Ryan Carson

Ryan Carson (GitHub: snarktank) is a CEO, founder, and developer known for creating influential AI agent frameworks and automation systems. He is a Builder in Residence at Amp and has built and sold three startups. He’s particularly known for developing Ralph (autonomous feature development), ai-dev-tasks (task management for AI agents), and Compound Product (self-improving product systems).

Background

  • Career: CEO and Founder, built and sold 3 startups
  • Role: Builder in Residence at Amp
  • GitHub: snarktank (1.5k+ followers, 19 repositories)
  • Contributions: 2,385 contributions in the past year
  • Social: Active on Twitter/X (@ryancarson) with 163k followers
  • Website: ryancarson.com

Key Projects & Frameworks

Ralph

An autonomous AI agent loop system that repeatedly executes AI coding tasks until project requirements are complete. Features:

  • Fresh context for each iteration (prevents context degradation)
  • Memory through git history, progress tracking, and JSON-based requirements
  • AGENTS.md file updates capturing discovered patterns
  • Feedback loops via testing and CI/CD
  • Browser verification capabilities

Stats: 7.3k+ stars on GitHub

AI Dev Tasks

A structured workflow system for AI-assisted feature development. Includes three core workflow files:

  • create-prd.md: Guides AI in generating Product Requirement Documents
  • generate-tasks.md: Breaks PRDs into step-by-step implementation tasks
  • process-task-list.md: Manages task-by-task execution with approval checkpoints

Works with multiple platforms: Cursor, Claude Code, Windsurf, and others.

Stats: 7.4k+ stars, 1.7k forks

Compound Product

A self-improving product system that reads daily reports, identifies the #1 actionable priority, and autonomously implements improvements. Built on Kieran Klaassen’s Compound Engineering methodology and Geoffrey Huntley’s Ralph pattern.

Stats: 268+ stars

Amp Skills

A collection of specialized skills for Amp AI coding agent, including:

  • Ralph skill for autonomous feature development
  • Agent browser for testing and automation
  • React best practices (40+ rules from Vercel)
  • Web design guidelines (100+ best practices)

Stats: 335+ stars

Philosophy & Approach

Structured AI Development

Carson emphasizes that AI agents, like new employees, need clear structure and context:

  • Clear task definitions and expected outcomes
  • Step-by-step decomposition rather than monolithic requests
  • Feedback loops for validation and improvement
  • Parent/child task hierarchies for complex features

Developer Priorities

  • Reduce complexity for AI agents through clear workflows
  • Break large features into manageable subtasks
  • Maintain context across iterations through persistent documentation
  • Validate before shipping

Solo AI Businesses

Advocates for one-person startups using AI agents to build:

  • Best time to be a one-person company with controlled time and family care
  • AI agents handle execution while humans handle strategy and judgment
  • Focus on pain pills (solve real problems) over vitamins (nice-to-have)

Key Insight

“You wouldn’t tell a new employee ‘Make me a super fun game’ and expect them to succeed. Treat AI the same way—give it context.”

Technologies & Platforms

Development Stack:

  • TypeScript, CSS, Shell, JavaScript, HTML
  • Claude Code and Amp CLI
  • GitHub for version control and workflow

LLM Providers Supported:

  • Anthropic (primary)
  • OpenRouter
  • AI Gateway

Impact & Influence

Carson’s frameworks have influenced how developers approach AI-assisted development by:

  • Providing concrete patterns (Ralph, ai-dev-tasks)
  • Emphasizing structured prompts and task decomposition
  • Building for autonomous execution while maintaining human control
  • Creating reusable skills and workflows

His work bridges Kieran Klaassen’s Compound Engineering concepts with practical implementation, making agent orchestration accessible to developers.

Active Presence

  • GitHub: @snarktank (676 followers)
  • Twitter/X: @ryancarson (163k followers)
  • LinkedIn: linkedin.com/in/ryancarson
  • Website: ryancarson.com

Last updated: January 2025
Confidence: High (public GitHub, verified data)
Practical relevance: Key figure in AI-assisted development frameworks and patterns