Episode 6: No-code and low-code agentic workflows
The sixth episode of our Agentic AI and agentic workflows series, on how visual no-code and low-code platforms are reshaping the way agentic systems are designed and deployed — from event-driven starts and knowledge retrieval to decision loops, tool use, and the moments where humans step in to guide or approve outcomes.
In this episode we explore how agentic AI is reshaping the way intelligent systems are built and deployed inside real organizations. Rather than treating AI as a passive tool that waits for prompts, we look at how to design systems that pursue objectives, make decisions, and coordinate actions across tools and data sources. We unpack how visual, no-code, and low-code platforms are changing AI development by making complex workflows easier to design, reason about, and evolve, while still leaving room for traditional programming where accuracy, control, or performance matter most.
We walk through how modern agent workflows are structured, from event-driven starts and knowledge retrieval to decision-making loops, tool usage, and the moments where humans step in to guide or approve outcomes. Through practical scenarios drawn from everyday business operations, we show how these ideas translate into working systems, and why safeguards, monitoring, and measurable outcomes are essential when agents operate at scale. It is a grounded look at building AI collaborators that can reliably support real work, not just answer questions.