, style, composition, and format; as models and context windows grow, it shades into context engineering.
Understanding prompt engineering
A model can only answer what it is asked. Prompt engineering is the practice of asking well: being specific about the goal, giving an example of the desired form, stating constraints, and structuring the request so the model’s attention lands where it should.
For generating art, the prompt carries the whole brief — subject, style, palette, composition, and the output format (a flat icon vs a detailed illustration vs a cut-ready file). Small wording changes move the result a lot.
As models improve, raw wording matters less and the surrounding context matters more — which is why prompt engineering is increasingly a subset of context engineering.
The AI SVG prompt guide
How to prompt for clean, editable vector art.
Keep exploring
Context engineering
Context engineering is the practice of deciding what information a model sees at inference time — which documents, memories, tools, and instructions to place in the context window — so it produces accurate, grounded output. It has largely superseded "prompt engineering" as models and context windows have grown.
AI agent
An AI agent is a system that uses a language model to pursue a goal across multiple steps — planning, calling tools, observing results, and adjusting — rather than producing a single response. Agents can read data, run code, generate assets, and act in software on a user’s behalf.
The design workspace where these ideas are real
Agents that generate, a canvas they can see and drive, and a brain that keeps every asset on-brand. Free to start.