I’ve been testing n8n in two setups recently: self-hosted and n8n Cloud — specifically from an AI agency perspective. Here’s the honest breakdown 👇 1. Cost: predictable vs elastic n8n Cloud - Fixed monthly pricing - No infra setup, no DevOps overhead - You pay for convenience and reliability Good if: - You want predictable costs - You’re running client workflows with clear volume limits - You don’t want to think about servers at all Self-Hosted n8n - Infra cost (VPS, DB, storage, backups) - Scales cheaper at high volume - But costs shift from “subscription” → “engineering time” Good if: - You’re running heavy workflows (AI agents, scraping, batch jobs) - You have technical capacity - You want long-term cost efficiency at scale 👉 At low–medium usage, Cloud is cheaper. 👉 At high throughput, self-hosted wins — if you know what you’re doing. 2. Performance: stability vs tunability Cloud - Stable, managed environment - Limited control over execution environment - Performance is “good enough” for most use cases Self-Hosted - You control: - You can optimize for: In practice: - Cloud = fewer surprises - Self-hosted = higher ceiling, more responsibility 3. Control & security: this is the real differentiator This is where the gap becomes very clear. n8n Cloud - Limited control over data locality - Not ideal for: Self-Hosted - Full control over: - Much easier to: For agencies, this matters a lot. Self-hosting turns n8n from “automation tool” into infrastructure you actually own. 4. Maintenance: invisible cost most people ignore Self-hosting isn’t free just because the software is. You’re responsible for: - uptime - backups - updates - monitoring - security patches If you ignore this, you’ll pay later — usually at the worst time. Cloud removes this entire surface area. Final take (practical recommendation) If I had to simplify it: - Use n8n Cloud when: - Use Self-Hosted n8n when: Cloud is great for execution.

Huge shoutout to the Top 5 Members of Brendan's AI Community for December. These are the people leading the way, sharing knowledge, and helping spread the AI culture: 🥇 @Hammad Zahid 🥈 @Jody Murfit 🥉 @Pavan Sai 🏅 @Alfonso Nava 🏅 @R K Thanks for showing up consistently, sharing knowledge, and helping others. ❤️ I also want to congratulate every single member of Brendan's AI Community! Because of your support, wins, questions, posts, and engagement, we're building something special here. Your energy fuels the entire group, and that's what makes this place different. Keep crushing it, keep showing up, and keep sharing your wins. The momentum you're building is exactly what turns learning into real results 🔥 December was strong. Let's make January even better 🔥 Who's going to be on next month's list? 👀

Happy New Years from Australia! Wishing everyone the best for 2026, let's crush it 💪 Drop some new years GIFS down below 👇

A lot of AI agencies treat automation tools like Zapier as “glue”. But the agencies scaling cleanly are moving toward n8n-style orchestration instead. Here’s why n8n fits real agency workflows better: 1. Logic-first automationn8n isn’t just “if this then that”. You can build real logic: - branching flows - conditional retries - fallbacks when APIs fail This matters when client workflows aren’t clean or predictable. 2. AI fits naturally into the flowing n8n, AI isn’t the workflow — it’s a step inside it. Example: - webhook → data cleanup → AI reasoning → validation → action instead of - prompt → hope → output That extra structure is what makes automations reliable. 3. Debugging like an engineer, not guessing like a marketer When something breaks: - you see exactly where - you replay executions - you inspect raw inputs and outputs That’s huge when clients ask “why did this happen?” 4. Client-specific customization without duplication The best agencies use: - the same core workflow - different config layers per client n8n makes that possible without rebuilding everything. The pattern I keep seeing: Zapier = speed for simple use casesn8n = control for production systems If your automations are becoming part of a client’s core ops, you need orchestration — not just triggers.

A lot of agencies say they “use n8n”. In reality, most are just wiring tools together. The agencies getting real leverage treat n8n as a control layer, not an automation toy. Here’s what that looks like in practice: • n8n as an orchestrator, not the worker AI models do the thinking. n8n decides when, why, and in what order they run. • Conditional flows based on client context Same workflow behaves differently for: – SMB vs enterprise – warm lead vs cold lead – existing client vs trial user This is done through branching logic, not separate workflows. • Error handling as a first-class citizen Good setups assume things will fail: – retries – fallbacks – human handoff when confidence drops No silent failures. • Logging everything that matters Every execution stores: – inputs – decisions taken – outputs – final outcome This becomes internal intelligence, not just logs. • One workflow, many clients Instead of cloning automations per client, they pass client configs as variables. Cleaner. Scalable. Maintainable. n8n isn’t powerful because it connects apps. It’s powerful because it lets you encode operational logic. That’s the difference between “automation” and an agency that actually scales.