Custom Email Responses with Smart Actions

Imagine this: You're knee-deep in NGINX server errors, sifting through logs in Elastic Discover. The AI Assistant is already helping you analyze error messages, providing context, and suggesting next steps. But what if we could take it a step further? Here's the secret sauce: Custom prompting to unlock hidden powers! 🔓 I found out that our AI Assistant can actually execute connectors, call Elasticsearch and Kibana APIs, and even generate queries. The key? Teaching it how to use these functions through clever prompting. Here's what I did: 1. Edited the user-specific prompt 2. Used tagged instructions (inspired by the Claude System prompt that was released) 3. Taught the AI how to call the Elastic email connector (steal my prompt below) Here are specific instructions for different types of queries: <email_instructions> If the user's query requires sending an email: 1. Use the Elastic SMTP connector with ID "Elastic-Cloud-SMTP". 2. Prepare the email parameters:   - Recipient email address(es) in the "to" field (array of strings)   - Subject in the "subject" field (string)   - Email body in the "message" field (string) 3. Include - Details for the alert along with a link to the alert - Root cause analysis - All of the details we discussed in this conversation - Remediation recommendations - Link to Business Health Dashboard 4. Execute the connector using this format:   execute_connector(    id="Elastic-Cloud-SMTP",    params={     "to": ["recipient@example.com"],     "subject": "Your Email Subject",     "message": "Your email content here."    }   ) 5. Check the response and confirm if the email was sent successfully. </email_instructions> The result? Magic! ✨ Now, when I ask the AI Assistant to send me an email summary of an error, it doesn't just say "I can't." Instead, it springs into action: - Analyzes the error - Crafts a detailed summary - Sends it directly to my inbox This is a complete transformation of our troubleshooting workflow. We've gone to a fully agentic process that can interact with external systems. The possibilities are endless: - Update ServiceNow tickets automatically - Send Slack notifications - Trigger remediation actions for known issues And the best part? You can customize this to work with any connector or webhook you have set up. It's like giving your AI Assistant superpowers tailored to your specific needs. #AIforSRE #ElasticObservability #AutomationTips #SRELifeHacks #AIOps https://lnkd.in/enNum-Nn

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!

First impressions matter. When a lead fills out a form or sends a message, silence shouldn’t follow. That’s where a CRM auto-response system comes in, quick, clear, and consistent. Here’s how to set it up: 🔹 Identify your key entry points Think contact forms, newsletter signups, demo requests, live chat, anywhere a lead first interacts with your business. 🔹 Create response templates Write clear, warm replies like: “Thanks for reaching out! We’ve received your message and will get back to you shortly.” Add value where possible—a link, a guide, or next steps. 🔹 Set up automation rules Inside your CRM, create a rule: “When [Form Submitted] → Send [Email Template] immediately.” This works across tools like HubSpot, ClickUp, Zoho, or Monday CRM. 🔹 Personalize the message Use tokens like [First Name], [Company], or [Service Interested In] to make each response feel human, not robotic. 🔹 Route to the right team Along with the auto-reply, automatically assign the lead or message to the relevant person or pipeline. 🔹 Track and optimize Monitor open rates, response time, and lead engagement. Refine your message based on what gets the best results. Auto-responses aren’t just polite. They show professionalism, build trust, and keep the conversation moving, right from the start.

Shipped a Gmail MCP Agent in ~1–2 hours. Calm build, zero drama, maximum signal. 😌⚙️ What it is: A 24/7 lead-nurturing system that runs on your Gmail account. It sends personalized outreach from a CSV (or Airtable, etc), follows up at smart intervals (3 & 7 days), watches for replies, scores interest, and can auto-respond to warm leads. It lives as an MCP (Model Context Protocol) server so you can start/stop/inspect it remotely. Why it’s different: - Always on: Dockerized service with health checks & auto-recovery Intelligent cadence: 3-day + 7-day follow-ups, rate limiting, resume where you left off - Full loop: reply detection → categorization → lead scoring → smart responses - Audit-ready: detailed logs + dashboard + MCP client commands (start | status | report | logs | stop) - Private & cost-savvy: runs on your stack, uses Gmail API (OAuth2), no third-party senders → saves $100s/mo vs. outreach SaaS Tech stack (small, sharp) - Python + Gmail API (OAuth2) - Jinja2 templates for true personalization - MCP server/client for remote control + monitoring - Docker + docker-compose for 24/7 deployment - CSV lead lists, comprehensive logging, deploy script, and a full guide What it’s doing now - Current test: 100 dental practices → initial outreach + day-3 + day-7 follow-ups. - Target outcomes (based on prior runs): 20–30% response, 10–15% “interested”, 80% of responses handled automatically. Who should care - Solo founders & agencies who need reliable outreach without hiring a team - Local services & B2B shops that want more booked conversations from the same leads - Anyone tired of paying $100+/month for email tools that lock you in and throttle you If you want to try it, engage with this post (like + drop a “MCP” or “ACCESS” in the comments) and I’ll send you access to the agent + quickstart. Calm ≠ slow. Calm = shipped. 🚀 UI is coming!