GenAI

Our AI visualizations worked 'pretty good'—which turned out to be the problem. Here's what we learned about building products during a massive technology shift, and why we now ship early, kill projects faster, and retry failed ideas every few months

Developer experience in the age of vibe coding

Design robust multi-agent AI systems in Google Cloud.

Strategies and parameters you can tune to improve the performance of Retrieval-Augmented Generation (RAG) applications for production.

In this blog piece, you’ll learn why and how we built LangGraph for production agents—focusing on control, durability, and the core features needed to scale.

Manus approaches to context engineering.

The blog explores how to apply practical context engineering techniques using Agno to build AI agents that are faster, more efficient, and better at collaboration. It covers core techniques that include crafting precise system messages, selectively managing context to reduce token use, applying few-shot learning to teach behavior, and coordinating multi-agent teams effectively.

A collection of Open Source agent and audio components that you can customize and extend.

Join Ryan Cicak, Solutions Engineer at Databricks, as he explores the art of fine-tuning models using serverless GPU compute. Discover how to pull models from Hugging Face, fine-tune them with ease, and serve them via API.

This cookbook provides a practical, end-to-end guide on how to effectively use evals as the core process in creating a production-grade a...

Applying the scientific method, building via eval-driven development, and monitoring AI output.

This cookbook provides a practical guide on how to use the OpenAI Platform to easily build resilience into your prompts. A resilient prom...

The world's leading open-source editor framework for creating content editing experiences like Notion or Google Docs insanely fast.

MDXEditor is an open-source React component that lets your users edit markdown documents naturally, just like in Google docs or Notion.

Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.

Taking care of your context is the key to building successful agents. Just because there’s a 1 million token context window doesn’t mean you should fill it.

In this article, we will understand the architecture of the multi-agent research system that Anthropic built.

How to test agent ideas in hours using Claude Code SDK without building orchestration infrastructure - proven methodology from consulting engagements

Agentic Design Patterns A Hands-On Guide to Building Intelligent Systems, Antonio Gulli Table of Contents - total 424 pages = 1+2+1+1+4+9+103+61+34+114+74+5+4 11 Dedication, 1 page Acknowledgment, 2 pages [final, last read done] Foreword, 1 page [final, last read done] A Thought Leader's ...

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