Dynamic Megaprompt

Adaptive, large-scale prompt engineering: it tailors extensive input to instance-specific needs for superior LLM output.

Dynamic Megaprompting is the next-gen evolution of prompt engineering, combining the depth of a multi-thousand-line mega-prompt with instance-aware adaptability. This technique employs a small, trainable learning network to adjust prompt properties dynamically (position, length, representation). It moves past fixed soft prompts. For example, a static 1500-word instruction set becomes a real-time, optimized context delivery system, boosting model performance and generalization across diverse inputs. We get precision at scale: maximum context, minimum overhead.

https://learnprompting.org/docs/dynamic_prompting