YCYeongseon Choeinyeongseonchoe.hashnode.dev00Handling streaming responses — real-time output58m ago · 14 min read · LLM App Foundations 101 (6/6) Example code: github.com/yeongseon-books/llm-app-foundations-101 The diagram below shows the basic event flow of a streamed response. One of the easiest ways to make aJoin discussion
YCYeongseon Choeinyeongseonchoe.hashnode.dev00Managing conversation state — building a multi-turn chatbot1h ago · 11 min read · LLM App Foundations 101 (5/6) Example code: github.com/yeongseon-books/llm-app-foundations-101 The diagram below summarizes how message history accumulates across turns. One of the first surprises Join discussion
YCYeongseon Choeinyeongseonchoe.hashnode.dev00Few-shot and chain-of-thought — steering better answers1h ago · 16 min read · LLM App Foundations 101 (4/6) Example code: github.com/yeongseon-books/llm-app-foundations-101 The diagram below shows how examples and stepwise reasoning steer one request. Post 03 established theJoin discussion
YCYeongseon Choeinyeongseonchoe.hashnode.dev00Prompt engineering basics — system, user, and assistant roles1h ago · 15 min read · LLM App Foundations 101 (3/6) Example code: github.com/yeongseon-books/llm-app-foundations-101 The diagram below shows the basic flow of role-based prompt construction. Prompt engineering is ofteJoin discussion
PMPrajwal Minglitch-guy0.hashnode.dev00Your Prompt is a Function Call1d ago · 10 min read · You sent a prompt. You got garbage back. You blamed the model. You were wrong. The model did exactly what it was told. It resolved a probability cascade through a stack of trained bias registers, starJoin discussion
YCYeongseon Choeinyeongseonchoe.hashnode.dev00LLM API first call — sending your first request1d ago · 13 min read · LLM App Foundations 101 (1/6) Example code: github.com/yeongseon-books/llm-app-foundations-101 The diagram below shows the smallest round trip behind a first LLM API call. The first confusing thingJoin discussion
ATAditya Trivediinadityatrivedi.hashnode.dev00Advanced Prompt Engineering Guide: Fundamentals to Multimodal1d ago · 10 min read · What is a Prompt ? A prompt is an input to a Generative AI model, that is used to guide its output. It may consist of text, image, sound, or other media. The ability to prompt models, especially with Join discussion
NSNishant Singhinnishant-singh.hashnode.dev00Testing AI Hallucinations in LLM-Backed APIs: A Framework Nobody Has Defined Yet3d ago · 59 min read · How do you write a test for a response that is confidently wrong? This is the most urgent open question in software quality right now — and most teams have no answer. Target Audience: AI Engineers · Join discussion
MAMaximilian Albekierinklausbuilds.hashnode.dev00KB-005: You're Using AI Wrong (Here's How to Fix That)5d ago · 15 min read · The Art and Zen of Motorcycle maintenance and AI Prompt engineering. Klaus Builds · AI Tooling · Prompting Most people use AI like a search engine. You type a question, you get an answer, you move onJoin discussion
NSNeeloppher Syedinneeloppher.hashnode.dev00Token Budget Negotiator5d ago · 7 min read · Everyone knows long prompts cost money. Almost nobody knows which parts of their prompt actually matter. Prompts accumulate over time, a system message, a style guide, a few-shot example or two, some Join discussion
