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[Mahax @Mahaximus_]

Andrew Ng just dropped a 2-hour course on Graph Engineering: from Loops to full automation

9:14 - Your first agent
33:11 - Loop engineering
1:02:46 - Graph engineering
1:30:15 - Agents that rewrite themselves
1:49:05 - Full graph system

Free, the best thing on graph engineering I've come across

Watch it, then build your first graph with the guide below

[Vikas gupta @vicky_grok]

🚨 GOOGLE JUST RELEASED A FREE 2-HOUR AGENT ENGINEERING COURSE

From your first AI agent...

To MCP tools...

To Loop Engineering...

To Graph Engineering...

To fully autonomous AI systems.

One of the best free AI engineering courses available.

Bookmark it and watch it today, then read the complete Graph Engineering playbook below.

[Dhairya Karekar @dkare1009]

Most people use LLMs.
Very few actually understand how they work under the hood.

If you want to go from prompt user → real AI engineer, study these 9 concepts in order:

1️⃣ Transformers — attention, tokens, self-attention basics
https://t.co/65pkMfS4og

2️⃣ Transformer tricks — what makes them stable & scalable
https://t.co/mnUQYpQ9q2

3️⃣ From Transformers → LLMs — how scale changes behavior
https://t.co/uXOVnCsmGA

4️⃣ LLM training — where “intelligence” actually emerges
https://t.co/RFkBljQ8Pi

5️⃣ Instruction tuning & alignment — why fine-tuning matters
https://t.co/nmZB6JE0NK

6️⃣ LLM reasoning — why models fail + what improves them
https://t.co/UY8V9bZjAU

7️⃣ Agentic LLMs — models that plan, call tools, and act
https://t.co/EZbxuxBimR

8️⃣ LLM evaluation — measure beyond demos & vibes
https://t.co/yZ4Uig7uGw

9️⃣ What’s next — trends that actually matter

Bookmark this. Study step-by-step. Your prompts will level up — and so will your builds.

CC: Author

[Morty @0xMortyx]

Anthropic Engineer Andrej Karpathy dropped a full 6-hour course on how to build LLMs from scratch and use it:

• 00:00 - Deep dive into LLMs
• 03:31:23 - Building ChatGPT from scratch
• 05:27:43 - How to use LLMs (Karpathy method)

This course can replace a $150K Stanford LLM senior degree.

Start watching today, then read article below

[Mr. Buzzoni @polydao]

I HAVEN'T OPENED CLAUDE AT MIDNIGHT SINCE I BUILT THIS FOLDER

I used to wake up, check what broke overnight, fix it by hand

-> now I wake up and the receipts are already sitting there, dated, graded, waiting on my review

here's what's actually inside the folder that replaced me:

• the contract
> CONTRACT.md - the shift rules, committed to the repo
> contract.local.md - my personal overrides, gitignored

• the harness (.claude/loops/)
> settings.json - spend caps and timeouts, set once and forgotten
> schedule.yml - when the next shift fires
> rubrics/ - code.md, writing.md, safety.md - graders that catch what I'd miss on a bad night
> pr-hunter/ - plan.md wakes it up, https://t.co/VUDfqGE1Fp does the actual work

• the state
> receipts/ - one folder per shift, 5,382 kept and counting
> trace.log - exactly what happened, zero guessing
> checkpoint.json - resumes right where the last shift stopped

• the edges
> https://t.co/agzjvw6VbF - the panic switch, still untouched
> .mcp.json - the exact tools it's allowed near

the folder wakes up so I don't have to

[reira @reiraxbt]

Andrej Karpathy spent 8 years at OpenAI and Tesla

Last week, he put everything he knows into one free 2-hour lecture

People pay $15k for bootcamps that teach half of this

You probably don't have 2 hours right now

Don't let this get lost in your feed

Watch it, then read the guide below and build your first loop

[Dhanian 🗯️ @e_opore]

As a System Design Engineer,

It will be good if you have an understanding of the below 40 System Design Case Studies👇

1. URL Shortener (TinyURL / Bitly)
2. Pastebin
3. Rate Limiter
4. Distributed Cache
5. Load Balancer
6. API Gateway
7. Notification System
8. Web Crawler
9. Search Autocomplete
10. Distributed Key-Value Store
11. Twitter/X Feed
12. Instagram
13. Facebook News Feed
14. YouTube
15. Netflix
16. Video Streaming Platform
17. WhatsApp / Real-Time Messaging
18. Uber / Ride-Sharing System
19. Google Maps
20. Food Delivery System
21. Amazon / E-Commerce Platform
22. Payment Processing System
23. Ticket Booking System
24. Hotel Booking System
25. Flight Booking System
26. Online Auction System
27. Distributed File Storage (Dropbox / Google Drive)
28. Cloud Storage System
29. Google Search Engine
30. Recommendation System
31. Ad Serving System
32. Metrics and Monitoring System
33. Logging and Log Aggregation System
34. Distributed Job Scheduler
35. Message Queue / Event Streaming Platform
36. Real-Time Collaboration System
37. Code Deployment Platform
38. Video Conferencing System
39. Ride-Sharing Location Tracking System
40. Distributed Transaction and Order Management System

📘 Grab System Design Case Studies Handbook:
https://t.co/ec73poyTBr

These case studies provide a strong foundation for learning how to design scalable, reliable, fault-tolerant, and high-performance distributed systems used by modern technology companies.

[Matt Dancho (Business Science) @mdancho84]

This GitHub is better than most $1,000 AI courses.

Chip Huyen's AI Engineering companion repo:

[Stiven @Stiven_SRB]

New Ox Home Mount - Hearthkeeper's Wandering Caravan. One seat for the player and 2x extra seats for?

[Interesting STEM @InterestingSTEM]

The complexity of the human brain and its functions

[PyQuant News 🐍 @pyquantnews]

This is literally the only book you need to build applications with foundation models.

I read all 532 pages (so you don't have to).

Here are the key points:

[Python Space @python_spaces]

Microsoft is offering MCP for beginners course for FREE!

- 11 lessons
- Code examples
- All for FREE

Find the course link 🧵 👇

[Eyo Eyo, PhD @Eyowhite3]

Sure they will always overlap.

[World of Warcraft @Warcraft]

Whether or not you’re prepared…

Legion Remix rolls out today. Give ’Em Fel!

[Leyst @LeystTv]

How-to get Sargerei Commander's Transmog Sets in Legion Remix! #worldofwarcraft

Check out the guide below! 👇

[World of Warcraft @Warcraft]

No thoughts, just WoW: Midnight 🌌

📖 New story campaign + lvl 90 cap
🌌 4 new zones to explore
👤 Haranir join the fight
🏰 Silvermoon City shines once again
⚔️ New Delves, Raids, Dungeons, & more!

Check the full blog here: https://t.co/b3C3ELyrfh

[Ronald van Loon @Ronald_vanLoon]

#AI Vs #GenerativeAI Vs #MachineLearning
by @Khulood_Almani

#ArtificialIntelligence #ML #MI

cc: @valaafshar @terence_mills @mikequindazzi

[Python Programming @PythonPr]

Machine Learning Algorithms!

[Femke Plantinga @femke_plantinga]

Is your RAG system a paperweight?

It is if it can't handle a simple follow-up question.

Building basic RAG is easy. The real challenge is engineering systems that go beyond simple retrieval and actually do more with your data. This is how you build a RAG pipeline that can think, reason, and adapt.

Here's how advanced 𝗽𝗿𝗼𝗺𝗽𝘁𝗶𝗻𝗴 𝘁𝗲𝗰𝗵𝗻𝗶𝗾𝘂𝗲𝘀 transform your RAG pipeline:

𝗖𝗵𝗮𝗶𝗻 𝗼𝗳 𝗧𝗵𝗼𝘂𝗴𝗵𝘁 (𝗖𝗼𝗧): Instead of jumping to an answer, the model breaks down complex queries into intermediate steps, making the LLM "show its work."

𝗧𝗿𝗲𝗲-𝗼𝗳-𝗧𝗵𝗼𝘂𝗴𝗵𝘁𝘀 (𝗧𝗼𝗧): Takes reasoning further by exploring multiple paths simultaneously. The system generates several potential solutions and evaluates which is most promising. This is how you systematically weigh different pieces of evidence from multiple retrieved documents.

𝗥𝗲𝗔𝗰𝘁 (𝗥𝗲𝗮𝘀𝗼𝗻𝗶��𝗴 + 𝗔𝗰𝘁𝗶𝗻𝗴): This framework lets the system *think* and *act* dynamically. It can reason about what information it needs, act to retrieve it, and then reason again based on what it found.

But beyond prompting, you need to fix your retrieval, too.

𝗤𝘂𝗲𝗿𝘆 𝗥𝗲𝘄𝗿𝗶𝘁𝗶𝗻𝗴 & 𝗘𝘅𝗽𝗮𝗻𝘀𝗶𝗼𝗻: Before hitting your vector database, change that vague user question into something your retrieval system can actually work with. This isn't just about synonyms, it's about understanding intent.

𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗥𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗲𝘀: Move beyond basic search. Think hybrid search (combining similarity and keyword), metadata filtering, and multi-step retrieval for complex queries.

This is where it really gets interesting: 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗥𝗔𝗚.

AI agents can reformulate queries on the fly, re-retrieve information if initial results miss the mark, and handle queries requiring multi-step reasoning across multiple documents. Moving from a one-shot solution with no reasoning into an intelligent system that thinks, reasons, and adapts.

Ready to go from basic RAG to a reasoning engine? We cover these techniques and more in our ebook on Advanced RAG Pipelines.

𝗗𝗼𝘄𝗻𝗹𝗼𝗮𝗱 𝘆𝗼𝘂𝗿 𝗳𝗿𝗲𝗲 𝗰𝗼𝗽𝘆 𝗵𝗲𝗿𝗲: https://t.co/X6VZdOVUgc

[Matt Dancho (Business Science) @mdancho84]

🚨NEW Whitepaper on AI Agents by OpenAI

The maker of ChatGPT shares how it builds AI Agents.

Get the 34-page white paper here: