📅 January 30, 2026 📁 Development Achievements 👀 0 views 🏷️ #Genspark #AI_Development #SNS_Development #Cost_Reduction

【Development Achievement】The complete record of developing an SNS app, which usually takes 3 months, in 1 week with Genspark

Table of Contents

Introduction: Completing 3 Months of Work in 1 Week

"If Slack and Teams are too expensive, why not build our own?"

This community app development project started with that idea. Typically, developing a full-fledged SNS app with a frontend and backend by oneself, including design and debugging, would take at least 3 months, or even half a year if one cannot work on it intensively.

However, by thoroughly utilizing an AI agent called Genspark, we succeeded in shortening this period to "effectively 1 week (4 full days of work)". This is not just about code generation, but a record of directing AI as an "engineering team."

Development Scale and Specifications: The True Nature of 22,500 Lines

The app developed this time is not a simple prototype. It's a full-stack application equipped with authentication, real-time notifications, DMs, and file management.

Application Scale

  • Total Lines of Code: Approx. 22,500 lines
  • Number of Files: 121 files
  • Frontend: Next.js 15, React (Approx. 11,000 lines)
  • Backend: Cloudflare Workers, Hono (Approx. 11,000 lines)

Even looking at the breakdown by feature, the AI generated a staggering amount of code that would be daunting for a human to type manually: post/reply functionality (4,000 lines), DM functionality (3,000 lines), and authentication (2,000 lines). The speed with which it handled TypeScript type definitions and adopted the latest technologies like Next.js 15 is unique to AI.

Astounding Cost Performance: $300 vs. 3 Months of Labor Costs

We are also disclosing the financial costs incurred for development.

  • Initial Charge: $100
  • Additional Credits: $200 (consumed for troubleshooting in the latter half of development, etc.)
  • Total: $300 (approx. 45,000 JPY)

Result: 90% Improvement in Development Efficiency

Considering 3 months of labor costs for one engineer, the cost of $300 is exceptional. AI development has proven to be not just a "time-saver," but an overwhelming "cost-reduction" solution.

Key to Success: The "Quality Check" Strategy of Decomposing the Process into 10 Stages

An app of this scale will never be completed by simply telling the AI, "Build an SNS app." The key to success lies in breaking down the development process into detailed steps and having humans perform "quality checks" at each phase.

My practiced "AI Orchestration Flow" is as follows:

  1. Concept Review: Brainstorming and requirement elicitation
  2. Requirement Definition Document Creation: Having the AI write the document
  3. Design Document Creation: Creating three detailed design documents
  4. Use Case Definition: Defining user actions
  5. Backend Implementation: First, building the backend processes
  6. Backend Test List Creation: Having it create the test plan
  7. Debugging (BE): Verifying API functionality
  8. Frontend Specification Document Creation: Designing the screen interface
  9. Frontend Implementation: UI construction
  10. Frontend Debugging: Integration testing

Important: Don't Leave Everything to AI; Create "Breaks" at Each Stage

If you try to have the AI write all the code at once, it gets confused. The key is to have it create documents for each stage, and only proceed to the next after human approval. This "separation of upstream and downstream" was the biggest reason I was able to significantly reduce my work hours.

The Gritty Reality: 18 Freezes and the "Limits of AI"

It wasn't all good. I must also convey the realistic "hardships" of AI development. Before the basic functionality was complete, I encountered the following problems:

  • Chat screen unresponsiveness (freeze): 18 times
    ※This phenomenon is not due to browser load, but a system error on Genspark's side that completely halts the response. It doesn't recover with a reload, and the only option is to start a new chat, so if you don't save frequently, all your work will be lost.
  • Bash (command operations) unusable: 8 times (due to sandbox environment connection loss, etc.)
  • Missing specifications: Realizing "Oh, this feature is missing" in the latter half of development (initial conceptualization was not thorough enough)
  • DB refactoring hell: The need to change the DB structure mid-way, leading to corrections generating a chain of bugs

"Unresponsiveness" is particularly troublesome. Its frequency tends to increase as the conversation history with the AI grows longer, forcing you to switch to a new chat. If you neglect to commit to Git or download documents, several hours of work can be lost in an instant.

Furthermore, "specification changes in the latter half of development" are also fatal. While AI builds according to instructions, it doesn't automatically consider "future scalability." If the human side fails to "read carefully" and "foresee" at the initial stage, there will be painful repercussions later on.

Summary: AI Development is "Orchestration," Not "Magic"

The experience of writing 22,500 lines of code in a week felt truly magical, but behind it lay meticulous process management and repeated troubleshooting.

AI is the "strongest worker," but not a "perfect supervisor." You are the supervisor. With appropriate instructions, frequent quality checks, and calm responses to problems, even an individual can create an app comparable to products from large corporations.

Next Up

The most challenging aspect of this rapid development was "frontend development." How did we break through the desperate situation where Next.js was too heavy to run and all testing tools failed? We will explain in detail in the next article.

Technology Stack Used

You Might Also Like