The Day 4 Hours of Work Disappeared: Lessons from Genspark Development and a Complete Recovery Manual

📑 Table of Contents

Introduction: The Nightmare Moment

One day in October 2024, I was performing a major refactoring of a fortune-telling website using Genspark. I spent 4 hours completing component restructuring, API design review, and database schema changes. I was at the stage of just a final check.

Then, the Genspark chat screen suddenly froze. When I reloaded the page... the conversation history had completely disappeared.

This article explains lessons learned to protect yourself from sudden AI tool halts and provides a complete recovery manual in case data is lost.

Incident Timeline: What Happened

13:00

Refactoring work started. Plan to significantly modify the existing codebase.

13:30

Component structure redesign completed. Genspark proposed a new file structure.

14:30

API design review completed. Standardized to RESTful design and organized endpoints.

15:45

Database schema changes completed. Advanced normalization and improved performance.

16:30

During final verification, I asked Genspark to "summarize the changes made so far."

16:35

Chat screen froze. No response, screen became unresponsive.

16:37

Page reloaded. Conversation history completely disappeared. All 4 hours of work records vanished.

16:40

Panicked state. Confused about what was lost and where to start recovery.

What Was Lost: A Breakdown of 4 Hours

Details of Lost Data

  1. Conversation History (All)
    • Design discussion content
    • Reasons for technical decisions
    • History of trials and errors
  2. Generated Code
    • New components (approx. 10 files)
    • API implementation (approx. 5 endpoints)
    • Database migration scripts
  3. Design Documents
    • New directory structure diagrams
    • Revised API design document
    • Database schema diagrams
  4. Debugging Information
    • Bugs found and their fixes
    • Records of performance improvements

Financial Loss Estimation

As a freelance developer, calculating at ¥5,000 per hour:

  • Lost work time: 4 hours
  • Direct loss: ¥20,000
  • Recovery work time: 2 hours
  • Additional loss: ¥10,000
  • Total loss: ¥30,000
Important: Data loss is not just a "waste of time," but a "direct financial loss."

Root Cause Analysis: Why the Data Disappeared

Cause 1: Context Window Overflow

After 4 hours of continuous use, the context window may have reached its limit. Exceeding GPT-4's 128k tokens can make the system unstable.

Cause 2: Server Error

A temporary failure on Genspark's server may have occurred, leading to the loss of session data.

Cause 3: Browser Memory Depletion

Extended use may have exhausted browser memory, potentially causing JavaScript to stop.

Root Cause: Lack of Backup

However, the true cause was my own lack of backups. I neglected the following measures:

Emergency Response: What I Did in the First 30 Minutes

Step 1: Calm Down (5 minutes)

I was about to panic, but first, I took a deep breath. Acting emotionally can make things worse.

Step 2: Check What Remains (10 minutes)

  • Local codebase: remained in its pre-change state
  • AI drive: old specifications remained
  • Git commit history: last commit was yesterday
  • Memo app: had a rough TO DO list from the start of work

Step 3: Rely on Memory and Record (15 minutes)

While the memory was fresh, I wrote down the following in my memo app:

Emergency Memo Content

  • List of changed file names
  • Overview of the new API design
  • Key database changes
  • Important decisions (why that design was chosen)

Recovery Efforts: How Much I Managed to Recover

Recovery Level 1: Memory-Based (30% Recovered)

Based on the emergency memo, I re-implemented relying on memory. However, I couldn't recall the detailed implementations, so only about 30% could be restored.

Recovery Level 2: AI Regeneration Request (60% Recovered)

In a new chat screen, I requested Genspark to regenerate based on the old specifications and emergency memo. However, a different implementation was generated than last time, resulting in reduced quality.

Recovery Level 3: Manual Correction (90% Recovered)

I manually corrected the AI's output, finalizing it while cross-referencing with my memory. Ultimately, about 90% was recovered, but it wasn't a complete restoration.

Time Spent on Recovery

  • Emergency response: 30 minutes
  • Re-implementation: 2 hours
  • Verification/Correction: 1 hour
  • Total: 3.5 hours

✅ Breakdown of Recovery Rate

  • Code: 95% recovered (AI regeneration covered most)
  • Design documents: 80% recovered (supplemented by memory and inference)
  • Decision-making process: 50% recovered (most of "why it was done" was lost)
  • Debugging information: 30% recovered (had to rediscover the same bugs)

7 Lessons Learned: To Never Repeat It

Lesson 1: Save every 15 minutes. Set a timer to make it a habit.
Lesson 2: Immediately save important changes to the AI drive. Never "save it all later."
Lesson 3: Migrate the chat screen every 1-2 hours. Extended use is risky.
Lesson 4: Regularly download to your local PC. Don't rely solely on the cloud.
Lesson 5: Commit frequently to Git. Not "after it works," but "at each logical break in changes."
Lesson 6: Record the reasons for decisions. Save not just "what" but also "why."
Lesson 7: Don't think "it won't happen to me." Data loss can happen to anyone.

Complete Preventive Measures: System Building Guide

Preventive Measure 1: Automatic Saving System

Backup system based on the 3-2-1 rule:

  • Original: AI drive
  • Copy 1: Local PC (automatic sync with Google Drive)
  • Copy 2: Git repository (GitHub)

Preventive Measure 2: Work Log Template

Create the following template in the AI drive at the start of each work session:

Work Log Template

# Work Log - [Date]

## Goal
- [What to do today]

## Changed Files
- [File name and its changes]

## Decisions Made
- [Why that implementation was chosen]

## Next Tasks
- [What to do tomorrow]

Preventive Measure 3: Chat Migration Checklist

Perform the following every 2 hours:

  1. Save current work to AI drive
  2. Copy important code locally
  3. Commit to Git
  4. Migrate to a new chat screen
  5. Load information from AI drive

Preventive Measure 4: Use a Timer

Set a timer on your smartphone or PC for 15 minutes. Always save when the alarm sounds.

Conclusion: Data Protection is Not "Insurance," It's "Essential"

The loss of 4 hours of work was one of the most painful experiences in my AI development career. However, the lessons learned from this experience are invaluable.

  • Data loss happens: Not "it couldn't possibly happen," but "it will happen someday."
  • Prevention is best: Recovery takes time and money.
  • 3-2-1 rule: 3 copies, 2 different media, 1 offsite.
  • Regular saving as a habit: Every 15 minutes, use a timer.
  • Chat migration: New chat every 1-2 hours.
  • Record decisions: Save not just "what" but also "why."
  • Emergency preparedness: Stay calm, record based on memory.
Conclusion: Data protection is not "troublesome work," but "an investment that saves your future self." Build your backup system now and ensure you never experience the same nightmare again.

As a next step, learn about building an automatic backup system and warning signs of chat screen freezes to ensure a foolproof system.

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