I Built a Workflow That Reads My Community’s Slack and Writes a Week of Posts in My Voice

I Built A Workflow That Reads: Building A Workflow That

As a community lead for a tech non-profit, I’ve learned that i built a workflow that reads my community’s Slack and writes a week of posts in my voice is a total big deal. It’s not just about saving time, but about providing value to my community. Here’s the thing — manually scrolling through our Slack channels, hunting for patterns, and building a content calendar was taking up way too much of my time.

I’m talking 15 to 20 hours a week, on top of my day job. That’s unsustainable, and it was starting to take a toll on my mental health..

So, I decided to build a pipeline that listens to conversations across our community workspace, surfaces overlooked questions, and turns shared concerns into content that helps more people. It scans our four busiest channels, drafts a reply to every real question for me to approve and send, and then takes the ones worth answering in public and writes them up in my voice. The posts are then dropped into Buffer, ready to schedule.

Why Manual Content Creation Wasn’t Working

The Challenges of Manual Content Creation

Manual content creation wasn’t only time-consuming, but it was also inefficient. The volume of questions was manageable, but the harder part was catching the ones that needed attention the most. Questions got buried under other conversations, and with members spread across different time zones, it was easy to miss something important.

Here’s the thing: deadline days were the worst, with hundreds of messages coming in at once. And honestly, the people who needed help the most often didn’t ask, either because they were new and didn’t want to look it, or they’d asked once and gotten buried..

That’s what pushed me to build something that could help me stay on top of things. I needed a system that could read what the community was asking, work out which questions were worth answering in public, and draft posts that sounded like me. I didn’t want to spend my time reviewing and approving every single post, but I did want to make sure that the content was high-quality and helpful.

How the Pipeline Works

The Five-Step Process

The pipeline runs in five steps: read, filter, archive, cluster, and publish. I built the workflow in Gumloop, a low-code canvas that lets me chain AI steps, API calls, and custom nodes together. The first three steps turn raw Slack traffic into a clean, taggable archive, while the last two decide what deserves a public answer and get it into Buffer.

Here’s how it works: the AI Extract Data node reads every message in our four channels, decides whether it’s a question, drafts a response, and tags it with a theme. The filter step keeps only the rows flagged as questions and drops everything else. The archive step writes everything into a Notion database, which has 10 fields, including who asked, which channel it came from, and the draft response.

Deciding What to Post

The Three Promotion Criteria

The pipeline uses three criteria to decide which questions deserve a public answer: can a member already solve this on their own, does it affect a meaningful slice of the community, and is it a real gap or just a doc fix? Each theme gets a quick gut-check against these criteria, and it has to clear at least two of them to be promoted. There’s also a promotion cap, which stops the model from promoting too many clusters at once.

The goal is to surface the questions that are worth answering in public, including the valuable ones that only a few people thought to ask. Those are the easiest to miss, and they’re often the ones the silent majority needs answers for. By using this criteria, I can make sure the content is relevant and helpful to my community.

Getting the Posts to Sound Like Me

Using Voice Samples and Hard Rules

Getting the posts to sound like me was a challenge, but I was determined to make it work. I showed the model samples of how I write, so it could pull out the patterns and match them as best it could. I used four samples: two peer replies, one longer-form post, and one DM.

Honestly, on top of the samples, I gave the prompt a few hard rules: titles have to be short and specific, posts have to open with the situation, and the tone stays conversational and peer-to-peer..

Truth is, it took a few rounds of testing before the tone really blended, but once it did, the posts started coming out the way I’d write them if I’d sat down and done it myself. And honestly, it’s been a huge relief to have this system in place. I can focus on reviewing and approving the content, rather than spending hours writing it from scratch.

So, to sum it up, i built a workflow that reads my community’s Slack and writes a week of posts in my voice has been a total real difference-maker for me. It’s saved me time, reduced stress, and allowed me to provide more value to my community. If you’re looking to streamline your community engagement, I highly recommend exploring similar solutions. With the right tools and a bit of creativity, you can build a system that works for you and your community. So, what are you waiting for? Start building your own workflow today and see the difference it can make!