Claude AI Integration Patterns

interface RetrievalFirstAI {
  // Claude's core principle: Find before you build
  retrievalStrategies: {
    patternMatching: PatternMatcher;
    templateRetrieval: TemplateEngine;
    componentComposition: ComponentAssembler;
    knowledgeSynthesis: KnowledgeSynthesizer;
  };
 
  // Minimize AI hallucinations through structured retrieval
  generationMinimization: {
    confidenceScoring: ConfidenceScorer;
    sourceValidation: SourceValidator;
    factChecking: FactChecker;
    incrementalBuilding: IncrementalBuilder;
  };
 
  // Continuous learning from successful interactions
  learningLoop: {
    interactionLogging: InteractionLogger;
    patternExtraction: PatternExtractor;
    modelRefinement: ModelRefiner;
    feedbackIntegration: FeedbackIntegrator;
  };
}

class ConstitutionalBusinessAI {
  private principles = {
    businessAccuracy: "Prioritize factual business information",
    stakeholderValue: "Maximize value for all stakeholders",
    transparency: "Explain reasoning and confidence levels",
    ethicalCompliance: "Ensure regulatory and ethical compliance",
    continuousImprovement: "Learn and improve from interactions"
  };
 
  async makeBusinessDecision(query: BusinessQuery): Promise<Decision> {
    // Constitutional AI chain
    const context = await this.retrieveBusinessContext(query);
    const options = await this.generateOptions(context);
    const evaluated = await this.evaluateConstitutionally(options);
    const selected = await this.selectOptimalChoice(evaluated);
 
    return {
      decision: selected,
      reasoning: this.explainConstitutionally(selected),
      confidence: this.calculateConfidence(selected),
      alternatives: evaluated.filter(opt => opt !== selected)
    };
  }
}

interface MultiAgentOrchestrator {
  agents: {
    leagueAnalyzer: LeagueAnalysisAgent;
    marketIntelligence: MarketIntelligenceAgent;
    contractGenerator: ContractGenerationAgent;
    riskAssessor: RiskAssessmentAgent;
    partnershipMatcher: PartnershipMatcherAgent;
  };
 
  async orchestrateBusinessProcess(process: BusinessProcess): Promise<Result> {
    // Dynamic agent selection based on process requirements
    const requiredAgents = this.selectAgentsForProcess(process);
 
    // Parallel execution with coordination
    const results = await this.coordinateAgentExecution(requiredAgents, process);
 
    // Consensus building and conflict resolution
    const consensus = await this.buildConsensus(results);
 
    // Learning from the orchestration
    await this.learnFromOrchestration(process, results, consensus);
 
    return consensus;
  }
}

class BusinessRAGSystem {
  private vectorStore: VectorStore;
  private claudeClient: ClaudeClient;
 
  async answerBusinessQuery(query: string, context: BusinessContext): Promise<BusinessAnswer> {
    // Step 1: Retrieve relevant business data
    const relevantData = await this.retrieveRelevantData(query, context);
 
    // Step 2: Structure the context for Claude
    const structuredContext = this.structureForClaude(relevantData, query);
 
    // Step 3: Generate response with Claude
    const response = await this.claudeClient.generate({
      prompt: this.buildBusinessPrompt(query, structuredContext),
      context: structuredContext,
      temperature: 0.1, // Low temperature for business accuracy
      maxTokens: 2000
    });
 
    // Step 4: Validate and fact-check the response
    const validated = await this.validateResponse(response, relevantData);
 
    return {
      answer: validated,
      confidence: this.calculateConfidence(validated, relevantData),
      sources: relevantData.map(d => d.source),
      reasoning: this.explainReasoning(validated)
    };
  }
 
  private buildBusinessPrompt(query: string, context: BusinessContext[]): string {
    return `
You are an expert business intelligence analyst specializing in sports league partnerships and betting markets.
 
Context Information:
${context.map(c => `- ${c.type}: ${c.content}`).join('\n')}
 
Query: ${query}
 
Instructions:
1. Answer based ONLY on the provided context
2. If information is insufficient, clearly state what additional data is needed
3. Provide specific, actionable business insights
4. Include confidence levels for your recommendations
5. Suggest next steps for implementation
 
Answer:`;
  }
}

class ConstitutionalContractGenerator {
  private constitution = {
    principles: [
      "Contracts must be fair and balanced for all parties",
      "Terms must comply with relevant gambling regulations",
      "Revenue sharing must be sustainable for league operations",
      "Data rights must protect league intellectual property",
      "Termination clauses must allow clean separation",
      "Dispute resolution must be efficient and cost-effective"
    ],
    constraints: [
      "No predatory terms or unfair advantages",
      "All parties must have equal bargaining power in spirit",
      "Terms must be understandable to non-lawyers",
      "Contracts must include performance metrics and reviews"
    ]
  };
 
  async generateConstitutionalContract(
    leagueProfile: LeagueProfile,
    sportsbookProfile: SportsbookProfile,
    marketConditions: MarketConditions
  ): Promise<Contract> {
    // Step 1: Gather all relevant context
    const context = await this.gatherContractContext(
      leagueProfile, sportsbookProfile, marketConditions
    );
 
    // Step 2: Generate initial contract draft
    const draft = await this.generateInitialDraft(context);
 
    // Step 3: Constitutional review and refinement
    const reviewed = await this.constitutionalReview(draft, context);
 
    // Step 4: Ethical optimization
    const optimized = await this.optimizeEthically(reviewed, context);
 
    // Step 5: Transparency explanation
    const explained = await this.addTransparencyLayer(optimized);
 
    return {
      contract: explained,
      constitutionCompliance: this.assessConstitutionCompliance(explained),
      ethicalScore: this.calculateEthicalScore(explained),
      transparencyReport: this.generateTransparencyReport(explained)
    };
  }
}

class PartnershipOrchestrator {
  private agents = {
    opportunityScanner: new OpportunityScannerAgent(),
    dueDiligenceAgent: new DueDiligenceAgent(),
    valuationAgent: new ValuationAgent(),
    negotiationAgent: new NegotiationAgent(),
    contractAgent: new ContractAgent(),
    monitoringAgent: new MonitoringAgent()
  };
 
  async orchestratePartnershipProcess(
    league: League,
    potentialPartners: Sportsbook[]
  ): Promise<PartnershipProcess> {
    // Phase 1: Opportunity Identification
    const opportunities = await this.agents.opportunityScanner.scan(
      league, potentialPartners
    );
 
    // Phase 2: Parallel Due Diligence
    const dueDiligenceResults = await Promise.all(
      opportunities.map(opp =>
        this.agents.dueDiligenceAgent.assess(opp)
      )
    );
 
    // Phase 3: Valuation and Risk Assessment
    const valuations = await Promise.all(
      dueDiligenceResults
        .filter(result => result.recommended)
        .map(result =>
          this.agents.valuationAgent.value(result.opportunity)
        )
    );
 
    // Phase 4: Negotiation Orchestration
    const negotiations = await this.orchestrateNegotiations(valuations);
 
    // Phase 5: Contract Generation
    const contracts = await Promise.all(
      negotiations
        .filter(neg => neg.agreement)
        .map(neg =>
          this.agents.contractAgent.generate(neg)
        )
    );
 
    // Phase 6: Ongoing Monitoring Setup
    const monitoring = await Promise.all(
      contracts.map(contract =>
        this.agents.monitoringAgent.setup(contract)
      )
    );
 
    return {
      process: {
        opportunities,
        dueDiligence: dueDiligenceResults,
        valuations,
        negotiations,
        contracts,
        monitoring
      },
      summary: this.generateProcessSummary({
        opportunities, dueDiligenceResults, valuations,
        negotiations, contracts, monitoring
      }),
      recommendations: this.generateRecommendations({
        opportunities, dueDiligenceResults, valuations,
        negotiations, contracts, monitoring
      })
    };
  }
}

class SelfImprovingBusinessIntelligence {
  private learningHistory: LearningEvent[] = [];
  private performanceMetrics: PerformanceMetrics;
 
  async processBusinessInteraction(
    query: BusinessQuery,
    response: BusinessResponse,
    outcome: BusinessOutcome
  ): Promise<void> {
    // Record the interaction
    const interaction = {
      query,
      response,
      outcome,
      timestamp: new Date(),
      context: await this.captureContext()
    };
 
    this.learningHistory.push(interaction);
 
    // Analyze performance
    const analysis = await this.analyzeInteraction(interaction);
 
    // Update models based on outcomes
    await this.updateModels(analysis);
 
    // Refine future responses
    await this.refineResponsePatterns(analysis);
 
    // Update performance metrics
    this.updatePerformanceMetrics(analysis);
  }
 
  private async analyzeInteraction(interaction: LearningEvent): Promise<Analysis> {
    return {
      accuracy: this.assessAccuracy(interaction),
      helpfulness: this.assessHelpfulness(interaction),
      efficiency: this.assessEfficiency(interaction),
      businessImpact: this.assessBusinessImpact(interaction),
      lessonsLearned: this.extractLessons(interaction)
    };
  }
 
  private async updateModels(analysis: Analysis): Promise<void> {
    // Update retrieval patterns
    if (analysis.accuracy < 0.8) {
      await this.improveRetrievalAccuracy(analysis);
    }
 
    // Update response generation
    if (analysis.helpfulness < 0.7) {
      await this.improveResponseHelpfulness(analysis);
    }
 
    // Update efficiency patterns
    if (analysis.efficiency < 0.6) {
      await this.improveEfficiency(analysis);
    }
  }
}

class EthicalBusinessDecisionMaker {
  private ethicalFramework = {
    principles: {
      fairness: "Ensure equitable outcomes for all stakeholders",
      transparency: "Make decision processes clear and auditable",
      accountability: "Accept responsibility for decision outcomes",
      sustainability: "Consider long-term business ecosystem health",
      privacy: "Protect sensitive business and personal information"
    },
 
    constraints: {
      noHarm: "Decisions must not cause foreseeable harm",
      legalCompliance: "All decisions must comply with applicable laws",
      marketIntegrity: "Maintain fair and competitive market conditions",
      dataEthics: "Handle data responsibly and with consent"
    }
  };
 
  async makeEthicalDecision(
    options: DecisionOption[],
    context: BusinessContext
  ): Promise<EthicalDecision> {
    // Evaluate each option against ethical framework
    const evaluations = await Promise.all(
      options.map(option => this.evaluateEthically(option, context))
    );
 
    // Rank options by ethical compliance
    const ranked = this.rankByEthics(evaluations);
 
    // Select optimal ethical choice
    const selected = this.selectOptimalEthicalChoice(ranked);
 
    // Generate ethical reasoning
    const reasoning = await this.generateEthicalReasoning(selected, context);
 
    return {
      decision: selected,
      ethicalEvaluation: evaluations.find(e => e.option === selected),
      reasoning,
      alternatives: ranked.filter(r => r !== selected).slice(0, 2),
      ethicalScore: this.calculateEthicalScore(selected)
    };
  }
}

interface ConstitutionalMetrics {
  // Business Performance
  businessAccuracy: number; // 0-1 scale
  stakeholderValue: number; // 0-1 scale
  decisionQuality: number; // 0-1 scale
 
  // Ethical Compliance
  fairnessScore: number; // 0-1 scale
  transparencyScore: number; // 0-1 scale
  accountabilityScore: number; // 0-1 scale
 
  // Constitutional Adherence
  principleCompliance: Record<string, number>; // Per principle
  constraintSatisfaction: Record<string, number>; // Per constraint
 
  // Learning & Improvement
  adaptationRate: number; // Rate of improvement
  errorRecovery: number; // Speed of error correction
  knowledgeGrowth: number; // Expansion of knowledge base
}

class ContinuousAIEvaluator {
  private metrics: ConstitutionalMetrics;
  private evaluationHistory: EvaluationEvent[];
 
  async evaluateContinuous(
    aiSystem: AISystem,
    timeWindow: TimeWindow
  ): Promise<EvaluationReport> {
    // Collect performance data
    const performanceData = await this.collectPerformanceData(aiSystem, timeWindow);
 
    // Assess constitutional compliance
    const constitutionalAssessment = await this.assessConstitutionalCompliance(performanceData);
 
    // Evaluate business impact
    const businessImpact = await this.evaluateBusinessImpact(performanceData);
 
    // Generate improvement recommendations
    const recommendations = await this.generateImprovementRecommendations(
      constitutionalAssessment, businessImpact
    );
 
    // Update evaluation history
    this.updateEvaluationHistory({
      timestamp: new Date(),
      assessment: constitutionalAssessment,
      impact: businessImpact,
      recommendations
    });
 
    return {
      period: timeWindow,
      overallScore: this.calculateOverallScore(constitutionalAssessment, businessImpact),
      constitutionalAssessment,
      businessImpact,
      recommendations,
      trends: this.analyzeTrends(),
      alerts: this.generateAlerts(constitutionalAssessment, businessImpact)
    };
  }
}

// Example: League Partnership Analysis
const leagueAnalysisPrompt = `
You are analyzing a potential partnership between a sports league and betting operator.
 
League Profile: {{league_profile}}
Market Data: {{market_data}}
Regulatory Context: {{regulatory_info}}
Competitive Landscape: {{competition_analysis}}
 
Task: "Analyze the partnership opportunity and provide:"
1. Partnership viability score (1-10)
2. Recommended revenue sharing structure
3. Key risks and mitigation strategies
4. Implementation timeline and milestones
5. Expected ROI for both parties
 
Be constitutional: Ensure fairness, transparency, and mutual benefit.
Base recommendations on data, not assumptions.
`;
 
const analysis = await claude.analyze({
  prompt: leagueAnalysisPrompt,
  context: {
    league_profile: retrievedLeagueData,
    market_data: marketIntelligence,
    regulatory_info: complianceData,
    competition_analysis: competitiveLandscape
  },
  constitution: businessEthicsFramework
});

const contractReviewPrompt = `
Review this partnership contract for ethical compliance:
 
Contract Terms: {{contract_terms}}
League Profile: {{league_profile}}
Market Conditions: {{market_conditions}}
 
Evaluate against principles:
- Fairness: Are terms balanced and equitable?
- Transparency: Are all terms clear and understandable?
- Sustainability: Can both parties thrive long-term?
- Compliance: Does it meet regulatory requirements?
 
Provide:
1. Ethical compliance score (1-10)
2. Specific concerns and recommendations
3. Suggested improvements
4. Alternative approaches if needed
`;
 
const review = await claude.review({
  prompt: contractReviewPrompt,
  constitution: ethicalContractFramework,
  factChecking: true,
  sourceValidation: true
});