Building Custom AI Development Workflows: Beyond Off-the-Shelf

┌─────────────────────────────────────────────────────┐
│                   Orchestrator                       │
│  ┌─────────┐  ┌──────────┐  ┌───────────────────┐  │
│  │ Trigger │──│ Context  │──│ Agent Selection   │  │
│  │ Manager │  │ Builder  │  │ & Execution       │  │
│  └─────────┘  └──────────┘  └───────────────────┘  │
└─────────────────────┬───────────────────────────────┘
                      │
    ┌─────────────────┼─────────────────┐
    │                 │                 │
┌───▼───┐        ┌────▼────┐       ┌────▼────┐
│ Code  │        │   PR    │       │  Docs   │
│ Agent │        │  Agent  │       │  Agent  │
└───────┘        └─────────┘       └─────────┘

interface Agent {
  name: string;
  description: string;
  triggers: Trigger[];
  contextBuilder: ContextBuilder;
  execute: (context: Context) => Promise<Result>;
}

const codeGenerationAgent: Agent = {
  name: 'code-generator',
  description: 'Generates code following team patterns',
  
  triggers: [
    { type: 'command', pattern: '/generate' },
    { type: 'file-created', pattern: '*.spec.ts' },
  ],
  
  contextBuilder: async (trigger) => {
    const relevantFiles = await findRelatedFiles(trigger.file);
    const teamPatterns = await loadPatterns();
    const styleGuide = await loadStyleGuide();
    
    return {
      files: relevantFiles,
      patterns: teamPatterns,
      styleGuide,
      request: trigger.input,
    };
  },
  
  execute: async (context) => {
    const prompt = buildCodeGenPrompt(context);
    
    const response = await llm.complete({
      model: 'gpt-4-turbo',
      messages: [
        { role: 'system', content: context.styleGuide },
        { role: 'user', content: prompt }
      ],
    });
    
    return {
      code: response.content,
      explanation: response.reasoning,
    };
  },
};

class ContextBuilder {
  async build(request: Request): Promise<Context> {
    // 1. Analyze the request
    const intent = await this.analyzeIntent(request);
    
    // 2. Find relevant code
    const relevantCode = await this.findRelevantCode(intent);
    
    // 3. Load team patterns
    const patterns = await this.loadPatterns(intent.domain);
    
    // 4. Get recent changes
    const recentChanges = await this.getRecentChanges();
    
    // 5. Build context window
    return {
      intent,
      code: this.prioritizeCode(relevantCode, intent),
      patterns,
      history: recentChanges,
      constraints: this.getConstraints(intent),
    };
  }
  
  private async findRelevantCode(intent: Intent): Promise<CodeFile[]> {
    // Semantic search over codebase
    const embeddings = await this.embedder.embed(intent.description);
    return await this.vectorStore.query(embeddings, { topK: 10 });
  }
}

const prReviewWorkflow = {
  trigger: 'pull_request.opened',
  
  steps: [
    {
      name: 'analyze-changes',
      action: async (pr) => {
        const diff = await github.getPRDiff(pr.number);
        return analyzeCodeChanges(diff);
      },
    },
    {
      name: 'check-patterns',
      action: async (pr, analysis) => {
        return checkAgainstPatterns(analysis, teamPatterns);
      },
    },
    {
      name: 'security-scan',
      action: async (pr, analysis) => {
        return securityScan(analysis.changedFiles);
      },
    },
    {
      name: 'generate-review',
      action: async (pr, analysis, patterns, security) => {
        return generateReview({ analysis, patterns, security });
      },
    },
    {
      name: 'post-review',
      action: async (pr, review) => {
        await github.createReview(pr.number, review);
      },
    },
  ],
};

const docGeneratorWorkflow = {
  trigger: 'file.modified',
  filter: (file) => file.endsWith('.ts') && !file.includes('.test.'),
  
  execute: async (file) => {
    // Extract functions and types
    const ast = await parseTypeScript(file);
    const exports = extractExports(ast);
    
    // Generate documentation for each export
    const docs = await Promise.all(
      exports.map(async (exp) => {
        const existingDoc = extractJSDoc(exp);
        
        if (existingDoc && !isOutdated(existingDoc, exp)) {
          return existingDoc;
        }
        
        return generateDocumentation(exp, {
          style: 'jsdoc',
          includeExamples: true,
          includeParams: true,
        });
      })
    );
    
    // Update file with new documentation
    return updateFileWithDocs(file, docs);
  },
};

class WorkflowOrchestrator {
  private workflows: Map<string, Workflow> = new Map();
  private eventBus: EventEmitter;
  
  register(workflow: Workflow) {
    this.workflows.set(workflow.name, workflow);
    
    // Set up triggers
    workflow.triggers.forEach((trigger) => {
      this.eventBus.on(trigger.event, async (data) => {
        if (trigger.filter && !trigger.filter(data)) return;
        
        await this.execute(workflow, data);
      });
    });
  }
  
  private async execute(workflow: Workflow, data: unknown) {
    const context = await workflow.contextBuilder(data);
    
    // Execute with retry and error handling
    const result = await retry(
      () => workflow.execute(context),
      { maxAttempts: 3, backoff: 'exponential' }
    );
    
    // Log and notify
    await this.logExecution(workflow, context, result);
    
    return result;
  }
}

interface WorkflowMetrics {
  executionCount: number;
  successRate: number;
  averageLatency: number;
  userSatisfaction: number;
  codeAcceptanceRate: number;
}

async function trackAndImprove(workflow: Workflow) {
  const metrics = await getMetrics(workflow.name);
  
  // Low acceptance rate? Analyze rejected outputs
  if (metrics.codeAcceptanceRate < 0.7) {
    const rejections = await getRejectedOutputs(workflow.name);
    const analysis = await analyzeRejections(rejections);
    
    // Update prompts based on analysis
    await updateWorkflowPrompts(workflow, analysis.improvements);
  }
}