Cj Z 🎯 Profile picture
Aug 24, 2022 16 tweets 9 min read Read on X
I’ve heard @NFT_GOD yesterday for the first time!

@GratefulApe_eth & @beast_eth hosted a super informative Twitter space.

If I sum up in one word, #Amazing!

* @NFT_GOD made some bold statements about NFT Space!

I'd like to share the main points with you:
🧵👇 Image
2/16
Abstract:

• Best Twitter Audience building strategy
• Sell shaming and how to tackle that
• Biggest mistake of NFT traders right now
• Best way to evaluate NFT projects
• How NFT space will look like in 5 years
• Will the #BAYC have historical value?
and much more...
3/16
- Best Twitter Growth Model

Quality over Quantity! Post twice a day but post best possible content.

Tweeting 40 times a day will burn you out and it won’t be much fun.

Keep posting best quality content and Twitter Algorithm will help you grow.

4/16
When you are under 1000 followers, it’s the best time!

You can do a lot of experiments to see what suits you the best.

Start with broad topics, then focus on what worked & what you like to say.

5/16
Authenticity is Everything!

People will detect from their sub conscious mind that if you are authentic or not, so talk about things that you know or passionate about.

6/16
We are in a good spot right now, the @amazon or other giant brands of Web3 are not built yet.

Grow an audience and you can do anything!

7/16
- Biggest mistake of NFT traders right now.

Biggest mistake people are making is chasing!

One project pumps and everyone on twitter will talk about it and some people will buy that & becomes liquidity exit.

Balancing your net worth is important.

8/16
Keep your life balanced.

Stop Dopamine hits!

Balancing is doing everything in a healthy way. Not too low & not too high on dopamine.

9/16
@NFT_GOD said the satisfaction he got by building an audience is same as winning good trades.

10/16
- Sell shaming

@NFT_GOD said he never felt guilty while trading stocks but he has to think about a lot of things before selling NFTs.

Keep emotions out of NFTs by treating them as an asset class.

Don’t be afraid of sell shaming. Take Profits!

11/16
- Best way to evaluate NFT projects.

Think of NFT projects as early-stage startups

Think like a VC and ask questions:
• What is different in this project?
• Team behind
• Track Record
• Plan

If you can’t find good answers, it’s just gambling!
12/16
- Is #BAYC going to have historical value or not?

@NFT_GOD said “I don’t think @BoredApeYC will have historical value like @cryptopunksnfts.

They messed up when they gone to video game (@OthersideMeta) route and odds of #BAYC to be successful is tough here"
13/16

- How NFT space will look like in 5 years

@NFT_GOD said “I don’t believe metaverse will happen in next 10 years. We don’t have the infrastructure for that right now”

After 5 Years we might see glimpses of Metaverse.
- Digital Assets
- Creator Economies
- Avatars
14/16
- What an average person wants from NFTs?

@NFT_GOD shared a story with his father that he couldn’t find the best pitch for his father till now, on how NFT Tech. will make his life easy.

Average person don’t care about #BAYC. The don’t want to spend 50k for that.
15/16
On-Boarding process should be easier and less risky.

NFT Tech. should go on background and product innovation should be the focus.

“No project has unique utility right now. Only Utility right now is Art and Historical value.”

16/16
End Remarks:

• Brilliant questions by @GratefulApe_eth & @beast_eth.

• Again, @NFT_GOD proved, he is different!

I appreciate his vision, unique perspective, and easy explanations.

NFT Tech has a bright future. Innovators worth gold in this space.

@cj_zZZz

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More from @cj_zZZz

Apr 10
I tested Gemini Pro 2.5 as my main coding model for 40+ hours.

Here're 2 documents that are working brilliantly well with Gemini.

"App flow document + App flowchart."

This made my Cursor workflow 10x better. Here's why it is working: ↓
Gemini Pro 2.5 has a 1 million token context window.

In simple terms it can scan upto 100,000 lines of code instantly to understand full codebase.

Claude & GPT models has 200k context window and that's why they struggle with large codebases.
But large context window doesn't mean Gemini doesn't hallucinate or assume things.

That issue is still there but I'm able to fix hallucinations by 95% in Gemini with my 'Context Boundary' technique.

You need to provide context with coding docs:
- PRD
- App flow doc
- Tech stack doc
etc

But here's how 2 docs are working really good with Gemini.Image
Read 7 tweets
Apr 8
Debugging is the most frustrating part of AI coding.

But it can be solved if you build a strong "wall of context" around AI models.

Here's how you can fix debugging in Cursor/Windsurf: ↓ Image
If you say "build me a spotify like app" and you expect AI to code the entire frontend and backend in 1 prompt. That's not possible.

AI models can output limited code in 1 request.

Also, AI models are not perfect they have 2 limitations:
1. AI hallucinations
2. Context window
So, first you need to provide deep context about your idea in the form of a context boundary around AI models.

To build this boundary, you need to turn your plain english idea into a set of coding docs:

1. Project Requirement Document (PRD)
2. App Flow Doc.
3. Tech Stack Doc.
4. Frontend Guidelines
5. Backend Structure

These 5 docs are your core docs. Let's expand them:Image
Read 11 tweets
Apr 6
Google's Gemini Pro 2.5 is the best AI coding model right now.

I use Gemini 2.5 + Sonnet 3.5 + GPT o1 models in my new coding workflow.

After using it for 20 hours, here're my finding: ↓ Image
I admit, Google has done a wonderful job this time with Gemini Pro 2.5 model.

They competed with Claude's Sonnet models for coding and the code quality is far better.

In new workflow I use:
- 80% of the time Gemini Pro 2.5
- 10% of the time Sonnet 3.5
- 10% of the time GPT o1
My findings after testing Gemini for 20+ hours:

1. Gemini is great for planning docs, understanding large codebases and one-shotting code snippets.

But there're some issues.

It struggles to understand the user's requests sometimes. (You need to be super clear) Image
Read 12 tweets
Apr 5
What is Vibe Coding?

Here's a complete Crash Course for you: 🧵 Image
2024 has changed coding forever.

It gave birth to AI coding models like Claude Sonnet 3.5, GPT 4o that can code better than junior devs.

We saw AI coding tools like Cursor, Windsurf, Bolt, Replit, Lovable etc built on top of AI coding models.

But..
The biggest change of all is that it made 'English' the largest coding language of all time.

Now anyone with an idea can code.

So people started coding landing pages, websites, web apps, mobile apps, browser extensions or even browsers.

Until recently this type of coding is given a name by @karpathy - Vibe Coding

"you forget about the code even exists...... Just see tuff, say stuff, run stuff and copy paste stuff, and it mostly works"Image
Read 12 tweets
Apr 4
Truth: AI coding models are good for code execution, but not good at planning.

If you let AI plan next step while coding, it will mess up the codebase.

You can solve this by attaching a detailed "Implementation Plan"

Here's how I create my plan: ↓
When you build production-grade applications, you need to sure about:
- What features you want in v1?
- What features are out-of-scope right now?
- How's your UI will look like?
- What tech stack are you using?

These are basic but core questions that AI tries to figure out itself if you don't provide context.
But here's the problem.

All the AI coding models have 1 core issue, that is "hallucinations"

In simple terms, AI models start to assume things on their own and mess up the code structure.

So if you don't hardwire your plan into AI, it'll make its own at every step.

That's a disaster.
Read 9 tweets
Mar 27
I built 36 projects in last 14 months, with AI code.

Today, I'm sharing my Coding Docs with you.

I use these 7-docs in Cursor/Windsurf to build a knowledge base for AI models.

Bookmark this post so you can copy the templates. ↓

1. Project Requirements Document (PRD)
These docs form a "knowledge base" for AI coding models so AI models car refer to them at any moment.

This Technique minimizes AI assumptions and hallucinations by 85-90%.

Here're other core docs that I attach:

2. App flow document
This docs is works like Google map for AI.
3. Tech stack document

This document lists all the technologies, dependencies, packages and APIs I use in the project.

This provides the technical framework to AI coding models.
Read 10 tweets

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