Mindvalley Stories
Case Study · AI Mastery

A yoga teacher with no coding background built a memory app now in beta

A first-time creator built People Keeper, an AI-powered app for remembering the names of casual acquaintances, now in beta at a yoga studio.

This creator had never written code, yet they built a working, multi-user app that helps people remember the barista, the yoga student and the networking contact. What makes the story stand out is how they got there: by treating AI as a thinking partner that challenged their assumptions, not just a faster pair of hands. It is a clear picture of what a curious beginner can make.

Karen Yoder
A first-time app creator with zero coding background, connected to a yoga studio community.

People Keeper — A Memory Sidekick Built Through AI Collaboration

Before

They wanted to fill a quiet gap in everyday life: the people who are more than strangers but not quite contacts, like baristas, yoga students and grocery clerks. They had no coding background. For weeks they worked on perfecting structured input forms, sure that a better form was the answer.

“I spent weeks perfecting structured input forms before asking "is there a better way?”

In their own words

The turning point

The shift came when they stopped working in executor mode and moved into creator mode, using AI to question their thinking instead of only to go faster. They finally asked, "is there a better way?" The AI suggested natural language brain dumps, where users just talk and the AI organises the details. That one question changed the whole design.

“I didn't need a better form. I needed to question why I was building a form at all.”

In their own words

After

They built People Keeper, a fully functional, multi-user app with an AI Quick Add that turns free-flowing notes into structured contact details, plus a business card scanner, search, pinning and archiving. It is in beta with real users at their yoga studio, with a feedback survey running. Along the way they handled real-world hurdles like SMS carrier compliance, and pivoted when they were blocked.

What it lets people do

People Keeper lets users capture a name and a few details the moment they meet someone, simply by talking or snapping a business card. Drawing on cognitive offloading and Jim Kwik's spaced repetition approach, it helps people stop rehearsing names anxiously and be present with the person in front of them.

What they learned

They came away convinced that AI holds information, not answers, and that the answers appear through curious collaboration. Their biggest lesson was to question assumptions relentlessly, because the simplest solution is often not the first instinct.

“AI has information, not answers — the answers emerge through curious collaboration”

In their own words

People Keeper — A Memory Sidekick Built Through AI Collaboration was built during AI Mastery.

Read the full submission
Project Title: People Keeper — A Memory Sidekick Built Through AI Collaboration Project Description: What I Built People Keeper is a personal memory tool that helps people remember the names and details of casual acquaintances — baristas, yoga students, networking contacts, grocery clerks. It fills the gap between strangers and contacts, grounded in cognitive offloading science and Jim Kwik's spaced repetition methodology. It's currently in beta with real users at my yoga studio. Achievements - Built a fully functional, multi-user PWA as a first-time app creator with zero coding background - AI-powered "Quick Add" brain dump that parses natural language into structured contact data - AI-powered business card scanner using computer vision - Full-text search, smart recency, pinning, archiving, and CSV import/export - Live beta with real users and an email-based feedback survey system - Navigated real-world complexities: SMS carrier compliance (A2P 10DLC), pivoting when blocked   Tools - Lovable (AI app builder — primary development environment) - Supabase (authentication, database, edge functions) - Google Gemini (AI contact parsing and business card scanning) Methodology Creator mode, not executor mode. Instead of using AI purely for speed, I used it as a thinking partner to challenge my assumptions. The breakthrough moment: I spent weeks perfecting structured input forms before asking "is there a better way?" AI suggested natural language brain dumps — users just talk, AI organizes. I didn't need a better form. I needed to question why I was building a form at all. Key Learnings 1. AI has information, not answers — the answers emerge through curious collaboration 2. Question assumptions relentlessly — the simplest solution often isn't your first instinct 3. Cognitive offloading is real — by capturing details correctly the first time, users shift from mental rehearsal (stress) to presence (connection) 4. Capture methods are neutral — product positioning determines who shows up and why, not the feature set Relevant URLs - Live beta: https://people-keeper-vault.lovable.app - People Keeper Story: https://lovable.dev/projects/61e0ed51-04d5-4618-8c58-7bb0535c0d20 - Built with: https://lovable.dev

Written 9 February 2026 Submitted by the storyteller

Every story is written by a Mindvalley student or by someone our teachers have worked with. How we collect and check stories

More from AI Mastery

People Keeper — A Memory Sidekick Built Through AI Collaboration: a AI Mastery case study | Mindvalley Stories