How to use n8n, and when to write the code instead

n8n is a visual automation tool: boxes for steps, lines for data, 1,200-plus prebuilt nodes for the apps your workflows touch, and since the AI wave, agent nodes that put a model in the loop. You can run it two ways, on n8n’s cloud or free on your own five-dollar server, and that split plus one pricing decision made it the default engine of the AI automation economy. It is also the center of a gold rush, and most of what you will read about it is written by people selling shovels: the real client money in n8n is small, steady, and reachable, and almost every big number attached to it is a course funnel.

The shape of the tool

A workflow starts with a trigger (a webhook, a schedule, a form, an app event) and flows through nodes that fetch, transform, branch, and send. The editor runs in your browser whether the instance is n8n’s or yours. For AI work there are agent and chain nodes wired to every major model provider, local models through Ollama, and MCP in both directions: your workflows can call outside MCP servers as tools, and a trigger node can expose your workflows as an MCP server for something like Claude to call. Two clean entry points: the cloud trial is 14 days with no card, and the community edition is free forever on your own hardware, minus a list of team features (environments, SSO, Git version control, workflow sharing) that solo builders mostly will not miss on day one.

The meter: one run, one execution

n8n’s pricing quirk is the reason experienced automators migrate to it, so learn the mechanic first. From n8n’s own pricing FAQ: an execution is “a single run of your entire workflow. It doesn’t matter how many steps are in the workflow or how much data it processes.” Zapier bills per task, meaning every step of every run; Make bills per module operation. A ten-step workflow that runs once a day costs you about 30 executions a month on n8n and about 300 tasks on Zapier. The receipts scale with ambition: one agency lead moved a ClickUp scan from Make that burned “over 10k operations each time” and now runs it twice a day, because the same job counts as one execution per run.

Cloud plans start around €20 a month for 2,500 executions and €50 for 10,000, billed annually, with unlimited active workflows (prices display by region, so check the page in your currency). Two traps hide in the small print. First, polling: a workflow that checks something every ten minutes fires 4,320 times a month all by itself, past the Starter cap before it has done anything useful. Prefer webhooks over schedules wherever the source app allows. Second, n8n has burned trust on pricing before: when it moved self-hosted enterprise tiers to per-execution pricing in 2025, heavy users in the announcement thread posted cost projections up 250 times over, and the CEO’s reply conceded that “no matter which metric is chosen, one group will be unhappy.” Individual plans were not the target, but the lesson transfers: the meter is friendly today, and it is theirs to change.

Self-hosting: the five-dollar instance and the rules that keep it alive

The community edition on a small VPS is the standard setup for builders, and the real budget is a few dollars a month plus your attention. The official path is Docker with a persistent volume, SQLite by default, Postgres when it matters. The docs say plainly that self-hosting “requires technical knowledge” and that mistakes “can lead to data loss, security issues, and downtime,” and the forum receipts say they mean it. The canonical horror thread is self-hosted workflows rolling back weeks after updates: “We lost WEEKS of updates. Completely gone… like someone restored a backup from two weeks ago over the top.” The pattern behind most of these stories is the same: latest tag, SQLite, no backup, updated on a whim.

So the self-host rules, all learned expensively by someone else:

• Pin your version. Never run the latest tag in production. Read release notes before moving; n8n ships releases weekly and 2.0 carried real breaking changes.
• Back up before every update. The volume holds your workflows, credentials, and encryption key. A copy costs seconds; the rollback thread is what not having one costs.
• Graduate to Postgres when it becomes a business. SQLite is fine to learn on. Once clients or volume depend on it, move, and past a couple hundred executions a day look at queue mode with Redis and workers.
• Give AI workflows memory headroom. Agent nodes on a 512MB instance die of out-of-memory errors mid-run; 2GB is the realistic floor once models are in the loop.

Building workflows that survive contact with production

The gap between a demo workflow and a production one is the whole craft, and the best summary in the community is a reviewer’s production-readiness checklist: most workflows “pass the ‘happy path’ check fine. They break when the unusual happens: a 504 retry, a credential rotation, a third-party API drift.” The habits that close the gap:

• Dedupe inbound events. Webhooks deliver twice; without an ID check “you ship duplicate orders / duplicate charges.”
• Tame the retries. Default per-node retry settings hammer a struggling API; add backoff and route final failures to an error workflow that alerts you and stores the payload, because execution logs expire and a failed payload you did not save is gone.
• Keep one known-bad test payload next to the happy-path one, and run both before every change ships.
• Put the AI agent on a leash. The recurring agent failure is the tool loop: an unexpected tool result and the agent “enters an infinite loop, calling the same tools repeatedly,” eating tokens until something stops it. One builder’s whole arc went from “Claude keeps inventing tools that are not listed” to the plea that explains the fix: “I just want a chatbot that has access to a couple of API calls.” Build exactly that. Deterministic nodes for the flow, small scoped model calls where judgment is needed, hard caps on iterations, and a human approval gate before anything irreversible.

The client money, under the guru numbers

This is why most of you are here, so here is the market with the funnels stripped out. The believable, repeated numbers from working practitioners: hourly rates from about €25 to 30 starting out, $50 to $75 established, up to $100 to $200 for veterans with a niche; one-time builds in the $500 to $2,000 range for something like an OCR-to-CRM pipeline; and maintenance retainers of a few hundred a month, priced, in one builder’s words, “low enough for a company to not scrutinize the bill.” Stack a handful of those retainers and it is real, unglamorous income. What sells is boring and provable: lead-gen and outreach pipelines, document intake to CRM, front-desk chat and voice for local businesses, content operations. The sellers who close say the word AI can hurt more than help; you are selling saved hours with a number attached, the same discipline as scoping any AI project.

Now the other half. The subreddit is wallpapered with $25K-MRR screenshots, and the pattern under them is consistent: the poster is selling a course, a template pack, or a coaching program. The most useful thread in the niche is a post-mortem by someone who bought in, built twenty agents from the paid templates, “and still no clients.” The replies deliver the verdict cheaper than the course did: “The people selling the classes are the only people making money here,” and, sharper, “The money you think they were making is from people like you. You are their target customer.” Even a builder genuinely selling automations admits the hype “is coming from content creators (who actually make money from content and courses, not from selling automation to real companies).” The trade is real. The gold rush around it is mostly people selling maps. If you want the client path, start where your first AI client actually comes from and price the work like a professional.

The license the gurus have not read

n8n is not open source; it ships under a Sustainable Use License that allows internal business use and forbids selling access to n8n itself. For client work the line runs exactly where most agency setups happen to be standing. Building workflows for clients as a consultant is explicitly permitted, no license needed. But n8n’s own support guidance draws the boundary: helping clients set up “their own internal instances” is fine, while hosting and managing “your clients’ workflows and credentials within your own internal n8n instance” requires an Enterprise license. The convenient one-instance-many-clients model, the default in every agency tutorial, is the violating one, and when someone described it on the forum the answer was blunt: that setup is treated as offering n8n as a service. White-labeling and charging for access are named as forbidden, and the commercial license is enterprise-priced; one startup reported a $50K quote.

Here is the useful part: the compliant pattern is also the better business. Have the client own the instance, on their cloud account or their VPS, and invite you in as an editor. Never hold their credentials in your own systems, never make yourself the thing they must pay to keep their automations alive. You lose the hosting margin and gain a clean handoff, a defensible legal position, and a client who trusts you with the next build. If your business model genuinely requires hosting automation for customers, use a tool licensed for it; Activepieces is MIT-licensed precisely where n8n is not.

Where it stops being worth it

The Primer rule is to know your off-ramp before the bill, or the 2 a.m. outage, surprises you.

• High-volume, latency-sensitive systems. Builders running serious load report the ceiling plainly: execution time limits, memory caps, state loss on crashes. n8n prototypes a pipeline beautifully; it is not the final home of one processing millions of events.
• You can already code, and the workflow is really just an integration. The recurring engineer take: “easier and cheaper to have Claude code something and then throw it in docker as API.” A Claude Code session writes, tests, and documents a bespoke integration in an afternoon, with real version control, which visual workflows still lack. n8n earns its place when the people maintaining the automation are not engineers, or when the glue between six SaaS apps is the whole job.
• The client will run it themselves and is not technical. Make’s simpler surface hands off easier; more than one agency owner keeps it around just for that.
• The middle path is real: point Claude at the n8n-mcp bridge and it will build and edit n8n workflows for you, which gets you AI-speed construction and a visual artifact a client can see. The tools we currently stand behind are on the Palette.

n8n earns its keep twice over: as the automation engine whose meter charges the run instead of the step, and as a genuine trade where a careful builder can stack real, modest retainers. It stops earning it when you scale a prototype past what a workflow tool should carry, host other people’s automations on a license that forbids it, or buy a map from someone whose only gold is selling them. Learn the tool, read the license, charge for outcomes, and let the course sellers keep each other company.