Gashe

#Crypto #Web3 #AirdropHunter #LifeTimeFighter,...

[om mishra @BuildWithOm]

Become a Top 1% Developer 🚀

Stage 1:
Learn to Code

Stage 2:
Build Small Projects

Stage 3:
Learn Git + GitHub

Stage 4:
Break Things

Stage 5:
Learn Debugging

Stage 6:
Build Real Projects

Stage 7:
Learn System Design

Stage 8:
Deploy to Production

Stage 9:
Contribute to Open Source

Stage 10:
Teach Others

Most people quit around Stage 4.

[Rahul @sairahul1]

https://t.co/uRsQBBhTcH

[yourclouddude @yourclouddude]

You’ll learn Python faster when you stop guessing what to learn next 🐍

[Peter Agboola @baba_Omoloro]

Teach Yourself Computer Science;

1. https://t.co/8A5UWq7ESz
2. https://t.co/boPhhL3RZm

All the resources you need to give yourself a world class computer science education, you can find it on the aforementioned websites.

[𝐓𝐡𝐞 𝐏𝐫𝐞𝐬𝐞𝐫𝐯𝐞𝐫 @ThePreserverofU]

26 WEBSITES WORTH MORE THAN MOST COLLEGE DEGREES

01. Courseradotorg → University courses free to audit
02. Brilliantdotorg → Interactive math and science learning
03. Wolfram Alpha → Answers any mathematical or factual question
04. GitHubdotcom → Learn coding from real‑world projects
05. Investopediadotcom → Finance and investing explained simply
06. Archivedotorg → Millions of free books and old websites
07. Project Gutenberg → 70,000 free classic books
08. Duolingodotcom → Learn any language for free
09. Notiondotso → Organize your entire life and learning
10. Our World in Data → Every global statistic visualized
11. Statistadotcom → Data and statistics on everything
12. OpenLibrarydotorg → Borrow millions of books online free
13. Hemingwayappdotcom → Write clearer and simpler instantly
14. NASAdotgov → Space science and research for free
15. PubMeddotgov → Access real scientific research papers
16. Edxdotorg → Free courses from Harvard, MIT, and more
17. TEDdotcom → Best ideas from the world’s best thinkers
18. Anki → The most powerful memory tool ever built
19. Canvadotcom → Design anything without being a designer
20. Skillsharedotcom → Creative and practical skill learning
21. Readwisedotio → Remember everything you ever read
22. GoogleScholar → Search real academic papers
23. Codecademydotcom → Learn to code completely free
24. ChatGPT → AI tutor available 24 hours a day
25. Figmadotcom → Learn professional design for free
26. Replitdotcom → Code anything from your browser

[Akshay Shinde @ConsciousRide]

12 End-to-End AI Engineer Projects in 2026

1) Production RAG Document Assistant

PDF/Q&A system with hybrid search (vector + BM25), reranking, citations, and eval metrics. Use LangChain/LlamaIndex + Pinecone/Chroma + FastAPI.
Why recruiters love it: Solves hallucinations, enterprise staple.

2) AI Resume Screener & Matcher

Upload JD + resumes —>> LLM parsing + embedding similarity + ranking dashboard. Add bias checks.
Pro move: Fine-tune a small model for domain-specific scoring.

3) Multi-Modal Chatbot (Text + Image + Voice)
Whisper for STT, GPT-4o/Claude vision, TTS. Add memory & tools.
Shows: Full multimodal pipeline.
Intermediate —>> Interview Magnet Tier

4) Autonomous AI Agent System (CrewAI/LangGraph)
Multi-agent workflow (e.g., research —>> summarize —>> email). With tool calling, planning, memory, and human-in-loop.ouEWE“LARGE”

5) Fine-Tuned Domain LLM + Serving

Fine-tune Mistral/Llama on your data (LoRA/QLoRA) -->> quantize —>> serve with vLLM/TGI + FastAPI. Compare cost/latency.

6) Real-time AI Monitoring & Observability Dashboard

Track LLM calls, latency, cost, hallucinations, drift. Use Prometheus + Grafana + LangSmith/Phoenix.
MLOps gold.
Advanced —>> “Senior AI Engineer” Tier

7) End-to-End MLOps Pipeline for LLM

Data versioning (DVC) —>> training (on cloud) —>> CI/CD deployment —>> A/B testing —>> rollback. Docker + Kubernetes/GCP.

8) Voice AI Agent / Study Coach

Real-time conversation with interruption handling, knowledge base (RAG), personalized learning paths.

9) Multi-Agent Coding/Research Assistant

Agents that browse, code, debug, and iterate together. Add eval harness.

10) Hybrid Search + Recommendation System

Combine traditional ML + LLMs for personalized recs (e.g., content or jobs) with feedback loop.

11) Private/Local AI App (Ollama + RAG)

Fully offline SLM app with local vector DB. Focus on privacy, quantization, on-device perf.

12) AI-Powered Enterprise Tool (e.g., Log Analyzer or Meeting Summarizer)

Ingest data —>> process with agents —>> actionable insights + dashboard. Deploy with auth & RBAC.

Bonus Rules to Get Hired:

• Production-grade everything: eval sets, guardrails, rate limiting, cost tracking, error handling
• Deploy on Vercel/Render/Fly.io + Cloud (AWS/GCP/Azure) - show metrics
• Killer READMEs: architecture diagrams, benchmarks, challenges & trade-offs, live demo link
• Write tests, use Docker, add CI/CD
• Track everything: tokens, latency, accuracy, $ spent

[Kanika @KanikaBK]

A SENIOR GOOGLE ENGINEER DROPPED A 421-PAGE DOC THAT NO ONE IS TALKING ABOUT.

It is called Agentic Design Patterns. 100% FREE.

Every AI builder paying $200/month for courses just got obsoleted.

This is the most comprehensive AI systems guide I have seen in 2026.

Code-backed and production-ready.👇

[Jobs with Aramide @AramideOyekunle]

Best YouTube Channels To Learn:

Cybersecurity - John Hammond
Networking - David Bombal
Python - Code With Harry
React - Codevolution
UI/UX - GFXMentor
JavaScript - Traversy Media
Java - kunal kushwaha
DevOps - Techworld with Nana
Blockchain - Telusko
AI/ML- Krish Naik
Web Development - Traversy Media
AWS - Code With Harry
SQL - Programming With Mosh
DBMS - edureka

[Shubh @TheSuperEng]

These No BS engineering blogs are a goldmine for serious backend and infra engineers:

1. Netflix TechBlog
2. Uber Engineering
3. Engineering at Meta
4. Cloudflare Blog
5. Stripe Engineering
6. Slack Engineering
7. GitHub Engineering
8. Airbnb Tech Blog
9. Dropbox Tech Blog
10. DoorDash Engineering
11. Pinterest Engineering
12. LinkedIn Engineering
13. Spotify Engineering
15. Shopify Engineering
16. Datadog Engineering

[Andrew Bolis @AndrewBolis]

AI is replacing people without the right skills.

Build AI skills to future-proof your career.

Knowing AI tools isn’t enough. It’s critical to learn the right AI skills.

These 9 skills outline how professionals work with AI, from basic interaction to system-level execution.

Building a few of them will expand your career options and opportunities.

Here’s the full breakdown of each skill:

[ 🔖 bookmark this post for later ]

1���⃣ Prompt Engineering

Write clear instructions that produce consistent, useful AI results.

Most people type one prompt and fix the output later. Professionals structured prompts that deliver repeatable outcomes across tools and tasks.

Tools: Claude, ChatGPT

2️⃣ Workflow Automation

Link platforms together to let AI handle your repetitive work.

This is how teams eliminate manual handoffs and turn routine processes into background systems.

Tools: n8n, Zapier

3️⃣ AI Image Generation

Produce professional-grade visuals for ads and products via text.

Instead of waiting on designers or stock assets, teams generate visuals on demand and iterate instantly.

Tools: NanoBanana (Gemini), Recraft

4️⃣ Vibe Coding

Ship working prototypes rapidly without deep manual code knowledge.

The technical wall is gone; founders are now launching functional products by describing their ideas instead of hiring expensive developers.

Tools: Lovable, Replit

5️⃣ Custom GPTs

Create tailored AI assistants for specific tasks without code.

This turns AI from a general tool into a system that understands your workflows, tone, and use cases.

Tools: OpenAI GPT Builder, Poe

6️⃣ AI Video Generation

Turn concepts into cinematic video content without editing expertise.

Scale video marketing and training at lower costs by generating polished scenes from text scripts.

Tools: Synthesia, Runway

7️⃣ AI-Assisted Development

Write and debug code faster using real-time AI guidance.

Developers focus on logic and architecture while AI handles syntax, errors, and refactoring.

Tools: Cursor, Google Antigravity

8️⃣ Agentic Coding

Assign full coding tasks to AI agents that strategize and execute.

Instead of guiding every step, you define goals and let agents plan and complete the work.

Tools: OpenAI Codex, Claude Code

9️⃣ RAG Systems

Link AI to your internal data for relevant, business-specific responses.

This replaces generic outputs with answers grounded in your documents, systems, and knowledge base.

Tools: LangChain, Haystack

AI tools aren’t enough. It’s critical to build AI skills.

Use this roadmap to:
➟ Identify which AI skills support your role or team
➟ Start with one skill and apply it in real work
➟ Expand only after you see results

That’s how AI becomes a long-term asset, not a distraction.

📌 Get Advanced ChatGPT Guide (free): https://t.co/kOBWfKrBaX

👉 Follow me @AndrewBolis for more and 🔄 Repost this to help others use AI

[Thomas Trimoreau @TTrimoreau]

At this point if AI writes 90% of code, who even survives in tech??

[Anuj @anujcodes_21]

🚨Anthropic just showed a 24-minute workshop on how to actually do prompts for Claude.

Taught by the people who built it.

Free. No registration. No paywall.

I've seen $300 courses that don't cover what they teach in the first 8 minutes.

Watch it and bookmark it now.

[Peter H. Diamandis, MD @PeterDiamandis]

Anthropic reports Claude now writes over 80% of its own production code — meaning an AI is the primary author of the systems training future versions of itself. Claude's research judgment matched human experts 22% of the time in 2024. Today it's 64%.

The recursive loop has started.

[KUYIK BASSEY @IamKuyikBassey]

Here is how to Start!

How to clone any successful YouTube channel and launch yours this week.

Step by step. Zero guesswork. 👇

Step 1 — Find your target channel
Go to YouTube. Search your niche. Find 2 to 3 channels doing exactly what you want to do. Pick the ones with consistent views even on older videos. Copy the links of their top 4 performing videos.

Step 2 — Take it to NotebookLM
Go to (notebooklm. google. com) It is completely free.
Click New Notebook.
Paste all 4 video links inside.

Then ask it this:

"Analyse these videos and tell me the exact blueprint. What topics do they cover. How do they structure their scripts. What makes these videos perform well. What patterns do you notice across all of them."

NotebookLM will break down the entire blueprint for you.

Step 3 — Take the blueprint to Claude AI
Copy everything NotebookLM gives you.
Open Claude AI.

Paste it and type:

"Based on this channel blueprint suggest 5 original video ideas I can create in this same niche. Give me a title, a hook and a brief outline for each one."

Now you have 5 ready to execute video ideas that are proven to work in your niche.

Step 4 — Write your first script
Pick your favourite idea from the 5.

Ask Claude AI:

"Write a full 6 minute YouTube script for this video idea. Make it conversational, beginner friendly and start with a strong hook that stops the scroll."

Script done in minutes.

Step 5 — Generate your voiceover
Go to ElevenLabs free plan.
Paste your script.
Pick a natural professional voice.
Download your voiceover for free.

Step 6 — Create your visuals
Go to Pika Labs or Canva for AI generated visuals and images.
Match them to your script sections.
Download everything free.

Step 7 — Edit your full video
Open CapCut desktop.
Import your voiceover and visuals.
Add automatic captions.

Add background music from YouTube Audio Library.

Export completely free. No watermark.

Step 8 — Design your thumbnail
Open Canva.
Study the thumbnails of your target channel.
Model the style. Bold text. Clean image. High contrast.

Design yours in under 10 minutes or use ChatGPT for free in less than seconds.

Step 9 — Set up your channel and upload
Create your YouTube channel.
Write a clear channel description.
Upload your video.
Open VidIQ free plan.
Add the best keywords to your title, description and tags.
Publish.

Step 10 — Repeat every single week
One video per week minimum.
Same day. Same time.
The algorithm rewards consistency over perfection.

Total tools used:
NotebookLM. Claude AI. ChatGPT. ElevenLabs. Pika Labs. CapCut. Canva. VidIQ.

Total cost: $0

This is exactly what I teach inside my recorded class.

Every step. Done live. With real examples.

The three day live class is now available as a full recorded session.

Watch it at your own pace.

Pause. Rewind. Repeat until your channel is live.

Link is in my bio. 🎯

[Tech Fusionist @techyoutbe]

Phase 00: Setup & Tooling (12 lessons)
Phase 01: Math Foundations (22 lessons)
Phase 02: ML Fundamentals (18 lessons)
Phase 03: Deep Learning Core (13 lessons)
Phase 04: Computer Vision (28 lessons)
Phase 05: NLP (29 lessons)
Phase 06: Speech & Audio (17 lessons)
Phase 07: Transformers Deep Dive (14 lessons)
Phase 08: Generative AI (14 lessons)
Phase 09: Reinforcement Learning (12 lessons)
Phase 10: LLMs from Scratch (22 lessons)
Phase 11: LLM Engineering (15 lessons)
Phase 12: Multimodal AI (25 lessons)
Phase 13: Tools & Protocols (23 lessons)
Phase 14: Agent Engineering (42 lessons)
Phase 15: Autonomous Systems (22 lessons)
Phase 16: Multi-Agent & Swarms (25 lessons)
Phase 17: Infrastructure & Production (28 lessons)
Phase 18: Ethics, Safety & Alignment (30 lessons)
Phase 19: Capstone Projects (85 lessons)

Link in Comment ✍️✍️
build by @ghumare64

[Saurabh Dubey @SaurabhDub28465]

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/nQqhVUFcqL
2. LLMs from Scratch: https://t.co/ubOoUe6vyH
3. Agentic AI Overview (Stanford): https://t.co/kjXIX43D0L
4. Building and Evaluating Agents: https://t.co/83gYRKeFR5
5. Building Effective Agents: https://t.co/MHmEK2zWYZ
6. Building Agents with MCP: https://t.co/omeYWlh3O4
7. Building an Agent from Scratch: https://t.co/edG3LXKGnr
8. Philo Agents: https://t.co/U9SkxSDV7A

Repos

1. GenAI Agents: https://t.co/AfZqWiGiRH
2. Microsoft's AI Agents for Beginners: https://t.co/GK6mxZIMRd
3. Prompt Engineering Guide: https://t.co/kwzJNVaMu4
4. Hands-On Large Language Models: https://t.co/lHm4S0iuCQ
5. AI Agents for Beginners: https://t.co/GK6mxZIMRd
6. GenAI Agents: https://t.co/83JIIIyxI8
7. Made with ML: https://t.co/N5vMxjVJlG
8. Hands-On AI Engineering: https://t.co/HavscaaycT
9. Awesome Generative AI Guide: https://t.co/kQR74oyupV
10. Designing Machine Learning Systems: https://t.co/el4wYszXKj
11. Machine Learning for Beginners from Microsoft: https://t.co/lCgRoyNZHF
12. LLM Course: https://t.co/nWv5XKwlfr

🗺️ Guides

1. Google's Agent Whitepaper: https://t.co/LSg2CNyzEk
2. Google's Agent Companion: https://t.co/NqE6RLjVlK
3. Building Effective Agents by Anthropic: https://t.co/Oolxsg0dxj
4. Claude Code Best Agentic Coding practices: https://t.co/lvgJ6XphoE
5. OpenAI's Practical Guide to Building Agents: https://t.co/AAbfO22cN3

📚 Books:

1. Understanding Deep Learning: https://t.co/rWGlscigIQ
2. Building an LLM from Scratch: https://t.co/BnLjj8RZPT
3. The LLM Engineering Handbook: https://t.co/5t64XWDxnR
4. AI Agents: The Definitive Guide - Nicole Koenigstein: https://t.co/j7HifJCexk
5. Building Applications with AI Agents - Michael Albada: https://t.co/nKkMGKiEI3
6. AI Agents with MCP - Kyle Stratis: https://t.co/54Lrbd9JS8
7. AI Engineering: https://t.co/W7x7c0B2bJ

📜 Papers

1. ReAct: https://t.co/F15yJ9qjGR
2. Generative Agents: https://t.co/FuG0nPgvSh
3. Toolformer: https://t.co/YVxz0njJO8
4. Chain-of-Thought Prompting: https://t.co/pzHWRsLHxB

🧑🏫 Courses:

1. HuggingFace's Agent Course: https://t.co/ij2gBu4HfN
2. MCP with Anthropic: https://t.co/1E3XNPWtoz
3. Building Vector Databases with Pinecone: https://t.co/FILukUkQTf
4. Vector Databases from Embeddings to Apps: https://t.co/hGSoowltVn
5. Agent Memory: https://t.co/3IFKV0d00J

❤️ Like
🔁 Repost
🔖 Bookmark

Follow @SaurabhDub28465 for more of these free courses, AI &Tech productivity content.

Comment link I'll share in the DM

[yourclouddude @yourclouddude]

Don’t overthink advanced Python projects.

• AI Chatbot (LLM + memory) → real AI workflows
• Full SaaS App (Auth + payments) → production skills
• API Gateway (FastAPI + rate limiting) → backend depth
• Web Scraper + Dashboard → data pipeline
• Automation System (emails/files/tasks) → real utility
• ML Model + Deployment → end-to-end AI
• Real-time Chat App (WebSockets) → async + scaling
• CLI Tool (package + publish) → dev tooling
• Microservices Project (Docker + APIs) → architecture
• Job Tracker App (DB + analytics) → portfolio proof

These aren’t projects.
They’re proof you can build.

[WANGAI @wangai_johnn]

Hey you;

Get a laptop, buy a headphone, go to YouTube, search Transcription, how to transcribe, English transcription short course.

Practice with sample tests, repeat. Go to Outlier or any other AI training platforms, esp US accounts.

End of Poverty!

[Sourabh Gurwani @SourabhGurwani]

Software Developer Roadmap to Get Hired in 2026

- Learn One Language Well → Java / Python / JavaScript / C++

-Master DSA → Arrays, Trees, Graphs, DP

- Learn Git & GitHub → Version control is non-negotiable

- Build Projects → Full-stack > Tutorial certificates

- Learn Databases → SQL + basic NoSQL

-Learn Backend → Spring Boot / Node.js / Django

- Learn Cloud Basics → AWS, Docker, CI/CD

- Use AI Tools → ChatGPT, Claude, Cursor

- Learn System Design → APIs, caching, scaling

- Build in Public → GitHub, LinkedIn, Portfolio

-Apply + Network → Referrals > Cold applications

-- Repeat for 6–12 months --

The harsh truth:

2026 won't reward the person who knows the most.

It will reward the person who can prove they can build

[Shraddha Bharuka @BharukaShraddha]

BLOCKCHAIN — MASTER TREE 🌲

Blockchain
│
├── 01. Foundations
│ ├── What is Blockchain?
│ ├── Distributed Ledgers
│ ├── Cryptographic Hashing
│ ├── Digital Signatures
│ ├── Peer-to-Peer Networks
│ └── Consensus Mechanisms
│
├── 02. Cryptography
│ ├── SHA-256
│ ├── Public Keys
│ ├── Private Keys
│ ├── Wallet Addresses
│ ├── Merkle Trees
│ └── Zero-Knowledge Proofs
│
├── 03. Bitcoin Layer
│ ├── Bitcoin
│ ├── UTXO Model
│ ├── Mining
│ ├── Proof of Work
│ ├── Lightning Network
│ └── Bitcoin Ordinals
│
├── 04. Ethereum Layer
│ ├── Ethereum
│ ├── EVM
│ ├── Gas Fees
│ ├── Proof of Stake
│ ├── Validators
│ └── Layer 2 Networks
│
├── 05. Smart Contracts
│ ├── Solidity
│ ├── Vyper
│ ├── ERC-20
│ ├── ERC-721
│ ├── ERC-1155
│ └── Contract Security
│
├── 06. DeFi Ecosystem
│ ├── DEXs
│ ├── Lending Protocols
│ ├── Yield Farming
│ ├── Liquidity Pools
│ ├── Stablecoins
│ └── DAOs
│
├── 07. Web3 Development
│ ├── Hardhat
│ ├── Foundry
│ ├── Ethers.js
│ ├── Wagmi
│ ├── Wallet Connect
│ └── Full-Stack dApps
│
├── 08. Blockchain Infrastructure
│ ├── Nodes
│ ├── RPC Providers
│ ├── The Graph
│ ├── IPFS
│ ├── Oracles
│ └── Cross-Chain Bridges
│
├── 09. Security & Auditing
│ ├── Reentrancy Attacks
│ ├── Flash Loan Attacks
│ ├── Smart Contract Audits
│ ├── Multi-Sig Wallets
│ ├── Key Management
│ └── Bug Bounties
│
└── 10. Future of Blockchain
├── Real World Assets (RWA)
├── AI + Blockchain
├── Decentralized Identity
├── Modular Blockchains
└── Autonomous Economies

Most people see crypto as coins.

The real innovation is programmable trust. 🚀

Save this if you're learning Blockchain in 2026. 🌲⛓️