Author: Olaitan Oladipo

Olaitan Oladipo holds a BSc in Sociology from Olabisi Onabanjo University. He is a self-taught automation builder who has spent years inside n8n doing the work that most tutorials skip: debugging OAuth errors at 2am, migrating client automations from Make.com mid-project, fighting reverse proxy misconfigurations on AWS EC2, and figuring out through trial and error what actually holds up in production versus what only looks clean in a demo. He is not a developer by training and not a SaaS founder. He is the person in the Discord server who actually answers the question instead of linking to the docs. His writing on n8n Automation Tutorial covers self-hosting, AI agent workflows, tool comparisons, and the security vulnerabilities the automation industry would rather not discuss. He has built AI-assisted invoice approval flows using OpenAI function calling, connected Claude via HTTP Request nodes, and holds considered opinions about Zapier, Make.com, LangChain, and CrewAI that their marketing teams would not appreciate. He writes for people who are technical enough to follow a tutorial but experienced enough to want the honest version.

The workflow passed every test. A client’s agent then approved a $47,000 invoice at 2am with no human review. The classification threshold was 0.7, and the vendor matched a pattern from three months earlier. Nobody received an alert, and the audit trail was a JSON blob in a Docker volume nobody had configured to surface. This is the governance problem nobody talks about honestly. Building the agent is genuinely not that hard in n8n, especially with the AI Agent node and HTTP Request nodes for external model calls. The hard part is deciding what happens when the agent does something…

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The Code node was running a client’s data processing logic, and I had not thought about what that meant for the host machine. Someone in the Discord asked about sandboxing, and I went back through my AWS EC2 setup to check. The n8n process had been executing arbitrary JavaScript with access to the host filesystem since I first deployed it. That was eighteen months of production workflows running without proper isolation. n8n 2.0’s Task Runners address exactly this problem, and the implementation is more considered than I expected. Workflow execution now happens in an isolated runner process, separate from the…

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A client called me on a Thursday afternoon because their Zapier account had stopped processing orders. They had hit their monthly task limit three weeks into the month, and nobody had seen it coming. There were no alerts, no warnings, and no dashboard widget counting down to zero in any way they had thought to monitor. That happened in 2024 and Zapier’s answer at the time was to upgrade the plan. Zapier’s May 2026 release includes three operationally meaningful updates for teams running production Zaps at scale. Usage spike alerts now notify account owners when task consumption is trending toward…

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I spent three hours last year trying to figure out why a client’s Stripe webhook was triggering a Slack notification nobody had set up and nobody could explain. The client had been on Make for two years and had accumulated sixty-four scenarios across four different teams. Nobody had a complete picture of what was connected to what. Make Grid, released to all paid users in May 2026, is the feature that would have saved those three hours. Make Grid gives you a real-time map of every scenario, connection, and agent across your entire Make account. The visualization shows where bottlenecks…

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