The First 100 People
Win 100 devoted users before building for a million
- Difficulty
- Moderate
- Time to result
- ~months to results
- Steps
- 5
- Confidence
- 98%
The method replaces an abstract million-user target with a sequence that begins at 100. Recruit a narrowly defined set of users individually, learn their needs through direct contact, and make the experience specific enough that they love it rather than merely tolerate it. Chesky argues that people who love a service voluntarily tell many others, turning advocacy into an early distribution engine. Once the first 100 are genuinely engaged, move through successive orders of magnitude—1,000, 10,000, 100,000—changing systems as each stage requires. The mechanism is focus: a small target permits high-touch learning and avoids the complexity that comes from pretending to operate at scale before demand exists.
Origin
Chesky attributes the core rule to Y Combinator founder Paul Graham and connects it to Airbnb's beginning with three guests during one San Francisco design conference.
Core principles
- 01A small group that loves a product can drive disproportionate word of mouth
- 02Direct contact makes early customer needs easier to understand
- 03Scale becomes manageable when pursued one order of magnitude at a time
How to run it
- 1
Narrow the starting problem
Choose a problem you understand for a small, reachable group. Do not begin by modelling the needs of a million hypothetical users.
Pro tip A problem shared by you and a close peer can provide a concrete starting point.
Watch out Do not mistake a tiny initial audience for a tiny eventual market.
- 2
Recruit people individually
Find the first users one at a time and create enough trust to speak with them directly.
Pro tip Treat recruitment as learning, not just acquisition.
- 3
Design for love
Understand each user's needs and improve the experience until it is distinctive enough to inspire active recommendation.
Pro tip Ask enthusiastic users how many people they have told.
Watch out Broad appeal that produces indifference is weaker than narrow, intense value.
- 4
Reach 100 before scaling
Concentrate on earning 100 devoted users before introducing systems intended for a much larger audience.
Watch out Premature scale adds complexity the team may not yet be able to manage.
- 5
Advance by orders of magnitude
After 100, redesign the work for 1,000, then repeat for each larger stage. Let the job evolve with proven demand.
Pro tip Treat each order of magnitude as a new operating problem.
In the wild
Airbnb began as a way for a few visitors to stay on airbeds during a sold-out San Francisco design conference. The founders were solving rent and accommodation problems for a handful of people, not initially designing a platform for millions of nightly stays.
→ The tiny, concrete use case became the starting point for a global service.
Illustrative example: a founder building scheduling software for independent physiotherapists recruits 20 local practitioners, watches each workflow, and fixes the repeated friction before buying broad ads. Referrals then supply the next cohort until the product reaches 100 active advocates.
→ The founder earns evidence and advocacy before adding scale-oriented complexity.
Common mistakes
Designing for an imaginary million
The team optimises for hypothetical scale before it understands why one person would care.
Counting lukewarm sign-ups
A large passive list can hide the absence of users who value the product enough to recommend it.
Is it for you?
Best for
It is best for founders with a new product and direct access to a narrow initial audience.
Not ideal for
It is not ideal for mature products whose main constraint is reliable operation at an existing large scale.
From the transcript
“it's better to have a hundred people love you than a million people that just sort of like you”
“Don't focus in a million Focus just in 100”
From the episode
Airbnb CEO: “IT WAS SO DARK WE NEARLY DIED!”. I Was Lonely, Deeply Sad & Wanted To Be Loved! [INSPIRING!] Brian Chesky