# Sightlines issue no.3: Raise the bar for how teams use AI — retained record

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Sightlines issue no.3: Raise the bar for how teams use AI
How do you drive AI adoption and make better decisions about what to build?
Share Sightlines issue no.3: Raise the bar for how teams use AI
Whether in Executive Briefing webinars or at Leadership Collective events, we’ve been chatting with leaders across product, design, and engineering to understand their biggest AI-related hurdles. This month, we’re zooming in on one question that continues to surface: How do you bridge the gap between the promise of AI and its impact in practice?
Push past faster output
AI can help teams move faster, but that doesn’t automatically lead to better work. Speed is only valuable if teams are moving in the right direction. Leaders should set the expectation that teams use AI not just to ship faster, but to explore more directions, work through edge cases before committing, and refine the details that make the product distinctly theirs.
Create the conditions for team-wide adoption
Individual AI fluency will only get you so far. To drive AI adoption across the entire team, leaders need to make learning and experimentation a shared practice. Here are a few ways to make that happen:
- Create dedicated spaces for peer-led training
- Bringing AI into existing team workflows
- Encourage product builders to share what they’re trying, including experiments that didn’t work
- Get hands-on with the tools and show your own work in progress
Go deeper: The guide to building an AI-native org
Worth repeating
Across Leadership Collective events, here are a couple of lines that stuck with us this month:
“When it looks like leadership just cares about moving fast, that’s a bad signal. We try to make it really clear that speed is not the goal. Of course we want to move fast, but if we’re moving fast and shipping slop, that’s not good.” Ian Silber, Head of Product Design, OpenAI
“I’ve heard people say ‘I have no time to play with AI tools, I have deliverables.’ As managers, one of the first things we can do is create time for our teams to play and make mistakes and figure things out.” Gui Seiz, Director of AI Product Design, Figma
Keep the conversation going:
- Watch: Figma’s Noah Levin on building connected AI workflows, from idea to ship
- Read: How to move fast toward the right thing How to move fast toward the right thing With AI, speed comes easy, but so does tech debt. That’s why the best teams don’t just ship something fast; they consider it carefully, build it efficiently, and make it stand out.
- Learn: Guides, demos, and hands-on resources for getting started with Figma AI across every stage
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