Software 2.0: Productivity Suite

The future of software development isn't just for software engineers anymore. With modern AI coding assistants like Claude, Gemini, and others, anyone can create custom applications tailored to their specific needs—no computer science degree required.

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What is Software 2.0?

A Paradigm Shift

Traditional programming (Software 1.0) required years of training to write code line by line. Software 2.0 represents a fundamental shift: you describe what you want in natural language, and AI assistants help you build it.

This isn't about replacing programmers—it's about democratizing the ability to create custom tools that solve your specific problems.

Why It Matters for Physicians

As a physician, you understand your workflow better than any software developer. You know which tasks are repetitive, which tracking tools you need, and which visualizations would help your learning.

With Software 2.0, you can build those tools yourself—or adapt existing ones to fit your exact needs.

Core Principles for Building with AI

1. Start Small & Iterate

Begin with a simple version of your tool. Get it working, then add features incrementally. AI assistants excel at iterative development.

2. Be Specific in Prompts

The clearer your description of what you want, the better the result. Provide examples, describe edge cases, and specify your preferences.

3. Test & Validate

AI-generated code needs testing just like human-written code. Start with non-critical applications and validate thoroughly before production use.

Explore the Collection

These tools were created for personal use to solve specific workflow challenges. They're offered as inspiration and starting points for your own projects. Feel free to use them as-is, modify them, or use them as examples for building something entirely new.

Ready to Build Your Own?

You Don't Need to Be a Programmer

If you can describe what you want, you can build it. Modern AI coding assistants like Claude Code (Anthropic), Google Antigravity, GitHub Copilot, and Cursor can help you create functional applications from natural language descriptions.

These tools handle the technical complexity while you focus on the clinical logic and user experience you need.

Getting Started Steps

1. Choose Your AI Assistant

  • Things are rapidly changing for the better - these are two great options but I'd briefly browse Reddit or ask a LLM what the current best tools are right now if you're reading this past Winter 2026.
  • Claude - Seems to be currently winning
  • Google Antigravity - Full-featured AI coding environment and all you need is your google account

2. Learn Basic Git (Optional but Highly Recommended)

  • Version control helps track changes
  • Easy to undo mistakes
  • Essential for collaboration
  • Lets you take risks and experiment fearlessly, makes the whole process a lot more fun and less tedious
  • Check out our Git Tutor to get started

3. Start with a Simple Project

  • Pick a small, repetitive task you want to automate
  • Describe it clearly to your AI assistant
  • Iterate based on results
  • Test thoroughly before relying on it

4. Explore & Adapt Existing Tools

  • Browse our GitHub repository
  • Clone projects you find useful
  • Ask AI to help you customize them
  • Share your improvements back to the community

Important Notice: Personal Projects Only

These tools are personal projects created for individual use. They are shared as examples and inspiration for what you can build with modern AI coding assistants.

Not for clinical use without validation: These tools have not been validated for clinical or production use. If you wish to use any of these tools in a real-world clinical setting, appropriate validation, testing, and customization by qualified IT departments and clinical informatics teams is required.

No warranties or guarantees: These tools are provided "as-is" without any warranties. Use at your own risk and always verify outputs before making any clinical decisions.

Built for learning and exploration: The primary purpose of sharing these projects is to demonstrate what's possible and to encourage you to build your own custom solutions for your unique needs.

A Solo Project (For Now) — Join Me!

This is currently a solo project by a practicing physician exploring the intersection of clinical medicine and modern AI development. The goal is to start a community where we can all benefit from each other's work.

I Genuinely Welcome Contributions

This project needs your expertise, ideas, and contributions. Whether you're a physician who has built your own tools, a developer interested in healthcare applications, or someone who just has ideas for improvements—I'd love to hear from you.

Ways to Contribute:

  • Share your own tools - Built something useful? Let's add it to the collection
  • Improve existing tools - Found a bug or have an enhancement? Submit a pull request
  • Documentation - Help make these tools more accessible to others
  • Ideas & feedback - Suggest new tools or improvements
  • Testing & validation - Help validate tools for broader use

Welcome to Software 2.0

Let's take a quick tour of what Software 2.0 means and explore a few example tools to see what's possible when you combine clinical expertise with AI coding assistants.

This will take about 2-3 minutes. You can skip it anytime if you prefer to explore on your own.

What Makes Software 2.0 Different?

Traditional software development (Software 1.0) required you to write code line by line—a skill that took years to master. Software 2.0 changes everything:

You describe what you want in natural language

"I need a tool to track my CME credits and budget for the year, with categories for conferences, online courses, and books."

AI helps you build it

Modern AI assistants like Claude, Gemini, and others can generate working code from your description, iterate based on your feedback, and help you customize it exactly how you need.

Example: RVU Data Tracker

Let's look at a real example. The RVU Data Tracker helps physicians track clinic volume and productivity.

The Problem

"I want to track my clinic visits and RVUs over time to understand my productivity and plan my compensation."

The Solution

Built with AI assistance in a few iterations, the tool provides:

  • Easy data entry for each clinic session
  • Visual charts showing trends over time
  • Exportable reports for compensation planning
  • Local storage—all data stays on your device
Try It Out

Example: Clinical Flowchart Generator

The Clinical Flowchart Generator turns clinical algorithms into visual diagrams—either by AI parsing text or manual creation.

The Problem

"I need to create visual flowcharts for clinical pathways to teach residents, but drawing them manually is tedious."

The Solution

This tool demonstrates advanced capabilities:

  • AI parsing of clinical text into structured flowcharts
  • Visual editor for manual refinement
  • Export to multiple formats
  • Runs entirely in your browser—no server needed
Try It Out

You Can Build This Too

Here's the important part: you don't need to be a programmer to create tools like these.

Start Small

Pick one repetitive task you do regularly. Describe it to an AI coding assistant. Iterate until it works.

Adapt Existing Tools

Clone a tool from our GitHub, ask AI to help you customize it for your needs.

All the tools on this page were built this way—combining clinical expertise with AI assistance. You can do the same.

Ready to Explore?

You've completed the tour! Now you can:

Browse Tools

Explore all 17 tools in the collection

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Learn to Build

Get started with your own projects

Getting Started Guide

View Source Code

See how these tools were built

GitHub Repository

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