It doesn't matter what tools you use for AI Agents. I've put together the ultimate curriculum to learn how to build AI agents. (bookmark it) From context engineering to evaluating, optimizing, and shipping agentic applications.
As usual, Anthropic just published another banger. This one is on context engineering. Great section on how it is different from prompt engineering. A must-read for AI devs.
this was based on the brilliant textbook: "Foundations of Large Language Models" by Tong Xiao and Jingbo Zhu (NiuTrans Research Lab) arxiv: arxiv.org/abs/2501.09223… highly recommend it if you're serious about understanding LLMs deeply.
I finally understand how large language models actually work After reading the 2025 textbook “Foundations of LLMs” It blew my mind and cleared up years of confusion Here’s everything i learned (in plain english):
Build a Multi-agent app with MCP using Google ADK without writing a single line of Python Code, in simple YAML. All of this in ~5 mins. Step-by-step tutorial with opensource code:
We are launching a 5-Day AI Agents course on Kaggle. Learn about AI Agent patterns, agent tools, context engineering, memory management, agent evaluations and building production grade multi-agent systems with A2A. 100% free and open to all.
I think we ALL want
📁 Matthew McConaughey says he wants a private LLM, fed only with his books, notes, journals, and aspirations, so he can ask it questions and get answers based solely on that information, without any outside influence.
Introduction to Reinforcement Learning. The only book you need to fundamentally understand how agents learn optimal behavior through trial and error. 100% free to read.
AI Agents can now turn research papers and URLs into working code. DeepCode uses multi-agent systems to convert PDFs, text prompts, and URLs into complete production-ready codebases with frontend, backend, and algorithms. 100% Opensource.
R.I.P Perplexity. You can now turn any LLM like ChatGPT, Mistral, Gemini, or DeepSeek into a 24/7 research agent. Here’s the exact mega prompt I use to automate all research for free:
link: kaggle.com/whitepaper-pro… my notes: OVERALL ADVICE 1. Start simple with zero-shot prompts, then add examples only if needed 2. Use API/Vertex AI instead of chatbots to access temperature and sampling controls 3. Set temperature to 0 for reasoning tasks, higher (0.7-1.0) for…
Google literally published a 69-page prompt engineering masterclass
Practice your #XSS muscles. x55.is/brutelogic/gym
x55.is
XSS Gym - Train your XSS Muscles
More than 30 different XSS cases to play with, show and share XSS Proofs-of-Concept (PoCs).
This guy literally dropped the best hands-on AI agents repo you’ll ever see
¿Sabías que podés manipular lo que responde una IA… y ni siquiera es hacking tradicional? 🤖 ¡Nuevo webinar! “Prompt Injection vs. Jailbreaking: ¿En qué se diferencian y qué amenazas representan?” dictado por Cristian Cardelino. 🚀 🤓 "Prompt Injection" y "Jailbreaking" son…
There is no better place on the internet to learn about Context Engineering than this repo. It's literally a course with a learning path. It gathers the best resources and covers the theory + code for anything related to context, RAG, memory, and agentic systems and more.
BREAKING: AWS just solved the biggest AI agent bottleneck. No more custom glue code. No more M×N tool chaos. No more protocol headaches. Introducing: Amazon Bedrock AgentCore Gateway Here's how it works:
this is over.. for traditional film studios Higgsfield just dropped Product-to-Video, you can now drop any product into any environment and.. the actor can even interact with it this is best way to do product commercial with AI.. for free here's how:
A graph-powered all-in-one RAG system! RAG-Anything is a graph-driven, all-in-one multimodal document processing RAG system built on LightRAG. It supports all content modalities within a single integrated framework. 100% open-source.
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