SpaceXAI engineer, Lauren Tan:
"GrokBot is the most powerful agentic tool we have ever shipped, but only 0.1% of users use it correctly
at SpaceXAI, I'm running a team of 15+ GrokBot agents. I have a Chief of Staff agent, 3 managers and 11 workers - that's the new engineering setup in 2026"
In a 1-hour talk, a SpaceXAI engineer reveals how to get 100% of every agentic tool you are using
worth more than a $500 agentic course on the internet
skip Netflix and watch today, it will change the way you use GrokBot forever, then read the article below
Google's Jeff Dean just dropped the best 1-hour lecture on AI engineering: from basics to Graphs
1:45 - LLM from scratch
17:22 - how to use AI models
30:03 - prompt engineering
52:35 - one human coordinating 100 agents
1:02:40 - where the coordination actually lives
27 years of building AI at Google, packed into one hour
Prompts → Agents → Loops → Graphs
most people will stop at the prompt engineering chapter and call it learning
he spends the last twenty minutes on the part that is still true next year
same model, same tokens, completely different week
watch it today
the full guide on graph engineering is below, save it while it is still early ↓
It was an honor to reunite with former President @iingwen, a courageous champion of democracy and a dear friend of America.
The bond between the United States and Taiwan is strong, and Congress’ commitment to the Taiwanese people and their freedom remains steadfast.
Taiwan received the first two of 66 F-16V Block 70 fighter jets from the US. 🇹🇼🇺🇸
No other country on earth will sell Taiwan a fighter jet. Not France, not Britain, not Japan, not any of the democracies that issue statements about Taiwan Strait stability. Every one of them has quietly decided its commercial relationship with Beijing outweighs Taiwan's ability to defend its airspace.
United States is the only country delivering these advanced variants of F-16 fighter jets equipped with AESA radar and latest generation avionics.
We'll be spending a lot more time trying to understand the outputs of language models. A few thoughts, tips & tricks:
Writing. Something I've had success with: Ask your LLM to explain something in ASD-STE100, it's a controlled language specification originally developed for aerospace maintenance documentation. LLMs well-versed in this language and it comes with heavy constraints on clean writing style that I often find a lot more readable. Sometimes I've tried to soften it a bit e.g. ask for "80% of the way to ASD-STE100" because the spec is quite stringent. But even better:
Diagrams / images. Instead of writing, ask your LLM to create a diagram. These can be a lot easier to process, parse, and understand. But even better:
Web pages. Ask for output "in HTML" to get a beautiful, interactive webpage. LLMs are getting really good at frontend and can create beautiful experiences, animations, etc. But even better:
Explainer videos. The output format I am most bullish on is fully custom / bespoke explainer videos generated on any arbitrary topic. Experiment with things like "Create a 3b1b style video explainer on X. Use my ElevenLabs API key for audio narration". (you'd need an API key for the latter or you can ask your LLM to find you decent free alternatives that use your local compute). This is actually starting to work!
In summary:
- As LLMs get better, they will do more and more of the legwork autonomously, and a lot more of our work will rise up the abstractions into oversight and understanding.
- Luckily, LLMs can help here too because as intelligence and code are increasingly abundant, you can ask for large, custom, discardable software artifacts (e.g. web apps, video explainers) that would have never made sense to create before. Push the boundaries here and you'll be surprised.
Anthropic pays $750,000+ a year for engineers who can build LLM architectures from scratch. Stanford taught the entire thing in 1 hour lecture & released it for free.
Bookmark & watch this today before someone takes it down ...
Sam Altman (CEO of OpenAI):
"Every night I have a few thousand agents running with GPT-6 Astra"
A few thousand AI agents, working overnight, monitored from his phone.
In 1 hour he shows what one person can build now, and how long that used to take a whole team.
Watch the him explain how, then read the full breakdown below👇