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I built a Python workflow to collect and organize information from approved public Telegram channels. The workflow can collect post text, timestamps, channel names, public links, view counts, and other fields visible in the public channel.
It cleans and structures the collected records and exports them to CSV or Excel for research, monitoring, or content analysis. The sample shows the collection process and organized output. No private messages, private groups, login bypasses, or personal account data were used.
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Lost 2 days building a complex n8n workflow. Here's what I learned.✌️
The project: A 12-node AI Receptionist automation for a luxury resort in Bangladesh. Multi-channel (WhatsApp, Telegram, Voice), 9 Google Sheets, Gemini API, payment automation, customer CRM.
What went wrong: Added a new voice integration node. Accidentally deleted the entire workflow.
Why it happened:
No JSON exports after milestones
No version control (Git)
Testing changes LIVE on production workflow
No documentation
Building locally with zero redundancy
The fix (now implemented):
✅ JSON backups after every 2-3 nodes
✅ GitHub versioning
✅ Clone workflows for testing
✅ Modular design
✅ Complete documentation
For automation professionals: You're not just builders—you're engineers.
Treat workflows like software:
Documentation
Version control
Backup strategy
Modular testing
Client delays = lost revenue + credibility damage.
Make the systems bulletproof.
How do you prevent data loss in your automation builds? 👇
#n8n #Automation #WorkflowAutomation #NoCode #LessonsLearned #make #AIAutomation #DataAnalyst #MachineLearning
I'd try restoring one of those JSON backups into a cloned workflow before the next handoff. That way you know it can actually get you running again.
been working on some complex workflow illustrations for a big tech startup landing page redesign... [WIP]
The code panel against that Temporal checklist makes the retry logic readable. Pairing it with a plain headline like Handling Failures is what lets a dense workflow land on a marketing page.
Title: Digital SAT Prep Video — Scripted & Animated
Description: Built a full Manim scene script for a Digital SAT explainer video, including a custom color palette, portrait-mode video config for short-form platforms, and timed scene sequencing with synced text animations.
Tools: Manim, Python
