Khizer Abbas

For brand collabs: khizer@joinsuperhuman.io

Hi, I’m Khizer.

TL;DR:
I help you stay ahead of AI and show you how to actually use it at work.
I’m Head of Marketing at Superhuman AI, the world’s biggest AI newsletter, where I took the newsletter from 150k to 1M+ readers.
On LinkedIn, I share AI tools, tutorials, and real-world use cases to help you work smarter.

Longer version (for the curious ones):
I’m the Head of Marketing at Superhuman AI, the largest AI newsletter on the internet. When I joined, we had 150,000 readers, now we’re at over 1 million and still growing.

My mission is simple: help you stay ahead in AI.

Every week, I share:
→ Practical AI tools & how to use them
→ AI tutorials & workflow breakdowns
→ Real use cases for professionals
→ Tips on automating tasks & making better decisions with AI

Beyond Superhuman, I’ve scaled multiple newsletters across different niches, from personal growth to SaaS, with subscriber bases ranging from 500K to over 2M.

I’ve spent $10M+ running paid ads (mostly Meta) across media, eCommerce, and lead gen, and I specialize in newsletter growth.

If you’re building a newsletter, or want to work smarter with AI, not just read about it, you’ll like what I share.

And if you’re a brand looking to get in front of thousands of people actively exploring AI, I also collaborate. Hit me up.

Head of Paid Acquisition

Helping grow the world's biggest AI newsletter through Paid Ads.

Microsoft literally dropped the best free Gen AI course.

Here are all the courses with links:

Before we begin, my team researches for hours and shares the best prompts and tutorials on how to use AI at work. 
Join 1M+ professionals here:
https://lnkd.in/eZ7QMnpD


00 – Course Setup
Learn: How to Setup Your Development Environment
https://lnkd.in/du5cFnSC

01 – Introduction to Generative AI and LLMs
Learn: Understanding what Generative AI is and how Large Language Models (LLMs) work.
https://lnkd.in/dPSzr2CT

02 – Exploring and comparing different LLMs
Learn: How to select the right model for your use case
https://lnkd.in/dkafWHZt

03 – Using Generative AI Responsibly
Learn: How to build Generative AI Applications responsibly
https://lnkd.in/dUceTrBn

04 – Understanding Prompt Engineering Fundamentals
Learn: Hands-on Prompt Engineering Best Practices
https://lnkd.in/dsTgJ33T

05 – Creating Advanced Prompts
Learn: How to apply prompt engineering techniques that improve the outcome of your prompts.
https://lnkd.in/dzdRD2DE

06 – Building Text Generation Applications
Build: A text generation app using Azure OpenAI / OpenAI API
https://lnkd.in/dszEqXhS

07 – Building Chat Applications
Build: Techniques for efficiently building and integrating chat applications.
https://lnkd.in/d62eCmXd

08 – Building Search Apps with Vector Databases
Build: A search application that uses Embeddings to search for data.
https://lnkd.in/dfjNnnkU

09 – Building Image Generation Applications
Build: An image generation application
https://lnkd.in/dGz3qAKu

10 – Building Low-Code AI Applications
Build: A Generative AI application using Low Code tools
https://lnkd.in/davKKzfx

Repost this to help others in your network.

Growing newsletter with Paid Ads | 2M+ subs driven | Follow to learn about AI

Claude Code will probably make 50,000 people millionaires. If not more.

Not because it's magic.

But because most developers won't bother learning it properly.

They'll try it once. Hit a wall. Move on.

Meanwhile, the ones who actually master it are shipping products in days that used to take months.

My team has put together every resource you need to get dangerous with Claude Code:

> 4 comprehensive courses 
> 7 battle-tested GitHub repos 
> 6 YouTube tutorials from builders actually using it 
> 6 creators worth following 
> 6 newsletters to stay sharp

This isn't theory. It's the exact stack people are using to build real products right now.

The gap between "I've heard of Claude Code" and "I ship with Claude Code" is about 2 weeks of focused learning.

Most won't put in the work.
That's your edge.

EDIT: You can get your Claude Code Resources + 5 more resources on AI Agents here - 

https://lnkd.in/dYFtfK6U

My engineering team just compiled everything we've learned building and shipping 60+ AI Agents to production.

Zero to Production Guide for AI Engineers (normally $500, free for my network)

What's inside:
Chapter 1: Understanding AI Agents fundamentals
Chapter 2: Popular frameworks comparison
Chapter 3: Specialized frameworks & protocols
Chapter 4: Step-by-step tutorial
Chapter 5: Hosting & deployment
Chapter 6: Security & compliance
Chapter 7: Advanced topics
Chapter 8: Your roadmap


Comment "Guide" or DM me - you'll get the link within 48 hours.

P.S. I've shared 100+ such tutorials here: https://lnkd.in/dYFtfK6U

I think developers who don't use Claude Code are falling behind.

Here's everything you need to get started:

📰 Newsletters: 

THE CODE 🔗 https://lnkd.in/dYFtfK6U

Every 🔗 https://lnkd.in/dVz9zafv 

JP 🔗 https://lnkd.in/d48UYbzZ 

Joe Njenga 🔗 https://lnkd.in/diYv-GuA 

Why Senior Engineers Who Master Claude Code Will Leave Their Competition Behind🔗 https://lnkd.in/dNQviZNA 

A Guide to Claude Code 2.0 and getting better at using coding agents 🔗 https://lnkd.in/dpbgawUQ

🎓 Long Courses:

Claude Code: A Highly Agentic Coding Assistant🔗 https://lnkd.in/dF6XyF4w 

Claude Code in Action 🔗 https://lnkd.in/dCgmg2va 

Claude Code for Everyone 🔗 https://lnkd.in/dXQ5U9d8 

Claude Code: Software Engineering with AI Agents🔗 https://lnkd.in/dj5KPMUd 

📦 Github Repos:

Claude-code-cheat-sheet 🔗 https://lnkd.in/dhW5b8eB 

Claude-code-template 🔗 https://lnkd.in/dgmqrp5y 

Awesome-claude-skills 🔗 https://lnkd.in/dxUMKSPR 

Awesome-claude-code-subagents 🔗 https://lnkd.in/dwabN-VX 

Awesome-mcp-servers 🔗 https://lnkd.in/dfqS3ZRp 

Claude-code-workflows 🔗 https://lnkd.in/dS7QFU4V 

Vibe-coding-playbook 🔗 https://lnkd.in/d3xqXDZr 

📹 Youtube Tutorials:

Claude Code Setup and Installation 🔗 https://lnkd.in/dhK5tKNy 

Claude Code is crazy good in 2026 🔗 https://lnkd.in/daXHQrWj 

My Claude Code Workflow for 2026 🔗 https://lnkd.in/dVPdn3G6 

Claude Code Skills: Automate Everything You Do🔗 https://lnkd.in/d7ah3v6C 

Build with Multiple AI Agents using Claude Code 🔗 https://lnkd.in/d-ez3kAH 

Build an AI Life Co-Pilot with Claude Code 🔗 https://lnkd.in/dxZ3BFaZ 

👥 Creators to Follow:

Ray Amjad 🔗 https://lnkd.in/dGpuZEBD 

Joe Njenga 🔗 https://lnkd.in/dWjU-rw8 

Daniel Avila 🔗 https://lnkd.in/dErqFxDx 

Alex Finn 🔗 https://lnkd.in/dhnN8arU 

Thariq 🔗 https://x.com/trq212 

Boris Cherny 🔗 https://x.com/bcherny 

Check out my profile for more such resources 👋

Claude Skills can make your AI-generated code more accurate.

Here's a collection of skills that you can just copy paste:

P.S. You can get more such resources on a bi-weekly basis here:
https://lnkd.in/dYFtfK6U

🔹 BACKEND SKILLS

Backend Development Guide https://lnkd.in/dq78M5aU

Web Backend Debugger https://lnkd.in/dtPe8KZp

Backend Migration Standards https://lnkd.in/ddFrC5jV

NestJS Expert https://lnkd.in/dFcCyFA2

Async Python Patterns https://lnkd.in/d4JFvRyU

Python Packaging https://lnkd.in/dsnqBikk

🔹 FRONTEND SKILLS

Frontend Design (Official) https://lnkd.in/dn44MSQh

Frontend Design Pro https://lnkd.in/dE37gXNC

Frontend Engineer https://lnkd.in/dQTYMExc

Frontend Designer https://lnkd.in/dMeRVGU2

Frontend Technologies https://lnkd.in/d3FuJrQj

React Expert https://lnkd.in/dDQ2sxQR

React Context Setup https://lnkd.in/dMfuTujb

Svelte Expert https://lnkd.in/dqFCdrQm

🔹 WEB DEVELOPMENT SKILLS

Next.js + shadcn/ui Builder https://lnkd.in/dWB8NHVY

Web Application Testing https://lnkd.in/dKiv-Wtc

Accessibility Testing https://lnkd.in/dNCpvf7T

React Native Expert https://lnkd.in/dSCiP49B

CI/CD Pipeline Setup https://lnkd.in/dJwghjRr

Payload CMS https://lnkd.in/dQxaNGJ3

Check the comments for the AI, Machine Learning, and Data skills:

If you’re serious about AI agents in 2026, this is the roadmap I share with engineers.

Here's everything you need to get start with it:

My team built 75+ AI agents and shares such tutorials and resources here:
https://lnkd.in/dYFtfK6U)

Level 1: Gen AI and RAG Foundations

1. Introduction to Generative AI
- Generative AI for Everyone by Andrew Ng by DeepLearning.AI
- https://lnkd.in/d2XCRaAw

2. Basics of Large Language Models (LLMs)
- H2O ai Large Language Models (LLMs) - Level 1 by Coursera and H2O.ai
- https://lnkd.in/due32aSn

3. Fundamentals of Prompt Engineering
- ChatGPT Prompt Engineering for Developers by DeepLearning.AI & OpenAI
- https://lnkd.in/drfVMsme

4. Data Handling and Processing
- Preprocessing Unstructured Data for LLM Apps by DeepLearning.AI & Unstructured
- https://lnkd.in/dWDyqeyg

5. Introduction to API Wrappers
- Getting Started with Generative AI API Specialization by Coursera & Codio
- https://lnkd.in/dKiQD5EV

6. Essentials of RAG
- Introduction to Retrieval Augmented Generation (RAG) by Coursera
- https://lnkd.in/ddmbeMy7

Level 2: AI Agents Specialization

1. Introduction to AI Agents
- Fundamentals of AI Agents Using RAG and LangChain by Coursera & IBM
- https://lnkd.in/dxgD2jFN

2. Exploring Agent Frameworks
- LangChain for LLM Application Development by DeepLearning.AI & LangChain
- https://lnkd.in/dCEw5_9M

3. Building a Simple AI Agent
- Build Autonomous AI Agents From Scratch With Python by Udemy
- https://lnkd.in/dss98f3C

4. Understanding Agent Workflows
- AI Agentic Design Patterns with AutoGen by Coursera & Microsoft
- https://lnkd.in/de9GBUqz

5. Learning About Agent Memory
- LLMs as Operating Systems: Agent Memory by DeepLearning.AI & Letta
- https://lnkd.in/dmMt6mSj

6. Evaluating Agent Performance
- Building Intelligent Troubleshooting Agents by Coursera & Microsoft
- https://lnkd.in/dnUhYZ7Y

7. Collaborating with Multiple Agents
- Multi AI Agent Systems with crewAI by DeepLearning.AI & CrewAI
- https://lnkd.in/dTudrD55

8. Implementing RAG in Agents
- Building & Evaluating Advanced RAG Apps by DeepLearning.AI, LlamaIndex & TruEra
- https://lnkd.in/dyMg8eV9

Follow me if you're building AI Agents 👋

If you're an AI Engineer or want to get into it, these are your weapons.

My team shares such tutorials and resources here:
https://lnkd.in/dYFtfK6U

This roadmap takes you from basics to building real AI systems:

1️⃣ Foundation Phase:

Microsoft ML Beginners

https://lnkd.in/dDtXCcRd

- 12 week curriculum
- Real world datasets
- Hands on projects

Microsoft AI Beginners

https://lnkd.in/d_7amH7G

- Neural networks basics
- Computer vision fundamentals
- Built with PyTorch

Karpathy Neural Networks

https://lnkd.in/dvW24stk

- Build from scratch
- Modern deep learning
- GPT architecture explained

---

2️⃣ Deep Dive Phase:

Deep Learning Papers

https://lnkd.in/dPkpvxTj

- 60 plus implementations
- Transformers and GANs
- Production ready code

Made With ML

https://lnkd.in/dRWvUnv8

- Notebooks to production
- MLOps best practices
- Deploy real systems

---

3️⃣ LLM Specialization:

Hands on LLMs

https://lnkd.in/dn5eSBv9

- Tokenization to deployment
- Fine tuning techniques
- RAG systems explained

Advanced RAG Techniques

https://lnkd.in/dQwddMsv

- 30 plus methods
- Speed and accuracy
- HyDE and GraphRAG

---

4️⃣ Agent Building:

Microsoft AI Agents

https://lnkd.in/dn4BJPGH

- AutoGen framework basics
- Build intelligent agents
- Beginner friendly course

Agents to Production

https://lnkd.in/duZbAzUJ

- Memory and orchestration
- Security and deployment
- Real world playbook

AI Engineering Hub

https://lnkd.in/dcfcZZ58

- 70 plus projects
- Ready to ship
- Real world examples

Python knowledge assumed.

This roadmap gets you building 
production AI systems.

Bookmark for later.

Agentic AI is exploding, but most people are learning it backwards.

Here's the strategic roadmap that actually builds expertise step-by-step:

My team built 75+ AI agents and shares such tutorials and resources here:
https://lnkd.in/dYFtfK6U)

Introduction to Agentic AI➣AI systems with autonomous decision-making capabilities
➣Key differences between traditional AI and intelligent agents
➣Core agent functions: perception, reasoning, and action
➣Business applications in workflow automation


Fundamentals of AI & ML➣Supervised and unsupervised learning methodologies
➣Deep learning and neural network architectures
➣Reinforcement learning for autonomous agents
➣Gradient descent and model optimization techniques


Programming & AI Frameworks➣Python libraries for building AI agents
➣API integration for function calling capabilities
➣LangChain, AutoGen, and CrewAI frameworks
➣Data handling and model orchestration patterns


Large Language Models (LLMs)➣Transformer-based architecture fundamentals
➣Tokenization and embedding techniques for NLP
➣Context management and memory limitations
➣Fine-tuning and prompt engineering strategies


Understanding AI Agents➣Agent architecture types and design patterns
➣Multi-agent collaboration and coordination workflows
➣Decision-making processes and reasoning chains
➣Task-oriented versus goal-oriented agent approaches


AI Memory & Knowledge Systems➣Short-term versus long-term memory management
➣Vector databases for knowledge storage and retrieval
➣Retrieval-augmented generation (RAG) implementation
➣Semantic search optimization and document processing


Decision-Making & Planning➣Autonomous goal formulation and execution strategies
➣Multi-agent problem-solving coordination
➣Hierarchical planning for complex agent tasks
➣Self-directed learning through feedback mechanisms


Advanced Learning & Adaptation➣Reinforcement learning with human feedback integration
➣Dynamic prompt optimization and control mechanisms
➣Instruction tuning for specialized task performance
➣Continuous improvement through reward-based training


Deploying AI Agents➣Cloud-based scaling for AI agent applications
➣Model deployment through API architectures
➣Performance optimization for low-latency responses
➣Monitoring systems and maintenance protocols


Real-World Applications➣Business process automation with intelligent agents
➣Autonomous research and data analysis systems
➣Workflow enhancement through smart agent integration
➣Decision support systems for executives


Check out comments for resources.

Repost this to help others in your network.

Damn — the founder of Claude Code just dropped his entire workflow.

His 13-step system is worth trying: 

Before we begin my team has built an ultimate Claude Code guide that can help you ship 10X faster. 

Get it here:
https://lnkd.in/dYFtfK6U

1/ Parallel Terminal Sessions 

He runs 5 Claudes simultaneously in his terminal. Tabs numbered 1-5. System notifications alert him when any Claude needs input. While one waits, he's working with another.

2/ Web + Mobile Parallelization 

On top of local sessions, he runs 5-10 more Claudes on claude .ai/code. He hands off local sessions to web using &, teleports back and forth with --teleport, and even kicks off sessions from his phone each morning to check in later.

3/ Model Choice: Opus 4.5 with Thinking Always

Yes, it's bigger and slower than Sonnet. But you steer it less and it handles tools better — making it faster in practice. Less babysitting, more shipping.

4/ Shared CLAUDE md 

The entire team shares a single CLAUDE md file, checked into git. Every time Claude does something wrong, they document it. Claude learns from collective mistakes. Compounding knowledge.

5/ GitHub Integration with @claude 

During code review, he tags @claude on PRs to update CLAUDE. md automatically. Uses the Claude Code GitHub action (/install-github-action). Their version of Compounding Engineering.

6/ Plan Mode First Most sessions start in Plan mode (shift+tab twice). 

He iterates back and forth until the plan is solid. Then switches to auto-accept edits mode and Claude usually one-shots the execution. A good plan is everything.

7/ Slash Commands for Inner Loops 

Every workflow he repeats multiple times a day becomes a slash command. Checked into git at .claude/commands/. His /commit-push-pr runs dozens of times daily. Saves prompting. Claude can use them too.

8/ Subagents for Common Workflows 

He uses dedicated subagents: code-simplifier cleans up after Claude finishes, verify-app has detailed testing instructions, code-architect for design decisions. Stored in .claude/agents/. Automation for the 80% of PR work.

9/ PostToolUse Hooks for Formatting 

A hook auto-formats Claude's code after every edit. Claude usually gets it 90% right — the hook catches the last 10% before CI complains later.

10/ Smart Permissions (Not --dangerously-skip-permissions) 

Instead of skipping all permissions, he uses /permissions to pre-allow specific safe commands. Checked into .claude/settings. json and shared with the team. Security without friction.

Continued in comments...

A highly motivated and experienced individual in leading teams and managing businesses. Skilled in Excel, G-Suite and SQL and a strong emphasis on data-driven decision-making. Proven ability to collect, analyze and interpret data for process improvement and cost efficiency.

taplio

The Battle

Khizer Abbas

Naushad Lalani

Followers

Posts

Engagements

Likes

Performance ScoreKhizer Abbas's LinkedIn Performance

Ready to grow your LinkedIn presence?

taplio

The Battle

Khizer Abbas

Naushad Lalani

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Khizer Abbas's LinkedIn Performance

Ready to grow your LinkedIn presence?

Performance ScoreKhizer Abbas's LinkedIn Performance