Ruby 개발과 페어 프로그래밍: Pivotal Labs가 말하는 협업의 기술
페어 프로그래밍은 단순한 공동 작업을 넘어 개발 과정에서의 표현력, 창의성, 공동체 의식을 극대화하는 Ruby의 철학과 맞닿아 있다.
Ruby 개발과 페어 프로그래밍: Pivotal Labs가 말하는 협업의 기술
페어 프로그래밍은 단순한 공동 작업을 넘어 개발 과정에서의 표현력, 창의성, 공동체 의식을 극대화하는 Ruby의 철학과 맞닿아 있다.
Мой опыт парного программирования с Chat GPT-5
Привет, Хабр! Про модели искусственного интеллекта сейчас не говорит только ленивый. Высказывается множество мнений и нередко они оказываются на противоположных полюсах: от полного скепсиса до убеждённости, что произошла новая научно-техническая революция. Жизненный опыт подсказывает, что истина где-то по-середине и инструмент будет полезным ровно настолько, насколько ты умеешь им пользоваться. В относительно недавнем интервью генеральный директор Microsoft Сатья Наделла заявил, что примерно 20-30 % кода в Microsoft уже сейчас генерируется ИИ и разработчикам надо будет адаптироваться. Мне тоже захотелось попробовать внедрить такого помощника в свои рабочие процессы и посмотреть, что из этого получится.
[Перевод] Vibe Coding — не оправдание для некачественной работы
ИИ-ассистенты обещают революцию в программировании, позволяя за минуты создать то, на что раньше уходили дни. Но за этой скоростью скрывается опасность — код, который выглядит рабочим, но разваливается при первом же необычном сценарии. "Vibe coding" требует не отказа от инженерной дисциплины, а нового уровня ответственности за то, что генерирует искусственный интеллект. — 7 правил безопасного vibe coding — Для каких целей подходит и не подходит vibe coding
https://habr.com/ru/articles/904560/
#искусственный_интеллект #разработка #vibe_coding #качество_кода #технический_долг #pair_programming #copilot #code_review #программная_инженерия #лучшие_практики
In live-streamed programming, developers broadcast their development work on open source projects using streaming media such as YouTube or Twitch. Sessions are first announced by a developer acting as the streamer, inviting other developers to join and interact as watchers using chat. To better understand the characteristics, motivations, and challenges in live-streamed programming, we analyzed 20 hours of live-streamed programming videos and surveyed 7 streamers about their experiences. The results reveal that live-streamed programming shares some of the characteristics and benefits of pair programming, but differs in the nature of the relationship between the streamer and watchers. We also found that streamers are motivated by knowledge sharing, socializing, and building an online identity, but face challenges with tool limitations and maintaining engagement with watchers. We discuss the implications of these findings, identify limitations with current tools, and propose design recommendations for new forms of tools to better supporting live-streamed programming.
In live-streamed programming, developers broadcast their development work on open source projects using streaming media such as YouTube or Twitch. Sessions are first announced by a developer acting as the streamer, inviting other developers to join and interact as watchers using chat. To better understand the characteristics, motivations, and challenges in live-streamed programming, we analyzed 20 hours of live-streamed programming videos and surveyed 7 streamers about their experiences. The results reveal that live-streamed programming shares some of the characteristics and benefits of pair programming, but differs in the nature of the relationship between the streamer and watchers. We also found that streamers are motivated by knowledge sharing, socializing, and building an online identity, but face challenges with tool limitations and maintaining engagement with watchers. We discuss the implications of these findings, identify limitations with current tools, and propose design recommendations for new forms of tools to better supporting live-streamed programming.
In live-streamed programming, developers broadcast their development work on open source projects using streaming media such as YouTube or Twitch. Sessions are first announced by a developer acting as the streamer, inviting other developers to join and interact as watchers using chat. To better understand the characteristics, motivations, and challenges in live-streamed programming, we analyzed 20 hours of live-streamed programming videos and surveyed 7 streamers about their experiences. The results reveal that live-streamed programming shares some of the characteristics and benefits of pair programming, but differs in the nature of the relationship between the streamer and watchers. We also found that streamers are motivated by knowledge sharing, socializing, and building an online identity, but face challenges with tool limitations and maintaining engagement with watchers. We discuss the implications of these findings, identify limitations with current tools, and propose design recommendations for new forms of tools to better supporting live-streamed programming.