WhoBuilt

A Founder's Playbook for Shipping 10x Faster with AI

Dec 14, 2025· 42 min· 4.0K views·Watch on YouTube

Speaker

Yana Welinder, head of AI at Amplitude and former founder, talks with Peter Yang on his podcast about shipping faster with AI, learning from users, and putting customer feedback alongside product analytics.

Bring founder ownership to product work

Welinder says founders see the whole company as their responsibility, while product leaders often focus more narrowly on product strategy and managing PMs. She argues that product work should be cross-functional in practice: PMs should do user research, design, and as much coding as they can.

Move from debate to shipping

Welinder says she would rather execute on several options than spend too long debating which one is best. At Amplitude, CEO Spencer Skates banned decisions by committee to help teams take ownership and move faster. She recommends demonstrating a faster approach through real launches, so colleagues can see what works.

Use early releases to learn with customers

Welinder says a rough first release can build trust when teams respond quickly to customer feedback. She describes fixing reported issues within 15 minutes and keeping users engaged with prompt updates and follow-up releases. Teams can start with a small group, improve the product, and expand access as it becomes more polished.

Use AI for rapid prototypes and daily work

Welinder iterates on prototypes between customer calls, incorporating one person's feedback before showing the next version. She also uses Sora videos in marketing and says some held viewers through to the end at rates of 50% or more. With ChatGPT Atlas, she triages email, drafts replies, and summarizes emotionally charged messages; she says AI-generated prompts and evals still need careful human review.

Connect customer feedback with product data

Welinder demos Amplitude Feedback, which brings support tickets and public reviews together with quantitative product analytics. Teams can find frequent requests, inspect what users said, create cohorts to study their behavior, and generate a draft PRD from feedback. She says accuracy remains essential for analytics, where even small data errors can undermine trust.

Takeaways

  • Give teams clear ownership so they can test ideas without waiting for committee decisions.
  • Ship to a small group, listen closely, and follow up quickly when users report problems.
  • Use AI to revise prototypes between customer conversations and test each iteration with users.
  • Treat AI-generated prompts as drafts: run evals and have a person check whether changes improve results.
  • Pair qualitative feedback with behavioral data to understand both what users say and what they do.

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