Automate low-priority email responses

I built a simple email manager in both OpenAI Agent Builder and n8n. One looked prettier. One actually worked. Here's what matters for GTM automation. Last week, I wanted to automate something simple: sorting and responding to emails based on keywords. Nothing crazy. Just a basic workflow every agency and SaaS operator needs. So I opened both Agent Builder and n8n. Same task. Let's see what happens. 𝗙𝗶𝗿𝘀𝘁 𝘁𝗿𝘆: 𝗢𝗽𝗲𝗻𝗔𝗜 𝗔𝗴𝗲𝗻𝘁 𝗕𝘂𝗶𝗹𝗱𝗲𝗿 The interface? Gorgeous. Seriously. Drag a node, drop it, connect things. The chat UI looked professional as hell. I'm sitting there thinking: "Okay, this is clean. I like this." Then I tried to make it trigger automatically when an email arrives. That's when reality hit LOL - the limitation nobody mentions: OpenAI Agent Builder has 𝗢𝗡𝗘 𝘁𝗿𝗶𝗴𝗴𝗲𝗿: "Start" Meaning? I have to manually click "start" every single time. No automatic email monitoring. No webhooks. No schedules. If I want it to run when Google Workspace Gmail receives a message? I need to build a separate system to call this agent. That's... not automation. That's just a chat interface with extra steps. —> Over in n8n - I had actual triggers: —> Gmail trigger: Fires when email arrives —> Schedule: Check inbox every hour —> Webhook: Any system can trigger it —> Slack, forms, CRM events - all native Set it up once. It runs in the background forever - and that's what real automation looks like, no? So the integration gap in OpenAI Agent Builder is 8 apps by default. Although you can connect more through Rube/MCP servers, but that's a setup hell. w n8n - 500+ apps just... ready. Plus an HTTP node that connects to literally anything with an API. For my simple email manager? I needed Gmail, Slack, and my CRM. n8n had all three natively. Done in 10 minutes. in terms of Model flexibility: I tried to switch Agent Builder to Claude for better writing. "OpenAI models only." Okay but... what if OpenAI goes down? What if Claude writes better for my use case? n8n lets me pick: Claude, Gemini, GPT-4, local models, whatever. Different models for different jobs. That's just smart. My takeaway from this is - Agent Builder is great 𝗶𝗳 𝘆𝗼𝘂 𝘄𝗮𝗻𝘁 𝗮 𝗽𝗼𝗹𝗶𝘀𝗵𝗲𝗱 𝗰𝗵𝗮𝘁𝗯𝗼𝘁 𝗶𝗻𝘁𝗲𝗿𝗳𝗮𝗰𝗲 (for now). But for actual GTM automation - stuff that runs without you, scales your ops, and connects your entire stack? n8n wins. Not even close. Here's what I learned: Stop chasing the "best tool." Businesses don't care if you use n8n or OpenAI Agent Builder. They care that you: —> Save them 15 hours/week of manual work —> Cut their response time from hours to minutes —> Automate processes that generate real ROI The tool is just how you get there. My setup now: n8n for 90% of automation work. Agent Builder when I need a pretty chat interface lmao. Simple as that. So quick q before you go: Q, What are you actually building with these tools right now? Drop a comment or DM me :) ~ Shri Nishkarsh Agarwal

How I built an AI email assistant that organizes, triages, and drafts replies. (without losing my brand voice). Last Friday, we ran a session on designing and building an AI agent for inbox management. Here’s what we covered: (and how you can follow the same steps): Step 1: Map your current process. Before you build anything, understand what you're already doing. → How do you currently handle email? → Where do things fall through the cracks? → What decisions do you make over and over? Most founders skip this step. But if you automate a broken system, you create chaos faster. Step 2: Fill out the Agent Canvas. We used our 5-part framework to map the full logic of the system: 1 - Triggers: What sets the process in motion? (e.g., new email, daily schedule) 2 - Decisions: What logic drives next steps? (e.g., is this urgent?) 3 - Actions: What should the agent do? (e.g., apply labels, draft reply) 4 - Tools: What platforms does it need? (e.g., Gmail, Slack, Claude) 5 - Guardrails: Where do humans stay in control? (e.g. drafts only, escalate via Slack) Step 3: Build your agent using natural language. Once the canvas was mapped, we used Lindy’s builder to create a real working agent (no code required). Example: → An assistant that runs 3x/day. → Checks for priority senders. → Applies labels. → Pulls answers from the knowledge base. → Drafts replies. → Pings Slack for anything urgent. No pre-built workflows. Just clear logic, explained in plain English. Step 4: Iterate. Most builds won’t work perfectly on the first try. That’s part of the process. We shared broken versions in the community, refined the templates, and got live feedback. The takeaway? You don’t need AI to answer everything. You need a system that understands how you triage, reply, and escalate. Then builds around that. And that’s exactly what we help founders do inside the Mighty AI Lab. Ready to build an AI email assistant? Join the Lab: https://lnkd.in/gjah4Yen

I spent all weekend playing with n8n. Here's an idiot-proof framework to understanding whether automating with n8n is right for your business: n8n is a visual workflow automation tool. Think: Zapier + Figma had a baby. The beauty of n8n beyond its intuitive UX is the ability to call out to LLMs. This is beyond transformative. Where Zapier historically relied on deterministic calls ("hit an API; either get a successful payload back or the whole run fails"), n8n allows you to bake in non-deterministic LLM calls. Example: "Upon e-mail receipt, call an LLM to classify the e-mail based on a prompt that I offer it." This would have been REALLY hard using deterministic code. You'd have to have some library of phrases or terms associated with deals, and even then probably fail to catch edge cases. LLMs shine in the messiness of unstructured text. So say you're trying to automate inbound triage: n8n can classify what's a "deal" vs. "non-deal" e-mail. Then, once the classification is complete, it can call out to a CRM and persist deal-labeled e-mails to a CRM and automatically draft a reply with next steps. That's nothing short of insane for roles that run on e-mail. Rather than clicking, opening, hand-writing a response, clicking again in a CRM, opening a drop-down to classify the deal... You do nothing. You simply show up with maximum energy and passion for the most critical part of the sale: the sale itself. n8n has already been widely adopted by technical teams, but the opportunity is truly infinite for businesses that aren't hip to the latest goings-on in Silicon Valley. So if you're a business that runs on messy text-based workflows that prior generation automation tools couldn't API away, n8n is worth a dive. And if you're an automation engineer, building automation tools, or a business that desperately needs to cut the overhead of manual drudgery, please reach out!