Run LLM assistants over company data
From the linked report, n8n shows up in a write-up about run LLM assistants over company data, with figures like 8. The linked post is the primary source for steps and outcomes.
- Agent or tool
- n8n
- Topic
- Software Development
- Reported on
- Added
- 2026-10-15
Why it matters
Coding agents are moving from autocomplete to doing whole tasks: reading a codebase, making a plan and changing many files. This case is a concrete example of where that works in practice. It is one of 109 sightings filed under Software Development on Agent Sightings (number 94 by interest), and one of 36 involving n8n.
How you could try it
Here is a reusable prompt, written by us in our own words, that captures the task. Paste it into n8n or any similar agent and adjust the details to your situation.
In this repo, run LLM assistants over company data. Read relevant code, apply a minimal patch, run available checks, and summarize the diff. Stop before merge or deploy.
The prompt breaks down into 3 steps you can check as the agent works:
- In this repo, run LLM assistants over company data.
- Read relevant code, apply a minimal patch, run available checks, and summarize the diff.
- Stop before merge or deploy.
Tip: Work on a fresh branch, ask for a plan before edits, and review the diff and test results before merging.
Source
Read the original first-hand account on Reddit: https://www.reddit.com/r/n8n/comments/1r3qalu/most_ai_agent_workflows_are_just_…. Our summary is a paraphrase; details are in the source.
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