How to Automate Twitter Posts with Activepieces, Apify, and ChatGPT

This post is adapted from my YouTube video: Activepieces Twitter Automation

Spending 10 minutes a day crafting a Twitter post doesn't sound like much - until you realize that compounds to over an hour a week of time that could be better spent elsewhere. That's why I built an automated Twitter pipeline using Activepieces, Apify, and ChatGPT that turns Reddit sentiment into daily social content.

Here's exactly how it works, step by step.

Why Activepieces?

For those unfamiliar, Activepieces is an open-source automation platform - think Zapier or Make, but self-hostable and fully customizable. It lets you string together APIs, build custom workflows, and automate repetitive tasks across platforms. As someone passionate about open-source technology and building self-hosted stacks, it's a natural fit.

The Workflow Architecture

The entire flow runs in five simple steps:

Catch a webhook from Apify when scraping completes
GET request to pull the scraped data
Delay for 10 minutes to ensure data is fully processed
ChatGPT action to generate a Twitter post from the data
Post to Twitter via the API

Let me walk through each step.

Step 1: Set Up Reddit Scraping with Apify

Apify is a web scraping marketplace - instead of building scrapers from scratch, you use pre-built "actors" that handle the heavy lifting. The Reddit Scraper Light actor is the workhorse here.

I created a saved task targeting the r/cryptocurrency and r/web3 subreddits. The configuration is straightforward: search for posts, filter out NSFW content, limit results to 10 per run, and use residential proxies for reliability.

Apify offers $5 of free monthly usage, which is surprisingly substantial for personal projects. If you're running this for clients, you'll want a paid plan since it can add up quickly.

The key detail is scheduling. I set the scraper to run daily at 6:34 AM - an intentionally odd time that helps the content feel less bot-driven and catches both early-morning and late-night audiences across time zones.

Step 2: Connect Apify to Activepieces via Webhook

To connect Apify to Activepieces, you need to set up an integration. In Apify, navigate to your task, click Add Integration, select HTTP Webhook, and paste your Activepieces webhook URL.

On the Activepieces side, create a Catch Webhook trigger. Run your Apify task once to test the connection - you should see the webhook fire and the data come through.

Step 3: Pull the Data with a GET Request

After the webhook triggers, the next step is a GET request to retrieve the full dataset from Apify. You'll find the endpoint by navigating to API > Endpoints in Apify and scrolling to "Get last run for dataset items."

I add a 10-minute delay between the webhook and the GET request. This might seem excessive, but it ensures the scraper has fully completed and all data is available. Better to wait a few extra minutes than to pull incomplete results.

Step 4: Generate Content with ChatGPT

This is where the magic happens. The ChatGPT integration in Activepieces uses an API key connection (called "pieces" in Activepieces).

Here's the prompt structure I use:

Use the following data to share a 100-400 character Twitter post from the perspective of Edward Chalupa. Edward is a digital marketer passionate about Web3, blockchain, DeFi, education, and nonprofits. He writes at a friendly, engaging 10th-grade reading level. Create an opinion based on the provided sentiment and share a deep analysis of a specific topic. Give a basis for your reasoning. Do not mention Reddit or its users. Use no more than three relevant hashtags. Only include copy from the body of the available data. Ignore any content shared by bots.

I use GPT-4o for cost efficiency, drop the temperature to 0.7 for slightly more accurate outputs, and set max tokens to 4096.

The reference data is the body content from the GET request - all the Reddit posts and sentiment data from the scraper. The result is something like: "Uniswap's exit might trigger a revenue crisis for Ethereum. Could this redefine DeFi dynamics? Watch the space. #DeFi #Ethereum #Web3"

That's content I would actually write, generated in seconds instead of minutes.

Step 5: Post to Twitter

The final step connects to the Twitter/X API via a developer account. On the free tier, you get one connection - which is all you need for a single automated posting workflow.

The text input is simply the ChatGPT output from the previous step. Publish the flow, and you're live.

Real-World Results

The automation produces one post daily, timed to catch peak engagement windows. Each post reads like a genuine take on current crypto sentiment - because the underlying data is real community discussion, not manufactured content.

The time savings compound quickly: 10 minutes per post, seven days a week, equals over an hour of reclaimed time. That's time better spent on strategy, client work, or building more sophisticated automations.

Key Takeaways

Schedule strategically. Pick non-round-number times for your automation triggers - it makes the output feel more organic and human.

Use saved tasks in Apify. If you're running multiple automations from the same actor (different subreddits for different audiences), tasks let you segment the data flows properly.

Fine-tune your prompts. The ChatGPT prompt is the single biggest lever for output quality. Be specific about voice, tone, reading level, and formatting rules.

Start simple, iterate later. This flow doesn't include images yet - that's a future enhancement. The 80/20 principle applies: get the text automation working first, then layer on complexity.

Edward Chalupa is a digital marketing specialist and founder of Whtnxt, a digital marketing and automation consultancy. Connect with him on LinkedIn or explore more at echalupa.com.