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That guy

[Mahax @Mahaximus_]

Don't waste 2 years learning to code.

The man who built Claude Code tells you what to learn instead.

82 minutes. Free:

24:03 - Anthropic's real engineering rules
27:44 - $100k+/month on Claude
40:42 - What to learn instead of coding

Writing code is the old job, building Loops is the new one.

Watch it, then read the guide below.

[Hanako @hanakoxbt]

Google just dropped the best 1-hour course on Graph Engineering: from one agent to a full 24/7 system

00:00 - what graphs are
09:16 - build an agent
21:15 - graph engineering explained
41:03 - graph engineering in practice
52:21 - self-improving graphs

free, and the best thing on graph engineering I have come across

Prompts → Agents → Loops → Graphs

most people will watch the first nine minutes and go back to typing into a chat box

same model, same tokens, and the only thing that changes is the shape you run it in

watch it today, then read the full guide on agents and graphs below

[Zane @ZaneOnAI]

Andrew Ng just released a 1-hour course on building agentic knowledge Graphs from scratch:

00:00 - Introduction to agentic knowledge Graphs
03:07 - Construction of agentic Graphs
14:00 - Architecture of multi-agent systems
23:00 - Building agentic graphs with Google ADK
01:06:03 - Why Graphs are the future of agentic AI

Worth more than 10 articles on loop engineering.

Watch it today, then read how to become a graph engineer in the article below.

[akari @akarixbt]

Stanford AI engineering course:

"Anyone can build an AI agent in 60 minutes"

Prompt → Agent → Automation → Revenue

Stanford just released a free course on building AI agents from scratch

00:00 - Build your first AI agent
48:17 - Create agents without coding
54:39 - Make $100K+ per month with agents

While you scroll, someone else is learning Anthropic's $750,000 skill

This free course beats most paid AI agent courses

Watch it today

Then use the guide below to build an agent that prompts itself

[rari @0xwhrrari]

Google Brain founder Andrew Ng:

"Prompting will be dead in 6 months

Agent harnesses built with loops and graphs will replace it"

Agent → Harness → Feedback → Loops → Graphs → Self-Improving Systems

In this 1-hour Stanford lecture, he explains what the best engineers are building instead and how you can start today

Prompt → Run → Verify → Improve

The first 20 minutes teach what most $1,500 courses try to sell you

For free

Bookmark and watch it today

Then read the guide below on building an agent harness that improves itself

[rari @0xwhrrari]

Andrej Karpathy spent 8 years at OpenAI and Tesla

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

Agents → Loops → Harness → Self-Improving Systems

People pay $14K for bootcamps that teach less than this

This lecture beats most paid AI engineering courses

You probably don't have 2 hours right now

Don't let this disappear from your feed

Watch it

Then read the article below

[rari @0xwhrrari]

Anthropic hired this engineer at $250K-$750K a year because he knows how to build harnesses for multi-agent systems

In this 15-minute workshop, he shows exactly how to build one from scratch

AI → Agents → Harness → Loops → Graphs

step 1 → start with the Claude Agent SDK - the harness handles loops, context, and sandboxing

step 2 → separate the brain from the hands - reasoning in one place, tools in a sandbox, 60% faster to first token

step 3 → run it server-side and log every step - close your laptop and it keeps running, crashes resume from the log

step 4 → make failure cheap - retry dead sandboxes and replay lost context instead of starting over

step 5 → turn yesterday's logs into new memory and skills - the harness wakes up smarter

Anthropic calls this "dreaming"

Most people spend weeks building this by hand

You don't have to

Bookmark and watch it

Then read the full harness engineering guide below ↓

[Dean W. Perkins @deanwperkins]

16 minute tutorial on how to build $50,000 cinematic websites (step by step) with Claude Fable 5

Save this before you lose it 🔖

[Anatoli Kopadze @AnatoliKopadze]

NVIDIA CEO, Jensen Huang:

"Nobody writes prompts anymore, the new job is building Loops and Graphs."

In 50 minutes he breaks down what replaced prompting and why most people haven't caught on yet.

It's the difference between using AI and having AI work for you.

Watch it, then read the guide below on how to build a system that improves itself.

[Anatoli Kopadze @AnatoliKopadze]

A Berkeley professor just leaked Anthropic’s CCA exam that opens the door to $750,000 jobs.

In 20 minutes he covers every single topic on the exam and explains how to actually solve it.

This exam shows exactly what you need to know about AI right now and what’s not worth your time.

Watch the presentation first, then read the guide below on how to build a system that improves itself.

[Anatoli Kopadze @AnatoliKopadze]

A Google Cloud engineer just showed how to build a full app with Claude from scratch.

He spent 26 minutes live on stage doing what most teams take weeks to do.

Worth more than any $500 vibe-coding course, no team, no setup, just Claude and a goal.

The ones who learn what Claude actually does are shipping what everyone else outsources to a team.

Watch it, then read the guide below on the Claude features 99% of users never find.

[Alex Prompter @alex_prompter]

Google Brain co-founder and Stanford professor, Andrew Ng, spent 149 minutes explaining how to prompt AI in 2026 better than any paid prompting course on the market.

This is what separates AI novices from power users:

1. "Think step by step" is dead advice.
This was standard prompting wisdom as recently as 2023. Andrew says the models have outgrown it.
"I no longer tell my AI model to think step by step. Instead, I'm more likely to just tell it to think hard. It knows what that means."
The most-repeated prompting tip on the internet became obsolete while most people kept using it.

2. Power users have empathy for the AI.
In an operational sense: they imagine being on the receiving end of their own prompt.
"If you could put yourself in the shoes of someone getting instructions from you, you can ask yourself, will they know enough about you to do a good job on the task you're assigning them?"
The best prompters anticipate what information the AI is missing.

3. Your biased questions get biased answers.
Andrew tested what happens when you frame a question with your preferred answer baked in. A Washington Post study he cites found ChatGPT agreed with users 10 times more often than it disagreed.
"If you give even a hint of what answer you're hoping for, there's a good chance the AI will just reflect back your preferences or your preconceptions."
Load a question with your preferred outcome and you're paying for a mirror and calling it analysis.

4. Never write the final text first.
Andrew Ng uses progressive outlining: outline first, critique the outline, iterate, expand to bullets, iterate again, and only then generate the final text.
"Editing the outline is very high leverage because you can change just a few words of the outline and this will result in an entire section of the article changing."
One edit at the outline level moves thousands of words. One edit at the sentence level moves one sentence.

5. Give feedback on options, not more instructions.
Instead of writing a longer prompt, Andrew asks AI for 3 to 5 options, then critiques them. His feedback becomes the context.
"One of the really good ways to figure out what additional context to give the AI is to give it feedback on the options it presents to you."
Your reaction to AI's output tells it more about what you want than another paragraph of instructions.

6. AI defaults to Reddit. Steer it to better sources.
Andrew cites data showing the most-cited website by AI models during web search is Reddit, followed by Wikipedia.
"If you don't steer the model in terms of what types of sources you prefer, there's a chance that it'll tend to pull text from whatever is most available rather than what's most reliable."
Ask for medical or financial information without specifying sources and you're getting Reddit-grade answers in professional packaging.

7. AI has jagged intelligence. No single model wins at everything.
Different models excel at different tasks, and which one leads changes with every new release. Andrew tests the same prompt across multiple models.
"There's some tasks where AI does poorer than human and some where it does much better than human and different AI models are jagged in different ways."
You get better results testing across providers and updating your intuitions about which tool fits which task.

Watch the full 149-minute course, then read the prompting playbook on GPT-5.6

[Rohit @heyrohitai]

Anthropic engineer:

"Don't just prompt Claude. Build a system that can prompt itself."

In this 45-minute session, she explains how Anthropic builds AI agents that can remember past work, learn from mistakes, and improve with every run.

It's one of the best free resources for learning how AI agents work.

Watch the session, then read the guide on building loops below.

[Codez @0xCodez]

Andrew Ng just released a 2-hour course on building agentic skills from scratch with Anthropic:

• 00:00 – How to build agent skills with Claude
• 22:32 – Claude pre-built skills for AI agents
• 41:07 – Agentic skills vs tools, MCP, subagents
• 01:06:06 – Skills for long-running agents

This 2-hour watch will replace 10 paid courses on building agents, by Anthropic themselves.

Watch it today, then read how to build self-improving agentic systems in the article below.

[codila @0xCodila]

Ex-Google engineer just dropped 1-hour course: loops, self-improving AI, memory systems - from scratch:

00:00 - the self-building agent
03:01 - soul.md runs everything
30:16 - RAG memory: pull 20 messages, not 2,000
31:48 - the loop that knows when to stop
35:14 - find the bug, fix the prompt
50:22 - how Claude compresses your memory

1 hour of his guide beats any paid agent course

watch & bookmark - then read Karpathy's loop method below

[Raytar @Raytar]

Anthropic engineer:

«You're not supposed to sit and re-prompt Claude all day.

You build one loop, and it does the work while you sleep.»

• 00:00 - Build your first agent that runs on its own
• 05:02 - The loop that fixes its own mistakes
• 16:43 - Why Claude forgets you between chats, and the fix

You can learn it in one afternoon.

30 minutes here replace what most people spend a year figuring out.

Watch it today, then read the guide on building loops below.

[Codez @0xCodez]

Andrej Karpathy just dropped a 6-hour course on how to build LLMs from scratch:

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

This course will replace a $90K Stanford LLM master’s degree.

Start watching today, then read how to become an AI engineer in article below.

[Anatoli Kopadze @AnatoliKopadze]

A Google Cloud engineer just showed how to build a full app with Claude from scratch.

He spent 26 minutes showing exactly what one person with Claude can do, completely free.

The exact workflow they use at Google, no team, no prior experience needed.

Worth more than any $500 vibe-coding course.

Watch it, then read the guide below on the Claude features 99% of users never find.

[Roan @RohOnChain]

My friend applied to 200 tech jobs in two years. No PhD. No Stanford.

Last month Anthropic offered him $750,000.

I asked him how he broke in from zero.

He sent me a course that was never supposed to get out. A 3-hour video to build a full LLM from scratch.

A developer teaches you exactly how LLMs like ChatGPT and Claude are actually built.

I watched it last night.

Halfway through, I realized it's embarrassingly simple to break into an AI lab.

Bookmark this and read the article below.

• 00:00 - intro to LLMs
• 05:43 - LLM transformer architecture
• 40:24 - training the LLM
• 1:30:27 - modernizing the LLM
• 2:33:53 - scaling the LLM

[Codez @0xCodez]

Google just dropped a 1-hour course on agentic engineering from scratch:

00:00 – How to build your first AI agent
08:24 – Build agent memory (short, persistent, long)
28:34 – Agentic loops, long-running AI agents
40:04 – How to build MCP (MCP vs API)
1:00:22 – Multi-agentic systems

This 1-hour watch will replace 10 paid agentic courses on the internet.

Watch it today, then read how to build a self-improving agentic system in the article below.