Documentation is a Graveyard: Why Your Discovery Process is Killing Your Velocity

Documentation is where tribal knowledge goes to die. In the average enterprise, documentation is a snapshot of a moment that no longer exists, written by someone who has likely left the company. When we talk about continuous discovery engineering managers often mistake it for a series of meetings or a Jira epic dedicated to "knowledge transfer." It isn’t.

True continuous discovery is a passive runtime event. It is the ability to extract the "truth" of a system not from what developers remember, but from how the system actually behaves in the hands of a user.

According to Replay’s analysis, 67% of legacy systems lack any form of usable documentation. This lack of visibility contributes significantly to the $3.6 trillion global technical debt bubble. When an Engineering Manager (EM) is tasked with a modernization effort, they usually face an 18-to-24-month horizon. Why? Because the first six months are spent in "Discovery Hell"—manually clicking through screens, reading obfuscated COBOL or Delphi code, and trying to map out business logic that hasn't been updated in documentation since 2012.

TL;DR: Manual documentation is a bottleneck. Continuous discovery should be a passive byproduct of system usage. By using Replay, EMs can convert video recordings of legacy workflows into documented React code and Design Systems, reducing discovery time by 70% and turning an 18-month rewrite into a few weeks of automated synthesis.

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Why Continuous Discovery Engineering Managers Need a New Paradigm#

The traditional discovery phase is a manual, error-prone process. It involves business analysts (BAs) writing requirements, developers reading old source code, and designers trying to recreate UI components from screenshots. Industry experts recommend moving away from this "Big Bang Discovery" toward a model where the system documents itself during execution.

Video-to-code is the process of capturing user interactions with a legacy application and using AI-driven visual reverse engineering to generate functional, documented frontend components and architectural flows.

For continuous discovery engineering managers, the goal is to eliminate the "Knowledge Tax"—the time spent figuring out what the current system does before you can build the new one.

The Cost of Manual Discovery vs. Visual Reverse Engineering#

Learn more about Legacy Modernization Strategies

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Implementing Continuous Discovery Engineering Managers Can Trust#

To make discovery a "passive runtime event," you must shift the point of capture. Instead of asking a developer to "go learn the system," you ask a subject matter expert (SME) to "show us the system."

By recording a user performing a standard workflow—for example, processing a loan application in a legacy PowerBuilder app—Replay captures the visual state, the DOM structure (or its visual equivalent), and the underlying data flows.

From Legacy UI to Documented React#

Consider a legacy table component. In an old ASP.NET WebForms app, this might be a mess of nested tables and inline styles. A manual rewrite requires a developer to inspect the CSS, understand the sorting logic, and then write a modern React equivalent.

With Replay, the "discovery" happens as the video is processed. The AI identifies the component boundaries, extracts the design tokens (colors, spacing, typography), and generates a clean, documented TypeScript component.

Example: Legacy Component Analysis (The "Before")

html
<!-- Legacy WebForms Table - Obfuscated and undocumented -->
<table id="ctl00_MainContent_Grid1" class="old-grid-style">
  <tr class="header">
    <td onclick="sort('UID')">User ID</td>
    <td>Status</td>
  </tr>
  <tr class="row">
    <td>10293</td>
    <td><span class="status-active">Active</span></td>
  </tr>
</table>

Example: Replay Generated React Component (The "After")

typescript
import React from 'react';
import { Table, Badge } from '@/components/ui';

interface UserRowProps {
  id: string;
  status: 'active' | 'inactive' | 'pending';
}

/**
 * @component UserStatusTable
 * @description Automatically discovered from Legacy Loan Module (Flow #4)
 * @generatedBy Replay AI Automation Suite
 */
export const UserStatusTable: React.FC<{ data: UserRowProps[] }> = ({ data }) => {
  return (
    <Table>
      <thead>
        <tr>
          <th>User ID</th>
          <th>Status</th>
        </tr>
      </thead>
      <tbody>
        {data.map((row) => (
          <tr key={row.id}>
            <td>{row.id}</td>
            <td>
              <Badge variant={row.status === 'active' ? 'success' : 'neutral'}>
                {row.status}
              </Badge>
            </td>
          </tr>
        ))}
      </tbody>
    </Table>
  );
};

This isn't just code generation; it's continuous discovery. The documentation is embedded in the component metadata, linked back to the original recording (the "Flow") where it was discovered.

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The Three Pillars of Passive Discovery#

For continuous discovery engineering managers to be successful, they must oversee three specific outputs that Replay automates: The Library, The Flows, and The Blueprints.

1. The Library (The Design System)#

Most legacy systems have "accidental" design systems—patterns that repeat but aren't codified. Replay’s Library feature identifies these repeating visual elements across recorded videos. It extracts global variables like hex codes and padding, creating a unified Design System.

Visual Reverse Engineering is the methodology of reconstructing the source design intent and functional logic of a software system by analyzing its visual output and runtime behavior rather than its source code.

2. The Flows (The Architecture)#

Documentation usually fails to explain how a user gets from Point A to Point B. By recording "Flows," EMs can see the state transitions. Replay documents these transitions automatically, creating a map of the application’s business logic. This is critical for regulated industries like Healthcare or Financial Services, where audit trails of "how a decision was made" are mandatory.

3. The Blueprints (The Implementation)#

Blueprints are the bridge between discovery and development. Once Replay has captured the legacy system's behavior, the Blueprint editor allows architects to refine the generated code before it enters the production codebase. This reduces the manual "40 hours per screen" to just "4 hours of refinement."

Discover how to automate your Design System

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Overcoming the "70% Failure Rate"#

Industry data shows that 70% of legacy rewrites fail or exceed their timeline. The primary reason is "Scope Creep" caused by undiscovered requirements. When discovery is a manual event, you only find what you are looking for.

When discovery is a passive runtime event, you find what is actually there.

According to Replay's analysis, enterprises using visual reverse engineering see a 70% average time savings in their modernization pipelines. By shifting the burden of documentation from the developer to an automated platform, EMs can ensure that their team is spending 90% of their time building new value, rather than 90% of their time archeologizing the past.

Case Study: Telecom Modernization#

A major Telecom provider had a 20-year-old CRM used by 5,000 agents. The source code was a mix of Java and legacy JavaScript libraries that no longer had active maintainers. A manual rewrite was estimated at 24 months.

By implementing a continuous discovery engineering managers strategy using Replay:

1. •Agents recorded their top 50 most common tasks (Flows).
2. •Replay's AI Automation Suite extracted a complete React component library.
3. •The team generated a functional "Modernized Baseline" in 3 weeks.
4. •The project was completed in 6 months, saving an estimated $4.2M in developer hours.

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Technical Deep Dive: Mapping Runtime State to React Props#

One of the hardest parts of discovery is understanding data mapping. In a legacy system, a field might be named

, but in the modern UI, it should be .

Replay’s AI Automation Suite performs semantic analysis on the surrounding context of the UI. It looks at labels, placeholder text, and the data types flowing into the component during the recording.

typescript
// Replay AI infers semantic meaning from legacy context
// Source: Legacy Recording #882 (Customer Profile Screen)
// Context: Field sits under "Contact Information" header

export interface CustomerProfileProps {
  /** @alias TXT_FLD_01 */
  customerEmail: string;
  /** @alias TXT_FLD_02 */
  phoneNumber: string;
  /** @alias DRP_DWN_01 */
  subscriptionTier: 'basic' | 'pro' | 'enterprise';
}

This mapping is documented as the "Blueprint" for the component. When the EM reviews the discovery progress, they aren't looking at a Word doc; they are looking at a live, interactive Library of components that are ready for implementation.

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Security and Compliance in Discovery#

For EMs in Financial Services, Insurance, or Government, the idea of "recording" workflows can raise red flags. This is why Replay is built for regulated environments.

• •SOC2 & HIPAA Ready: Data is encrypted at rest and in transit.
• •PII Masking: Automated redaction of sensitive user data during the recording process.
• •On-Premise Deployment: For air-gapped environments or highly sensitive data, Replay can run entirely within your VPC.

This ensures that continuous discovery engineering managers can maintain the highest security standards while still benefiting from the speed of automated reverse engineering.

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The Future of the Engineering Manager Role#

The role of the EM is shifting from "Project Manager" to "Platform Architect." In the old world, the EM had to constantly ask, "Is the documentation updated?" In the new world, the EM asks, "Is the discovery engine running?"

By making documentation a passive runtime event, you remove the friction between the "as-is" state and the "to-be" state. You allow your developers to work in a modern stack (React, TypeScript, Tailwind) immediately, rather than forcing them to spend months as "Legacy Historians."

The $3.6 trillion technical debt problem won't be solved by writing more manuals. It will be solved by platforms that can see, understand, and translate the digital past into a functional future.

Ready to modernize without rewriting? Book a pilot with Replay

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Frequently Asked Questions#

How does continuous discovery differ from traditional requirements gathering?#

Traditional requirements gathering is a proactive, manual phase that happens before coding begins, often resulting in "stale" data. Continuous discovery for engineering managers is a passive, ongoing process where the system’s actual behavior is captured and documented in real-time as users interact with it, ensuring the documentation is always a reflection of the current "truth."

Can Replay handle legacy systems that aren't web-based?#

Yes. Replay's Visual Reverse Engineering platform is designed to analyze the visual output and interaction patterns of legacy UIs, including desktop applications (Delphi, PowerBuilder, VB6) and mainframe emulators, converting those visual flows into modern, web-standard React components and documented Design Systems.

What is the average time savings when using Replay for discovery?#

According to Replay's analysis, enterprises save an average of 70% in time and labor. A process that typically takes 40 hours per screen using manual discovery and coding can be reduced to approximately 4 hours using Replay’s automated AI suite.

Is the code generated by Replay production-ready?#

Replay generates a "Modernized Baseline"—high-quality, documented React/TypeScript code that mirrors the logic and UI of the legacy system. While it provides a 90% head start, we recommend a final architectural review (using the Replay Blueprint editor) to ensure the generated components align with your specific internal coding standards and backend API integrations.

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Ready to modernize without rewriting? Book a pilot with Replay