Hello, I'm Lana Cooper, a technical writer specialising in AI adoption, internal AI workflows, and AI-powered products.
I work across information architecture, internal knowledge bases, workflow documentation, human-in-the-loop review, output-quality guidance, and documentation governance.
| Project | Focus |
|---|---|
| Internal AI Adoption for a Cross-Functional Team | Role-based onboarding, task ownership, and quality checks for client-facing work. |
| AI Customer-Support Response Quality Framework | A weighted 5 rubrics, shared error taxonomy, and escalation rules for daily use. |
| User Documentation for an AI-Generated Reporting Feature | Feature limitations, review steps, onboarding, and troubleshooting guidance. |
| Area | Tools |
|---|---|
| Writing and publishing | Confluence, Notion, SharePoint, Google Workspace, GitHub, MkDocs |
| Workflows and diagrams | Miro, Lucidchart, Figma, Loom |
| Drafting and prompt testing | ChatGPT, Claude, Copilot, Gemini |
| Output review and QA | Google Sheets, Airtable (rubrics, scoring sheets, review logs) |
Languages: English · Russian
For the past five years, I have worked across data and product analysis, LLM evaluation, AI training, and quality review.
I turn AI workflows and product features into clear, practical materials, including:
- Standard operating procedures (SOPs)
- Knowledge-base content
- User guides and product documentation
- Evaluation rubrics and quality checklists
- Troubleshooting guidance
- Workflow diagrams
My goal is to help people use technical tools, including artificial intelligence, in ways that are understandable, useful, and responsible.