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Designing an Agentic Workflow for Automated Documentation

Role:

AI Content Architect & Project Lead

Challenge:

Wix's knowledge base documentation process was manual and labor-intensive, and the team needed a path to scale. With thousands of articles to maintain across rapidly evolving products, the team couldn't scale using traditional methods. The company needed both a vision for what AI-assisted documentation could look like and proof that it could actually work.

Contribution:

Mapped specialized agent roles across the full documentation lifecycle, from intake through final editing. The design includes a novel verification step where the editing agent re-runs documented steps in a browser to confirm accuracy.
Built three working proof-of-concept agents as Claude skills. Three working proof-of-concept agents covering context-mapping, outline drafting, and editing. Ran them through head-to-head LLM comparison testing across GPT, Claude, and Gemini to choose the right model per agent. Integrated our internal KB Retrieval MCP so the agents can pull from existing documentation in context.
Partnered with developers in our Tel Aviv office to package a long-dormant internal script into a Claude skill that now writes directly to our help desk platform, eliminating one of the biggest manual bottlenecks in the workflow. Hosted team trainings, built a small site for writers to learn the system, and refined each agent based on real-world testing feedback.

Outcome:

The team is actively testing the agents and providing structured feedback. Adopted as a priority initiative for the global content team, with active testing and feedback from writers across the org. The architecture provides the blueprint, the working agents prove the approach in practice, and the workflow is being developed toward full production use.

Skills:

AI System Design; Agentic Workflow Architecture; Agent Prototyping; Claude Skills Development; MCP Integration; LLM Comparison Testing; Process Automation; Figma; Cross-Functional Collaboration

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