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As a product discovery coach, I help product teams make better decisions about what to build. I teach them how to: - Identify clear business outcomes - Uncover unmet customer needs, pain points, and desires - Discover the right solutions that deliver both business value and customer value My book Continuous Discovery Habits has sold over 100,000 copies, we've taught over 15,000 students from 102 countries through the Product Talk Academy, and reach 100,000s of product people through our free blog posts and social media content. If you aren't satisfied with how your teams decide what to build, get in touch.
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Worthy Read: How GiveDirectly increased donations by over $3 million/year through experimentation by Olivia Chen "Sometimes people who don't have money just need money!" 💡 Learn how GiveDirectly is transforming charitable giving through direct cash transfers to families in extreme poverty. This article shares their data-driven approach and successful product experiments that increased donations by $3 million annually 📈 Key takeaways: 🎯 Direct cash transfers are backed by 500+ academic studies 💪 Recipients like Rose use funds for business, education, and basic needs 🔄 Monthly donors have 12x the lifetime value of one-time donors 💳 Adding Apple Pay and Google Pay boosted trust and convenience ✨ Website redesign with embedded donation forms increased conversion by 35% ❓ If you received an unexpected $850, what would you invest it in? Share your thoughts in the comments below.
I'm starting to experiment with creating LLM tools to help product teams better identify opportunities from their customer interviews. I'm evaluating how the different models perform based on my prompt/knowledge base. For an interview where I identified 26 different opportunities: ChatGPT (through a customGPT, so 4-0) identified 10: 2 were real, ☣️ 8 were complete hallucinations I could not believe how bad this was. I asked ChatGPT to add ⏰ timestamps to each opportunity. It made up time stamps. I quoted the timestamp range from the original transcript to show it it was hallucinating. It apologized, acknowledged its mistake, and tried again. It made up more opportunities. it was insane. ✅ My verdict: Do not use ChatGPT to identify opportunities Claude Sonnet 3.7: Identified 15 opportunities, all of them were real. 3 were ones that I had missed. 2 allowed me to better frame opportunities I had already found. Claude cited exact quotes from the transcript and provided timestamps so that I could verify. ✅ My verdict: With the right instructions Claude is a helpful thought partner when identifying opportunities. Please don't outsource your synthesis work. LLMs are amazing thought partners. But they make mistakes. They hallucinate. They miss important stuff. Even though Claude was decent, I still identified 14 opportunities it missed. As I further refine how i use these tools, I'll share tips and best practices and will eventually publish tools for folks to try themselves. More to come. Claude Sonnet 3.7
Is AI coming for your job? Maybe your current job. But probably not all of your possible jobs. Companies will likely get smaller. But when companies get smaller, it becomes easier to start a company. My bet is we are going to end up with a lot more smaller companies. And our larger companies will just be giant amalgamations of smaller teams. I doubt jobs will go away. Humans will always create things. But how we create things is rapidly changing. If your job is far away from the creation of things, maybe get more involved in the creation of things. It’s never been easier. I’m not worried about the future. I know how to create things. I’ll always find a way.
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