Teresa Torres

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 140,000 copies, we've taught over 18,000 students from 100+ 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.

Product Discovery Coach

I help digital product teams adopt continuous product discovery practices including a regular cadence of customer interviews, rapid prototyping, and assumption testing. I emphasize strong critical thinking practices to ensure there is a strong connection between what the teams are learning in their research activities with the product decisions that they are making. 

Recent clients include: Allstate, CarMax, CapitalOne, Snagajob, Spotify, among others. 

"When I started using Claude Code, I thought I was just building personal productivity tools. I didn't realize I was also learning context engineering—the same skills that product teams use to build production AI products."

Ever wondered how your daily AI habits connect to building actual AI products? In this article, I break down how the context management skills you're already developing directly translate to production context engineering.

Learn how product teams are solving the same problems you face:

🔧 Breaking big tasks into smaller, focused prompts (just like keeping CLAUDE.md files compact)
💾 Building external memory systems to store context outside the window  
✂️ Curating what goes into each conversational turn to prevent bloat
🔄 Repeating critical information so it's fresh when decisions are made
🤖 Using multiple agents to multiply available context windows

The article shows real examples from companies like Incident.io, Rest, Trainline, and others who've learned these patterns through trial and error. "If you'd break it down for a human, break it down for the LLM" - solid advice that applies whether you're coding or building products.

Check out the article: https://buff.ly/J2jDPfK 

🤔 Which context management trick from your daily AI use do you think would be most valuable in a production AI product? Share your thoughts in the comments below.

Author, Speaker, Product Discovery Coach @ ProductTalk.org

Context Engineering: 5 Strategies for AI Product Success

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