I launched my MVP Development Agency in October Till now, I’ve...
Prajwal Tomar@PrajwalTomar_
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Apr 27, 2025
~3 min read
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I launched my MVP Development Agency in October
Till now, I’ve built 18 MVPs for clients with AI coding tools.
Here’s everything I learned in last 7 months.
Bookmark this if you want to build faster and smarter with AI: ↓
Till now, I’ve built 18 MVPs for clients with AI coding tools.
Here’s everything I learned in last 7 months.
Bookmark this if you want to build faster and smarter with AI: ↓
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1/ Why planning is critical for AI coding
AI models from Gemini or Sonnet are great at writing code.
But without context, they hallucinate.
And this hallucinations leads to:
• 100s of Bugs
• Wasted tokens
• Messy codebase
Planning is not optional. This is how you make AI to work like a real dev.
AI models from Gemini or Sonnet are great at writing code.
But without context, they hallucinate.
And this hallucinations leads to:
• 100s of Bugs
• Wasted tokens
• Messy codebase
Planning is not optional. This is how you make AI to work like a real dev.
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2/ Start with brainstorming
Before writing anything, I use ChatGPT Voice to think out loud.
• What am I building?
• Who is it for?
• What are the top 3 features?
Voice helps you think faster and clearer than typing long prompts.
Simple, but powerful.
Before writing anything, I use ChatGPT Voice to think out loud.
• What am I building?
• Who is it for?
• What are the top 3 features?
Voice helps you think faster and clearer than typing long prompts.
Simple, but powerful.
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3/ Build a Knowledge Base
Once the idea is clear, I create project documents.
These docs act as a live “Knowledge Base” for the AI to use while building.
Without them, Cursor has no real memory of what you want. It starts hallucinating and end up messing the entire codebase.
With project docs, it becomes 10x more accurate.
Once the idea is clear, I create project documents.
These docs act as a live “Knowledge Base” for the AI to use while building.
Without them, Cursor has no real memory of what you want. It starts hallucinating and end up messing the entire codebase.
With project docs, it becomes 10x more accurate.
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4/ Documents you need
Here is the minimum set of docs I create:
• PRD → What and why we are building
• App Flow → Full user journey
• Tech Stack → Tools, libraries, APIs
• Frontend Guidelines → Fonts, layouts, UI rules
• Backend Structure → DB schema, auth, storage
• Implementation Plan → 50+ step build checklist
• Security Guidelines → Secure defaults from day one
This is the real secret to clean AI builds.
Here is the minimum set of docs I create:
• PRD → What and why we are building
• App Flow → Full user journey
• Tech Stack → Tools, libraries, APIs
• Frontend Guidelines → Fonts, layouts, UI rules
• Backend Structure → DB schema, auth, storage
• Implementation Plan → 50+ step build checklist
• Security Guidelines → Secure defaults from day one
This is the real secret to clean AI builds.
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5/ How I generate these fast
I used to create all these documents manually inside ChatGPT.
It worked, but it took a lot of time.
Now I use CodeGuideDev to speed things up.
It generates:
• Full project docs
• Rich system prompts for each file
• A quick editor to update things easily
• 1-click export ready for Cursor
It saves hours and cuts down 85 percent of hallucinations.
I used to create all these documents manually inside ChatGPT.
It worked, but it took a lot of time.
Now I use CodeGuideDev to speed things up.
It generates:
• Full project docs
• Rich system prompts for each file
• A quick editor to update things easily
• 1-click export ready for Cursor
It saves hours and cuts down 85 percent of hallucinations.
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6/ Load everything as Project Rules inside Cursor
Once your documents are ready:
• Create a /cursor/rules/ folder inside your project
• Drop all your planning docs there (PRD, App Flow, Tech Stack, etc.)
Cursor treats these as rules for coding and it reads them actively while coding, not just your last prompt.
This builds a real-time knowledge base for the AI and massively reduces errors while building.
Once your documents are ready:
• Create a /cursor/rules/ folder inside your project
• Drop all your planning docs there (PRD, App Flow, Tech Stack, etc.)
Cursor treats these as rules for coding and it reads them actively while coding, not just your last prompt.
This builds a real-time knowledge base for the AI and massively reduces errors while building.
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7/ Smart building inside Cursor
When you start:
• Enable Agent Mode
• Pick Gemini 2.5 pro or Sonnet 3.5/3.7 model
• Always reference your Implementation Plan
• Build feature-by-feature
• After each feature implementation do the following:
1. Test
2. Debug smartly (attach docs if needed)
3. Commit
Do not rush. Build clean.
When you start:
• Enable Agent Mode
• Pick Gemini 2.5 pro or Sonnet 3.5/3.7 model
• Always reference your Implementation Plan
• Build feature-by-feature
• After each feature implementation do the following:
1. Test
2. Debug smartly (attach docs if needed)
3. Commit
Do not rush. Build clean.
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8/ The real MVP loop
The real loop I follow:
• Plan deeply
• Load full context
• Implement one small feature
• Test
• Commit
• Repeat
No guesswork. No chaos.
Just steady, real progress.
The real loop I follow:
• Plan deeply
• Load full context
• Implement one small feature
• Test
• Commit
• Repeat
No guesswork. No chaos.
Just steady, real progress.
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9/ TLDR:
If you want to build real products with AI:
• Plan first
• Generate strong project docs
• Load them as Project Rules in Cursor
• Build with clear context, not random prompts
• Test everything.
• Commit after every feature
I use ChatGPT Voice, CodeGuideDev, and Cursor together.
This is how you vibe code without breaking things.
Bookmark this for your next build.
If you want to build real products with AI:
• Plan first
• Generate strong project docs
• Load them as Project Rules in Cursor
• Build with clear context, not random prompts
• Test everything.
• Commit after every feature
I use ChatGPT Voice, CodeGuideDev, and Cursor together.
This is how you vibe code without breaking things.
Bookmark this for your next build.
