Define your goal (what you want AI to help with)
Choose the right tool or model for the task (chat, coding, images, search, automation)
Provide clear inputs (data, prompts, requirements, constraints)
Write effective prompts (specific, include context, specify output format)
Verify assumptions and required context (definitions, scope, target audience)
Run a small test first (sample inputs, expected outputs)
Review outputs for accuracy, completeness, and relevance
Iterate prompts or settings to improve results
Use AI-generated outputs as drafts when needed (especially for complex or high-stakes tasks)
Validate with reliable sources or domain checks
Protect sensitive data (avoid sharing secrets; use proper access controls)
Follow privacy, copyright, and compliance requirements
Use AI for automation where appropriate (workflows, scripts, integrations)
Track performance and quality over time (accuracy, time saved, error rates)
Document your process (prompts, inputs, evaluation criteria)
Keep humans in the loop for decisions that require accountability
Monitor for failure modes (hallucinations, bias, outdated info, formatting errors)
Scale up gradually (more inputs, broader use, stronger safeguards)