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From Writing Code to Designing Systems: How the Developer Role is Changing — Chris Noring, Microsoft

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AI Engineer· published 2026-07-11· 0:23:05· en-US· indexed 2026-08-10 19:53

Open on YouTube

Scene timeline

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What was stored

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whisperx 326
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word timings on 326 cues

Provenance

Each pipeline stage, its state and the model that produced it
stage state model started took
fetch done 2026-08-10 17:40 1m 29s
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chunk done 2026-08-10 17:42 0s
text_embed done 2026-08-10 19:53 0s
keyframe done 2026-08-10 17:42 2m 04s
ocr done 2026-08-10 17:44 21s
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Transcript

326 cues· 4,174 words· 21,433 chars

  1. 0:14 Hey folks, we are starting a little bit early as we are at capacity.
  2. 0:18 So thank you all for showing up.
  3. 0:19 My name is Chris Noring.
  4. 0:21 My daytime job is at Microsoft, where I work a lot with AI engineering.
  5. 0:27 Right, so this session is called From Writing Code to Designing Systems.
  6. 0:31 So show of hands, how many of you are coding like you normally do?
  7. 0:37 Not many hands, right?
  8. 0:38 So most of you, I think, have shifted into more of a systems approach, right?
  9. 0:42 So maybe I'm talking to people who have already done the shift.
  10. 0:48 That's not always the case, by the way.
  11. 0:50 So sometimes when you go out at conferences, people are like, I'm hacking away.
  12. 0:54 I've tried Claude.
  13. 0:55 I've tried Copilot.
  14. 0:57 Interesting.
  15. 0:57 How many are using Claude, by the way?
  16. 0:59 No judgment.
  17. 1:00 How many are using Copilot?
  18. 1:03 Okay, half and half, maybe more Claude, that's fine.
  19. 1:06 We are very good friends of Claude, I should say that.
  20. 1:08 We are even showing up at events together, so Anthropic, good stuff.
  21. 1:13 So what I mean to tell you today is maybe tell you a story that you already know.
  22. 1:17 You know that your world has changed.
  23. 1:19 You know that in the old days, 100% on keyboard, and you might still be on the keyboard.
  24. 1:24 You just do different things with your time.
  25. 1:27 But we all knew that we were the limitation, right?
  26. 1:30 We were brilliant engineers.
  27. 1:32 We did 100% of the code, but...
  28. 1:34 linear progress.
  29. 1:35 It was just you trying to advance things.
  30. 1:37 It was up to you whether a feature was being built or not.
  31. 1:41 And sometimes you had to choose a scenario where, well, I don't have time to build this feature because I'm doing this over here.
  32. 1:48 That's no longer a limitation.
  33. 1:50 So what's happening?
  34. 1:52 I think most of you still have a job, right?
  35. 1:54 So you know that your job didn't disappear.
  36. 1:57 you know that your center of gravity has moved.
  37. 1:59 So you are no longer 100% developers, but you are now in a different position, which some people might argue.
  38. 2:06 I mean, many of us, I think, have chosen our profession because we love coding, right?
  39. 2:12 Right?
  40. 2:13 I think so.
  41. 2:14 So to some extent, we're still writing code.
  42. 2:17 We just are very, very precious with our time what we write, right?
  43. 2:21 Because we now have so many helpers, but
  44. 2:24 Many of you have heard the term AI slope, right?
  45. 2:28 I see nods here.
  46. 2:29 So you understand in the early days of these AI tools, you were like, oh my God, I can't believe it produced this kind of code.
  47. 2:35 It gives me more work than before.
  48. 2:37 I had to rewrite all that code.
  49. 2:39 But now we're coming into a place where guardrails is a big thing of our existence.
  50. 2:44 So you are stuck with an AI tool.

Chapters

  1. 0:00 The evolving developer role
  2. 3:14 New AI-driven workflow
  3. 6:46 Implementing guardrails
  4. 9:35 Using skills for consistency
  5. 12:48 Deploying custom agents
  6. 16:10 Scaling through delegation

Open at this second