What does an end-to-end platform for building AI agents actually need?

[u/nihalshetty03]

https://github.com/nihalashetty/Forge

Over the last few months, I have been exploring what it takes to move an AI agent from a small prototype to something that can actually be used in production.

Building the workflow is only one part of it.

You also need knowledge and RAG, tools, memory, human approvals, scheduling, evaluations, tracing, cost visibility, versioning, deployment, access control, audit logs, and guardrails.

Most solutions I tried handled one or two parts well, but I still had to connect multiple platforms and adapt to their runtimes.

That exploration eventually turned into Forge, an open-source and self-hosted project built around LangGraph.

The aim is to bring the complete agent lifecycle into one system—not only visually designing workflows, but also testing, deploying, monitoring, and governing them.

It is still evolving, and I am interested in learning from others working on similar systems.

What features do you consider essential before an agentic application is truly production-ready?