Context Engineering ebook
GenAI
Context Engineering 2.0: The Context of Context Engineering
Karl Marx once wrote that ``the human essence is the ensemble of social relations'', suggesting that individuals are not isolated entities but are fundamentally shaped by their interactions with...
The Era of Agentic Organization: Learning to Organize with Language Models
We envision a new era of AI, termed agentic organization, where agents solve complex problems by working collaboratively and concurrently, enabling outcomes beyond individual intelligence. To...
cubic blog: The real problem with AI coding
Tech debt and comprehension debt
ML Systems Textbook
Agent Engineering 101
A practical guide to Agent Engineering: the intersection of software, systems and security engineering.
Bitter lessons building AI products | Hex
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
Designing APIs for vibe coding
Developer experience in the age of vibe coding
You Still Need to Think
Multi-agent AI system in Google Cloud | Cloud Architecture Center
Design robust multi-agent AI systems in Google Cloud.
A Guide on 12 Tuning Strategies for Production-Ready RAG Applications
Strategies and parameters you can tune to improve the performance of Retrieval-Augmented Generation (RAG) applications for production.
Building LangGraph: Designing an Agent Runtime from first principles
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.
Context Engineering for AI Agents with LangChain and Manus - YouTube
Context Engineering in Manus
Manus approaches to context engineering.
Psychologically Enhanced AI Agents
Psychologically Enhanced AI Agents
Unleashing the Emergent Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-Collaboration
Context Engineering in Multi-Agent Systems
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.
LLMs Reproduce Human Purchase Intent via Semantic Similarity Elicitation of Likert Ratings
Agentic Context Engineering: Evolving Contexts for Self-Improving Language Models
ElevenLabs UI | ElevenLabs UI
A collection of Open Source agent and audio components that you can customize and extend.
Databricks Fine-Tuning: MLflow Sweep Comparison & Fast Model Serving Demo (Llama/ Unsloth)
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.
Learning through the Variation Theory: A Case Study
Evaluation-Driven Development of LLM Agents: A Process Model and Reference Architecture
Evaluation-Driven Development of LLM Agents
Unlike deterministic systems, an LLM agent’s output is often probabilistic, meaning multiple responses may be valid within a given scenario.
Eval Driven System Design - From Prototype to Production
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...
An LLM-as-Judge Won't Save The Product—Fixing Your Process Will
Applying the scientific method, building via eval-driven development, and monitoring AI output.
Building product evals is simply the scientific method in disguise. That’s the secret sauce. It’s a cycle of inquiry, experimentation, and analysis.
Building resilient prompts using an evaluation flywheel
This cookbook provides a practical guide on how to use the OpenAI Platform to easily build resilience into your prompts. A resilient prom...
Tiptap Rich Text Editor - the Headless WYSIWYG Editor
The world's leading open-source editor framework for creating content editing experiences like Notion or Google Docs insanely fast.
MDXEditor - the Rich Text Markdown Editor React Component
MDXEditor is an open-source React component that lets your users edit markdown documents naturally, just like in Google docs or Notion.
Effective context engineering for AI agents
Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.
Context Engineering Guide in 2025