Stay informed with the latest product releases, launch announcements, and market insights from the SmaugBrain team.
Learn how to build observable AI agent systems with structured logging, metrics, and distributed tracing. A practical guide for production AI agent operations.
Learn practical strategies to reduce AI agent operational costs by 40-70% through model tiering, context management, caching, and monitoring.
<p>Learn how to select and implement the right AI agent orchestration pattern for your production environment. Compare sequential, parallel, and hierarchical patterns with practical examples.</p>
Comprehensive guide to securing AI agents in production — threat models, defense-in-depth patterns, prompt injection defenses, and implementation checklists for reliable autonomous systems.
Learn how to measure, optimize, and scale AI agent performance. Practical guide covering latency reduction, throughput scaling, and common pitfalls.
A comprehensive guide to testing and validating AI agent systems for production deployment, covering tool reliability, decision logic, workflow testing, monitoring, and security.
Learn the practical strategies for prompt engineering and context management that separate prototype agents from production-grade systems.
Learn how to build reliable AI agent tool calling with proper parameter validation, error handling, and retry patterns for production systems.
Learn practical strategies for managing context windows in production AI agents, from chunking techniques and summarization pipelines to cost optimization and error handling.
Learn how to detect and respond to performance drift in production AI agent systems with practical monitoring strategies and implementation checklists.
Learn how to implement comprehensive observability for AI agents in production.
<p>Learn how to balance AI agent autonomy with human oversight using proven human-in-the-loop patterns for production systems.</p>
Production-ready integration patterns for AI agents: direct API calls, database middleware, event-driven architecture, ESB integration, and GraphQL federation with security and observability best practices.
A comprehensive guide to managing agent state in production — from session persistence to distributed checkpoints and event sourcing.
Learn how to design and implement multi-agent AI systems with coordination patterns, failure handling, and production best practices.
Retrieval-Augmented Generation (RAG) has become the standard approach for giving AI agents access to domain knowledge without retraining. This guide covers architecture patterns, embedding strategies, retrieval pipelines, and production considerations.
Comprehensive guide to decision intelligence for AI agents: exploration vs exploitation, MDPs, decision trees, utility theory, and production patterns.
A practical guide to sequential, parallel, hierarchical, and graph-based AI agent orchestration patterns for production systems. Learn when to use each pattern with real-world examples and decision frameworks.</p>
Production AI agents face errors constantly. This guide covers practical error handling and recovery strategies for building resilient AI agent systems.
Production AI agents face errors constantly. This guide covers practical error handling and recovery strategies for building resilient AI agent systems.
Production AI agents face errors constantly. This guide covers practical error handling and recovery strategies for building resilient AI agent systems.
Production AI agents face errors constantly. This guide covers practical error handling and recovery strategies for building resilient AI agent systems.
Learn how to test AI agents effectively with practical strategies, evaluation metrics, and a production readiness checklist. Covers unit testing, integration testing, semantic validation, and common pitfalls.
Learn essential security practices for AI agents in production — from authentication and authorization to injection prevention and monitoring.
Learn how to build compliant, auditable AI agent systems with practical governance frameworks, audit trails, and human-in-the-loop design patterns.
Learn how to deploy AI agents to production with proper architecture, testing, monitoring, and reliability patterns. A practical guide for engineering teams building autonomous systems.
Learn how to deploy AI agents to production with proper architecture, testing, monitoring, and reliability patterns. A practical guide for engineering teams building autonomous systems.
Learn how to deploy AI agents to production with proper architecture, testing, monitoring, and reliability patterns. A practical guide for engineering teams building autonomous systems.
Learn how to deploy AI agents to production with proper architecture, testing, monitoring, and reliability patterns. A practical guide for engineering teams building autonomous systems.
A production-ready framework for preventing data leaks in AI Agent systems covering input filtering in-flight encryption output sanitization and monitoring patterns.
Read the guide to set up your Agent, review your plan, and continue in your workspace.
