Agent orchestration: code-based flow vs LLM planning
Search interest hit 480 monthly US searches by May 2026. Learn when to use code-based guards versus LLM planning for reliable agent flow.
Search interest hit 480 monthly US searches by May 2026. Learn when to use code-based guards versus LLM planning for reliable agent flow.
With 170,000 GitHub stars, OpenCode grows fast. Learn why default tool settings allow unrestricted bash access and how to enforce approval.
CrewAI 1.14.6a2 fixes state serialization for 54.7k-star repo, adding GPG verification and blocking environment variable leaks in tool execution.
With fewer than one-third linking AI to outcomes, agent orchestration provides the governance gates and cross-use memory engineers need.
crewAI 1.14.6 patches structured output leaks and enforces strict checkpoint restoration for reliable multi-agent orchestration in production systems.
CrewAI version 1.15.1 separates autonomous crews from event-driven flows, offering engineers precise low-level control without LangChain dependencies.
Enforce deterministic security before code enters repos. This layer validates 28+ entity types to block secrets in AI-generated artifacts.
With 51% of pros deploying agents, learn why LLM control flow matters more than chat for complex app logic and safety.
Agentic design patterns explained by build: the escalation rule, the four-beat verify loop, multi-agent token costs, and how to pick the minimum structure.