🌊 Wave 151: AI Agent Engineering
Reviewed: June 4, 2026
The definitive guide to building production-grade AI agents — memory systems, orchestration, evaluation, and the skills that matter.
Wave 151 focuses on the engineering foundations of reliable AI agents. From memory architecture to multi-agent orchestration, these resources cover what it takes to move agents from demos to production.
📚 Articles
Deep-dive into agent memory architectures: working memory, episodic memory, semantic memory, and RAG-based retrieval. Includes 2026 best practices, code examples, and a production checklist.
How to coordinate dozens or hundreds of AI agents working together. Covers manager-worker, pipeline, swarm, marketplace, and hierarchical patterns with practical recommendations.
The 7 essential skills knowledge workers need to thrive in an AI-augmented workplace: orchestration, context engineering, critical thinking, and more. Includes a 6-month skill roadmap.
🛠️ Interactive Tools
Score your AI agent across 24 criteria in 6 categories: Task Completion, Reliability, Reasoning, Safety, Observability, and Scalability. Get a production readiness verdict with prioritized improvement suggestions.
🎯 Key Takeaways
- Memory is layered: Working, episodic, semantic, and procedural memory each serve different purposes. Production agents need all four.
- Orchestration pattern matters: Start with manager-worker. Add complexity only when the task demands it.
- Evaluation is continuous: Use structured frameworks to measure agent quality, not just vibes.
- Skills are shifting: The most valuable human skill is orchestration — designing and managing AI workflows, not executing them manually.
🌊 Wave 151 — Published May 28, 2026
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