Unlock AI Coding with Workflow-Driven, Tuned Prompt Chains 🔑

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AI Summary

Summary of Video Transcript

• The video presents a systematic workflow for using AI coding assistants to plan and implement new features in software development.
• The workflow is modeled after human software engineering processes and uses a chain of prompts designed to work with an AI coding assistant.
• The process is demonstrated by building features into an app started in a previous tutorial, emphasizing the workflow and prompt techniques over the specific app or tools used.
• The workflow chain consists of prompts that feed into each other, guiding the user from requirement analysis to feature implementation.
• The workflow includes:
  • Analyzing the implementation status of app requirements.
  • Generating user stories for a sprint based on prioritized requirements.
  • Breaking down user stories into discrete implementation steps.
  • Implementing code for each step and verifying the code.

Detailed Instructions and URLs Extracted

• The GitHub repository containing the prompts for the workflow is mentioned, but the exact URL is not provided in the transcript.
• Commands for interacting with the AI coding assistant (AER) are detailed, such as chat mode, readon, # analy D prompt, save to file, and SL chat mode code.
• Instructions for using the workflow chain are provided, including how to add context to AER, invoke prompts, and switch between ask and code modes.
• The process of creating and verifying implementation plans before making code changes is outlined.
• Tips for troubleshooting, such as using the implementation status command and the undo command in AER, are given.
• The video concludes with the implementation of the last user story for the sprint and some cleanup of the project.

Self-Promotion and Off-Topic Content

• The author’s self-promotion and the announcement of a new school community are not included in the summary as per the instructions.