🧠

Validated Learning

Validated learning emphasizes rapid experimentation over extensive planning. Using a Build-Measure-Learn feedback loop, quickly develop a Minimum Viable Product (MVP) to collect actionable metrics from actual customer usage. This empirical data then informs whether to pivot or persevere, ensuring product development is closely aligned with market needs and conserves resources.

Table

Experiments

Experiment

Date

Measurement

Build

Learnings

Goal

Prototype 3 - Testing UI | Hristo

Jul 31, 2024

Form inputs, Questions

A script for testing: Setup a form on our website: https://collabberry.xyz/assessment-prototype-01

Milena: https://www.notion.so/rndadocs/Test-Milena-bf91160cf0a54148890fecbf4372017a?pvs=4 Hristo: https://www.notion.so/rndadocs/Prototype-User-Testing-Debrief-181e97985e904ae08a8046249bf9975a

Validate, that the user understands how to asses peers via the form and rating system.

Prototype 2 | RnDAO test

Jul 8, 2024

A form for triggering a review of the agreement of the contributor with the org. https://docs.google.com/forms/d/e/1FAIpQLSeju9haQEwe_l3dY6OcHFJO5UddYwicsQyfp-rgfgkT1r8q3A/viewform All assessments are optional. Added a question "How well do you think the team performed this month?" https://docs.google.com/forms/d/e/1FAIpQLSf8n7x7RFQsJDhLGkOSDbV1sctBsZc_9Yeqx3xgFU4HG3lWIQ/viewform

Prototype 1 | RnDAO initial

Jun 16, 2024

A form simulating the assessment.

Problems derived from the following feature requests (sorted by severity) • I can’t stop funds to be sent to contributors who ghosted • Unfair distribution of funds: Team members get rewarded without contribution • How do I know if the commitment was fulfilled? • I don’t know how to rate as I have no context on some team members • The system is too rigid • Too complex

Test Milena

Validated Learning

Validated learning emphasizes rapid experimentation over extensive planning. Using a Build-Measure-Learn feedback loop, quickly develop a Minimum Viable Product (MVP) to collect actionable metrics from actual customer usage. This empirical data then informs whether to pivot or persevere, ensuring product development is closely aligned with market needs and conserves resources.