Starting January 20th i'm running a free 30-day AI automation build sprint for anyone who wants to stop consuming AI content and actually ship something real. This is async so no live calls. The goal is simple: by Day 30, you’ll have one working AI automation running in n8n. Each week includes: – a focused build step – templates released as needed – clear “done” checkpoints This is free, but it’s not casual. If you want to finish something instead of bookmarking another tutorial, this is for you. Comment BUILD below if you want to take part in this upcoming sprint

Stop losing money to unorganized receipts. In this tutorial, learn how to build a fully automated AI receipt inbox that turns messy phone photos into structured bookkeeping records instantly. We tackle the "messy phone gallery" problem by using n8n and OpenAI Vision to extract merchant names, dates, totals, and taxes automatically. By the end of this video, you’ll have a professional-grade system that renames your files, archives them to Google Drive, and saves the data into an n8n Data Table with built-in de-duplication logic. What you will learn: How to trigger workflows using n8n Forms. Standardizing binary file data with simple code nodes. Using OpenAI Vision to "read" and categorize receipt images. Structuring AI output into clean JSON for databases. Setting up "Upsert" logic to prevent duplicate entries. Mapping and storing files in the Google Drive ecosystem.

Most people “choose an AI tool” the same way they pick a new app. Pretty UI ✅ Cool demo ✅ A friend said it’s amazing ✅ Then 3 weeks later… outputs are inconsistent security is a question mark nobody knows who owns the generated content integration turns into a duct-tape project leadership asks “is this compliant?” and everything stalls AI is everywhere. And every tool claims it’s “enterprise-ready.” But the real risk isn’t picking the wrong tool. It’s picking the right tool… for the wrong reasons. Because “it works in a demo” is not the same as “it works in production.” So here’s the evaluation framework I use (and it’s in the image): 1️⃣ Core functionality + performance Accuracy, reliability, data quality, scalability 2️⃣ Security + data privacy Data handling, prompt/model security, privacy compliance 3️⃣ Usability + integration Ease of use, API/workflow integration, support + training 4️⃣ Ethical + responsible use Bias/fairness, transparency, accountability And the 3 questions people forget: ✅ Cost + licensing ✅ IP + ownership ✅ Compliance standards (SOC 2, ISO, etc.) When you score tools across these buckets, the “best” AI tool usually changes. Sometimes the flashy one drops to the bottom. Sometimes the boring one becomes the obvious winner. If you’re buying, building, or recommending AI in 2026: Stop asking: “What’s the coolest model?” Start asking: “Can we trust, secure, integrate, and govern it?”

Build a WhatsApp AI voice agent using n8n, Twilio and ElevenLabs! In this step-by-step tutorial, you'll learn how to capture WhatsApp voice notes, transcribe them with AI, generate smart responses, convert them back into natural-sounding audio, and send them to users automatically. Perfect for businesses wanting after-hours automation or creators building advanced AI workflows. In this video, we walk through the full pipeline—from receiving the WhatsApp message, routing it through Twilio, normalizing payloads in n8n, validating voice files, transcribing audio using ElevenLabs, generating an AI response with OpenAI (or any LLM), converting that reply back into speech, hosting the file, and finally delivering the voice note back to WhatsApp. You’ll also learn how to customize voices, use your own cloned voice, and securely configure gateways, webhooks and credentials. This tutorial expands on the previous WhatsApp automation video, but focuses specifically on AI voice note handling, error-proofing workflows, and production-ready best practices for routing media, managing storage, and preventing failed API calls. The full n8n template is attached

If you’re vibe coding and your app keeps breaking, you don’t need more prompts. You need 7 rules. ✅ Rule 1: Start with ONE sentence What the app does, who it’s for, and what “done” means. ✅ Rule 2: Ask for a plan before code “Give me the steps, file structure, and data model first.” ✅ Rule 3: Build the smallest working version One screen. One action. One result. Then expand. ✅ Rule 4: Lock decisions early Stack, routes, database, auth. Changing these mid-build is how projects die. ✅ Rule 5: Give constraints, not vibes Examples: TypeScript only. No new libraries. Validate inputs. Keep functions pure. ✅ Rule 6: Test as you go After every change: run it, click it, break it. Don’t pile up edits. ✅ Rule 7: When it bugs out, report like an engineer Not “it doesn’t work.” Say: error + what you expected + what happened + the file. Vibe coding works when you drive and the AI copilots. What tools do you currently use for vibe coding?