• The Prompt Report: A Systematic Survey of Prompting Techniques

    "The Prompt Report," is the result of an extensive study analyzing over 1,500 academic papers on prompting conducted by a team of researchers from leading institutions. It introduces a structured taxonomy of 58 prompting techniques organized into six categories, highlighting effective strategies such as Few-Shot and Chain-of-Thought prompting. Additionally, the report discusses the importance of In-Context Learning and assesses the performance of various prompting techniques while offering insights into future challenges and developments in human-AI interactions.

    Key Points
    - A systematic analysis resulted in the creation of "The Prompt Report," detailing over 58 prompting techniques within a comprehensive 80-page document.
    - The report categorizes prompting techniques into six problem-solving areas, enabling users to identify and apply the best methods for their tasks.
    - In-Context Learning (ICL) allows language models to perform tasks based on examples within prompts, emphasizing the power of Few-Shot techniques.
    - Effective prompt design hinges on various factors including the quality, quantity, and format of examples used in prompts.
    - Benchmarking results reveal Few-Shot Chain-of-Thought techniques as superior for reasoning tasks, while Self-Consistency is less effective than anticipated.
    - Comparisons show that AI-driven prompt engineering tools can outperform manual efforts, highlighting advancements in automated prompting techniques.
    - The report addresses future challenges in prompting, including prompt drift, multilingual applications, and integrating multimodal inputs.

    https://learnprompting.org/blog/the_prompt_report
    https://huggingface.co/papers/2406.06608
    https://www.researchgate.net/publication/381318099_The_Prompt_Report_A_Systematic_Survey_of_Prompting_Techniques

    #PromptReport #PromptEngineering #InContextLearning #FewShotLearning #ChainOfThought #PromptingTechniques #AI #NLP #LanguageModels #HumanAIInteraction #PromptDrift #MultilingualAI #LearnPrompting #AISurvey #PromptTaxonomy #SelfConsistency #PromptTools
    The Prompt Report: A Systematic Survey of Prompting Techniques "The Prompt Report," is the result of an extensive study analyzing over 1,500 academic papers on prompting conducted by a team of researchers from leading institutions. It introduces a structured taxonomy of 58 prompting techniques organized into six categories, highlighting effective strategies such as Few-Shot and Chain-of-Thought prompting. Additionally, the report discusses the importance of In-Context Learning and assesses the performance of various prompting techniques while offering insights into future challenges and developments in human-AI interactions. Key Points - A systematic analysis resulted in the creation of "The Prompt Report," detailing over 58 prompting techniques within a comprehensive 80-page document. - The report categorizes prompting techniques into six problem-solving areas, enabling users to identify and apply the best methods for their tasks. - In-Context Learning (ICL) allows language models to perform tasks based on examples within prompts, emphasizing the power of Few-Shot techniques. - Effective prompt design hinges on various factors including the quality, quantity, and format of examples used in prompts. - Benchmarking results reveal Few-Shot Chain-of-Thought techniques as superior for reasoning tasks, while Self-Consistency is less effective than anticipated. - Comparisons show that AI-driven prompt engineering tools can outperform manual efforts, highlighting advancements in automated prompting techniques. - The report addresses future challenges in prompting, including prompt drift, multilingual applications, and integrating multimodal inputs. https://learnprompting.org/blog/the_prompt_report https://huggingface.co/papers/2406.06608 https://www.researchgate.net/publication/381318099_The_Prompt_Report_A_Systematic_Survey_of_Prompting_Techniques #PromptReport #PromptEngineering #InContextLearning #FewShotLearning #ChainOfThought #PromptingTechniques #AI #NLP #LanguageModels #HumanAIInteraction #PromptDrift #MultilingualAI #LearnPrompting #AISurvey #PromptTaxonomy #SelfConsistency #PromptTools
    The Prompt Report: Insights from The Most Comprehensive Study of Prompting Ever Done
    learnprompting.org
    Discover actionable insights from The Prompt Report, the most comprehensive study of 1,500+ papers and 58 prompting techniques ever done.
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  • The Learn Prompting course is well-regarded, with a 4.8-star rating and over 82,000 enrolled learners. Reviews highlight its clear explanations, making it suitable for beginners. It provides a strong foundation in prompt engineering, while advanced skills are developed through practical application and experimentation. The course is also free and open-source, which makes it accessible.

    https://learnprompting.org/
    The Learn Prompting course is well-regarded, with a 4.8-star rating and over 82,000 enrolled learners. Reviews highlight its clear explanations, making it suitable for beginners. It provides a strong foundation in prompt engineering, while advanced skills are developed through practical application and experimentation. The course is also free and open-source, which makes it accessible. https://learnprompting.org/
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  • A gold mine for prompt engineering code.

    Grab the link on GitHub:
    https://github.com/anthropics/courses/tree/master/prompt_engineering_interactive_tutorial/Anthropic%201P

    After completing this course, you will be able to:

    • Recognize common failure modes
    • Master the basic structure of a good prompt
    • Understand Claude's strengths and weaknesses
    • Build strong prompts from scratch for common use cases

    #PromptEngineering #AI #Claude #Anthropic #GitHub #Prompting #AIML #LLM #LargeLanguageModels #GenerativeAI #FailureModes #PromptStructure #AISolutions #AICourse
    A gold mine for prompt engineering code. Grab the link on GitHub: https://github.com/anthropics/courses/tree/master/prompt_engineering_interactive_tutorial/Anthropic%201P After completing this course, you will be able to: • Recognize common failure modes • Master the basic structure of a good prompt • Understand Claude's strengths and weaknesses • Build strong prompts from scratch for common use cases #PromptEngineering #AI #Claude #Anthropic #GitHub #Prompting #AIML #LLM #LargeLanguageModels #GenerativeAI #FailureModes #PromptStructure #AISolutions #AICourse
    courses/prompt_engineering_interactive_tutorial/Anthropic 1P at master · anthropics/courses
    github.com
    Anthropic's educational courses. Contribute to anthropics/courses development by creating an account on GitHub.
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  • Where can you learn "Prompt Engineering" Handson ?

    Vibetest.io is a platform focused on teaching prompt engineering. It offers hands-on coding challenges to help users learn how to communicate effectively with AI models such as Claude and GPT-4. The platform aims to enable users to transform code through improved prompting techniques. It emphasizes practical application and direct experience to master the art of prompt engineering.

    https://vibetest.io/

    #vibetestio #promptengineering #ai #gpt4 #claude #prompting #ailearning #promptdesign #codingchallenges #aiplayground #learnai #promptcrafting #promptdeveloper #aieducation #durableknowledge
    Where can you learn "Prompt Engineering" Handson ? Vibetest.io is a platform focused on teaching prompt engineering. It offers hands-on coding challenges to help users learn how to communicate effectively with AI models such as Claude and GPT-4. The platform aims to enable users to transform code through improved prompting techniques. It emphasizes practical application and direct experience to master the art of prompt engineering. https://vibetest.io/ #vibetestio #promptengineering #ai #gpt4 #claude #prompting #ailearning #promptdesign #codingchallenges #aiplayground #learnai #promptcrafting #promptdeveloper #aieducation #durableknowledge
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  • So whats the next big fad .... "Context Engineering".
    So WHAT IS CONTEXT ENGINEERING?

    𝟭. It’s Feature Engineering—but for AI Agents.
    (*Check what's feature engineering down below)
    𝟮. The art of filling the context window with exactly what’s needed.
    𝟯. You’re managing “working memory” like an operating system manages RAM.
    𝟰. Agents need engineered context: instructions, tools, memories, examples, feedback.
    𝟱. Poor context = forgotten steps, broken tools, bad decisions.
    𝟲. Long-running agents hit context limits fast—engineering is essential.
    𝟳. Vibe coding doesn’t scale—context engineering does.

    In the context of AI prompting, feature engineering refers to the process of creating, selecting, and transforming input data (features) to improve the performance of a machine learning model. It involves using domain expertise and various techniques to make the data more suitable for the AI model to learn from and generate better outputs.

    Check the following links for context:
    - Langchain Explanation on what it is:
    https://youtu.be/4GiqzUHD5AA?si=BEIThE_HOT-i3I9T
    - First post l saw talking about this was by Andrej Karpathy (@karpathy):
    https://x.com/karpathy/status/1937902205765607626
    - And you may wish to follow this lady she dove right into it detail ... never mind hte course it hella expensive !:
    https://x.com/MaryamMiradi/status/1940810454013518178

    #contextengineering #featureengineering #aiagents #langchain #promptengineering #aioptimization #machinelearning #contextwindow #workingmemory #aiprompting #vibecoding #aiperformance #contextualization #aitraining #aiscaling
    So whats the next big fad .... "Context Engineering". So WHAT IS CONTEXT ENGINEERING? 𝟭. It’s Feature Engineering—but for AI Agents. (*Check what's feature engineering down below) 𝟮. The art of filling the context window with exactly what’s needed. 𝟯. You’re managing “working memory” like an operating system manages RAM. 𝟰. Agents need engineered context: instructions, tools, memories, examples, feedback. 𝟱. Poor context = forgotten steps, broken tools, bad decisions. 𝟲. Long-running agents hit context limits fast—engineering is essential. 𝟳. Vibe coding doesn’t scale—context engineering does. In the context of AI prompting, feature engineering refers to the process of creating, selecting, and transforming input data (features) to improve the performance of a machine learning model. It involves using domain expertise and various techniques to make the data more suitable for the AI model to learn from and generate better outputs. Check the following links for context: - Langchain Explanation on what it is: https://youtu.be/4GiqzUHD5AA?si=BEIThE_HOT-i3I9T - First post l saw talking about this was by Andrej Karpathy (@karpathy): https://x.com/karpathy/status/1937902205765607626 - And you may wish to follow this lady she dove right into it detail ... never mind hte course it hella expensive !: https://x.com/MaryamMiradi/status/1940810454013518178 #contextengineering #featureengineering #aiagents #langchain #promptengineering #aioptimization #machinelearning #contextwindow #workingmemory #aiprompting #vibecoding #aiperformance #contextualization #aitraining #aiscaling
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  • Exciting News! Dive into the world of AI with this fantastic interactive tutorial on prompt engineering by Anthropic! Whether you're a curious beginner or a seasoned tech enthusiast, this course is designed to spark your creativity and enhance your understanding of AI-driven solutions. Don't miss out on the opportunity to learn from the best and elevate your skills! Check it out here: https://github.com/anthropics/courses/tree/master/prompt_engineering_interactive_tutorial/Anthropic%201P

    Welcome to Anthropic's educational courses. This repository currently contains five courses. We suggest completing the courses in the following order:

    Anthropic API fundamentals - teaches the essentials of working with the Claude SDK: getting an API key, working with model parameters, writing multimodal prompts, streaming responses, etc.
    Prompt engineering interactive tutorial - a comprehensive step-by-step guide to key prompting techniques. [AWS Workshop version]
    Real world prompting - learn how to incorporate prompting techniques into complex, real world prompts. [Google Vertex version]
    Prompt evaluations - learn how to write production prompt evaluations to measure the quality of your prompts.
    Tool use - teaches everything you need to know to implement tool use successfully in your workflows with Claude.

    #AI #MachineLearning #ArtificialIntelligence #TechTrends #Innovation #FutureTech #AICommunity #LearnAI #TechEducation #DigitalSkills #AIRevolution #TechLovers #CodingLife #InteractiveLearning #AnthropicAI #PromptEngineering #ExploreAI #TechSavvy #AIInsights #SkillUp
    🚀 Exciting News! 🚀 Dive into the world of AI with this fantastic interactive tutorial on prompt engineering by Anthropic! Whether you're a curious beginner or a seasoned tech enthusiast, this course is designed to spark your creativity and enhance your understanding of AI-driven solutions. Don't miss out on the opportunity to learn from the best and elevate your skills! Check it out here: https://github.com/anthropics/courses/tree/master/prompt_engineering_interactive_tutorial/Anthropic%201P Welcome to Anthropic's educational courses. This repository currently contains five courses. We suggest completing the courses in the following order: Anthropic API fundamentals - teaches the essentials of working with the Claude SDK: getting an API key, working with model parameters, writing multimodal prompts, streaming responses, etc. Prompt engineering interactive tutorial - a comprehensive step-by-step guide to key prompting techniques. [AWS Workshop version] Real world prompting - learn how to incorporate prompting techniques into complex, real world prompts. [Google Vertex version] Prompt evaluations - learn how to write production prompt evaluations to measure the quality of your prompts. Tool use - teaches everything you need to know to implement tool use successfully in your workflows with Claude. #AI #MachineLearning #ArtificialIntelligence #TechTrends #Innovation #FutureTech #AICommunity #LearnAI #TechEducation #DigitalSkills #AIRevolution #TechLovers #CodingLife #InteractiveLearning #AnthropicAI #PromptEngineering #ExploreAI #TechSavvy #AIInsights #SkillUp
    courses/prompt_engineering_interactive_tutorial/Anthropic 1P at master · anthropics/courses
    github.com
    Anthropic's educational courses. Contribute to anthropics/courses development by creating an account on GitHub.
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