Prompting
The surrounding code and infrastructure that turns a raw language model into a useful application.
The surrounding code and infrastructure that turns a raw language model into a useful application. A scaffold includes the prompt template, retrieval pipeline, tool definitions, output parsing, error handling, retry logic, and user interface. The model is the engine, but the scaffold is the car. Most of the engineering effort in AI applications goes into scaffolding, not model selection.
In practice, developers reach for Scaffold (AI) when they need the capability described above as part of an AI feature or workflow.
Hands-on guides, comparisons, and tutorials that cover Prompting.
The surrounding code and infrastructure that turns a raw language model into a useful application.
Scaffold (AI) sits in the Prompting part of the AI stack. Understanding it helps you make better decisions when building, debugging, and shipping AI features.
Developers Digest publishes tutorials and videos that cover Prompting topics including Scaffold (AI). Check the blog and YouTube channel for hands-on walkthroughs.
A prompting technique where you include a small number of input-output examples in the prompt to show the model the pattern you want it to follow.
Safety constraints and validation layers applied to AI model inputs and outputs.
An attack where malicious input tricks an AI model into ignoring its instructions and following attacker-supplied commands instead.

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