Simo

[Ruben Hassid @rubenhassid]

People think learning Claude takes days. It doesn't.

I wrote 17 free guides that teach it in hours:

Claude 101: https://t.co/QQDmzBAoH5
Claude Code: https://t.co/o782qegoKu
Claude Skills: https://t.co/RgQUCNMqzQ
Claude Connectors: https://t.co/cSPMBUNmRG
Claude for Excel: https://t.co/ZgmUFXd0Iw
How to Prompt: https://t.co/Sw2tg2PMMc
Claude Certificates: https://t.co/LyV7fegv4c
Claude for your team: https://t.co/NakViTGCAL
Stop Prompting Claude: https://t.co/45xPLDRB6Y
AI Slides (PPT in 2026): https://t.co/OY7cHDTV7l
Claude Design: https://t.co/FhlRSlH0aD
Set up Claude Cowork: https://t.co/4jygw4M1RO
Claude to sound like you: https://t.co/LyV7fegv4c
Stop writing like AI: https://t.co/JXKAVP6hdS
Claude as your computer: https://t.co/tQDrcs8drQ
Claude Cowork + Project: https://t.co/xU97EpdrEe
Stop hitting Claude limits: https://t.co/Yu24rPQafQ

___

1. Save this list for later (three dots, top right).
2. Share it with a friend by ♻️ reposting this image.
3. Subscribe to my free newsletter: https://t.co/psB7XxAv8w.

[Khusboo Tayal @KhusbooT14835]

Stop wasting hours trying to learn AI.

I have already done it for you.

With one list. Zero confusion. And no fluff.

📹 Videos:

1. LLM Introduction: https://t.co/ZQ8cRyxQMc
2. LLMs from Scratch: https://t.co/5cXkoFoBq9
3. Agentic AI Overview (Stanford): https://t.co/r01WVP63IU
4. Building and Evaluating Agents: https://t.co/RZ5iwNFB74
5. Building Effective Agents: https://t.co/EAbyGtJP7R
6. Building Agents with MCP: https://t.co/qGaa6HZs4E
7. Building an Agent from Scratch: https://t.co/XYAHtweAj6
8. Philo Agents: https://t.co/5X7RLCrqqP

🗂️ Repos

1. GenAI Agents: https://t.co/T7OI3lEMiD
2. Microsoft's AI Agents for Beginners: https://t.co/RoczPeg6bB
3. Prompt Engineering Guide: https://t.co/uFeOxKoho7
4. Hands-On Large Language Models: https://t.co/hilw0TI9sz
5. AI Agents for Beginners: https://t.co/RoczPeg6bB
6. GenAI Agents: https://t.co/WJP36aCtuH
7. Made with ML: https://t.co/Ot2SInu7u2
8. Hands-On AI Engineering: https://t.co/KPPoOdAGb5
9. Awesome Generative AI Guide: https://t.co/OAjaVMQ5bv
10. Designing Machine Learning Systems: https://t.co/UmDjhU7BSf
11. Machine Learning for Beginners from Microsoft: https://t.co/Ha786iUXh0
12. LLM Course: https://t.co/N3WFR450VV

🗺️ Guides

1. Google's Agent Whitepaper: https://t.co/w1fNlFJf1d
2. Google's Agent Companion: https://t.co/FWJhygskx1
3. Building Effective Agents by Anthropic: https://t.co/F6QUm85KdJ
4. Claude Code Best Agentic Coding practices: https://t.co/FTog5jzXOw
5. OpenAI's Practical Guide to Building Agents: https://t.co/7fWN9gHJeg

📚 Books:

1. Understanding Deep Learning: https://t.co/vPcK7qWEXn
2. Building an LLM from Scratch: https://t.co/UJ6AeTKFpT
3. The LLM Engineering Handbook: https://t.co/3GahjRThX3
4. AI Agents: The Definitive Guide - Nicole Koenigstein: https://t.co/5IlsaOESBJ
5. Building Applications with AI Agents - Michael Albada: https://t.co/GbBDeqvsJ4
6. AI Agents with MCP - Kyle Stratis: https://t.co/qqyRrEZGZS
7. AI Engineering: https://t.co/HjfZgWGkzR

📜 Papers

1. ReAct: https://t.co/x2wv54Jcf9
2. Generative Agents: https://t.co/QYawZJcsg0
3. Toolformer: https://t.co/KrqTr7p5lM
4. Chain-of-Thought Prompting: https://t.co/RgMA887Thm

🧑🏫 Courses:

1. HuggingFace's Agent Course: https://t.co/CWVB0m0Z8d
2. MCP with Anthropic: https://t.co/j7yEn5ImAc
3. Building Vector Databases with Pinecone: https://t.co/0uG5JElJPF
4. Vector Databases from Embeddings to Apps: https://t.co/NP8ZO8JOW4
5. Agent Memory: https://t.co/hsXvMifen0

Follow @KhusbooT14835 for more!!

👇 Comment “AI” for more resources

Repost for your network ♻️

Bookmark for future.

[Alif Hossain @alifcoder]

People are quietly making $5k–$20k/month with Claude.

Not by being smarter. By using better prompts.

📘 The Ultimate Claude Prompt Handbook — 1,500+ proven prompts for freelancing, content, copywriting, digital products, and online income. Plug and profit.

Normally $179 → FREE for 48 hrs.

Like + RT + comment 'Handbook' and I'll DM it.

Follow me so the DM goes through.

[ZARA @HeyZaraKhan]

100 Claude Repos that will completely change your life:
(save this)

1. Terminal AI coding agent https://t.co/gkTwIb7T9s
2. Ready-to-use starter apps https://t.co/PtEclReNCv
3. Official agent skills https://t.co/1RZ7lpP3xB
4. Plugin marketplace https://t.co/GVeknTu56n
5. Full ecosystem https://t.co/HOkmGrvrvL
6. Master list https://t.co/BVrGRmcQdV
7. 1000+ plugins https://t.co/8lzXVbeps2
8. Huge skills library https://t.co/wnArbr7a7N
9. Curated skills https://t.co/apIhhs1UEG
10. Cross-platform skills https://t.co/7wcdPfFLSh
11. LLM pipelines https://t.co/iqzPWyUrXk
12. Agent workflows https://t.co/bXPebvjN4v
13. Multi-agent systems https://t.co/o6NGMPl9h7
14. Team-based agents https://t.co/Ay1jn8wFpZ
15. AI dev team https://t.co/IXZNK0ym7r
16. Code agents https://t.co/Uq0aHekO6Y
17. Auto PR fixes https://t.co/zbCEAnFHlD
18. AI coding assistant https://t.co/rAeiD6uphU
19. Code search https://t.co/gDIpT7KMs3
20. Agent standards https://t.co/S6YyQF6v8v
21. Productivity plugins https://t.co/xOowIKylVb
22. AI SDK https://t.co/eIYxaxaDLm
23. Memory layer https://t.co/mXiinRZafi
24. Voice agents https://t.co/mWSwV3YifX
25. Deploy agents https://t.co/NtTWJdcqx4
26. Web agents https://t.co/b8HiXRrI7G
27. Reasoning agents https://t.co/fMvI18BxYn
28. Long-term memory https://t.co/sJK9vrePQI
29. AI apps infra https://t.co/RYXlG8O4xD
30. API layer https://t.co/i7JfKyvYy1
31. Clean UI https://t.co/vqyN30JVso
32. Self-hosted UI https://t.co/mi8adckJBZ
33. Modern UI https://t.co/auzUkeggzf
34. Desktop app https://t.co/8yK33a3izg
35. Next.js clone https://t.co/9zpY0oN5Qv
36. Template https://t.co/2kkhJIIafG
37. Claude-ready UI https://t.co/yoaCZQco7W
38. Minimal UI https://t.co/dh9HOubWu8
39. Lightweight UI https://t.co/lr4f3N8CKv
40. Adaptable UI https://t.co/f6ekpq25Ik
👇

[Rishi @RishiUvaach]

You're building AI agents without a system. That's why they keep failing.

Here’s the right system to go from idea → working agent

1. Define the job
What problem are you solving?
Who’s the user? What does success look like?

2. Design the brain
Clear system prompt, role, instructions, guardrails
(This is where most agents fail)

3. Pick the right model
Speed vs cost vs intelligence
Don’t overpay for simple tasks

4. Add tools
APIs, databases, MCP servers, custom functions
Agents become powerful when they can act, not just answer

5. Give it memory
Short-term + long-term context
So it learns, adapts, and improves over time

6. Orchestrate everything
Workflows, triggers, retries, agent-to-agent communication

7. Build the interface
Chat, app, API, Slack bot
Make it usable, not just functional

8. Test + improve
Evals, latency checks, real-world feedback
Iteration is the real moat

[Rohit @ai_rohitt]

Claude just dropped 13 free AI courses (with certificates).

No $500 course needed.

No “guru” required.

Just real skills, straight from Anthropic.

Here’s the full list:

1. Claude 101
https://t.co/9bQ7NlWwmL

2. AI Fluency: Frameworks & Foundations
https://t.co/2H6Wr4eOWN

3. Introduction to Agent Skills
https://t.co/qozyrdLwyV

4. Building with the Claude API
https://t.co/60bwB2FFQ0

5. Claude Code in Action
https://t.co/88VdISzLIi

6. Introduction to Model Context Protocol
https://t.co/EQrdwEQZdQ

7. MCP: Advanced Topics
https://t.co/3pDv4Bpdgk

8. AI Fluency for Students
https://t.co/nLWu1PbxVa

9. AI Fluency for Educators
https://t.co/kRz3G2gMOp

10. Teaching AI Fluency
https://t.co/8MLctE9O4L

11. AI Fluency for Nonprofits
https://t.co/qGuWQiV5lI

12. Claude with Amazon Bedrock
https://t.co/HCPSbQ72nv

13. Claude with Google Vertex AI
https://t.co/0NKyFoZ1a6

If you go through even half of these, you’ll be ahead of 95% of people using AI.

Most people won’t.

Because they’re still watching random YouTube videos, buying overpriced courses, or “learning AI” without actually building.

Don’t be that person.

Do this instead:

1. Bookmark this post (you’ll come back)
2. Pick 1 course and start today
3. Share it with someone who needs this

👇Comment "Course" for more resources.

Free. Practical. No excuses.

[Ruben Hassid @rubenhassid]

Instead of watching Netflix tonight.

Spend a day mastering Claude here: https://t.co/Vn60ElPZ2i

→ Level 1 - 24 min: The basics.

Claude For Dummies: https://t.co/HNa5MrCLVU
Claude Setup: https://t.co/jw2qdIcjnh

→ Level 2 - 1 hour: Real workflows.

Claude Cowork: https://t.co/uWTpOI3Woc
Claude for teams: https://t.co/qxlcqhf8bM
Claude Design: https://t.co/ZY8Fg5D2ea
Cowork + Projects: https://t.co/Q7AN9CZAbO
Claude for slides: https://t.co/L0bPMgXci6
Claude Skills: https://t.co/6cHYYfjXEA

→ Level 3 - 3.5 hours: The pro moves.

Avoid sycophancy: https://t.co/5i8xSJBGUl
Claude Code: https://t.co/UgE9xBXVbE
Claude 101: https://t.co/OvBmlvnVqL
Stop hitting Claude limits: https://t.co/j5fEzSH5br
Stop Prompting: https://t.co/j1LATSJiat

→ Level 4 - 8 hours: Expert mode.

Claude Computer: https://t.co/TxYuHPjgbV
Build with Claude API: https://t.co/RcCbfNjlzz

Pro tip: Don't binge it. Do one level per sitting.

Actually apply each guide before moving to the next

[Vishakha Singhal @vishisinghal_]

Most people think using Claude Code is about writing better prompts.

It’s not.

The real unlock is structuring your repository so Claude can think like an engineer.

If your repo is messy, Claude behaves like a chatbot.

If your repo is structured, Claude behaves like a developer living inside your codebase.

Your project only needs 4 things:

• the why → what the system does
• the map → where things live
• the rules → what’s allowed / forbidden
• the workflows → how work gets done

I call this:

The Anatomy of a Claude Code Project 👇

━━━━━━━━━━━━━━━

1️⃣ CLAUDE.md = Repo Memory (Keep it Short)

This file is the north star for Claude.

Not a massive document.

Just three things:

• Purpose → why the system exists
• Repo map → how the project is structured
• Rules + commands → how Claude should operate

If CLAUDE.md becomes too long, the model starts missing critical signals.

Clarity beats size.

━━━━━━━━━━━━━━━

2️⃣ .claude/skills/ = Reusable Expert Modes

Stop repeating instructions in prompts.

Turn common workflows into reusable skills.

Examples:

• code review checklist
• refactoring playbook
• debugging workflow
• release procedures

Now Claude can switch into specialized modes instantly.

Result:

More consistent outputs across sessions and teammates.

━━━━━━━━━━━━━━━

3️⃣ .claude/hooks/ = Guardrails

Models forget.

Hooks don’t.

Use hooks for things that must always happen automatically.

Examples:

• run formatters after edits
• trigger tests after core changes
• block sensitive directories (auth, billing, migrations)

Hooks turn AI workflows into reliable engineering systems.

━━━━━━━━━━━━━━━

4️⃣ docs/ = Progressive Context

Don’t overload prompts with information.

Instead, let Claude navigate your documentation.

Examples:

• architecture overview
• ADRs (engineering decisions)
• operational runbooks

Claude doesn’t need everything in memory.

It just needs to know where truth lives.

━━━━━━━━━━━━━━━

5️⃣ Local CLAUDE.md for Critical Modules

Some areas of your system have hidden complexity.

Add local context files there.

Example:

src/auth/CLAUDE.md
src/persistence/CLAUDE.md
infra/CLAUDE.md

Now Claude understands the danger zones exactly when it works in them.

This dramatically reduces mistakes.

━━━━━━━━━━━━━━━

Here’s the shift most people miss:

Prompting is temporary.

Structure is permanent.

Once your repository is designed for AI:

Claude stops acting like a chatbot...

…and starts behaving like a project-native engineer. 🚀

[Hunter Kallay @lazukars]

🚨BREAKING: You can now run Claude Code for FREE.

No API costs. No rate limits. 100% local on your machine.

Here's how to run Claude Code locally (100% free & fully private):

[Dhairya @dkare1009]

Stop wasting hours trying to learn AI. 📘📚

I have already done it for you.

With one list. Zero confusion. And no fluff

📹 Videos:

1. LLM Introduction: https://t.co/Qja4lkQubw

2. LLMs from Scratch: https://t.co/DAtGeO5Q4B

3. Agentic AI Overview (Stanford): https://t.co/APcq2ouTyw

4. Building and Evaluating Agents: https://t.co/UeCQBsliKq

5. Building Effective Agents: https://t.co/B2tpQHbte7

6. Building Agents with MCP: https://t.co/CwVBIVUR2y

7. Building an Agent from Scratch: https://t.co/u2jhiZyEKt

8. Philo Agents: https://t.co/lFMIus6afo

🗂️ Repos

1. GenAI Agents: https://t.co/yoTno6S9pJ

2. Microsoft's AI Agents for Beginners: https://t.co/EGGYhcMXWJ

3. Prompt Engineering Guide: https://t.co/fSCoEaG1CN

4. Hands-On Large Language Models: https://t.co/TvpkfJNAip

5. AI Agents for Beginners: https://t.co/EGGYhcMXWJ

6. GenAI Agentshttps://lnkd.in/dEt72MEy

7. Made with ML: https://t.co/cCWWXKhAmu

8. Hands-On AI Engineering:https://t.co/fiLwjmYoY9

9. Awesome Generative AI Guide: https://t.co/MEhtfRlP82

10. Designing Machine Learning Systems: https://t.co/l21VO4spri

11. Machine Learning for Beginners from Microsoft: https://t.co/d3EPcDKuc7

12. LLM Course: https://t.co/xXxETt9y4q

🗺️ Guides

1. Google's Agent Whitepaper: https://t.co/rVDu4EznqD

2. Google's Agent Companion: https://t.co/IWjvSpTbRY

3. Building Effective Agents by Anthropic: https://t.co/0wK5pe6bsE.

4. Claude Code Best Agentic Coding practices: https://t.co/fu7GHgvVpQ

5. OpenAI's Practical Guide to Building Agents: https://t.co/sXpo72Q5fg

📚Books:

1. Understanding Deep Learning: https://t.co/YRV9Kz7Gw6

2. Building an LLM from Scratch: https://t.co/naslph9Isd

3. The LLM Engineering Handbook: https://t.co/BwmUJ6OOwM

4. AI Agents: The Definitive Guide - Nicole Koenigstein: https://t.co/ZIDeOOaUd7

5. Building Applications with AI Agents - Michael Albada: https://t.co/409SxeQ578

6. AI Agents with MCP - Kyle Stratis: https://t.co/3k9lFG49ok

7. AI Engineering: https://t.co/tHfgc3xlAo

📜 Papers

1. ReAct: https://t.co/8yV9k9RREi

2. Generative Agents: https://t.co/PpaAbCwubR.

3. Toolformer: https://t.co/mSfjjT72hs

4. Chain-of-Thought Prompting: https://t.co/uGktDnG9DJ.

🧑🏫 Courses:

1. HuggingFace's Agent Course: https://t.co/4MLjHKduIg

2. MCP with Anthropic: https://t.co/EnUWTrvIzC

3. Building Vector Databases with Pinecone: https://t.co/AmQzrCW44v

4. Vector Databases from Embeddings to Apps: https://t.co/HZbr4UBTlA

5. Agent Memory: https://t.co/TxvrpeCkuR

Repost for your network ♻️

[Inference @inference_net]

The LLM Engineering Roadmap.

If you want to start today, here's the roadmap👇

1️⃣ LLM Foundations
Start by understanding Python and LLM APIs and how they work.
Learn prompt engineering, structured outputs, and tool use.

↳ Python/Typescript Basics
↳ LLM APIs
↳ Prompt Engineering
↳ Structured Outputs
↳ Function Calling

2️⃣ Vector Stores
Before building anything, you need to understand how text becomes vectors.
Learn embedding models, chunking strategies, and similarity search.

↳ Embedding Models (OpenAI Ada, Cohere, BGE)
↳ Vector Databases (Pinecone, Qdrant, ChromaDB, FAISS)
↳ Chunking Strategies
↳ Similarity Search

3️⃣ Retrieval-Augmented Generation (RAG)
This is how LLMs answer questions using your data.
You learn how to retrieve context and feed it correctly.

↳ Orchestration Frameworks (LangChain, LlamaIndex)
↳ Ingesting Documents
↳ Retrieval Methods (Dense, BM25, Hybrid)
↳ Reranking
↳ Prompt Templates

4️⃣ Advanced RAG
This steps helps you understand how to make RAGs reliable and accurate.

↳ Query Transformation
↳ HyDE
↳ Corrective RAG
↳ Self-RAG
↳ Graph RAG

5️⃣ Fine-Tuning
Sometimes prompts are not enough for a specialised use case.
Fine-tuning will help you understand how models learn domain-specific behaviour.

↳ Data Preparation
↳ LoRA, QLoRA, DoRA
↳ SFT, DPO, RLHF
↳ Training Tools (Unsloth, Axolotl, HF TRL)

6️⃣ Inference Optimization
Once systems work, they need to be fast and affordable.
This step focuses on learning performance and cost efficiency.

↳ Quantization (GGUF, GPTQ, AWQ)
↳ Serving Engines (vLLM, TGI, llama.cpp)
↳ KV Cache
↳ Flash Attention
↳ Speculative Decoding

7️⃣ Deployment
Models are useless if they stay in notebooks.
Here you learn how to ship LLM systems to users.

↳ GPU Scheduling
↳ Cloud Platforms (AWS Bedrock, GCP Vertex AI)
↳ Docker, Kubernetes
↳ FastAPI, Streaming (SSE)

8️⃣ Observability
This step helps you track quality, latency, and cost.

↳ Tracing (LangSmith, Langfuse, Arize Phoenix)
↳ Latency (TTFT)
↳ Token Usage
↳ Cost Tracking

9️⃣ Agents
Agents allows LLMs to plan and use tools.
Learn them to understand how LLMs solve multi-step and complex tasks.

↳ Frameworks (LangGraph, CrewAI, Autogen)
↳ Function Calling
↳ Memory Systems
↳ Patterns (ReAct, Plan-and-Execute, Multi-Agent)

🔟 Production & Security
Production LLM systems can fail in subtle ways.
This step helps you prevent misuse, outages, and cost spikes.

↳ Prompt Injection Defense
↳ Guardrails (NeMo, Guardrails AI)
↳ Semantic Caching
↳ Fallbacks & Rate Limiting

♻️ Repost if you found this insightful

Follow us for more AI engineering content!

[Mr. Tariq @AiWithTariq]

MY COUSIN SUBMITTED 52 JOB APPLICATIONS.

ZERO RESPONSES.
ZERO INTERVIEWS.

Then I uploaded his resume to GROK and got 11 replies in 9 days.

Here are the 7 prompts I used:

[ℏεsam @Hesamation]

this is hands-down the best AI engineering channel to follow right now. there is so many videos presented by top researchers and engineers from the biggest companies on the most recent and up-to-date topics you must know. @aiDotEngineer is dominating youtube right now.

[Alex Prompter @alex_prompter]

If you're still coding without Claude, you're wasting hours.

I built 23 projects using these prompts.

Here are 8 Claude coding prompts that replaced my entire workflow:

[ℏεsam @Hesamation]

some dude gathered all the resources you need to start building your own agents. it has videos, repos, books, papers, and courses from Googl, Anthropic, OpenAI, etc teaching LLMs, agents, and MCP.

this is available on google docs for free: https://t.co/uw81kwh1cv

credits to Shivang Bhargava.

[Tom Dörr @tom_doerr]

open-source stock market app with real-time prices, alerts, and company insights

[Sumanth @Sumanth_077]

Web scraping will never be the same!

Firecrawl is an open-source framework that takes a URL, crawls it, and converts it into a clean markdown or structured format.

100% Open Source

[Swapna Kumar Panda @swapnakpanda]

Best FREE Courses for Absolute Beginners in 2024:

❯ Python
https://t.co/54ZBQw4eJU

❯ SQL
https://t.co/vDJLyFovMj

❯ JavaScript
https://t.co/3zOFRUQV8b

❯ Java
https://t.co/KQ9ivwWtBM

❯ C#
https://t.co/ObGQQDBcsy

❯ HTML and CSS
https://t.co/ouSjOyHsFy

❯ React
https://t.co/ueo6cuKwvV

❯ MongoDB
https://t.co/xzsxyuTjHt

❯ Kafka
https://t.co/MV9I7LYlvf

❯ Redis
https://t.co/u6a3zJX6vr

❯ C
https://t.co/vYn1B4O7eU

❯ C++
https://t.co/cwjCQGZPEy

❯ Linux
https://t.co/uYsNyJwzx0

❯ Cyber Security
https://t.co/HYjO7y0Qn8

❯ DevOps
https://t.co/DlTa48mu5F

❯ CI/CD
https://t.co/yfFsOlbuhO

❯ Docker
https://t.co/jGr29AlsJb

❯ Kubernetes
https://t.co/WuY2fT7J1B

❯ Data Science
https://t.co/hPXhwTjZWY

❯ Data Analysis
https://t.co/jCzMOmPm2O

❯ Machine Learning
https://t.co/5Qa2PdXDWC

❯ Deep Learning
https://t.co/oR872iBP6g

❯ Excel
https://t.co/lhoeQTlfRY

❯ PowerBI
https://t.co/Msr9CUtKbr

❯ Tableau
https://t.co/5WZYVJsawI

[TheSecMaster @TheSecMaster1]

😍 Some Usefull Ebooks Pack 😍

AWS:-
https://t.co/2Hw13k80ng

AZURE
https://t.co/E1JkHVz1xt

CCDA
https://t.co/jlngY8svg7

CCNA SECURITY
https://t.co/eXTkyZMPNZ

CEH
https://t.co/wTiYlcPnae

CISA
https://t.co/quowMXggoK

CISM
https://t.co/ybmd1l6OT8

CISSP
https://t.co/fxkEwSZ7K5

CMMI
https://t.co/c4epZdjW8Y

CRISC
https://t.co/xMhMDHfBtW

FIREWALL
https://t.co/IKIOqaZjR5