Tag

Prompt Engineering

24 articles

LLM IntegrationWhat the Research Actually Says About Prompting ReasoningThe taxonomy of reasoning elicitation, and the uncomfortable retrieval-vs-reasoning debate every agent builder should sit withJuly 3, 20264 minJuly 3, 20264 min
LLM IntegrationA Field Guide to Model-Specific PromptingHow prompting actually differs across Claude, GPT, Gemini, Llama, and Mistral, and what transfersJuly 3, 20265 minJuly 3, 20265 min
LLM IntegrationA Real Prompt Engineering Case Study: 65.6 to 91.7 F1 on Job ClassificationWhat a production classification system teaches about which prompt tweaks actually move the needleJuly 3, 20264 minJuly 3, 20264 min
LLM IntegrationPrompt Functions: Treating Prompts as Reusable FunctionsA 2023 chat trick that quietly became how we build LLM systemsJuly 3, 20266 minJuly 3, 20266 min
LLM IntegrationGenerating Code with Prompts: The Fundamentals Still MatterComments to code, SQL from schemas, and the verification habit that separates working code from plausible codeJuly 3, 20266 minJuly 3, 20266 min
LLM IntegrationDataset Diversity: Fixing Repetitive Synthetic GenerationsWhy your generated dataset all sounds the same, and the seeding trick that fixes itJuly 3, 20267 minJuly 3, 20267 min
RAGGenerating a Synthetic Dataset for RAGUse a big model to train a small retriever, for about $55 instead of a month of labelingJuly 2, 20266 minJuly 2, 20266 min
LLM IntegrationGenerating Synthetic Data with PromptsTurn a model into a data factory for tests, evals, and cold-start training, without spending a month labelingJuly 2, 20266 minJuly 2, 20266 min
LLM IntegrationBias in Prompting: How Your Prompt Design Skews the ModelThe distribution and order of your few-shot examples can quietly bias the model. Here is how to test for it.July 2, 20266 minJuly 2, 20266 min
LLM IntegrationFactuality: Prompting to Reduce HallucinationThree prompt-level moves that cut made-up answers, and where prompting stops being enoughJuly 2, 20266 minJuly 2, 20266 min
LLM IntegrationAdversarial Prompting: Injection, Leaking, and JailbreakingThe three attacks that break LLM apps, and the defences that actually hold upJuly 2, 20268 minJuly 2, 20268 min
LLM IntegrationGraph Prompting, ExplainedWhat it means to prompt a model with nodes and edges, and when it actually helpsJuly 2, 20268 minJuly 2, 20268 min
Prompt Engineering, Properly · Part 14Prompting Reasoning Models Is Almost the Opposite of Prompting Chat ModelsWhy the step-by-step prompts you learned in this series can hurt an o3 or Claude with thinking onJuly 1, 20267 minJuly 1, 20267 min
LLM IntegrationMultimodal Chain-of-Thought: Reason Over the Picture, Then AnswerA two-stage framework that generates a rationale from text and image first, then infers the answer from that rationaleJuly 1, 20265 minJuly 1, 20265 min
LLM IntegrationPAL: Let the Model Reason in Words, but Let Python Do the MathProgram-Aided Language Models offload the actual computation to an interpreter, so arithmetic bugs stop wrecking your reasoningJuly 1, 20266 minJuly 1, 20266 min
LLM IntegrationDirectional Stimulus Prompting: Train a Tiny Model to Whisper Hints to a Big OneA small tuneable policy model generates hints that steer a frozen black-box LLM, no access to its weights requiredJuly 1, 20265 minJuly 1, 20265 min
LLM IntegrationActive-Prompt: Stop Guessing Which Few-Shot Examples to AnnotateUse the model's own uncertainty to pick which questions are worth a human-written reasoning chainJuly 1, 20266 minJuly 1, 20266 min
LLM IntegrationART: Let the Model Write Its Own Tool-Using ReasoningAutomatic Reasoning and Tool-use, and why it reads like an early sketch of the agents we build todayJuly 1, 20265 minJuly 1, 20265 min
Prompt Engineering, Properly · Part 7Generated-Knowledge Prompting: Surface Facts Before You AnswerHave the model write down what it knows first, then answer using that as contextJune 29, 20266 minJune 29, 20266 min
Prompt Engineering, Properly · Part 6Self-Consistency: Sampling Your Way to Better AnswersRun the same reasoning prompt several times, then take the majority answerJune 29, 20265 minJune 29, 20265 min
Prompt Engineering, Properly · Part 5Chain-of-Thought PromptingStandard and zero-shot CoT, when step-by-step reasoning actually helps, and what it costsJune 29, 20267 minJune 29, 20267 min
Prompt Engineering, Properly · Part 4Zero-Shot vs Few-Shot PromptingWhen examples help, how many to use, how to pick them, and where few-shot quietly breaks downJune 29, 20267 minJune 29, 20267 min
Prompt Engineering, Properly · Part 3The Anatomy of a Good PromptInstruction, context, input, and output indicator, plus the design habits that make them workJune 29, 20267 minJune 29, 20267 min
Prompt Engineering, Properly · Part 2The Settings That Change Your OutputTemperature, top_p, max tokens, stop sequences, and the penalties, and when to touch eachJune 29, 20266 minJune 29, 20266 min