Move your company from risky 'shadow AI' usage to a structured, safe, and scalable program. This workflow details how to survey your team, collaborate with stakeholders, and build a centralized knowledge center for approved AI tools and data guidelines.
with Claire Vo
Before implementing new rules, send a company survey to understand current AI usage. Ask about personal sentiment toward AI, familiarity with company policies, and awareness of which tools are available and approved. This data will be your benchmark for success.
Analyze the survey results to find the biggest areas of confusion. The Pendo survey revealed that employees were using personal ChatGPT accounts and didn't know which data was safe to use, highlighting a clear need for guidance.
Work directly with Legal, Security, IT, and Finance to create an official AI policy. This ensures that the guidelines you create are compliant, secure, and practical for the entire organization.
Create a single source of truth (e.g., on your company intranet) that contains an alphabetized table of approved AI tools. For each tool, include its status, security and legal notes, and clear data-sharing guidelines.
For each tool in your knowledge center, be explicit about what data can be used. Use clear labels like 'Internal Data Only,' 'No PII (Personally Identifiable Information),' or 'Public Data Only.' This removes ambiguity and empowers employees to experiment safely.
Establish a formal process for employees to request access to approved tools or to submit new tools for evaluation by the cross-functional team. This keeps your AI program dynamic and responsive to your team's needs.
Follow Sahil Lavingia's method for delegating small but impactful maintenance tasks, like fixing an internal Slack report, to the AI agent Devin. This workflow shows how to use simple, clear prompts to fix code and update system prompts without distracting your engineering team.
Learn Gumroad CEO Sahil Lavingia's process for rapidly prototyping a UI with v0, then using the AI agent Devin to autonomously code, implement, and submit the feature for review, turning a multi-day task into a one-hour workflow.
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