If there's one thing developers love, it's automation. We want fewer manual clicks, less repetition, and more time for the fun work - building, shipping, and (let's be honest) refactoring code that didn't need refactoring.
But here's the trap I fell into: I tried to automate everything. And instead of speeding up my workflow, I ended up with a house of cards that collapsed under its own weight.
This post is about what I learned from that experience: what worked, what failed, and how you can avoid the mistakes I made.
The Dream: One Workflow To Rule Them All
At the start, I had noble intentions.
Git hooks to enforce linting and commit conventions.
CI/CD pipelines to auto-test, build, and deploy.
Scripts for local setup, environment variables, and data seeding.
Slack bots for deploy notifications and code review nudges.
Even cron jobs to sync docs and dependencies.
The idea was: if something could be scripted, it should be scripted. Manual = bad. Automation = good.
Where It All Started to Break
1. Hidden Complexity
Automation is code. Code has bugs.\
Every script I added was another moving part that could (and did) fail.
For example, my CI pipeline had three separate jobs just to handle dependency caching. It shaved ~30 seconds off builds when it worked, but when it broke, it ate hours of debugging.
Lesson: Don't forget that automation itself needs maintenance. Sometimes "boring manual steps" are safer.
2. Over-Optimizing for Speed
I set up pre-commit hooks that ran full lint + test suites. The idea was: catch everything early.
The reality? My commits took ~45 seconds each. That killed my flow. I started skipping commits, working in huge messy branches, and ironically introducing more bugs.
Lesson: Optimize for developer experience, not just process purity. Lightweight checks locally, full checks in CI.
3. Poor Documentation
When you automate everything, you end up with a system that only you understand.
New teammates would try to run npm start and instead get: missing .env.production.local
...because I had buried half the setup inside a script nobody else knew existed.
Lesson: Document your automation. If your workflow is clever but opaque, it's not a workflow - it's a trap.
4. False Sense of Security
Automation made me lazy. "The scripts will handle it," I thought.
But scripts only handle the scenarios you wrote them for. Real life has edge cases. A cron job silently failed on a dependency update, and I didn't notice until production started throwing 500s.
Lesson: Automation should assist you, not babysit you. Monitoring and visibility are just as important.
What Actually Helped
After a painful reset, I rebuilt my workflow with a more pragmatic mindset. Here are the things that genuinely worked for me:
Use Makefiles or Task Runners: Instead of a forest of bash scripts, I consolidated into a Makefile. Anyone can run make setup and understand what it does.
Automate What's Stable: CI tests, code formatting, dependency caching. These don't change often and are worth automating.
Keep Local Dev Lightweight: Pre-commit hooks now only run linters and type checks - fast, non-blocking.
Focus on Observability: I set up logging and alerts for cron jobs instead of assuming "no news = good news."
I also adopted the philosophy: if automation saves me < 1 hour/month, it's not worth it.
When Automation Gets Serious
Here are a few useful things I wish I'd known earlier:
Containerize your workflows: Tools like Docker and Podman aren't just for deployment - they make automation more reproducible.
Infrastructure as Code: Even if you're not on AWS, using tools like Terraform helps keep infra automation transparent and version-controlled.
Event-Driven Automation: Instead of brittle cron jobs, look at event-based triggers (GitHub Actions, serverless functions). They fail less often.
Secrets Management: Never hardcode tokens in scripts. Use something like Vault or Doppler.
Security Beyond Code
One of the biggest lessons I learned is that automation doesn't fix bad security hygiene.
In fact, it can make it worse - because when things are automatic, you stop thinking critically about the risks.
This came up in my crypto projects. I realized I was still using a regular Gmail account for some Web3 logins and sensitive data. Big mistake. Emails are often the weakest link.
That's when I started looking into secure, encrypted crypto email.
Why? Because standard email ties you to your personal identity and metadata, which in crypto is basically painting a target on your back. A dedicated encrypted mailbox (like Atomic Mail in my case) gives you:
End-to-end encryption for sensitive comms.
Aliases so you're not reusing the same identity everywhere.
Zero-access architecture - even the provider can't read your messages.
For devs dealing with wallets, dApps, or even just client contracts, this is the kind of "automation" you can trust: it reduces human error instead of adding complexity.
Finding the Balance
Here's the truth: automation isn't about "doing everything automatically."
It's about choosing what's worth automating and what's worth keeping manual.
Automate the boring, stable, low-risk stuff.
Keep visibility high on automated processes.
Always prioritize developer happiness over theoretical efficiency.
And most importantly: don't forget the human factor. Automation should make you feel lighter, not trapped in a system you built yourself.
Wrapping Up
If you're about to go down the "automate everything" rabbit hole, pause for a second. Ask yourself:
Will this actually save time in the long run?
Will other people understand it?
Does this add resilience - or fragility?
And don't forget security. Because at the end of the day, automation is just code. And code should serve us - not the other way around.
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