DEV Community: alex

I built a LinkedIn job scraper that sends daily digests to Discord (no login, no code)

alex — Sat, 28 Feb 2026 21:13:58 +0000

I got tired of manually checking LinkedIn every day, so I automated it.

Built a Make.com scenario that:

Scrapes LinkedIn jobs via Apify (no login required)
Filters for Easy Apply + remote + entry level
Sends a clean daily digest to Discord

Example output:
🔷 Automation Engineer — Acme Ltd
📍 United Kingdom | 💼 Full-time | ⏰ 2 hours ago
🔗 https://linkedin.com/jobs/view/...
－－－

How it works

HTTP POST → Start Apify actor (worldunboxer/rapid-linkedin-scraper)
Sleep 90s → Wait for scrape to finish
HTTP GET → Fetch results from Apify dataset
Iterator → Loop through jobs
Filter → Easy Apply only
Set Variable → Format each job entry
Text Aggregator → Combine into one message
HTTP POST → Send to Discord webhook

Key lessons learned

The JSON escaping problem — Line breaks in aggregated text break Discord's JSON. Fix: use Make.com's "Data structure" input method instead of raw JSON string. It escapes everything automatically.

Apify actor quirks — The actor sometimes ignores keyword parameters and returns random jobs. Workaround: add a local filter on job_title contains "keyword" after the iterator.

Running cost — Apify charges $0.001 per result. Daily runs with 5 results = ~$0.15/month. But you get 5 dollars a month for free to use however you want from apify.

The template

Packaged it as a Gumroad product with the blueprint + setup guide.
link

Happy to answer questions about the build in the comments.

Instagram Hashtag Research Bot with Make.com + Apify

alex — Fri, 27 Feb 2026 12:30:06 +0000

Today's build: automated Instagram hashtag research that delivers to Discord.

The Stack
Make.com — workflow orchestration
Apify (Instagram Hashtag Analytics actor) — scraping engine
Discord — delivery channel

The Flow
HTTP POST (start Apify run)
→ Sleep 30s
→ HTTP GET (fetch results)
→ Set Variables (format hashtag lists)
→ HTTP POST (Discord webhook)

Key Make.com snippet
To extract all hashtags from the Apify response array and join them line by line:

map() pulls the hash field from each object in the array. join() puts them on separate lines.
Simple but took me a minute to figure out.

What it returns
Three hashtag groups per niche: Related, Related Frequent, and Niche.

This is hashtag research based on Instagram's public graph — useful for content planning, not real-time trending.

*Get the blueprint
*
Gumroad → includes JSON blueprint + setup guide.
Full writeup on Hashnode → alexkraft.hashnode.dev

Real-time Gumroad sales tracker with Make.com + Google Sheets + Discord

alex — Mon, 23 Feb 2026 15:07:25 +0000

The problem:

Selling on Gumroad. Refreshing the dashboard too often. Classic. Automated it.

The flow:

Gumroad webhook
→ Log sale to Google Sheets
→ Update dashboard timestamp
→ Read total sales count
→ Discord: sale notification (always)
→ [Filter: milestone + not a test sale]
→ Discord: milestone alert (conditional)

Test vs real sales

Gumroad sends a test flag on every webhook. Both flow through the same scenario — just labelled differently in the sheet and in Discord.

Milestone alerts are filtered to real sales only.

What's in the package
Blueprint (JSON), setup guide, README. $9 on Gumroad.

→ Get it here

Built by Alex Kraft — automation developer. Follow the journey: alexkraft.hashnode.dev | linkedin.com/in/alexandru-bobo | dev.to/alexkraft

Automated Cold Outreach with Make.com + Apify + Google Sheets (No Code)

alex — Sat, 21 Feb 2026 11:46:14 +0000

Built a no-code automation that handles the full cold outreach pipeline for local businesses.

The flow:
Google Maps scrape → filter leads with emails → deduplicate → add to sheet → send personalised email → mark as sent

Tools used:
Make.com (workflow automation)
Apify (Google Maps scraper)
Google Sheets (lead database)
Gmail (email sending)

The interesting part is the duplicate check — before adding any lead, it searches column B of the sheet for that email. If it already exists, the whole branch is skipped. Keeps the sheet clean across multiple runs.
The email is personalised with the scraped business name using {{32.title}} from the Iterator module output.

I released it as a ready-to-import blueprint with docs.

👉 [Link here]