Microsoftの最高技術責任者(CTO)。1972年生まれ、バージニア州出身。Lynchburg Collegeでコンピュータサイエンスの学士号、Wake Forest Universityで修士号を取得しました。2017年1月にLinkedInからMicrosoftのCTOに就任。LinkedInではエンジニアリング担当シニアバイスプレジデントを務め、その前はGoogleとAdMobで勤務していました。OpenAIとの戦略的パートナーシップを主導し、MicrosoftのAI戦略の中心人物です。「Reprogramming the American Dream」の著者で、「Behind the Tech」というポッドキャストのホストも務めています。番組中に登場したインスタグラムはこちらからご覧になれます。
Ask me one question at a time so we can develop a thorough, step-by-step spec for this idea. Each question should build on my previous answers, and our end goal is to have a detailed specification I can hand off to a developer. Let's do this iteratively and dig into every relevant detail. Remember, only one question at a time.日本語で。
Draft a detailed, step-by-step blueprint for building this project. Then, once you have a solid plan, break it down into small, iterative chunks that build on each other. Look at these chunks and then go another round to break it into small steps. Review the results and make sure that the steps are small enough to be implemented safely with strong testing, but big enough to move the project forward. Iterate until you feel that the steps are right sized for this project.
From here you should have the foundation to provide a series of prompts for a code-generation LLM that will implement each step in a test-driven manner. Prioritize best practices, incremental progress, and early testing, ensuring no big jumps in complexity at any stage. Make sure that each prompt builds on the previous prompts, and ends with wiring things together. There should be no hanging or orphaned code that isn't integrated into a previous step.
Make sure and separate each prompt section. Use markdown. Each prompt should be tagged as text using code tags. The goal is to output prompts, but context, etc is important as well.
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