Google just released free 1-hour course on building agentic knowledge Graphs from 0% to 100%: 10% → 4:01 - how to build a GraphRAG agent 30% → 15:00 - Graph Engineering explanation 55% → 30:00 - Agentic search Engineering 80% → 35:48 - Graph Engineering practice 100% → 47:06... - self-improving agents in graphs this free Google course mass replaces a $500 graph engineering bootcamp - learn it in 60 min to 100% watch it today - then read the full graph playbook in the article below ↓show more

more and more alpha on Graphs from Codila, thanks

happy that you like it! I’m try to give what I use myself and hope it’s also useful for you

lowkey opening X is the fastest way for me to feel behind. bro wtf is this graph engineering. a few days back i heared about loop engineering. are not they same.

the self-improving agents section is the actual hard part in practice how does it handle cycles when the graph contradicts itself mid-run

100% graphs skills from one Google course? no way man, what a brilliant material

yeeeees, this 1-hour video is REAL practice, after that you personally will can make the same so glad that it's useful for people

Mostly they do colab such as Kaggle Vibe Coding one

i didn't know google had such free lessons

they have so many good lectures, will share it after once I’ve studied

Strong free resource on the capability side. Once these systems move from notebook to production and start spanning tools and models, the harder operational question becomes: can you still reconstruct what the agent was authorized to do, what it actually did, which model ran, and whether the declared constraints held — after the fact, by a stranger.

now i understand graphs 100% thanks for another alpha

in other words, get you to use more tokens to make money. Prompting doesn't make enough. They need thousands of agents regurgitating what is already known.

A free hour replacing a $500 bootcamp, saving this now

Ok I will send my agent watch it for me.

@grok 元動画のリンクを探して

ngl the $500 bootcamp guys are having a very bad tuesday rn 💀

what's the practical use of this?

Graph engineering is the part everyone skips and then wonders why retrieval quality is bad. good that it's getting its own chapter here

sheeesh codila! underrated point. a great agent with a bad harness is still a bad agent

agentic workflows are starting to look less like a prompt and more like assembling a small engineering department

Don’t let the “master 100% in one hour” claim fool you. The real value isn’t memorizing terms like GraphRAG or agentic search—it’s learning to model agent states, dependencies, and feedback loops explicitly. The course gives you the map; real engineering skill still comes from building, evaluating, and debugging actual systems.

@grok is it worth it ? Google is super behind you and Claude are better

she is superstar

graph engineering is getting viral

Free courses raise the floor. They rarely move the people who already know they should start.

@grok where can I find original video from Google?

60 minutes free and it covers the whole stack? Yeah I'm watching this today

this exactly what i’m looking for

I didn't know Google could still do something related to neural networks

from where u got? can u provide me the link.

Worth watching ❤️

She is so hot!

It's surprisingly common. The more rules you add, the more the model spends its attention following instructions instead of solving the problem. Simplicity is often an optimization, not a compromise.

Please don't attribute non official work to @Google