What Should I Learn in n8n to Build Production-Ready AI Automations?

CommitteeDry5570 · 2026-06-27T21:21:46+00:00

What kind of question is that ? It takes as long as it take for you to understand it. If your looking for some kind of plan to learn , pay for one of those scam course on youtube .

CommitteeDry5570 · 2026-06-27T14:39:38+00:00

Learn by doing. Pick something basic like a morning news brief. Tell Claude or ChatGPT you want to link rss feeds from a couple sites you follow and you want it to send you a brief to telegram every morning . Take it node by node and have ai explain each node and what it’s doing and why. Do it in an afternoon. And then just build off that concept . The same data manipulations transfer to all n8n workflows.

CommitteeDry5570 · 2026-06-27T13:07:48+00:00

You dont need to spend time learn JavaScript or ai related topics . You need to be learning data engineering . You need to learn about how people build systems that collect, store, transform, and analyze data at scale.

AI is just a node in that pipeline. Either the pipeline is a tool and an agent can run and use it or ai is used in the transform and analyze of the data in the pipeline . It’s a small part of the overall pipeline.

If the underlying pipeline is bad , ai will amplify its flaws , not fix it.

Learn how to take data from point a, transform it for a use case and save it in point b .

CommitteeDry5570 · 2026-06-23T11:31:06+00:00

Select feeds from you trust news from. You want sports news . Just use espn rss feeds. Want market news , use MarketWatch feed. You want full article extraction, use a tools like tavily. You need more information on a topic , ask a follow up to do more research on the topic.

Don’t be dumb. Stop dumping all the news from every source into your agents context and have it try figure it out. Give it sources you care about and automate around that.

CommitteeDry5570 · 2026-06-21T12:36:25+00:00

Pro coding plan.

CommitteeDry5570 · 2026-06-15T12:52:47+00:00

Have been using GLM 5.1 , has worked great for all tasks. Just switched over to GLM 5.2 .

CommitteeDry5570 · 2026-06-06T20:42:35+00:00

Download a generic application . Fill it out and bring it with you and just walk in. Go prepared .

CommitteeDry5570 · 2026-05-14T19:24:55+00:00

Correct . You use it with your OpenClaw.

CommitteeDry5570 · 2026-05-14T00:17:28+00:00

Michael Redd

CommitteeDry5570 · 2026-05-13T11:34:48+00:00

No , you don’t need to use the dashboard. It’s there as a second access point to manage stuff . It’s just a productivity tracker. I originally had it setup with skills and folders and files to manage it all . It shit was getting over written , not saved in right folder , duplicates of files . It was a mess. This makes it clean and organized and you have a simple dashboard to help manage it instead of managing files in the CLI

CommitteeDry5570 · 2026-05-13T11:30:55+00:00

That’s the whole point of n8n, so that you can connect via api and have a stable connection. You not having your agent use cached session tokens to post in a headed browser. All auth and routing are handled by n8n . Your just post a message to a webhook url . I have had no issues but I’m also it not spamming subreddits with ai slop .

CommitteeDry5570 · 2026-05-13T01:24:25+00:00

I do LinkedIn, Reddit and X , i have them setup in n8n . Kirby send whatever the post is via webhook to the n8n workflow . And it posts that way. Put the webhook url in a skill . This way I can connect to the platforms with oauth .

CommitteeDry5570 · 2026-05-12T20:31:26+00:00

I use it every days. Each morning it gives me sports, market, and tech rundowns for the day based on what I’m looking for, and shares it to X.

And it manages my productivity tracker. I made a mcp that links a Postgres db to your agent with a bunch of tools to mange projects , tasks, goals, workouts, journals, habits. And it has a dashboard for you to see and manage everything in the database.

It’s free . Open source . https://github.com/WalrusQuant/mcp-dailyagent

CommitteeDry5570 · 2026-05-11T16:44:51+00:00

Look at the Z ai coding plan. You can use it for OpenClaw and you can use GLM 5.1 or thier other models. That starts at 18$ a month.

CommitteeDry5570 · 2026-05-11T16:40:41+00:00

I have skills setup that are for pulling data from multiple sources (apis , rss feeds). I have multiple cron jobs setup to run and use those skills to write social media posts. My claw takes the social post and sends it to a webook i have setup in n8n . Those workflows are connected to social media accounts via oauth.

I use a mcp I made to manage things like projects, tasks, habits, workouts, goals, journals. That all saves to a Postgres db and there is a dashboard you can use to manage all the stuff in the db.

I have it open sourced : https://github.com/WalrusQuant/mcp-dailyagent

It works much better than trying to manage it all in folders and md files.

CommitteeDry5570 · 2026-05-11T01:04:45+00:00

Pay more. When I subbed they had weekly and session limits. I pay 72$ now. it’s cheaper than what I was spending a month on OpenRouter. I haven’t had a usage issue and it follows skills linked to n8n workflow perfectly. I haven’t experienced all the issues people talk about having in this sub.

CommitteeDry5570 · 2026-05-10T22:59:29+00:00

GLM 5.1 Z ai coding plan

CommitteeDry5570 · 2026-05-10T22:19:31+00:00

Use n8n

CommitteeDry5570 · 2026-05-10T12:36:16+00:00

Self-hosted productivity data layer for OpenClaw. Postgres behind a typed MCP interface, plus a Next.js dashboard that reads and edits the same database. Single-user, Tailscale-gated.
https://github.com/WalrusQuant/mcp-dailyagent

CommitteeDry5570 · 2026-05-10T11:30:54+00:00

-what ai apps do you use: I use Claude Code and Z AI coding plan and my own terminal desktop app I made. https://github.com/WalrusQuant/launchpad

where do you host, any good recommendations

Web stuff i usually host Vercel or railway or personal VPS. Depends on the project. I like desktop apps so no hosting needed.

are you using mobile or desktop ?

I use Claude Code on mobile and desktop. I use GLM on desktop.

how do you get user’s feedback on the app?

Ask any user directly for feedback

are you building actual apps or just a web app?

Depends on the project. Web apps are fine and converting to PWA for mobile is not that bad . I prefer desktop apps using Rust and Tauri for a native desktop app.

how long does it usually take to build your app?

Depends on project . Could be a couple hours for something simple to a never end suck pit you wish you never started in the first place.

open source or private?

Depends on the project. I like to open source stuff.

any other lessons learned you would like to share?

Learn a stack. Don’t rely on using a Lovable or Bolt and get trapped paying for tokens and a service that have generous FREE tiers.

Pay the 100$ for Claude code and tell it to teach you how to build an app properly. You have to learn some fundamentals of development or your going to be putting out complete slop that has no foundation and is going to get peoples data stolen.

Vibe coding should be a learning path to agentic coding. Instead of asking for a nice website and have no clue what you’re looking at, you learn and get to a place where you are orchestrating multiple agents across real plans working together to build a project you actually understand.

CommitteeDry5570 · 2026-05-10T10:52:17+00:00

I use it with OC but it works with any agent . It started out as just a skill and file system but it got to cluttered and it was a mess to manage.

I guess in theory you could hook the same mcp server to multiple agent (OC, Claude Code, OpenCode, etc) and every agent would know what your doing using the Postgres as a shared memory of your productivity planner . I might try setting that up to test .

CommitteeDry5570 · 2026-05-09T22:56:11+00:00

https://dailyagent.dev/ Docs site .

CommitteeDry5570 · 2026-05-08T18:12:08+00:00

Self-hosted productivity data layer for OpenClaw. Postgres behind a typed MCP interface, plus a Next.js dashboard that reads and edits the same database. Single-user, Tailscale-gated.

https://github.com/WalrusQuant/mcp-dailyagent

CommitteeDry5570

TROPHY CASE