Thank you for joining! ❤️

Thanks so much for tuning into my talk, Slow Down to Speed Up with AI at SP today! I really hope you found it informative and helpful 🙂

Questions or feedback?

If you have any questions or feedback at all, please don't hesitate to reach out! You can find my profile here:

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Connect with me on LinkedIn 👉 linkedin.com/in/trungvose (connect, not just follow 😁)

If you share anything from the session, please tag me. It always makes my day ☀️

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• Trung Vo's Bio
• Website: trungvose.com
• Email: [email protected]
• Github: github.com/trungvose
• Twitter @trungvose
• Google Developer Profile: g.dev/trungvose
• Angular Singapore Events: angularsg.com
• Angular Singapore Community: t.me/angularsg
• Ask me anything: trungvose.com/chat

Resources from the talk

As promised, here's a link to my slides and some other useful resources for your reference:

⭐️ Slide

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https://1drv.ms/b/c/7a5c48d7c1de5ba4/IQB_XMdwgDwGQK4vFbczAkMlATy56jy9zxkgAn_7Lwcjtrc?e=ZkaSdN

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Angular Spotify

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Give a ⭐️ to angular-spotify if you like it. Thanks!

https://github.com/trungvose/angular-spotify

Slow down to speed up

• Explore → Plan → Code → Commit

  • Plan mode
  • Thoughts?
  • https://github.com/obra/superpowers
  • https://github.com/mattpocock/skills

• Workflow (personally, I used superpowers)

  https://github.com/shanraisshan/claude-code-best-practice

  

Workflow for AI Coding (watch this please)

Full Walkthrough: Workflow for AI Coding — Matt Pocock

Junior engineer with different kind of intuition

AI-native juniors carry potential advantages that are easy to underestimate. They need to prove themselves, which creates motivation to master new tools. They’re willing to make mistakes, which is essential in stochastic AI environments where perfect output isn’t guaranteed and experimentation is the path to quality. And they lack organisational baggage, with no preconceptions about the “right way” to build software. A junior engineer doesn’t have to unlearn twenty years of habits. They can adopt AI-native workflows as their default mode of working from day one.

There’s also something more fundamental at play. Junior engineers who grow up with AI tools develop a different kind of intuition. They learn to evaluate AI output rather than write everything from scratch. They learn to prompt effectively, to recognise when an agent is confidently wrong, and to navigate between multiple AI-generated options. These are the skills of supervisory engineering, and juniors are learning them natively in a way that many seniors are struggling to acquire.

https://sausheong.com/from-vibe-coding-to-agentic-engineering-1ca3ca72b5ac