The CTO Guide to 'Extraction-First' Architecture: A New Paradigm for Modernization

70% of legacy rewrites fail or exceed their timeline. This isn't a failure of talent; it's a failure of methodology. When you decide to modernize a legacy system, you aren't just writing new code—you are attempting a high-stakes archaeological dig into a $3.6 trillion global technical debt pile. Most organizations spend 18 to 24 months trying to rebuild what they don't fully understand, only to realize the "source of truth" was never the outdated documentation, but the undocumented behavior of the live system.

TL;DR: Extraction-First Architecture replaces manual "code archaeology" with visual reverse engineering, reducing modernization timelines from years to weeks by using video as the source of truth for generating documented React components and API contracts.

The Death of the "Big Bang" Rewrite#

The traditional approach to modernization is fundamentally flawed. CTOs are often forced to choose between a "Big Bang" rewrite—which carries a massive risk of logic loss—and the "Strangler Fig" pattern, which often results in a decade-long transition period where you are forced to maintain two parallel stacks.

The core issue is that 67% of legacy systems lack any meaningful documentation. When your senior architects spend 40 hours per screen just to map out dependencies and business logic, you aren't innovating; you're paying a premium for discovery.

Modernization Strategy Comparison#

What is Extraction-First Architecture?#

Extraction-First Architecture is a new paradigm that treats the running application—not the stale codebase—as the primary source of truth. Instead of reading through thousands of lines of spaghetti COBOL, Java, or legacy .NET, you record real user workflows.

By using Replay, you record a session of a user navigating a legacy screen. The platform performs visual reverse engineering to extract the DOM structure, CSS states, and underlying data flows. It then transforms this "black box" behavior into a clean, documented React component library.

The Shift from Archaeology to Engineering#

In a traditional rewrite, your engineers spend 80% of their time on discovery and 20% on implementation. Extraction-First flips this ratio. By automating the discovery phase, you move from 40 hours of manual work per screen to just 4 hours with Replay.

💰 ROI Insight: For an enterprise application with 100 screens, a manual rewrite costs approximately 4,000 engineering hours. Replay reduces this to 400 hours, representing a 90% reduction in discovery costs and a 70% overall time saving.

Implementing the Extraction-First Workflow#

Moving to an extraction-first model requires a shift in how your architecture team views "legacy." It is no longer a burden to be discarded, but a blueprint to be harvested.

Step 1: Visual Recording and Mapping#

Instead of starting with a blank IDE, your team records the legacy application in action. This captures the exact state of the UI, including edge cases that are rarely documented. Replay’s engine analyzes these recordings to identify reusable patterns.

Step 2: Component Extraction#

The platform identifies UI patterns and extracts them into a standardized Design System (The Replay Library). This ensures that your modernized frontend isn't just a clone, but a structured, scalable React implementation.

typescript
// Example: Automatically generated React component from Replay Extraction
// This component preserves legacy business logic while using modern hooks

import React, { useState, useEffect } from 'react';
import { LegacyDataConnector } from '@replay/internal-tools';

interface CustomerProfileProps {
  id: string;
  onUpdate: (data: any) => void;
}

export const CustomerProfile: React.FC<CustomerProfileProps> = ({ id, onUpdate }) => {
  const [loading, setLoading] = useState(true);
  const [profileData, setProfileData] = useState<any>(null);

  // Replay extracted the exact API contract from the legacy network trace
  useEffect(() => {
    async function fetchLegacyState() {
      const response = await LegacyDataConnector.get(`/api/v1/cust/${id}/meta`);
      setProfileData(response.data);
      setLoading(false);
    }
    fetchLegacyState();
  }, [id]);

  if (loading) return <SkeletonLoader />;

  return (
    <div className="modern-container">
      <h2>{profileData.displayName}</h2>
      {/* Business logic for conditional rendering extracted from video session */}
      {profileData.status === 'PREMIUM' && <PremiumBadge />}
      <button onClick={() => onUpdate(profileData)}>Update Record</button>
    </div>
  );
};

Step 3: API Contract Generation#

One of the biggest bottlenecks in modernization is the backend. Legacy systems often have "mystery meat" APIs with no Swagger/OpenAPI definitions. As you record workflows, Replay generates API contracts based on actual network traffic.

yaml
# Generated OpenAPI Spec from Replay Flow Extraction
openapi: 3.0.0
info:
  title: Legacy Insurance Claims API
  version: 1.0.0
paths:
  /claims/{claimId}/validate:
    post:
      summary: Extracted from "Submit Claim" workflow
      parameters:
        - name: claimId
          in: path
          required: true
          schema:
            type: string
      responses:
        '200':
          description: Validation successful
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ValidationResult'

Step 4: E2E Test Automation#

Because the extraction is based on real user flows, Replay generates E2E tests (Cypress/Playwright) that mirror the legacy behavior. This provides a "safety net" that ensures the modernized version behaves exactly like the original.

⚠️ Warning: Never attempt a rewrite without a baseline of E2E tests generated from the legacy system. Without this, you will inevitably miss silent business rules buried in the UI logic.

Solving the "Black Box" Problem in Regulated Industries#

For CTOs in Financial Services, Healthcare, and Government, "just rewrite it" is a dangerous proposition due to compliance risks. You cannot afford to lose a single validation rule or data transformation step.

Replay is built for these high-stakes environments. It offers:

• •SOC2 & HIPAA Readiness: Data handling that meets federal and industry standards.
• •On-Premise Availability: Keep your extraction process within your own VPC or air-gapped environment.
• •Technical Debt Audit: A comprehensive report of what was extracted, what was refactored, and what remains in the legacy state.

The Role of AI in Extraction-First#

The future of modernization isn't just about moving code; it's about understanding intent. Replay’s AI Automation Suite analyzes the extracted flows to identify redundant logic and technical debt.

1. •Pattern Recognition: AI identifies that 15 different legacy pages are actually using the same underlying "Data Grid" logic, allowing you to consolidate them into a single React component.
2. •Logic Translation: It translates legacy state management (often a mess of global variables) into modern React Context or Redux patterns.
3. •Documentation Synthesis: It generates human-readable documentation for the new system based on the old system's behavior.

💡 Pro Tip: Use the "Blueprints" feature in Replay to visually edit the extracted components before they are committed to your repository. This allows architects to enforce coding standards at the point of extraction.

Case Study: From 18 Months to 6 Weeks#

A Tier-1 Insurance provider faced a common dilemma: a legacy claims processing system built in 2005 that was blocking their move to the cloud. A manual rewrite was quoted at 18 months with a $4M budget.

Using Replay, they:

1. •Recorded the 45 core workflows of the claims adjusters.
2. •Extracted the UI into a modern React-based Design System in 10 days.
3. •Generated OpenAPI specs for the legacy mainframe connectors.
4. •Delivered the modernized frontend in 6 weeks.

The result? A 70% reduction in time-to-market and a system that was fully documented from day one.

Frequently Asked Questions#

How long does legacy extraction take?#

While a manual screen reconstruction takes 40+ hours, Replay reduces this to approximately 4 hours. For a standard enterprise application, the initial extraction of core flows typically takes 2 to 8 weeks, depending on the complexity of the underlying business logic.

What about business logic preservation?#

This is the primary advantage of Extraction-First. Because we use "Video as the source of truth," we capture how the system actually behaves, including hidden validation rules and state changes that are often lost in code-only migrations. Replay generates functional components that mirror this behavior precisely.

Does this replace my engineering team?#

No. It empowers them. Instead of doing the "grunt work" of manual UI reconstruction and API mapping, your engineers focus on high-value tasks: optimizing the new architecture, implementing new features, and refining the user experience.

Can Replay handle complex, multi-step forms?#

Yes. Replay’s "Flows" feature is specifically designed for complex, multi-state workflows. It tracks data as it moves through various steps, ensuring that the extracted React components maintain the correct state transitions.

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Ready to modernize without rewriting? Book a pilot with Replay - see your legacy screen extracted live during the call.