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CJ Zafir Profile picture
@cjzafir
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 @cjzafir

CJ Zafir Profile picture
Aug 16
Introducing Codespace

A virtual computer that runs custom Claude Code on server.

It is using 2 models: Kimi K2 + Claude Sonnet 4 in a sync.

I achieved same code quality with 2x better reasoning and 53% less model cost.

Access it today @CodeGuidedev
(500 credits for everyone)
We fixed some core issues:
1. It works with new and existing codebases and it won’t touch your existing code.

It can scan large codebases, 10M tokens (250,000 lines of code) and remember all core details.

Just attach your GitHub Account and select the repo you want to work on. Image
Image
2. It works autonomously (you don’t need to hit accept all) everytime.

It generates 7 docs to build a solid knowledge base to refer and create detailed tasks/sub-tasks list on autopilot.

Resulting in 88% less hallucinations and better code structure. Image
Read 8 tweets
CJ Zafir Profile picture
Aug 14
Every AI startup is focused on "Build me an ........... app" (New projects)

But what about millions of existing codebases on GitHub with billions of lines of code?

To focus on existing codebases, I built a coding environment: Codespace.

(Explained below)
Simple Steps:
1. Connect your GitHub Account
2. Open Codespace and select the repo you want to work on. (AI agent will make an isolated environment for every request)
3. Let AI agent Analyze, generate docs and tasks list
4. analyze the kanban board to track tasks
5. Go have coffee and wait for the agent to email you when done.
I built a Claude Code wrapper that:
- runs on cloud (access it with phone, or laptop)
- can analyze upto 10M token size codebases
- has better visual UI & flow
- generate docs (knowledge base)
- tasks/sub-task list (2x better than claude)
- notifies me when its done via email
Read 5 tweets
CJ Zafir Profile picture
Jun 27
I built "Clade Tasks" to make Claude Code 10x better and 2x cheaper.

I integrated 3 engines in 1 flow:

1. Claude Code (best agentic coding interface)
2. CodeGuide (to provide deep context to AI)
3. Taskmaster (to create detailed implementation plan)

Here's how it works: ↓
Claude Code is the most powerful AI coding tool right now.

Yes better than Cursor/windsurf.

But Claude 4 (the underlying model) can spit out unnecessary files/code and burn tokens.

Also it's plan mode is good but I found a better alternative: ↓
1. Plan before code

"Build me x, y, z." type prompts don't work because of no technical context.

So turn your idea into a set of well structured docs:
- PRD
- Tech stack doc.
- App flow doc
- UI guidelines
- backend structure
etc

@CodeGuidedev write these docs in only 3 steps Image
Read 7 tweets
CJ Zafir Profile picture
Jun 15
The most important document in AI coding: PRD
(Project Requirements Document)

It serves like a blueprint & explains:
- project's overview
- tech stack
- user flow
- core features
- ui details
- backend schema
- security guidelines
- regulations

Here's how you can create PRDs:
Before you create a PRD, brainstorm with ChatGPT voice.

This step will help you finalize what features you want in your version 1.

In the end ask ChatGPT: "now add all approved features in one document and create a detailed draft)

Now it's time to create a PRD.
I use @CodeGuidedev to create all my coding docs including PRD

It uses 03 + 04-mini + Sonnet 4 model to create extensive set of docs

Flow is simple

Step 1: Open "New Project" and paste the feature draft in the input field

Step 2: Now select AI tools & AI models you'll use
Read 8 tweets
CJ Zafir Profile picture
Apr 18
What are AI Agents?

OpenAI just published 30-page guide on AI agents.

I explained the guide in 10 points. Bookmark this: Image
1. Agents ≠ basic workflows

A normal “workflow” just runs a fixed list of steps with an LLM; it doesn’t think for itself.

On the other hand, Agents are systems that independently accomplish tasks on your behalf.

Workflows are linear. Agents are dynamic & autonomous. Image
2. Use agents for the complex jobs

Agents handle changing rules, tricky choices, and unstructured data better than any fixed script.

Pick jobs that need judgment, change a lot, or rely on messy text, images, or PDFs. Image
Read 12 tweets
CJ Zafir Profile picture
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

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