Hey everyone,
For the past several months we've been building something that came out of a frustration most of you probably know well.
We love n8n for what it does. But the moment a workflow needed real agent behavior, document retrieval, approval checkpoints, and full observability in the same place, we kept fighting the platform instead of building. It wasn't designed for that and it's not a criticism, just a different problem.
So we built Heym. Self-hosted, source-available, visual canvas for AI-native workflows. Multi-agent orchestration, built-in knowledge retrieval, human review checkpoints, MCP support. Launched today on Product Hunt and the repo just went public.
We're two engineers and genuinely curious: for those of you building real AI workflows with agents and orchestration, what's the part that breaks down most often in your current stack?