I had a chance to chat with Blake Barnes (VP Product at Google Workspace) about the future of work, apps, and human skills. Blake leads products like Gmail and Google Calendar.

You can listen to the full conversation on Spotify and Apple Podcasts, or watch the video on YouTube.

What we discussed:

* AI and its promise of productivity

* Productivity killers at work and how AI might solve them

* The impact of MCP on the future of apps

* The future of Gmail: will it always be a list of emails or will it change like Search did?

* Building trust into AI-powered experiences

* Advice for companies who want to get started with AI for internal productivity

* The human skills that will become more valuable in the future

Microsoft invited me to attend Microsoft Build in Seattle earlier this week, and I had a chance to interview Ryan Cunningham, the CVP of Power Platform Intelligent Apps before quickly rushing to catch my flight.

I sat down with Ryan for a 15-minute conversation to discuss the rise of vibe coding and agents, where their real value lies, and the importance of human oversight and control.

You can listen to the full conversation on Spotify and Apple Podcasts, or watch the video on YouTube.

I’m planning on interviewing more people soon, so leave a comment or email me at [email protected] with any questions or topic requests.

If you have any anonymous feedback about this interview, you can leave it here.

Sarah Burton is a Lead Product Designer at Dovetail, a customer insights hub that helps companies better understand their customers so they can build better products and services for them. They just launched Dovetail 3.0, which includes a series of AI features that help you analyze and extract insights from customer surveys, interviews, and app store reviews.

In my conversation with Sarah, we discuss:

🤖 How to balance AI automation and human expertise

🔍 The importance of understanding customer problems before jumping too quickly on the AI train

🧠 Design tactics to help you deal with AI’s unpredictable nature

Chapters

00:00 Introduction to Dovetail 02:51 The Next Generation of Customer Analysis and Insights 09:52 The Role of AI in Enhancing Customer Insights 13:03 Human-Centric AI Integration Principles 19:59 Three Levels of AI Automations 24:56 Understanding Customer Needs and AI Opportunities 27:25 Integrating Design and Engineering for AI Solutions 29:21 Designing for Unpredictability in AI 36:52 Designing for Trust and Transparency in AI 43:02 Navigating AI Pressure in Design

My main takeaways from this conversation:

* Don’t start from AI and retrofit problems to it. Start from your customer problems and then see if AI is a good solution.

* AI features don’t need to be binary (on or off) because outputs can still be useful even if they’re not perfect.

* Design AI systems with a “human-in-the-loop” mindset. People want to control and collaborate with AI, instead of automating every single task.

* Make AI solve problems and tasks that people hate to do so they can focus on what they love to do.

* Don’t expect your customers to be prompt engineers. Design an interface that helps them get their task done effectively and do the hard work behind the scenes.

* AI is enabling an advanced level of understanding and analyzing customer sentiment by making it easy to ask a question across a large body of qualitative data.

* If you’re integrating AI in your product, it needs to convey trust and provide transparency about its outputs.

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Welcome to the Year 2049! Join me on the journey to discover and understand how AI can solve meaningful problems in our life and work. You'll hear from researchers, designers, engineers, and other innovators tackling problems we care about and creating a future we're excited about.