Automating Dev Workflows with Scripts

by admin in Productivity & Tools 25 - Last Update December 3, 2025

Rate: 4/5 points in 25 reviews

For the longest time, I resisted scripting my daily tasks. It felt like a form of procrastination—why spend an hour writing a script to automate a task that only takes two minutes? It seemed like a classic case of a developer over-engineering a simple problem. I was wrong, and it took me an embarrassingly long time to realize just how much mental energy I was wasting on repetitive, mindless work.

Why I finally gave in to automation

The turning point wasn\'t a single big event. It was the slow, creeping realization that the \'two-minute task\' was never just two minutes. It was starting a new feature branch, which meant creating the branch, pulling the latest from main, creating a new test file, and updating a task tracker. It was deploying a small fix, which involved running tests, linting, building the container, pushing it, and then SSH\'ing into a server to pull the new image. Each step was small, but together they were a constant drain on my focus. I realized I was spending more time on the \'process\' of coding than on the actual coding itself.

My first scripts that changed everything

I didn\'t try to build a master script to rule them all. Honestly, that was my first failed attempt. I learned my lesson and started small, focusing on the most frequent and annoying tasks. These are the ones that gave me the quickest wins.

The \'new project\' setup

Every time I started a small project or a proof-of-concept, I\'d create the same folders: /src, /tests, /docs, /.github. Then I\'d initialize a Git repository, create a .gitignore file, and install a few base dependencies. I wrote a simple Bash script that does all of this with one command. It asks for a project name and then builds out my entire preferred starting structure. It\'s my personal boilerplate generator, and it saves me from a dozen tedious clicks and commands every single time.

The one-command build and deploy

This one was a game-changer. Our team\'s staging deployment process had about six manual steps. It was easy to forget one, especially on a Friday afternoon. I chained them all together in a script. Now, a single command does the following:

Runs all unit and integration tests.
Lints the entire codebase to check for style issues.
Builds the production-ready application.
Pushes the final build to our artifact repository.
Sends a notification to our team\'s Slack channel.

It not only saves time but also enforces consistency and prevents \'oops, I forgot to run the tests\' errors. I sleep better knowing the process is repeatable and reliable.

The biggest mistake I made when starting

My initial impulse was to create a perfect, complex, all-in-one script. I spent a weekend trying to build a \'dev assistant\' that could handle everything. It became a monstrous, unmaintainable mess that I quickly abandoned. The real success came when I changed my mindset. My advice is this: don\'t try to automate your entire workflow. Find the single most annoying, repetitive task you do more than five times a day and automate just that. Once that script is solid and you\'re using it without thinking, find the next one. Small, incremental automation is sustainable and incredibly powerful.

Choosing the right tool for the job

I often get asked whether to use Bash, Python, or something else. My personal rule of thumb is simple. If the task is mostly about running other command-line tools and moving files around, I stick with Bash. It\'s simple, it\'s everywhere, and it\'s perfect for chaining commands. If the task requires any real logic, like parsing JSON from an API call, handling complex error conditions, or managing state, I immediately reach for Python. Its readability and powerful libraries make it a much better choice for anything more than a few lines. Honestly, the best tool is the one you know well enough to be productive with right now.

Ultimately, automating my workflow wasn\'t about saving a few minutes here and there. It was about preserving my creative energy for the complex problems that I\'m actually paid to solve. It\'s about reducing friction and staying in a state of flow for longer. And for that, the upfront investment has paid for itself a hundred times over.

Frequently Asked Questions (FAQs)

What's the easiest task for a developer to automate with a script?

From my experience, the easiest and most rewarding first task is creating a 'new project' script. It's a process you do often but is filled with repetitive steps like making directories (src, tests), initializing Git, and creating a default .gitignore file. Automating this provides an immediate and satisfying win.

Should I use Bash or Python for my automation scripts?

My personal rule is this: if the script is primarily for running other command-line programs and managing files, I use Bash. It's fast and native to the terminal. The moment I need to handle data, make an API call, or implement any complex logic, I switch to Python for its superior readability and extensive libraries.

How do I keep my personal automation scripts organized?

I learned this the hard way. At first, my scripts were scattered everywhere. Now, I keep a dedicated `scripts` directory in my home folder and add it to my system's PATH. This way, I can run any of my custom scripts from any directory in the terminal just by typing its name. I also version control this folder using Git.

Can scripting actually make me less productive by taking too much time to write?

Absolutely, if you fall into the trap of over-engineering. I made this mistake early on. The key is to only automate tasks that are highly repetitive. If a task takes you 30 seconds and you do it 20 times a day, spending an hour to automate it pays for itself in less than a week. Start small and focus on high-frequency tasks.

What is the difference between personal workflow scripting and CI/CD?

I think of it in terms of scope and trigger. My personal scripts automate my individual, local development tasks—things I run on my own machine to speed up my work. CI/CD (Continuous Integration/Continuous Deployment) is a team-level automation that is triggered by code repository events, like a push to a branch, to automatically build, test, and deploy the application for everyone.