I recently joined the team at Hypr Live for a conversation about how we’re using AI in engineering at Collecting Cars and The Collecting Group. It was great to dig into how AI is evolving, and how we’re evolving with it.
You can watch the full episode here:
Here are three takeaways from the discussion, and two I should have mentioned:
- Augmenting with AI is a skill
- Experience compounds the value
- AI fluency is a team responsibility
- No excuse
- Guardrails matter
1) Augmenting AI is a skill
It’s not plug-and-play. Knowing how to prompt, review, guide, and refine AI output is a skill. And like all skills, it takes practice, exposure, and feedback to develop. I believe it’s something we all need to be working on.
2) Experience compounds the value
The more experience you bring to the table, the more value you can safely unlock from AI. You know what “good” looks like, can spot subtle issues, and course-correct early. AI is a multiplier, not a shortcut.
3) AI fluency is a team responsibility
An AI champion can help kick things off, but the real power comes from team-wide curiosity and experimentation. With things evolving so quickly, shared learning beats isolated heroes every time.
4) No excuses
I forgot to say this on the podcast, but it’s crucial: AI doesn’t ship code, engineers do. Engineers remain fully accountable for what’s shipped. “That bug was AI” is not a valid excuse. As agentic AI evolves, this may change, but for now, accountability rests firmly with us.
5) Guardrails matter
If you’re unsure where to start, we recommend using Gemini while logged in with your work email. As part of our Enterprise Google Workspace setup, this keeps everything ring-fenced, private, and compliant. And if you’re experimenting with new tools or workflows, share it with the team. That openness reduces risk, avoids incidents, and keeps the learning loop alive.
Would love to hear how others are thinking about this. How are you building confidence and fluency with AI across your teams?
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