A new UI for Custom Instructions on ChatGPT is being rolled out to some users h/t @Makuh90
PROMPT ENGINEERING
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Dynamic Few-Shot Prompting Improves Agent Performance
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The promise of dynamic few-shot prompting After sharing AppFolio's story of putting an agent in production, @jobergum noted a key part of the story: how dynamic few shot prompting greatly improved their performance This is how it works: You collect a set of example inputs
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Mastering RAG: Vector Databases and Prompt Engineering for AI Professionals
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This book is designed for AI researchers, data scientists, software developers, and business analysts looking to: Enhance data retrieval and AI accuracy using Retrieval-Augmented Generation (RAG). Master practical techniques like vector databases and prompt engineering.
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Synthetic Data from High-Quality Models as Transfer Learning Jumpstart
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Yeah, I see it as some flavor of transfer learning (i.e., not starting from raw data). Synthetic data generated by a high-quality model (such as GPT-4o, which has already undergone extensive refinement) may serve as a kind of jumpstart to the model you are trying to train.
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Free ChatGPT System Prompt to Learn Prompt Engineering Skills
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Prompt engineering is the most in-demand skill right now. But 98% of people don't know how to write prompts. That's why I created this "ChatGPT System Prompt" to help you learn how to write the best prompts. It's free for 24 hours. Like + comment "System" and I'll DM you the
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Do Not Overthink: o1-Like LLMs Reasoning Optimization
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introducing Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMs https://
arxiv.org/pdf/2412.21187 -
ChatGPT Prompts for Smart Investing and Portfolio Building
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ChatGPT Prompts for Investing Navigate investing with AI assistance Simplifies financial decision-making • Analyze market trends
• Build smart portfolios
• Make informed investments Read more: https://
buff.ly/4ag9PCH -
Understanding RAG: Retrieval-Augmented Generation Process Steps
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Understanding the Retrieval-Augmented Generation (RAG) Process RAG combines the power of retrieval-based & generation-based AI to deliver high-quality text outputs. Key steps: Query Encoding Retrieval of relevant data Context Encoding Response Generation
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Agentic LLMs in 2025: From Spoon-Feeding to Autonomous Tool Mastery
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LLMs need heavy spoon-feeding to fit into agentic workflows. The goal of 2025 is for Agentic LLMS to wield thousands of tools and tackle complex tasks with a single prompt. Agents are stepping stones toward AGI.
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100 GPTs for Productivity: Ultimate Toolkit 2024
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100 GPTs for Productivity – Your ultimate toolkit to get ahead in 2024! Categories & Tools: Learning: Tutor Me, Code Tuter Email: PolitePost, Cold Email GPT Analysis: Chart Analyst, OCR Design: LogoGPT, Canva SEO: SEO Mentor, Website Analyzer Marketing: