“architecture”
The "Tool-Discovery" Protocol: How Gemini 3 Agents Find and Map New Capabilities
Build truly autonomous, self-expanding AI applications using the Tool-Discovery Protocol. Learn how Gemini 3 agents dynamically browse, map, and bind new API capabilities on the fly.
Choosing the Right Multi-Agent Pattern: Balancing Complexity and Cost
Explore the primary multi-agent patterns—from single agents to sophisticated coordinators—and learn how to choose the right one for your AI project based on task complexity and budget.
AI APIs vs. Local Models: A Developer's Guide to Choosing the Right Tool
Should you use an API like Gemini or run a local model with Ollama? We compare the pros and cons of each approach for developers.
The 2026 Guide to Vector Databases: Choosing the Right One for Your AI App
A comprehensive guide to choosing the right vector database in 2026, comparing top options like Pinecone, Weaviate, Milvus, and pgvector.
Designing Agent Skills for Enterprise Environments
A comprehensive guide on balancing operational efficiency, standardized architecture, and security when designing AI Agent Skills for organizations.
Building an AI-Powered Publishing Studio with ADK: A Multi-Agent Approach
Explore how a multi-agent system built with the Agent Developer Kit (ADK) can automate and optimize the entire publishing pipeline from research to editing.
Integrating AI Agent Skills: Filesystem vs. Tool-Based Approaches
Explore the two primary methods for integrating skills into AI agents—direct filesystem access and secure tool-based execution—and learn which is right for your project.
Building Autonomous Agents with the Google ADK
A deep dive into the architecture and capabilities of agents built with the Google Agent Development Kit (ADK), exploring skills, tools, and security.