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Business Reporting Automation
Automated a company's recurring reporting end to end on AWS Glue: monthly finance reporting with auto-generated presentation decks, scheduled business and regulatory reports for three marketplaces, a failed-payments Slack notifier plus operational alerts, and Basecamp-to-warehouse and helpdesk integrations — removing manual preparation from every monthly cycle.
The network for creativity
Join 1.25M professional creatives like you
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Creatives on Contra have earned over $150M and we are just getting started
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⚡ Automation Isn't the Hard Part. Knowing What to Automate Is.
Everyone talks about AI, n8n, Make, Zapier, and no-code automation. But there's a step people often skip:
What should actually be automated?
Not every manual task needs automation.
Sometimes the workflow is already too complicated.
Sometimes the process changes every week.
Sometimes automating a bad process just makes the bad process faster. 😅
Before building an automation, I like to ask
→ 📈 Does it happen often enough to matter?
→ ⏱️ Is it wasting meaningful time?
→ ⚠️ Does manual work create mistakes?
→ 🚀 Will automation actually improve the workflow?
Only after understanding the workflow should you choose the right solution — whether that's automation, AI, or simply a smarter process.
Don't automate everything.
Automate what shouldn't require a human.
What's one process in your work that you think is ready for automation? 👇
#DigitalTransformation #FutureOfWork #Startups #Entrepreneurship #BusinessGrowth #TechInnovation #SaaS #Freelancing
Automating Error Handling
I've recently worked on an error handling automation project, using n8n to connect Google Sheets, Telegram, and Gmail. The goal was to reduce manual monitoring and quickly identify issues. I'm happy to say it's been a success, and I've saved a significant amount of time. My tech stack includes n8n, Google Sheets, and Telegram, which have all been instrumental in this project.
#n8n #automation #ErrorTrigger #GoogleSheets
Follow for more: https://go.phonezait.de/
33 memories went in. 33 came back. The harder part was proving they still answered the same questions.
We ran a real GitHub issue + 31 comments through Memanto's OKF migration path. Result: 0 skipped, 0 removed, 0 changed—and 5/5 golden-question recall before and after.
74-second proof: https://youtu.be/E_r7tzmHtq0
Code, tests and one-command reproduction: https://github.com/moorcheh-ai/memanto/pull/1813
If you build agent-memory systems, what evidence would you require before deleting the source?
AI-assisted editing and synthetic narration; every result shown is from the reproducible command.
