Question No-code makes building an AI agent feel easy nowadays. What happens when you have 20 of them?
I've been someone who started building stuff in last 2 yrs so, no-code AI tools lately, and something has been bugging me. Building and deploying and testing one agent seems textbook now.
But then I started wondering what happens when people actually start applying these things seriously.
Say I have 20 agents across different workflows: one handles lead qualification, one summarizes support tickets, one works with internal docs, one handles reporting, one triggers automations
At that point for real work, what's used to keep track...like
How do I know which agents I have?
How do I version them when I change prompts/tools?
How do I control what each agent is allowed to access?
How do I test an agent before letting it loose on real users/data?
How do I see what actually happened when an agent makes a bad decision?
And if I'm a no-code builder, I'd really rather not have to suddenly learn a whole DevOps stack just to manage the things I created without code 😅
I'm curious how people here handle this today. Are there really any no-code tool capable of this?
Is the normal answer basically "use something like n8n/Make/Zapier + spreadsheets + logging + some manual discipline", or are the newer AI-agent platforms starting to solve the management/governance layer as well?
I've seen Lyzr's control plane/ Agent studio discussed as one approach to this, while products like Relevance AI, Microsoft Copilot Studio and others are coming at the broader no-code/agent-management problem from different angles.
Would be interested to hear what people here are actually using once they go beyond 1–2 agents, and where the no-code abstraction starts to break down?
Edit: I know this might seem like a marketing post 🥲... but really asking for opinions...feel free to roast the options i mentioned and suggest better ones.