AI Development Overview: Understand from Planning to Operation in 7 Steps

📑 Table of Contents

Introduction: Drawing the "Blueprint" of AI Development

Have you started "AI development" using Genspark, ChatGPT, GitHub Copilot, etc., but feel "I don't know what to do next"?

Many beginners, focusing too much on immediate code generation, lose sight of the overall development flow. As a result, they face problems like:

  • "I built a prototype, but what's next?"
  • "Are specifications really necessary?"
  • "At what stage should testing be done?"
  • "What is deployment? How do I do it?"

This article explains the entire picture of AI development in 7 steps, clarifying what to do and how long each step takes.

The 7-Step Overview of AI Development

Step Phase Estimated Duration Main Deliverables
1 Conception & Planning 1-3 days Project Concept Document, Requirements List
2 Prototype Creation 3-7 days Minimum Viable Demo
3 Specification Writing 2-5 days Technical Specifications, API Design Document
4 Development & Implementation 1-4 weeks Implemented Codebase
5 Testing & Debugging 1-2 weeks Tested Stable Version
6 Deployment & Release 1-3 days Released Service
7 Operation & Maintenance Ongoing Update History, Incident Response Records

Total Duration: Approximately 2-3 months for small projects, 3-6 months for medium-sized projects is a guideline.

Important: Even in AI development, the flow of "Plan → Implement → Test → Release → Operate" remains the same as conventional development. AI "accelerates" each step, but it cannot "skip" them.

Step 1: Conception & Planning (1-3 Days)

🎯 Purpose of this step

Clarify "what to build," "why to build it," and "for whom to build it."

What to do

  1. Idea Organization
    • What problem needs to be solved?
    • Who are the users?
    • Are there similar existing services?
  2. Feature List Creation
    • Essential features (MVP: Minimum Viable Product)
    • Nice-to-have features
    • Features to add in the future
  3. Technology Selection
    • Languages and frameworks to use
    • Database type
    • Hosting service
  4. Schedule Planning
    • Deadlines for each phase
    • Target release date

How to Utilize AI

It is effective to input your concept into Genspark and get feedback. Refer to the Detailed Guide to the Conception Phase.

Prompt Example

"I want to create a web app with [functionality] for [purpose]. The target users are [user persona], and I plan to use [tech stack]. Please tell me about the feasibility and improvements for this concept."

Deliverables

  • Project Concept Document (Markdown format recommended)
  • Functional Requirements List
  • Tech Stack List

Step 2: Prototype Creation (3-7 Days)

🎯 Purpose of this step

Verify if the idea is "feasible" and finalize the development direction.

What to do

  1. MVP Definition
    • Implement only the minimum necessary features
    • Prioritize "working" over "perfect"
  2. Technical Verification
    • Confirm if the selected tech stack is actually usable
    • Check API operation
    • Performance testing (simplified version)
  3. User Feedback
    • Have friends and family try it out
    • Confirm "Do you want to use it?"

How to Utilize AI

Generating prototype code is one of AI's strongest areas. However, use it with an understanding of the Limitations of AI Code.

Prompt Example

"Using [tech stack], create a simple prototype with only [feature 1] and [feature 2]. No database is needed; it just needs to work with dummy data."

Deliverables

  • Working prototype (code)
  • Technical verification report
  • User feedback records

Decision Criteria

If the prototype is judged "feasible," proceed. If it seems impossible, re-evaluate the concept (pivot).

Step 3: Specification Writing (2-5 Days)

🎯 Purpose of this step

Create the "blueprint" for development and eliminate ambiguity during implementation.

What to do

  1. Functional Specifications
    • Detailed operation of each function
    • Screen transition diagrams
    • User stories
  2. Technical Specifications
    • Directory structure
    • Database design (ER diagram)
    • API design (endpoint list)
    • Authentication/authorization mechanism
  3. Non-functional Requirements
    • Performance goals (response time, etc.)
    • Security requirements
    • Scalability

How to Utilize AI

AI can draft specifications. However, understand the Problems with AI-generated Specifications and always have a human review them.

Deliverables

  • FunctionalSpecifications.md
  • TechnicalSpecifications.md
  • APIDesignDocument.md
  • Database Design Diagram (ER Diagram)
Warning: Skipping "troublesome specifications" will lead to repeatedly asking "What should I do here?" later, ultimately wasting time.

Step 4: Development & Implementation (1-4 Weeks)

🎯 Purpose of this step

Build a functional system based on the specifications.

What to do

  1. Environment Setup
    • Set up the development environment
    • Create a Git repository
    • Configure CI/CD pipeline (optional)
  2. Implement Feature by Feature
    • Start with high-priority features
    • Test each feature individually
    • Commit regularly (save to Git)
  3. Code Review
    • Review AI-generated code
    • Refactoring
  4. Documentation Update

How to Utilize AI

AI excels most at this stage. Refer to the 7 Steps of Genspark Development to proceed with efficient development.

Estimated Time Allocation

  • Environment Setup: 1-2 days
  • Frontend: 1-2 weeks
  • Backend: 1-2 weeks
  • Integration: 2-3 days

Step 5: Testing & Debugging (1-2 Weeks)

🎯 Purpose of this step

Discover and fix bugs, making the system stable.

What to do

  1. Unit Test
    • Check if each function works correctly
  2. Integration Test
    • Check if multiple features work together
  3. E2E Test (End-to-End Test)
    • Simulate actual user operations
  4. Bug Fixing

How to Utilize AI

  • Automatic test case generation
  • Bug cause analysis
  • Suggestion of corrective code

Deliverables

  • Complete set of test code
  • Bug fix history
  • Test results report

Step 6: Deployment & Release (1-3 Days)

🎯 Purpose of this step

Publish the developed system to a production environment, making it available to users.

What to do

  1. Prepare Production Environment
    • Contract a hosting service (Vercel, Heroku, AWS, etc.)
    • Domain acquisition (optional)
  2. Deployment
    • Upload code to the production environment
    • Set environment variables
    • Database migration
  3. Operation Check
    • Operational testing in the production environment
    • Performance confirmation
  4. Monitoring Setup
    • Error log collection
    • Access analysis (Google Analytics, etc.)

Recommended Services

  • Vercel: Best for Next.js (free plan available)
  • Heroku: Multi-language support (free plan ended, low-cost plans available)
  • AWS: For enterprise (pay-as-you-go)

Step 7: Operation & Maintenance (Ongoing)

🎯 Purpose of this step

Keep the system running stably and continue improvements based on user feedback.

What to do

  1. Monitoring
    • Regular review of error logs
    • Performance monitoring
    • Tracking user count trends
  2. Bug Handling
    • Fixing user-reported bugs
    • Prioritizing based on urgency
  3. Feature Addition/Improvement
    • Reflecting user feedback
    • Regular updates
  4. Security Updates
    • Addressing library vulnerabilities
    • Regular security checks

Continuous Improvement

Operation is not a "goal" but a "new beginning." It is crucial to listen to users and continuously evolve the system.

Key AI Utilization Points in Each Phase

Phase AI's Role Human's Role
Conception & Planning Idea refinement, research on similar services Final decision, priority setting
Prototype Code generation, advice on technology selection Operational verification, feedback collection
Specification Writing Drafting, formatting Review, detailing
Development & Implementation Code generation, refactoring Architecture design, code review
Testing Test case generation, bug analysis Test execution, bug fix judgment
Deployment Deployment script generation Environment setup, operational verification
Operation & Maintenance Log analysis, error cause identification Priority judgment, user support
Key Point: AI is excellent as an "executor," but the "decision-maker" is always human. Human leadership in each phase is the key to success.

Summary: The Importance of Grasping the Overall Picture

Understanding the overall picture of AI development provides the following benefits:

  • Eliminates uncertainty: "What to do next" becomes clear
  • Allows time management: Can estimate the duration of each phase
  • Improves quality: Avoids skipping tests and specifications
  • Increases completeness: Designs with deployment and operation in mind
  • Boosts learning efficiency: Clarifies which knowledge to learn
Conclusion: AI development is not just about "code generation." By understanding all 7 steps from planning to operation, and by fostering collaboration between AI and humans at each step, high-quality systems can be built in a shorter timeframe.

As a next step, refer to the Detailed Genspark Development Workflow and the Practical Guide to the Conception Phase to begin your actual development.

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