GenAI

Agentic systems often reach a plateau after proof-of-concept because they depend on humans to diagnose edge cases and correct failures. T...

As AI agents powered by Large Language Models (LLMs) become increasingly versatile and capable of addressing a broad spectrum of tasks, ensuring their security has become a critical challenge. Among the most pressing threats are prompt injection attacks, which exploit the agent's resilience on natural language inputs -- an especially dangerous threat when agents are granted tool access or handle sensitive information. In this work, we propose a set of principled design patterns for building AI agents with provable resistance to prompt injection. We systematically analyze these patterns, discuss their trade-offs in terms of utility and security, and illustrate their real-world applicability through a series of case studies.

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...

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...

Tech debt and comprehension debt

A practical guide to Agent Engineering: the intersection of software, systems and security engineering.

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.