Agents on longer tasks need more than one loop
DeepLearning.AI course teaches multi-loop agent design for reliable long-running tasks
“completion of work does not necessarily guarantee quality”
DeepLearning.AI launched a course on designing feedback loops for LangChain-based agents, covering agent loops, verification loops, and optimization loops. The course addresses a real gap in agentic system design: task completion alone doesn't ensure quality, requiring layered feedback cycles. Relevant for practitioners building production agents but more educational content than a primary industry signal.