Few-shot prompting shows the model two or three worked examples of the task, then the real input, and it imitates the pattern. It is faster and cheaper than fine-tuning for small adjustments, though fine-tuning wins when examples must be many or consistent.
The book · Volume 6 of 7
AI for Video: A Complete Guide to Intelligence in Video Products: From Models and Inference to Computer Vision, Speech, Search, and Generative Video
Few-shot prompting is often enough to steer a model, and knowing when it stops being enough saves a fine-tuning project. This volume covers few-shot prompting as part of its ML minimum for product decisions: prompting versus fine-tuning, vision-language models, model artifacts, and the lifecycle of an AI feature. Written by Nikolay Sapunov, CEO at Fora Soft.
Wondering if few-shot prompting is enough or you need fine-tuning?
Send us examples of the task, and we will test few-shot prompting against a fine-tuned baseline and tell you which is cheaper for the accuracy you need. 250+ video products shipped since 2005.
