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About

Overview

Skene is a fully automated PLG iteration engine that helps products grow without growth teams. Built for indie developers and early-stage startups, Skene handles continuous optimization of onboarding, activation, and retention โ€” all based on understanding the customer code. The platform observes user actions to detect friction and activation drop-off. It then automatically creates and tests improved versions of user flows, measures impact, and deploys the winning configuration.

At a glance

Skene in a Nutshell

Who is it for?

Indie developers and early stage startups seeking product-led growth without a dedicated growth team

Problem

Teams struggle to optimize onboarding and activation workflows as user behavior changes. They face friction and activation drop-off that drains retention and growth without continuous testing and iteration. Small teams often lack the time or resources to run systematic experiments across user flows.

Solution

Skene automates PLG iteration by observing user actions to identify friction, automatically creating and testing improved onboarding and activation flows, measuring impact, and deploying the winning configuration. It continuously optimizes the customer journey based on actual usage signals.

What makes it unique

Skene eliminates the need for a dedicated growth team by delivering automated experiments and deployments targeted at onboarding and activation. It operates end to end, from friction detection to live deployment, tuned to each product by analyzing customer code and behavior. This end-to-end automation is designed for indie developers and early-stage startups who cannot staff a growth squad.

In practice

Use Cases

01

Detect onboarding friction

02

Test activation flows automatically

03

A/B test user journeys

04

Improve retention through activation

05

Deploy winning configurations

06

Observe and react to drop-off

Good to know

Frequently Asked Questions

Behind the product

Meet the Maker

Teemu Kinos

Maker of Skene ยท On LaunchIt since 2025

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