AI-powered IDEs can help you get projects done quicker with multiple agents working together.
In this course, Ania shows you how to build and deploy an app using TRAE IDE's AI-powered development workflow.
You'll learn about multi-agent collaboration, AI-assisted planning, full-stack development, and more.
https://t.co/6RgIEfNt53
A Holomorphic Map Turns Every Arrow the Same Way
A complex-differentiable map f = u + iv looks, up close, like multiplication by one complex number f'(p).
So its differential is complex-linear: df(zX) = z df(X) for every complex z.
Top row: X and zX at the point p, and the image df(zX) at f(p).
Bottom row: X alone, its image df(X), and z df(X).
The two coral arrows on the right are always the same arrow, while z turns and stretches.
When z = i this is exactly the Cauchy-Riemann pair
du/dx = dv/dy, du/dy = -dv/dx
and the live values at p (for f(z) = i e^z) stay equal the whole time.
The grid lines through p and their images cross at right angles: the map is conformal.
Google Intelligent Eyewear hands-on: Gemini, a camera and speakers on your face
Google’s intelligent eyewear is finally here with a launch price and date. It teamed up with Samsung, Gentle Monster and Warby Parker to put its Gemini AI into stylish frames for your face. Here’s how our experience with some preview units went.
The Complete LLM & Generative AI Developer Stack (2026)
Building AI applications is no longer just about choosing an LLM.
You need the right ecosystem of tools to build, connect, retrieve, evaluate, and deploy intelligent applications.
Here's a developer roadmap covering 9 essential categories:
LLMs: GPT, Gemini, Llama, Claude, DeepSeek, Qwen, Mistral
Frameworks: LangChain, LlamaIndex, Haystack, txtai
Vector Databases: Chroma, Pinecone, Qdrant, Milvus, Weaviate
Data Extraction: Crawl4AI, Firecrawl, ScrapeGraphAI, Docling
LLM Platforms & Inference: Hugging Face, Ollama, Groq, Together AI
Text Embeddings: Nomic, Sentence Transformers, OpenAI, Voyage AI, Cohere
Evaluation: Giskard, Ragas, DeepEval, Promptfoo, TruLens
Observability: Langfuse, LangSmith, Arize Phoenix, Helicone
Agent Frameworks: CrewAI, AutoGen, LangGraph, OpenAI Agents SDK
What should you learn first?
Start with Python, understand how LLM APIs work, build a RAG application, explore vector databases, and then move towards AI agents.
Don't try to learn every tool at once. Build real projects and understand when to use each technology.
📚 Learn AI & Agentic AI:
• AI Fundamentals for Beginners: https://t.co/fgXUlXFhhI
• Learn Agentic AI & Build Multi-Agent Systems: https://t.co/6YL07X3nMO
Save this roadmap and share it with someone learning Generative AI!