• VibeTest encompasses a range of tools and platforms focused on enhancing interactions with AI and automating quality assurance (QA) testing for websites. One of the primary offerings is VibeTest.io, which specializes in teaching prompt engineering. This platform provides hands-on coding challenges that help users effectively communicate with AI systems such as Claude and GPT-4, aiming to improve the transformation of code through better prompts (https://vibetest.io/ ) (https://github.com/browser-use/vibetest-use ).

    On the other hand, the Vibetest MCP (Multi-Channel Platform) servers automate QA testing by deploying AI agents to identify various website issues, including UI bugs, broken links, and accessibility problems. This system is designed to streamline the testing process by launching multiple browser agents that crawl and evaluate web pages for technical flaws (https://apidog.com/blog/vibetest-use-mcp/ ) (https://www.mcpworld.com/en/detail/9ab49d16442b62a5e1ec9de97e05726d ). The Vibetest-use MCP server specifically focuses on these automated testing capabilities, emphasizing its efficiency in detecting and flagging potential issues (https://github.com/luk1337/VibeTest ).

    Overall, VibeTest is at the intersection of AI prompt engineering and automated web testing, providing valuable resources for both developers looking to enhance their AI interactions and teams aiming to ensure the quality of their web applications.

    https://vibetest.io/enterprise
    https://vibetest.io/

    #VibeTest #PromptEngineering #QAAutomation #AITesting #WebTesting #VibeTestIO #Claude #GPT4 #MCP #Selenium #Cypress #AccessibilityTesting #UIBugs #BrokenLinks #AutomatedTesting
    VibeTest encompasses a range of tools and platforms focused on enhancing interactions with AI and automating quality assurance (QA) testing for websites. One of the primary offerings is VibeTest.io, which specializes in teaching prompt engineering. This platform provides hands-on coding challenges that help users effectively communicate with AI systems such as Claude and GPT-4, aiming to improve the transformation of code through better prompts (https://vibetest.io/ ) (https://github.com/browser-use/vibetest-use ). On the other hand, the Vibetest MCP (Multi-Channel Platform) servers automate QA testing by deploying AI agents to identify various website issues, including UI bugs, broken links, and accessibility problems. This system is designed to streamline the testing process by launching multiple browser agents that crawl and evaluate web pages for technical flaws (https://apidog.com/blog/vibetest-use-mcp/ ) (https://www.mcpworld.com/en/detail/9ab49d16442b62a5e1ec9de97e05726d ). The Vibetest-use MCP server specifically focuses on these automated testing capabilities, emphasizing its efficiency in detecting and flagging potential issues (https://github.com/luk1337/VibeTest ). Overall, VibeTest is at the intersection of AI prompt engineering and automated web testing, providing valuable resources for both developers looking to enhance their AI interactions and teams aiming to ensure the quality of their web applications. https://vibetest.io/enterprise https://vibetest.io/ #VibeTest #PromptEngineering #QAAutomation #AITesting #WebTesting #VibeTestIO #Claude #GPT4 #MCP #Selenium #Cypress #AccessibilityTesting #UIBugs #BrokenLinks #AutomatedTesting
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  • 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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  • Consider this post as very very important: What is contnext engineering and where can you go to learn learn about this?

    Context engineering is the delicate art and science of filling the context window with just the right information for the next step." — Andrej Karpathy. A frontier, first-principles handbook inspired by Karpathy and 3Blue1Brown for moving beyond prompt engineering to the wider discipline of context design, orchestration, and optimization.

    https://github.com/davidkimai/Context-Engineering
    https://deepwiki.com/davidkimai/Context-Engineering
    https://www.datacamp.com/blog/context-engineering

    #contextengineering #andrejkarpathy #3blue1brown #davidkimai #promptengineering #contextwindow #contextdesign #contextorchestration #contextoptimization #ai #llms #deepwiki #datacamp #datascience #ainews
    Consider this post as very very important: What is contnext engineering and where can you go to learn learn about this? Context engineering is the delicate art and science of filling the context window with just the right information for the next step." — Andrej Karpathy. A frontier, first-principles handbook inspired by Karpathy and 3Blue1Brown for moving beyond prompt engineering to the wider discipline of context design, orchestration, and optimization. https://github.com/davidkimai/Context-Engineering https://deepwiki.com/davidkimai/Context-Engineering https://www.datacamp.com/blog/context-engineering #contextengineering #andrejkarpathy #3blue1brown #davidkimai #promptengineering #contextwindow #contextdesign #contextorchestration #contextoptimization #ai #llms #deepwiki #datacamp #datascience #ainews
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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/
    0 Comments ·0 Shares ·284 Views
  • Anthropic Academy - Build with Claude

    Start developing Claude-powered applications with our comprehensive API guides and best practices

    https://www.anthropic.com/learn/build-with-claude

    What you learn (Explore by topic)
    - Claude 4
    Learn how to harness the intelligence and capability of our latest models, Claude Sonnet 4 and Claude Opus 4
    - APIs & SDKs
    Learn about Anthropic's APIs, SDKs, and other development tools
    - Agents
    Build autonomous agents and agentic systems that understand, plan, and execute complex tasks
    - Model Context Protocol (MCP)
    Build advanced applications with the Model Context Protocol
    - Claude Code
    Speed up your development with Claude Code
    - Tool use
    Extend Claude's capabilities by connecting to external tools and APIs
    - Extended thinking
    Improve Claude's ability to solve complex tasks by allowing it to reason
    - Retrieval augmented generation (RAG)
    Build effective RAG systems to enhance Claude's responses with external data
    - Prompt engineering
    Create effective prompts that maximize Claude's performance
    - Evaluations
    Test and improve Claude's performance with structured evaluations
    - Prompt caching
    Optimize performance and reduce costs by reusing Claude's responses
    - Vision
    Harness Claude's ability to understand and analyze visual information
    - Computer use
    Learn how to use Claude models to interact with a computer desktop environment
    - Hackathon hacker guide
    Resources to help you get started with Claude, whether you're hacking with us at an event or on your own
    Anthropic Academy - Build with Claude Start developing Claude-powered applications with our comprehensive API guides and best practices https://www.anthropic.com/learn/build-with-claude What you learn (Explore by topic) - Claude 4 Learn how to harness the intelligence and capability of our latest models, Claude Sonnet 4 and Claude Opus 4 - APIs & SDKs Learn about Anthropic's APIs, SDKs, and other development tools - Agents Build autonomous agents and agentic systems that understand, plan, and execute complex tasks - Model Context Protocol (MCP) Build advanced applications with the Model Context Protocol - Claude Code Speed up your development with Claude Code - Tool use Extend Claude's capabilities by connecting to external tools and APIs - Extended thinking Improve Claude's ability to solve complex tasks by allowing it to reason - Retrieval augmented generation (RAG) Build effective RAG systems to enhance Claude's responses with external data - Prompt engineering Create effective prompts that maximize Claude's performance - Evaluations Test and improve Claude's performance with structured evaluations - Prompt caching Optimize performance and reduce costs by reusing Claude's responses - Vision Harness Claude's ability to understand and analyze visual information - Computer use Learn how to use Claude models to interact with a computer desktop environment - Hackathon hacker guide Resources to help you get started with Claude, whether you're hacking with us at an event or on your own
    0 Comments ·0 Shares ·499 Views
  • 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.
    0 Comments ·0 Shares ·449 Views
  • Where to find Anthropic's on-demand Courses:

    https://github.com/anthropics/prompt-eng-interactive-tutorial

    https://www.anthropic.com/learn

    https://github.com/anthropics/courses

    This repository contains an interactive tutorial created by Anthropic to provide a comprehensive understanding of prompt engineering within the Claude language model. The tutorial covers various aspects of prompt engineering, from basic prompt structure to advanced techniques for building complex prompts.

    #Anthropic #Claude #PromptEngineering #AIML #LanguageModels #InteractiveTutorial #GitHub #PromptStructure #AdvancedTechniques #AIeducation #AICourse #PromptBuilding #GenerativeAI #AItools
    Where to find Anthropic's on-demand Courses: https://github.com/anthropics/prompt-eng-interactive-tutorial https://www.anthropic.com/learn https://github.com/anthropics/courses This repository contains an interactive tutorial created by Anthropic to provide a comprehensive understanding of prompt engineering within the Claude language model. The tutorial covers various aspects of prompt engineering, from basic prompt structure to advanced techniques for building complex prompts. #Anthropic #Claude #PromptEngineering #AIML #LanguageModels #InteractiveTutorial #GitHub #PromptStructure #AdvancedTechniques #AIeducation #AICourse #PromptBuilding #GenerativeAI #AItools
    0 Comments ·0 Shares ·466 Views
  • 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
    0 Comments ·0 Shares ·476 Views
  • The ever-so careful Anthropic ! Meticulously daling with the fundamentals the complete exact opposite of OpenAI (Oh wait they are ex-OpenAI emplyess by the way .. right ?)

    Anthropic’s new Research feature adopts a multi-agent architecture where a lead Claude model orchestrates specialized subagents that search the web and other tools in parallel, enabling dynamic, breadth-first investigations that outperform single-agent approaches. Achieving dependable performance required careful prompt engineering—teaching agents how to delegate, scale effort, choose tools, and think aloud—as well as bespoke evaluation methods that combine LLM-as-judge metrics with human review. While the system delivers significant accuracy and speed gains, it also introduces engineering and economic challenges such as heavy token consumption, stateful error handling, and complex deployment, all of which demand rigorous observability, iterative testing, and robust production safeguards.

    #claude #anthropic #research #multiagent #airesearch #webresearch #perplexity #searchgpt #tavily #aiagents #promptengineering #llmasajudge #aiorchestration #parallelprocessing #breadthfirst #tokenoptimization #aiobservability #productionai #aitools #aievaluation

    https://www.anthropic.com/engineering/built-multi-agent-research-system
    The ever-so careful Anthropic ! Meticulously daling with the fundamentals the complete exact opposite of OpenAI (Oh wait they are ex-OpenAI emplyess by the way .. right ?) Anthropic’s new Research feature adopts a multi-agent architecture where a lead Claude model orchestrates specialized subagents that search the web and other tools in parallel, enabling dynamic, breadth-first investigations that outperform single-agent approaches. Achieving dependable performance required careful prompt engineering—teaching agents how to delegate, scale effort, choose tools, and think aloud—as well as bespoke evaluation methods that combine LLM-as-judge metrics with human review. While the system delivers significant accuracy and speed gains, it also introduces engineering and economic challenges such as heavy token consumption, stateful error handling, and complex deployment, all of which demand rigorous observability, iterative testing, and robust production safeguards. #claude #anthropic #research #multiagent #airesearch #webresearch #perplexity #searchgpt #tavily #aiagents #promptengineering #llmasajudge #aiorchestration #parallelprocessing #breadthfirst #tokenoptimization #aiobservability #productionai #aitools #aievaluation https://www.anthropic.com/engineering/built-multi-agent-research-system
    How we built our multi-agent research system
    www.anthropic.com
    On the the engineering challenges and lessons learned from building Claude's Research system
    0 Comments ·0 Shares ·427 Views
  • Unlock the potential of AI with Anthropic's guide to prompt engineering for Claude! This comprehensive resource helps developers craft effective prompts to maximize Claude's capabilities in various applications. Learn key strategies for optimizing your prompts to improve response quality and relevance, whether you're focused on creative writing, coding assistance, or more specialized tasks. With practical examples and detailed tips, you'll gain the insights needed to create powerful interactions with AI. Start enhancing your projects with Claude's advanced capabilities today!

    #AIPromptEngineering #ClaudeAI #MachineLearning #TechInnovation #Anthropic#anthropic #claude #promptengineering #ai #artificialintelligence #promptdesign #machinelearning #largeLanguageModels #llm #nlp #naturalLanguageProcessing #promptoptimization #airesearch #aitools #googlebard #chatgpt #gemini #aiwriting #aicoding #aichatbot

    https://docs.anthropic.com/en/docs/build-with-claude/prompt-engineering/overview
    Unlock the potential of AI with Anthropic's guide to prompt engineering for Claude! 🌟 This comprehensive resource helps developers craft effective prompts to maximize Claude's capabilities in various applications. Learn key strategies for optimizing your prompts to improve response quality and relevance, whether you're focused on creative writing, coding assistance, or more specialized tasks. With practical examples and detailed tips, you'll gain the insights needed to create powerful interactions with AI. Start enhancing your projects with Claude's advanced capabilities today! 🤖✨ #AIPromptEngineering #ClaudeAI #MachineLearning #TechInnovation #Anthropic#anthropic #claude #promptengineering #ai #artificialintelligence #promptdesign #machinelearning #largeLanguageModels #llm #nlp #naturalLanguageProcessing #promptoptimization #airesearch #aitools #googlebard #chatgpt #gemini #aiwriting #aicoding #aichatbot https://docs.anthropic.com/en/docs/build-with-claude/prompt-engineering/overview
    0 Comments ·0 Shares ·714 Views
  • VibeTest.io is a platform that helps users learn and practice prompt engineering through coding challenges. It focuses on improving communication skills with AI systems like Claude and GPT-4 to transform code. The platform allows users to measure their prompt engineering skills by solving problems, with the aim of providing users with a valuable skillset. It appears to be a hands-on tool for those looking to enhance their abilities in this area.
    #VibeTestio #promptengineering #Claude #GPT4 #AIcommunication #AICodingChallenges #promptdesign #AISkills #LangChain #promptflow #AIliteracy #generativeAI #promptoptimization

    https://vibetest.io/
    VibeTest.io is a platform that helps users learn and practice prompt engineering through coding challenges. It focuses on improving communication skills with AI systems like Claude and GPT-4 to transform code. The platform allows users to measure their prompt engineering skills by solving problems, with the aim of providing users with a valuable skillset. It appears to be a hands-on tool for those looking to enhance their abilities in this area. #VibeTestio #promptengineering #Claude #GPT4 #AIcommunication #AICodingChallenges #promptdesign #AISkills #LangChain #promptflow #AIliteracy #generativeAI #promptoptimization https://vibetest.io/
    0 Comments ·0 Shares ·690 Views
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