영상 목록으로

GitHub

3 ways to streamline AI code reviews across your team

플랫폼
YouTube
길이
2:01
사용 언어
영어(미국)
조회수
5.3천
컷 간격 중앙값
10.00s
얼굴 노출
79%
어두운 프레임
8%
GitHub 3 ways to streamline AI code reviews across your team at 0:00close presenter
GitHub3 ways to streamline AI code reviews across your team
0:00
GitHub 3 ways to streamline AI code reviews across your team at 0:05
GitHub3 ways to streamline AI code reviews across your team
0:05
GitHub 3 ways to streamline AI code reviews across your team at 0:06
GitHub3 ways to streamline AI code reviews across your team
0:06
GitHub 3 ways to streamline AI code reviews across your team at 0:06
GitHub3 ways to streamline AI code reviews across your team
0:06
GitHub 3 ways to streamline AI code reviews across your team at 0:08medium presenter
GitHub3 ways to streamline AI code reviews across your team
0:08
GitHub 3 ways to streamline AI code reviews across your team at 0:09close presenter
GitHub3 ways to streamline AI code reviews across your team
0:09
GitHub 3 ways to streamline AI code reviews across your team at 0:16close presenter
GitHub3 ways to streamline AI code reviews across your team
0:16
GitHub 3 ways to streamline AI code reviews across your team at 0:27close presenter
GitHub3 ways to streamline AI code reviews across your team
0:27
GitHub 3 ways to streamline AI code reviews across your team at 0:34
GitHub3 ways to streamline AI code reviews across your team
0:34
GitHub 3 ways to streamline AI code reviews across your team at 0:35close presenter
GitHub3 ways to streamline AI code reviews across your team
0:35
GitHub 3 ways to streamline AI code reviews across your team at 0:38close presenter
GitHub3 ways to streamline AI code reviews across your team
0:38
GitHub 3 ways to streamline AI code reviews across your team at 0:43close presenter
GitHub3 ways to streamline AI code reviews across your team
0:43
GitHub 3 ways to streamline AI code reviews across your team at 0:44close presenter
GitHub3 ways to streamline AI code reviews across your team
0:44
GitHub 3 ways to streamline AI code reviews across your team at 0:47close presenter
GitHub3 ways to streamline AI code reviews across your team
0:47
GitHub 3 ways to streamline AI code reviews across your team at 0:50close presenter
GitHub3 ways to streamline AI code reviews across your team
0:50
GitHub 3 ways to streamline AI code reviews across your team at 0:50close presenter
GitHub3 ways to streamline AI code reviews across your team
0:50
GitHub 3 ways to streamline AI code reviews across your team at 0:51
GitHub3 ways to streamline AI code reviews across your team
0:51
GitHub 3 ways to streamline AI code reviews across your team at 0:53
GitHub3 ways to streamline AI code reviews across your team
0:53
GitHub 3 ways to streamline AI code reviews across your team at 0:55
GitHub3 ways to streamline AI code reviews across your team
0:55
GitHub 3 ways to streamline AI code reviews across your team at 1:01close presenter
GitHub3 ways to streamline AI code reviews across your team
1:01
GitHub 3 ways to streamline AI code reviews across your team at 1:02close presenter
GitHub3 ways to streamline AI code reviews across your team
1:02
GitHub 3 ways to streamline AI code reviews across your team at 1:06close presenter
GitHub3 ways to streamline AI code reviews across your team
1:06
GitHub 3 ways to streamline AI code reviews across your team at 1:10close presenter
GitHub3 ways to streamline AI code reviews across your team
1:10
GitHub 3 ways to streamline AI code reviews across your team at 1:14close presenter
GitHub3 ways to streamline AI code reviews across your team
1:14
GitHub 3 ways to streamline AI code reviews across your team at 1:18close presenter
GitHub3 ways to streamline AI code reviews across your team
1:18
GitHub 3 ways to streamline AI code reviews across your team at 1:22close presenter
GitHub3 ways to streamline AI code reviews across your team
1:22
GitHub 3 ways to streamline AI code reviews across your team at 1:26close presenter
GitHub3 ways to streamline AI code reviews across your team
1:26
GitHub 3 ways to streamline AI code reviews across your team at 1:30close presenter
GitHub3 ways to streamline AI code reviews across your team
1:30
GitHub 3 ways to streamline AI code reviews across your team at 1:34close presenter
GitHub3 ways to streamline AI code reviews across your team
1:34
GitHub 3 ways to streamline AI code reviews across your team at 1:38close presenter
GitHub3 ways to streamline AI code reviews across your team
1:38
GitHub 3 ways to streamline AI code reviews across your team at 1:42close presenter
GitHub3 ways to streamline AI code reviews across your team
1:42
GitHub 3 ways to streamline AI code reviews across your team at 1:45
GitHub3 ways to streamline AI code reviews across your team
1:45
GitHub 3 ways to streamline AI code reviews across your team at 1:46
GitHub3 ways to streamline AI code reviews across your team
1:46
GitHub 3 ways to streamline AI code reviews across your team at 1:49close presenter
GitHub3 ways to streamline AI code reviews across your team
1:49
GitHub 3 ways to streamline AI code reviews across your team at 1:54close presenter
GitHub3 ways to streamline AI code reviews across your team
1:54
GitHub 3 ways to streamline AI code reviews across your team at 1:56
GitHub3 ways to streamline AI code reviews across your team
1:56

3 ways to streamline AI code reviews across your team 자막 전문

브랜드가 작성한 것이 아니라, 영상의 오디오를 음성 모델이 받아쓴 것입니다. 아무 줄이나 클릭하면 그 순간으로 이동합니다.

  1. 0:00How should organizations manage reviewing all the code that AI generates?
  2. 0:08We understand, of course, the importance of DevOps and reviewing all of that code
  3. 0:13before it eventually gets pushed out to production.
  4. 0:16But I talk to developers who often feel overwhelmed by the amount of code
  5. 0:21and that sometimes they're really spending more time reading and reviewing that code
  6. 0:27than they would have spent if they would have just written it by themselves.
  7. 0:30How can we help streamline that review process?
  8. 0:34I see growing review backlogs as a signal that the overall system
  9. 0:39hasn't yet been calibrated for the newer agentic ways of working.
  10. 0:43Often, one or more of the following might be occurring.
  11. 0:46First, the work an agent picked up may have been poorly scoped.
  12. 0:51In our agentic engineering system, we would see this as an opportunity
  13. 0:55to improve the health of shared knowledge or the direct mode.
  14. 0:59It's about improving the inputs, for example, acceptance criteria
  15. 1:02or relevant prior decisions, so the review then becomes easier.
  16. 1:07Second, reduce the scope of what agents are asked to do,
  17. 1:11so poor requests are smaller and reviewable in one pass.
  18. 1:15Those who are familiar with coding best practices
  19. 1:17will recognise that keeping PRs small is not a new concept.
  20. 1:21It's actually a great example of how engineering fundamentals have not changed,
  21. 1:26and engineers should continue to bring those fundamentals to how they work with agents.
  22. 1:31GitHub's Stack PRs feature is useful here too.
  23. 1:35Third, try to avoid letting those reviews pile up.
  24. 1:38This is about understanding that the system itself needs reconsideration
  25. 1:42as agents are increasingly used and the modes that people and agents play changes.
  26. 1:48While output may be increasing, engineers may find they spend more time in the direct
  27. 1:53and assess modes rather than in the perform mode.
27줄 · 300단어