The Testing Academy · Class Notes Sunday, 30 August (IST)
Live class · study guide

Running n8n on your own machine, and the six agents built on it

Yesterday was n8n in the cloud. Today it runs on your laptop, free, with Ollama as the brain, and then six agents get built on top: Jira fetch, Jira create, a local-model test case generator, bug triage into a spreadsheet, an RCA agent, and a social media poster. Includes the honest number on how AI-written posts actually perform.

By Pramod Dutta, The Testing Academy. Study notes from the live AI Tester Blueprint 4x class, rebuilt from the session recording and cross-checked against chapter_08_n8n in the AITesterBlueprint4x repository, pushed during the session. The six agent JSONs and three prompt files named here are the ones actually committed. No API keys are reproduced.

01

The local setup, free and yours

Yesterday used the n8n cloud trial. Today it runs on your own machine, which costs nothing and has no token limit.

Terminal
node --version        # anything above 13 is fine
npm --version         # version does not matter

npm i n8n -g          # same command on Windows and Mac
npx n8n               # prints a local URL, open it

You create an account on first run, and it is local, nothing leaves your machine. If you already had one and forgot the password, there is a user-management reset command rather than a reinstall.

For the brain, Ollama with a small model. Only the URL is needed; the API key field is optional.

Model Works on
Gemma 3 1B 8GB RAM and up
Llama 3.2 3B 8GB RAM and up
Local: n8n + Ollama 100% free, no token limits Nothing leaves the machine Slow. Integrations are harder. Only runs while your machine is on. Cloud n8n Fast, and Google or Jira connect easily Runs 24/7 on a public URL Metered. The quota ran out mid-class, after roughly ten tickets.
Learn on local because it is free. Deploy to cloud because it stays up.

The one that bites: not every local model can call tools. Gemma answered chat fine but could not drive the Jira agent, because it does not support tool calling. Switching to Llama 3.2 3B fixed it, and the agent then fetched a real ticket and generated a test plan. If your local agent silently refuses to use its tools, that is the first thing to check, and it is a model capability rather than a wiring mistake.

And the standing rule, repeated again: do not install this on a company laptop without permission.

02

The six agents

All six are committed in chapter_08_n8n/Agents/ as importable JSON:

# Agent Does
1 Fetch Jira ticket Reads a ticket by key
2 Create Jira ticket Files a bug from a description
3 Fetch Jira and create test cases, local LLM The same job on Ollama, no cloud
4 Bug triage The one below, and the one that matters
5 RCA automation Root cause on a production bug
6 Social media Schedule, write, illustrate, post
03

The bug triage agent

The shape is three nodes, and the whole thing is readable at a glance.

Jira, get manyAI agentGoogle Sheet JQL: type = bug,newest first, limit 50 priority, severity,first-pass verdict append a rowper ticket A spreadsheet is the right output here: it is what the review meeting already reads.
Fetch, judge, append. Everything else is prompt work.

Two prompt files are committed rather than one, and the pair is the lesson: 01_Raw_BugTriage.prompt.md is the first draft, and 02_ModifiedBugTriagePrompt.prompt.md is the same intent rewritten to be tool-aware after ChatGPT was asked to improve it. Keeping both lets you see what changed and why, which is the same instinct as the BLAST tracking files from yesterday.

This agent is at roughly twenty per cent on its own, and the session said so plainly rather than overselling it. It has no company context: it has never seen your Confluence, your PRDs, or your test repositories. Adding RAG is what takes it to around seventy. The last thirty per cent is human, permanently. The pitch is not that review disappears, it is that the review meeting shrinks: the same method as yesterday's triage crew, where the arithmetic is worked through properly.

04

The RCA agent, and a warning about building with AI

The RCA agent was built by asking ChatGPT for both the prompt and the n8n workflow JSON, then importing the JSON straight into n8n. It works, and the session immediately put a fence around it:

Do not use n8n's build-with-AI or JSON import until you have built four or five workflows by hand. The reason is the same one from the hiring conversation: importing a workflow you cannot read produces something you cannot debug, cannot explain, and cannot modify when it breaks. Build them manually first, then let AI accelerate what you already understand.

05

The social media agent, and an honest number

The sixth agent is a content pipeline: a 9am schedule trigger, pick a topic, draft a LinkedIn post, generate an image with Gemini, add hashtags, merge, review, post. It can be one agent with Gemini attached as a tool, or several smaller agents, and the modular version is easier to tune because you can fix one step without disturbing the rest.

Then the part worth repeating, because most people selling this will not tell you:

Pure AI posts underperform badly. The figures given from real accounts: AI-written posts land somewhere around seven to thirteen likes, against roughly two hundred and seventy to a thousand for posts written by hand. The conclusion drawn was not "do not automate", it was mix the two: automate the drafting, the image and the scheduling, and keep a human in the part that makes it sound like a person. Worth holding next to the 60-day branding challenge.

For distribution, an upload-post.com node can fan one post out to nineteen or more platforms, with a free tier of ten a month.

06

Tasks and announcements

  • Replicate the five agents built in class, and post screenshots or proof of them running.
  • Build the sixth, the social media agent, and build the RCA agent from the shared prompt.
  • Code, prompts and the sample spreadsheet are in chapter_08_n8n of the AITesterBlueprint4x repository.
  • Coming next: Langflow, RAG, MCP, CrewAI, Python and LangChain.
  • Certification sessions are being scheduled this week, targeting AI Fluency part 2 and the Claude architect certification.
  • Previous: BLAST and the first agent that runs without you. Related guides: n8n for QA and 10 n8n QA workflows.