fireflies-migration-deep-dive

name	fireflies-migration-deep-dive
description	Execute Fireflies.ai major re-architecture and migration strategies with strangler fig pattern. Use when migrating to or from Fireflies.ai, performing major version upgrades, or re-platforming existing integrations to Fireflies.ai. Trigger with phrases like "migrate fireflies", "fireflies migration", "switch to fireflies", "fireflies replatform", "fireflies upgrade major".
allowed-tools	Read, Write, Edit, Bash(npm:*), Bash(node:*), Bash(kubectl:*)
version	1.0.0
license	MIT
author	Jeremy Longshore <[e-mail]>

Fireflies.ai Migration Deep Dive

Overview

Comprehensive guide for migrating to or from Fireflies.ai, or major version upgrades.

Prerequisites

• Current system documentation
• Fireflies.ai SDK installed
• Feature flag infrastructure
• Rollback strategy tested

Migration Types

Type	Complexity	Duration	Risk
Fresh install	Low	Days	Low
From competitor	Medium	Weeks	Medium
Major version	Medium	Weeks	Medium
Full replatform	High	Months	High

Pre-Migration Assessment

Step 1: Current State Analysis

# Document current implementation
find . -name "*.ts" -o -name "*.py" | xargs grep -l "fireflies" > fireflies-files.txt

# Count integration points
wc -l fireflies-files.txt

# Identify dependencies
npm list | grep fireflies
pip freeze | grep fireflies

Step 2: Data Inventory

interface MigrationInventory {
  dataTypes: string[];
  recordCounts: Record<string, number>;
  dependencies: string[];
  integrationPoints: string[];
  customizations: string[];
}

async function assessFireflies.aiMigration(): Promise<MigrationInventory> {
  return {
    dataTypes: await getDataTypes(),
    recordCounts: await getRecordCounts(),
    dependencies: await analyzeDependencies(),
    integrationPoints: await findIntegrationPoints(),
    customizations: await documentCustomizations(),
  };
}

Migration Strategy: Strangler Fig Pattern

Phase 1: Parallel Run
┌─────────────┐     ┌─────────────┐
│   Old       │     │   New       │
│   System    │ ──▶ │  Fireflies.ai   │
│   (100%)    │     │   (0%)      │
└─────────────┘     └─────────────┘

Phase 2: Gradual Shift
┌─────────────┐     ┌─────────────┐
│   Old       │     │   New       │
│   (50%)     │ ──▶ │   (50%)     │
└─────────────┘     └─────────────┘

Phase 3: Complete
┌─────────────┐     ┌─────────────┐
│   Old       │     │   New       │
│   (0%)      │ ──▶ │   (100%)    │
└─────────────┘     └─────────────┘

Implementation Plan

Phase 1: Setup (Week 1-2)

# Install Fireflies.ai SDK
npm install @fireflies/sdk

# Configure credentials
cp .env.example .env.fireflies
# Edit with new credentials

# Verify connectivity
node -e "require('@fireflies/sdk').ping()"

Phase 2: Adapter Layer (Week 3-4)

// src/adapters/fireflies.ts
interface ServiceAdapter {
  create(data: CreateInput): Promise<Resource>;
  read(id: string): Promise<Resource>;
  update(id: string, data: UpdateInput): Promise<Resource>;
  delete(id: string): Promise<void>;
}

class Fireflies.aiAdapter implements ServiceAdapter {
  async create(data: CreateInput): Promise<Resource> {
    const firefliesData = this.transform(data);
    return firefliesClient.create(firefliesData);
  }

  private transform(data: CreateInput): Fireflies.aiInput {
    // Map from old format to Fireflies.ai format
  }
}

Phase 3: Data Migration (Week 5-6)

async function migrateFireflies.aiData(): Promise<MigrationResult> {
  const batchSize = 100;
  let processed = 0;
  let errors: MigrationError[] = [];

  for await (const batch of oldSystem.iterateBatches(batchSize)) {
    try {
      const transformed = batch.map(transform);
      await firefliesClient.batchCreate(transformed);
      processed += batch.length;
    } catch (error) {
      errors.push({ batch, error });
    }

    // Progress update
    console.log(`Migrated ${processed} records`);
  }

  return { processed, errors };
}

Phase 4: Traffic Shift (Week 7-8)

// Feature flag controlled traffic split
function getServiceAdapter(): ServiceAdapter {
  const firefliesPercentage = getFeatureFlag('fireflies_migration_percentage');

  if (Math.random() * 100 < firefliesPercentage) {
    return new Fireflies.aiAdapter();
  }

  return new LegacyAdapter();
}

Rollback Plan

# Immediate rollback
kubectl set env deployment/app FIREFLIES_ENABLED=false
kubectl rollout restart deployment/app

# Data rollback (if needed)
./scripts/restore-from-backup.sh --date YYYY-MM-DD

# Verify rollback
curl https://app.yourcompany.com/health | jq '.services.fireflies'

Post-Migration Validation

async function validateFireflies.aiMigration(): Promise<ValidationReport> {
  const checks = [
    { name: 'Data count match', fn: checkDataCounts },
    { name: 'API functionality', fn: checkApiFunctionality },
    { name: 'Performance baseline', fn: checkPerformance },
    { name: 'Error rates', fn: checkErrorRates },
  ];

  const results = await Promise.all(
    checks.map(async c => ({ name: c.name, result: await c.fn() }))
  );

  return { checks: results, passed: results.every(r => r.result.success) };
}

Instructions

Step 1: Assess Current State

Document existing implementation and data inventory.

Step 2: Build Adapter Layer

Create abstraction layer for gradual migration.

Step 3: Migrate Data

Run batch data migration with error handling.

Step 4: Shift Traffic

Gradually route traffic to new Fireflies.ai integration.

Output

• Migration assessment complete
• Adapter layer implemented
• Data migrated successfully
• Traffic fully shifted to Fireflies.ai

Error Handling

Issue	Cause	Solution
Data mismatch	Transform errors	Validate transform logic
Performance drop	No caching	Add caching layer
Rollback triggered	Errors spiked	Reduce traffic percentage
Validation failed	Missing data	Check batch processing

Examples

Quick Migration Status

const status = await validateFireflies.aiMigration();
console.log(`Migration ${status.passed ? 'PASSED' : 'FAILED'}`);
status.checks.forEach(c => console.log(`  ${c.name}: ${c.result.success}`));

Resources

• Strangler Fig Pattern
• Fireflies.ai Migration Guide

Flagship+ Skills

For advanced troubleshooting, see fireflies-advanced-troubleshooting.