Ai Agents
5 articles
Governing Enterprise AI Agents: A Three-Layer Architecture and an Ethics-to-Engineering Checklist
Enterprise AI agents require robust governance to prevent failures like data breaches or scope creep. This article presents a three-layer architecture and an ethics-to-engineering checklist to ensure responsible development and deployment.
Why AI Agents Can't Trust Their Own Reflection: Choosing a Self-Correction Architecture
AI agents struggle with self-correction due to a "self-correction blind spot," failing to identify their own reasoning errors. Prioritizing external verification mechanisms over internal reflection is crucial for building robust and reliable self-correcting AI systems.
Comparing AI Agent Architectural Patterns for SaaS Platforms
Integrating AI agents into SaaS platforms requires careful architectural decisions. This article compares key patterns like Single-Agent, Orchestrator-Worker, and Event-Driven architectures, detailing their trade-offs for scalability, complexity, and performance to guide your selection.
Emerging AI Agent Development Tools and Frameworks
Despite one-third of organizations citing quality as the biggest barrier to production, 57.
Google AI agents to conduct advanced searches for users
This summer, Google AI Pro and Ultra subscribers will gain access to specialized AI agents.