n8n

A basic AI Agent connected to an OpenAI model worked in the previous version but throws a null property error after upgrading.

Affects: n8n cloud users

After upgrading, the editor cannot keep its websocket connection when run behind an nginx reverse proxy.

Affects: Self-hosters behind a reverse proxy

With a Gemini model the workflow errors on the model, while swapping to GPT-4o makes the same MCP workflow work perfectly.

Extracting text from a roughly 300 KB PDF uploaded through the Form node stops with an out-of-memory error on a self-hosted Docker install.

Affects: Self-hosted Docker users

Clicking next on a multi-page form trigger produces an endless loop instead of advancing, which worked before 2.0.

Affects: Self-hosted users

Affects: n8n cloud users running MCP agents

Affects: Admins running n8n on AWS

Affects: Startup using n8n as a backend

Affects: Teams using queue mode with workers

Affects: Power users

Affects: Self-hosted Docker users

Affects: Self-hosters on Railway

Affects: Windows users

Affects: Microsoft 365 users on n8n cloud

Affects: Self-hosted Postgres users

Affects: Self-hosted Docker users

Affects: Users of Vertex AI models

Affects: Self-hosted users

Affects: Teams self-hosting n8n with non-technical users

Affects: Users building AI agents with memory

Affects: Docker users

Affects: Users with Postgres chat memory

Affects: Self-hosted users

Affects: Users processing email or spreadsheet data

Affects: Self-hosted Docker users

A consultant building automations for clients wants a first-party way to turn an n8n workflow into code when the client needs a full app. Migrating from n8n to code is currently a worry.

Affects: Consultants building automations for clients

Compared with Node-RED, n8n lacks a dashboard component for watching a running system. The author calls this a gap for monitoring live workflows.

Affects: Engineers running production AI workflows

The SSO support is described as lackluster and user permissions management is weak. The team says this stops n8n from being truly enterprise grade.

Affects: Organizations adopting n8n at enterprise scale

With DeepSeek through Ollama in an AI Agent, the think block makes valid JSON output impossible to parse. The user wants an option to remove it.

Affects: Users running reasoning models locally

AI nodes time out after five minutes, which makes them unusable with slower local models. The user asks for an environment variable to configure the limit.

Affects: Users running local LLMs

Affects: Small business owner

Affects: Developers who prefer Python or other languages

Pulling any n8n image after 2.3.0 fails during layer extraction, and the only fix found was pinning the older version.

Affects: Self-hosters on older Docker

After about 30 minutes the polled Entra node fails with an expired token. Retrying does not help but opening and closing the node revives it.

Affects: Self-hosted users

After hitting execution limits even with their highest enterprise license, the team coded alternative paths for their use cases and stopped using n8n.

Affects: Startup evaluating n8n as backend

The author found maintaining all workflows in the GUI too time consuming and moved to an in-IDE tool, saving about 80% of the time.

Affects: Developers with an existing Next.js app

After trying n8n, Make and Zapier, the author found that a single change can break a whole automation. This and the setup time led them to build a different agent platform.

Affects: People automating multiple workflows

The team valued n8n's step-by-step visibility but needed more customization and deeper control, so they moved to a code framework.

Affects: Teams building AI agents

The author hit 3-5 second execution times and needed custom scripts inside visual workflow tools. They built their own code-first engine for heavy workflows.

Affects: Developers building complex workflows