Reverse-Engineered AI Workflow Behind $2B Acquisition Now a Claude Code Skill
Published:Jan 3, 2026 08:02
•1 min read
•r/ClaudeAI
Analysis
This article discusses the reverse engineering of the workflow used by Manus, a company recently acquired by Meta for $2 billion. The core of Manus's agent's success, according to the author, lies in a simple, file-based approach to context management. The author implemented this pattern as a Claude Code skill, making it accessible to others. The article highlights the common problem of AI agents losing track of goals and context bloat. The solution involves using three markdown files: a task plan, notes, and the final deliverable. This approach keeps goals in the attention window, improving agent performance. The author encourages experimentation with context engineering for agents.
Key Takeaways
- •Manus's AI agent workflow, acquired by Meta for $2B, is based on a simple file-based approach.
- •The core pattern involves three markdown files: task plan, notes, and deliverable, to manage context and goals.
- •The author implemented this pattern as a Claude Code skill, making it easy to replicate and experiment with.
Reference
“Manus's fix is stupidly simple — 3 markdown files: task_plan.md → track progress with checkboxes, notes.md → store research (not stuff context), deliverable.md → final output”