The 4-Phase AI Workflow That Improves Data Infrastructure Faster скачать в хорошем качестве

The 4-Phase AI Workflow That Improves Data Infrastructure Faster

The most common difficulties teams face when incorporating artificial intelligence into data workflows are data quality and data infrastructure issues. This video introduces the context engineering framework of Product Requirements Prompts (PRP) to help turn these big data obstacles into opportunities to improve your data management and stop waiting to employ AI to enhance data analytics and data engineering processes. This is the foundational Claude Code masterclass I wish I had when I started. By the end of this video, you’ll learn what PRP is and how it provides context for data object creation, and how to create SQL-based data objects using the templated custom commands I’ve linked for you below. If you want to stop waiting on better data infrastructure and start getting value out of AI in your data, this video is made for you. I also want to give major credit to Rasmus Widing    / @rasmuswiding  , as I’ve adapted the original PRP context engineering framework he created for this use case with data. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ MY MATERIAL Product Requirements Prompt (PRP) for Data Objects Video Guide: https://github.com/kyle-chalmers/data... PRP INITIAL.md Template File: https://github.com/kyle-chalmers/data... generate-data-object-prp.md Claude Code Custom Command: https://github.com/kyle-chalmers/data... prp-data-object-execute.md Claude Code Custom Command: ​​https://github.com/kyle-chalmers/data... RESOURCES Context Engineering Quick Start (Product Requirement Prompts)    • Production-Ready AI Code in One Pass: The ...   by Rasmus Widing    / @rasmuswiding   Context Engineering is the New Vibe Coding (Learn this Now)    • Context Engineering is the New Vibe Coding...   by Cole Medin    / @colemedin   Snowflake Sample Data TPC-H: https://docs.snowflake.com/en/user-gu... ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 00:00 - The Data Obstacles that Prevent AI Adoption 01:21 - What You Will Learn and the Value Story 03:55 - How Product Requirements Prompts (PRP) for Data Objects Can Solve Problems 07:47 - Phase 1 Overview: Defined Requirements (INITIAL.md) and Template 14:01 - Phase 2 Overview: Generate PRP (/generate-data-object-prp) 15:30 - Phase 3 Overview: Execute PRP (/prp-data-object-execute) 16:39 - Phase 4 Overview: Promote to Production (Human-Executed) 17:27 - PRP Example 1: Customer Order Summary View Requirements 19:45 - Generate the Customer Order Summary View PRP 21:24 - Reviewing the Customer Order Summary View PRP 22:31 - Execute the Customer Order Summary View PRP 23:28 - Reviewing the Output for the Customer Order Summary Object 26:31 - PRP Example 2: More Complex Multi-Grain Dynamic Table Requirements 27:57 - Generate the Multi-Grain Order Analytics PRP 29:35 - Reviewing and Iterating on the Multi-Grain Order Analytics PRP 32:19 - Execute the Multi-Grain Order Analytics PRP and Potential Enhancements 33:33 - Reviewing and Altering the Output for the Multi-Grain Order Analytics Object 36:37 - Wrapup of the PRP for Data Objects Video ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 👋 I'm Kyle Chalmers and after 8+ years leading data teams, I'm here to make AI approachable for all data professionals and enthusiasts. Subscribe for weekly/bi-weekly insights, demos, and lessons on the future of data work. Connect with my business: https://www.kclabs.ai/ Connect with me on LinkedIn:   / kylechalmers   I plan on introducing more content in my Substack publication in the future as well: https://substack.com/@kylechalmers1 #ContextEngineering #ClaudeCode #ClaudeCommands #DataEngineering #AIForDataTeams #AIMasterclass #ClaudeAI #DataWorkflow #Snowflake #SQLAutomation #DataQuality #PromptEngineering #GenAI #AIProductivity #DataAnalytics #BusinessIntelligence #TechEducation #DataCareers #PRPFramework #productrequirementsprompt #DataInfrastructure #DataInfrastructure #AIDataPipelines