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Written by Max Zeshut
Founder at Agentmelt · Last updated Sep 9, 2026
The ability of large language models to learn new tasks from examples provided directly in the prompt, without any model retraining or fine-tuning. You include a few input-output examples in your prompt, and the model generalizes the pattern to handle new inputs. In-context learning is what makes AI agents adaptable: a support agent can learn your company's response style from 3-5 examples, a sales agent can match your email tone from a few samples, and a coding agent can follow your project's conventions from example code.
A sales agent prompt includes 3 examples of emails that got replies from enterprise prospects. The agent generalizes the pattern—short subject lines, specific pain points, clear CTA—and applies it to new prospects without any model training.
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