How to automate Gmail for freelancers

Just built a 2-way intelligent email agent using n8n in ~10 mins, and recorded a step-by-step video for anyone looking to automate smart email workflows. 📌 Stack used:- 🔁 n8n (as the orchestrator) 🧠 OpenAI GPT model (for intelligent responses) 📬 Gmail (fetch + send + reply) 📊 Google Sheets (as a logging layer and intermediate state handler) 🧩 Workflow breakdown:- 🔘 Triggered via a manual button (can be scheduled or webhook-based) 📥 Pulls recent Gmail threads using getAll: message 📝 Feeds each email to OpenAI’s message model for response generation 📄 Logs both user email and GPT-generated reply into Google Sheets 📤 Sends the AI-generated response using Gmail (sendAndWait) 🔄 Monitors new replies using Sheets as state memory 📧 Sends a contextual follow-up using reply: message ⚙️ This is an early prototype of how AI + automation tools can transform email communication pipelines. 💡 Use cases:- 📞 Automated customer support 🎯 Lead engagement 🤖 Smart autoresponders 📂 Inbox triaging assistants If you are exploring LLM-powered agents, n8n automation, or building AI workflows with no-code tools - this is for you. Interested in learning more about AI agents? Dr. Raj Abhijit Dandekar (MIT PhD) is conducting a 10-day bootcamp on AI agents. See details here: https://lnkd.in/gn4aDWKW ***** 🔄 Feel free to reshare if this could help someone in your network! 👤 Follow me, Sreedath Panat, for more content on AI, ML, and automation workflows!

SO many times I've wished I could talk to my Gmail and ask questions. But since Google hasn't set up those tools yet (get crackin' Alphabet!), I created a fairly easy AI workaround to make it possible. The idea with this is that you'll use a Google App Script (don't worry, you don't need to know code!) to analyze your messages. Here's how it works: 1. Put a Google label on any emails that you want to review. That might be all emails from a certain date range, or just the ones sent to a certain person or company. This is an important first step, because AI can't read your entire inbox at once. 2. Ask ChatGPT to create a Google App Script for you using this exact prompt: “Can you create a Google Apps Script that pulls all Gmail messages with the label ‘[Your Label Name]’ into a spreadsheet with columns for Date, To, From, Subject, and Body?” You’ll get a clean, copy-paste-able script that you can drop into https://script.google.com. When you run the script, it’ll export every email with that label into a Google Sheet — no coding experience required. 3. Once your messages are in your Sheets (or an exported spreadsheet) you can ask ChatGPT to help you analyze them. You can say things like: How many times did I email this person in June?” OR “Summarize my back-and-forth with this client.” OR "Are there any pending to dos for this account?" This AI workflow is one of the most helpful ways I’ve found to review my own communication, whether I’m wrapping up a project, prepping for a meeting, or just making sure I didn’t forget to follow up. It's literally saved me half a day of analysis every months. Happy to share the exact script and prompts I've use if you want to try it!

Here's how I built an AI system that reads my newsletters for me. No subscriptions, no workspace requirements, just Google Apps Script, Gemini and Gmail. I have tons of unread newsletters (still) creating constant guilt. Standard automation tools either cost too much (Zapier) or didn't fit my setup (make.com). Enters Apps Script from Google. Thanks Samuel Tschepe for the tip! This works if you use Gmail and want complete control over how your newsletters get summarized. No monthly fees (yet). No forced integrations. 1. Label your Gmail newsletters Lable your incoming AI newsletter emails "AI News". This separation is crucial. You want a clean workspace where the AI can focus only on content worth processing, not mixed in with your regular email. 2. Write your AI prompt for Apps Script. Open Google Apps Script (script.google.com). This lives in the Google ecosystem, so no new accounts needed. Use ChatGPT or Gemini to write your initial script. Be specific about what you want: summary style, tone of voice, what patterns to identify, output format, language handling if you read multilingual content, grouping by themes or topics, highlighting counterintuitive insights. 3. Iterate until the output matches your needs. Your first version won't be perfect. Mine wasn't. Test the script on a small batch of newsletters. Read the digest it produces. Note what's missing, what's too verbose, what tone feels off. Go back to your AI, explain what needs adjustment, regenerate the script. I went through 5-6 iterations before I got output that actually suited my needs. Let's see how it holds up. 4. Set up your digest delivery. Configure the script to send results to your main email. The one you actually check and keep clean. Set the schedule using Apps Script's time-based triggers. I use Tuesdays and Thursdays. You might prefer weekly. The key is matching your actual capacity to process information. Make sure the digest includes: reference to original newsletters, clear headlines for scanning, pattern identification across multiple newsletters, date range covered. 5. Maintain and refine over time. Run this for 2-3 weeks before making major changes. You need real usage data to know what's working. Adjust the prompt as your needs evolve. Maybe you want deeper summaries. Maybe you want more aggressive filtering. Maybe certain newsletter types need different treatment. My wish: To go from newsletter guilt to curated insights delivered exactly when I have time to engage with them. Let's see if this actually works this time... ...and if not, then it was still a fabulous AI experiment worth doing.