n8n close to release v3 💀 and some users still using 1.x.x

BTW Don’t update to the latest 2.9.*. It’s full of UI bugs 🤡

Still working on the n8n workspace. It’s an NSKHA website for n8n tools that combines all our n8n projects in one place.

n8n Manager started as a shell script (https://github.com/Automations-Project/n8n-data-manager). Now it has grown into a 30K+ line CLI, and it still works as pure shell. (V5 still not released public)'

Because it contains a lot of features and settings, I’m building a frontend form builder to generate direct commands for n8n Data Manager, like backups and restores. It includes all the features we need for our clients. And yeah, it does exactly what n8n Enterprise does with environments. In fact, the new shell syntax is built to be compatible with environments, so when you have enterprise clients, they can still use it to link between free instances and enterprise ones.

It also has a nice UI and a very interactive CLI that guides newbies. At the same time, it supports importing data directly from URLs, like importing workflows from direct S3 URLs and similar sources.

Data types? It includes five modes: full, workflows, creds, enterprise, and database.

1. Full: in and out for workflows, creds, folders, tags, projects, and tables.

2. Workflows: in and out for workflows, single or bulk.

3. Credentials: in and out for creds with three types: pure creds (danger), encrypted, and stubs (schema only, no values, best for clients).

4. Enterprise: in and out, exactly the same as the default settings of n8n Enterprise environments.

5. Database: get a dump of the entire n8n database as a single compressed file.

n8n Manager doesn't stop here. Shell update was already done a few months ago but still not released because it relies on other projects. two more projects linked.

- Data Manager VS Code: an IDE extension that helps you deeply vibe-code and fix workflows. It converts n8n workflows into a framework where every part of the n8n workflow is treated as a file, giving the AI low context to work with, saving your budget and getting better results.

The extension itself is used to initialize workflows from your n8n Cloud. Once vibe-coding is done, it builds everything back into a new workflow and uploads it.

- n8n Manager Nodes: a package of custom nodes (currently four) that brings n8n features inside n8n. This includes a backups node, an internal API node, an instance sync node, and a refactored version of an official node with bug fixes and improvements.

these tools are already used by our clients, and bugs are actively fixed. So when this stuff is released public, you get battle-tested tools

And the final really big projects are:

- Node Builder:

It’s an npm package linked to an AI that can build any n8n node from Postman, OpenAPI, or Swagger into a fully functional n8n node. It’s trained on the n8n project itself, and the npm package and its CLI generate all files from A to Z for future node development. Even GitHub issue reports are generated. The user only pays for AI credits and provides the node’s SVG logo and the collection URL or file, then comes back after about 15 minutes to get a fully tested node. (I’ll release a node built with this CLI soon, and I believe it will be better than any node we’ve created before.) It’s linked to a web UI because the Node Builder needs some input, like GitHub and npm tokens. We’ll make it very interactive for newbies, so the n8n community can create nodes every day, just like they create workflows.

- Docker Builder:

A CLI that installs n8n fully configured with one click. where you can build your one line link to share with client to install

Converting n8n workflows into files gives you the ability to use an IDE at its full power to edit complex n8n workflows. I already stated before that we should feed the AI with the n8n files.
reddit.com/r/n8n/comments/1q4qx4f/two_years_ago_i_began_asking_people_to_give_ai/

I don’t care if they feed it or not because we own the #1 GPT for n8n. We almost have control over prompting for millions of users, so once all our projects are done, I will change the GPT to fully promote the new tools and push the n8n framework into daily use.

Why do I believe it’s going to be a used?

- It solves a real problem if you’re dealing with A.I + n8n workflows.

- It optimizes the cost of investigating workflows.

- There are already baked-in tools to help you do it.

🤟- Everything is free, nothing is paid. nskha is just community users, we got our money from our clients not community users, though it still will benefit us getting clients so somehow we are getting paid in other ways while you free user will not get paywall.

Why is the n8n framework going to save budget? Is it only about minifying files before sending them to the AI, as stated: reddit.com/r/n8n/comments/1q47uai/newbies_reminder_sharing_n8n_workflows_with_ai/

No, it’s called a framework because it treats the workflow as a framework. There are no expressions or JS code inside the workflow file. Instead, there are only $ref pointing to files that contain the actual data.

This is going to give you:

- Savings in cache budget. If the IDE sees that a file hasn’t been edited, it won’t send it again as new context code.
- Smarter IDE indexing by focusing only on the real data you care about. On each edit, there’s a history for that file, so the AI can know exactly what was updated and where.
- A final step of data minification, where the IDE already safely supports Python and JavaScript minification, allowing the AI to work with a much smaller context.
- All of this without even mentioning the linked skills and npm scripts + linting, which the AI should always check.

Today I built a prototype of what an n8n competitor does.

You know there’s a competitor to n8n that many enterprise companies move to called Airbyte. This n8n competitor has a very smart and advanced idea: it updates the workflow based on historical data.

Let’s say you’re mapping automation data between two services, for example Airtable to Google Sheets. The data is dynamic, and on each request, new fields can be added or removed. Airbyte can generate a mapping schema based on all tested data from previous executions. This avoids errors or workflow stops when something changes between the two sources.

This feature honestly made me sad about why n8n doesn’t have it, even though it feels like a basic idea. You just grab execution data, generate a schema of all possible keys, and build a final full schema. That schema can then be used to build expressions or JS code that accepts all possible keys, along with their types and other metadata.

I cloned this idea into n8n-manager. I fetch all workflow inputs and outputs, then generate multiple schema types for each node’s operation output. In the end, I get schema files for each node. When an AI developer looks at this, it can automate the most accurate results for that workflow without reading tons of raw data or repeatedly tracking executions.

If there’s a problem in a specific node, you can get all its outputs as a compact schema of keys, plus an example of the latest schema with real data. The AI can see the actual output values, but in a combined form from multiple workflow executions. This gives much better debugging for AI, and its answers become way more accurate and cover more edge cases.

This isn’t fully integrated into n8n-manager yet. For now, I’ve made npm scripts for live testing on a real client project.

don’t update to 2.11.1 if you’re on an arm64 server. n8n is currently broken on arm servers with that version.

2.11.0 safe.

💀I keep getting a lot of failing upgrades/deployments due to bugs and breaking changes in recent n8n versions. I asked my clients to stick with 2.11.0 for now.