Context Engineering, Product Philosophy, and the Thinking of the endgame Xiankun Wu x Aakash Gupta

Listen to AI PM expert Aakash Gupta's full interview with Kuse founder and CEO Xiankun Wu on Spotify, explore why context is becoming the foundation of next-generation AI products, and how that philosophy shaped the rise of Kuse.

Watch now: https://youtu.be/jxxD3tVJm0o

‍Spotify: https://open.spotify.com/show/7vVEMqCSKb7I7xPk8xZtg5‍

Apple Podcast: https://podcasts.apple.com/in/podcast/product-growth-podcast/id1763555775

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1. Growth That Didn't Follow the Usual Playbook

While most startups competed for attention on X and TikTok, Kuse grew by leaning into Threads: a fast-growing platform in Taiwan and Hong Kong with generous reach and minimal competition.

Across hundreds of intern-run accounts, Kuse showcased daily practical use cases:

Markdown → clean layouts

Exam paper generation

Document processing

Web-based presentations

Everyday workflows teachers, students, and creators love

This produced 3M+ monthly impressions, thousands of daily site visits, and a uniquely international early community, all with zero advertising spend.

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2. MVO Before MVP

Kuse's product process flips the traditional sequence. Instead of "build the feature first and fix AI behavior later," the team begins by stabilizing Minimal Viable Output.

What should the model produce?

Can it do so consistently?

Is the reasoning chain correct and repeatable?

Only when the output is solid do they invest in UI, workflows, UX polish, and interactive layers. This avoids wasted engineering effort and ensures every new feature is grounded in real AI capability, not wishful design.

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3. The Pivot That Defined Kuse

Kuse didn't begin as a knowledge engine. Our team originally built a design agent, an infinite canvas for creative briefs. But real users told a different story. They uploaded PDFs, research papers, class notes, and internal documentation instead of design descriptions.

AI design wasn't the pain point. Understanding information was.

Following users rather than the original vision became the turning point. The pivot to a horizontal knowledge engine accelerated adoption dramatically and set the foundation for the product Kuse is known for today.

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4. "Born out of inevitable" mindset

Xiankun described the long-term vision from a different perspective: AI will eventually handle many tasks faster and more reliably than humans. So the question becomes: what should human  beings experience feel like?

For Kuse, the answer is: a playground where people can still enjoy using it and feel the fulfillment of creating something, even when AI can do it faster.

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Curious to explore more?

‍Drop the full interview video (https://www.youtube.com/watch?v=jxxD3tVJm0o) into Kuse, let Kuse summarize it for you, and see what new magic happens!