bigaiguy's Few-Shot Prompting Thread: Examples Beat Long Descriptions

On October 8, blogger bigaiguy posted a thread systematically covering Few-Shot Prompting techniques. The core claim: instead of describing your needs in 500 words, just show the model examples and let it learn from the patterns—3 good examples beat a long description.

Confirmed

• Provides a copyable template: task description + 2-3 "Input / Ideal Output" example pairs
• The number of examples needn't be fixed at 3; adjust based on the task, model, and example quality. With varied inputs, avoid near-identical examples—quality over quantity is key
• Examples should precisely convey tone, structure, length, format, and level of detail; e.g., for information extraction, demonstrate pulling JSON out of natural-language sentences
• Learning use case: give an analogy-style example like "API = a waiter who delivers food," then have the model explain new concepts such as vector database in the same format
• Email use case: paste 3 emails you've written yourself and let the model mimic how you open, argue, and close
• Tweet use case: give 3 tweets you like and have the model analyze hook structure, sentence length, tone, and rhythm before writing—while banning copying wording or openers; far more effective than vague instructions like "make it go viral"
• Advanced technique: provide both good and bad examples and have the model explain the key differences between them, so new output aligns with the good example and avoids the bad one's problems; this replaces fuzzy instructions like "write more like a human" or "write like an expert"

Why it matters

• Examples communicate style and format standards far more precisely than long instruction blocks, making them a low-cost way for ordinary users to improve AI output quality; pairing positive and negative examples further turns subjective requirements into actionable criteria

2026-10-08 ~ 2026-10-08 · 9 related posts

• [source] Few-shot thread: 3 perfect example outputs beat long descriptions — bigaiguy · 2026-10-08
• Few-shot post writing: make AI dissect example posts before writing — bigaiguy · 2026-10-08
• Few-shot email writing: feed your own emails to clone your voice — bigaiguy · 2026-10-08
• Few-shot for learning: make the model mimic your analogy style — bigaiguy · 2026-10-08
• Few-shot thread: teaching models JSON extraction with input-output pairs — bigaiguy · 2026-10-08
• Few-shot examples: quality over quantity, and show the input range — bigaiguy · 2026-10-08
• [source] Few-shot prompting tutorial: 3 examples beat 500 words of description — bigaiguy · 2026-10-08
• [source] Prompting trick: show the AI bad examples alongside good ones — bigaiguy · 2026-10-08
• Stop Saying 'Make It Better': Few-Shot Prompting Works Best With Good and Bad Examples — bigaiguy · 2026-10-08