Skip to main content

​
Personalized AI Assistants

The most common use case: building AI assistants that truly know your users. What profiles provide:
  • User’s expertise level (adjust technical depth)
  • Communication preferences (brief vs detailed, formal vs casual)
  • Tools and technologies they use
  • Current projects and priorities
Example prompt enhancement: 
const systemPrompt = `You are assisting ${userName}.

Their background:
${profile.static.join('\n')}

Current focus:
${profile.dynamic.join('\n')}

Adjust your responses to match their expertise level and preferences.`;
Result: An assistant that explains React hooks differently to a junior developer vs a senior architect.

​
Customer Support Systems

Give support agents (or AI) instant context about customers. What profiles provide:
  • Customer’s product usage history
  • Previous issues and resolutions
  • Preferred communication channels
  • Technical proficiency level
Benefits:
  • No more “let me look up your account”
  • Agents immediately understand customer context
  • AI support can reference past interactions naturally
// Support agent dashboard
async function loadCustomerContext(customerId: string) {
  const { profile } = await getProfile(customerId);

  return {
    summary: profile.static,      // Long-term customer info
    recentIssues: profile.dynamic // Current tickets, recent problems
  };
}

​
Educational Platforms

Adapt learning content to each student’s level and progress. What profiles provide:
  • Learning style preferences
  • Completed courses and topics
  • Areas of strength and weakness
  • Current learning goals
Example adaptation: 
// Profile might contain:
// static: ["Visual learner", "Strong in algebra, struggles with geometry"]
// dynamic: ["Currently studying calculus", "Preparing for AP exam"]

const tutorPrompt = `You're helping a student with:
${profile.static.join('\n')}

Current focus: ${profile.dynamic.join('\n')}

Adapt explanations to their learning style and build on their strengths.`;

​
Development Tools

IDE assistants and coding tools that understand your codebase and habits. What profiles provide:
  • Preferred languages and frameworks
  • Coding style and conventions
  • Current project context
  • Frequently used patterns
Example: 
// Profile for a developer:
// static: ["Prefers TypeScript", "Uses functional patterns", "Senior engineer"]
// dynamic: ["Working on auth refactor", "Recently learning Rust"]

// Code assistant knows to:
// - Suggest TypeScript solutions
// - Use functional patterns in examples
// - Provide senior-level explanations
// - Connect suggestions to the auth refactor when relevant

​
Knowledge Base Assistants

Internal tools that understand each employee’s role and responsibilities. What profiles provide:
  • Department and role
  • Projects they’re involved in
  • Access level and permissions context
  • Areas of expertise (for routing questions)
Example: 
// HR assistant that knows:
// - Employee's team and manager
// - Their location/timezone
// - Recent PTO requests
// - Benefits elections

const response = await hrAssistant.answer(
  "When is my next performance review?",
  { profile: employeeProfile }
);
// Can answer with specific dates, manager name, etc.

​
E-commerce Recommendations

Personalized shopping experiences beyond basic recommendation engines. What profiles provide:
  • Style preferences
  • Size information
  • Past purchases and returns
  • Budget range
  • Occasions they shop for
Example conversation: 
User: "I need something for a wedding next month"

// Profile knows: prefers classic styles, size M, budget-conscious,
// previously bought navy suits