95% of My Work Happens in VS Code

Right now, as I write this, my desktop has six VS Code windows open. One for this article. One for a course I’m developing. One for a data analysis pipeline. One for a research paper draft. One for a custom tool I’m building. One for meeting prep. Behind them, a browser with a dozen tabs and my email. That’s it. That’s my entire workstation.

Word, Excel, PowerPoint, SPSS, R Studio, Endnote, even Overleaf in the browser: I barely use any of them anymore to actually do my work. And I don’t miss them.

Why VS Code?

VS Code is a free, open-source code editor made by Microsoft. But calling it a “code editor” undersells it. It’s a general-purpose working environment that handles text, code, data, notebooks, terminals, and extensions for almost anything you can imagine. Here’s why I use it instead of a dozen separate apps:

• It’s free. No subscription, no license, no “educational pricing.” Just download it and start working.
• AI assistants live inside it. GitHub Copilot, Claude, and other AI coding assistants integrate directly into VS Code. The AI sees your files and your project context, and helps you in real time. CLI tools like Claude Code, OpenAI Codex, and Google Gemini CLI bring even more powerful agentic capabilities into your terminal.
• Everything is a text file. Markdown for writing, LaTeX for papers, Python or R notebooks for data, HTML for presentations, CSV for data. When everything is text, everything is searchable, versionable, and portable.
• One environment, zero context-switching. No more bouncing between Word, Excel, PowerPoint, and a stats package. It’s all in one place.

And if you’re an academic or student: sign up for GitHub Education and you get GitHub Copilot for free, plus a stack of other developer tools, with no reason to pay for Cursor, Windsurf, or any other premium tool. That said, once you start using AI assistants for everything, a paid tier can be worth it for the best models. Full disclosure: I use the free tiers for OpenAI and Gemini, but I pay for Claude, primarily through their CLI tool, Claude Code. You don’t need to pay anything to get started, but as your usage grows, the upgrade pays for itself quickly.

What I Actually Use It For

Writing

Papers, course materials, blog posts, grant applications, reviews: I write all of it in Markdown inside VS Code. Markdown is plain text with simple formatting: **bold**, *italic*, # Heading. It takes five minutes to learn and works everywhere. For papers that need LaTeX, I use the Overleaf extension and edit those projects directly inside VS Code, with the AI helping me write and debug LaTeX without ever opening a browser tab.

Why not Word? Because Word files are opaque blobs that break version control, create formatting nightmares when you collaborate, and lock your content into a proprietary format. Markdown is clean and portable, and it plays perfectly with git. When I need a formatted PDF or Word document for submission, I convert with a single command using Pandoc.

Data Analysis

Jupyter notebooks and Python scripts inside VS Code: pandas, matplotlib, seaborn, scikit-learn, all in the same editor where I write my papers, taking me from raw data to publication-ready figures without leaving the window. I can hand it a messy repeated-measures dataset and ask for a full mixed-effects model with post-hoc comparisons and a residuals check. It writes the code, I review and run it. It’s particularly good at catching statistical mistakes I might have glossed over. I haven’t opened SPSS or Stata in years.

Lecture Slides and Course Content

I’ve written about this in detail: I code all my lecture slides in HTML using reveal.js and AI assistants. But the slides are just part of it. Reading guides, assignment briefs, rubrics, student resources: all written in Markdown or HTML inside VS Code, version-controlled in git, generated and updated with AI assistance. And if your university uses a platform like iLearn, Canvas, or Blackboard, you can paste the HTML directly in and your content looks super professional, for almost no extra work, and no more fighting the horrible built-in text editors.

Editing and Reviewing

When I review a paper or edit a colleague’s draft, I dictate my comments into a Markdown file as I read, then ask the AI to help me draft the review and make sure I haven’t missed anything. For grant reviews, I paste the criteria in too, so the AI helps me address every one systematically.

One note on privacy: I don’t feed the paper or grant itself to the AI, only my own comments and notes. If I do need the AI to read a paper directly, I use a local model on my own machine, so nothing leaves my computer (more on why local LLMs matter).

Building Custom Tools

This is where things get interesting. Because VS Code is a coding environment, I don’t just use existing tools. I build the ones I need. I built a benchmarking tool that scrapes publication and grant funding data, analyses it, and generates figures and slides, ranking my school against every other psychology school in Australia to identify our strengths and where we need to improve. It didn’t need to be polished, just a quick, practical tool that solves a real problem.

Here’s the thing: I’ve been coding for near 40 years, but what used to take me weeks or even months to develop I can now do in hours or days. The AI makes building these tools so fast that it’s worth doing even for one-off tasks. Things I’d never have bothered to build before, I now put together in an afternoon.

And the rest: research ideas, conference abstracts, reference management, to-do lists. If it involves text or code, and almost everything does, it happens in VS Code.

The Desktop

This isn’t about being a minimalist. It’s about speed. Every time you switch apps, you lose context. You wait for it to load, remember where you left off, find the right file. Those transitions add up to hours every week. When everything lives in one environment, with one set of keyboard shortcuts, one search function, and one AI assistant that understands your whole project, you move fast.

”But I’m Not a Programmer”

You don’t need to be. Most of my research students in psychology have never written a line of code before they start working with me, and within a week or two they’re up and running. I even get my undergraduates going in a single one-hour lab, and by the end of the semester they’re AI-assisted productivity pros. And, importantly, they know how to use these tools to enhance their critical thinking and problem-solving skills, not bypass them. (I write more about this in a related article.)

The AI is the key. You don’t need to memorise syntax or commands. You describe what you want, the AI writes the code, and you learn by doing. Without even knowing it, you actually become a coder, but you never need to become a software developer.

If you can write an email, you can use VS Code. The learning curve is real (budget an hour or two to get comfortable) but the productivity gain on the other side is enormous.

Where This Is Going

I think the future involves fewer standalone SaaS applications and more environments like this. The boundary between using a tool and building one is starting to blur.

Getting Started

If you’re curious, here’s how to start:

1. Download VS Code. It’s free. Install it.
2. Sign up for GitHub and GitHub Education. Use your university email. You’ll get Copilot for free.
3. Install GitHub Copilot from the VS Code extensions marketplace. This is your AI assistant.
4. Pick one task you currently do in another app (writing a document, analysing some data, creating a presentation) and try doing it in VS Code instead.
5. Ask the AI for help constantly. “How do I create a Markdown file?” “How do I run a Jupyter notebook?” “How do I make this text bold?” There are no stupid questions when you’re talking to an AI.

And once you’re in, explore the extensions marketplace: Overleaf and LaTeX, Jupyter notebooks, CSV viewers, PDF readers, Zotero integration. Whatever your workflow involves, there’s probably an extension that brings it into VS Code.

For a step-by-step version of all this (setup, the extensions worth installing, and what to actually use it for) see the VS Code for Academics guide.

You won’t switch everything overnight. I didn’t. But once you see how much faster you work with an AI assistant in a unified environment, you’ll start migrating more of your workflow, and the separate apps will quietly disappear from your dock.

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The best tool is the one that gets out of your way and lets you think. For me, that’s VS Code with an AI assistant. Everything else is overhead.

Michael Richardson Professor, School of Psychological Sciences Faculty of Medicine, Health and Human Sciences Macquarie University

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AI Disclosure: This article was written with the assistance of AI tools, including Claude. The ideas, opinions, experiences, and workflow described are entirely my own. The AI helped with drafting, editing, and structuring the text. I use AI tools extensively and openly in my research, teaching, and writing, and I encourage others to do the same. Using AI well is a skill worth developing, not something to hide or be ashamed of.

It’s also worth acknowledging that the AI models used here (and all current LLMs) were trained on vast quantities of text written by others, largely without explicit consent. The ideas and language of countless researchers, educators, and writers are embedded in every output these models produce. Their collective intellectual labour makes tools like this possible, and that contribution deserves recognition even when it can’t be individually attributed.