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dif.sh

Git-native feature flagging and experimentation framework that stores flags as Markdown files inside repositories for developers and coding agents.

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Product Overview

What is dif.sh?

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dif.sh is a developer-centric feature flag and A/B testing tool that manages experimentation configurations directly within the source repository . Instead of managing flags across external SaaS dashboards, teams define flags, rollouts, and experiments as version-controlled Markdown files with structured frontmatter . The platform compiles configurations into a lightweight, type-safe client at build time, catches test collisions in CI, and generates machine-readable context files so coding agents retain historical experiment memory across sessions .


Key Features

  • Git-Native Markdown Architecture

    Treats flags, A/B tests, and holdouts as version-controlled Markdown files inside the repository, making pull requests the single approval mechanism.

  • Coding Agent Context Generation

    Compiles active experiments and learnings into a structured JSON file that AI coding assistants ingest at session startup to maintain context.

  • Compile-Time Collision Prevention

    Validates exclusion groups and targeting rules during build time, failing the CI pipeline if concurrent experiments clash on the same user.

  • Zero-Latency Client Generation

    Emits an ultra-small, strongly typed client directly into application code, resolving variants locally without external runtime network calls.

  • Surface-Based Knowledge Retention

    Maintains dedicated Markdown logs for individual application surfaces so concluded experiment findings automatically inform subsequent test drafts.


Use Cases

  • Agentic Software Engineering : Enables coding agents in Cursor, Claude, or Copilot to understand active flags and prior test outcomes before editing user-facing code.
  • Progressive Feature Rollouts : Engineers can safely release features behind staged percentage rollouts and target specific user attributes without committing customer lists.
  • Isolated Front-End A/B Testing : Product and growth teams can run conversion tests with guaranteed mutual exclusion, preventing contradictory UI variants from conflicting.
  • Automated CI/CD Verification : DevOps pipelines automatically check frontmatter integrity, missing test declarations, and flag conflicts before merging code.

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