Doing Hard Things While Living Life: Why We Built Vade Studio in Clojure

A server crash during a Valentine's date became the turning point. The pursuit of technical complexity was costing more than just code - it was costing life itself. This is a story of how three developers built an ambitious no-code platform using Clojure.

Feature image of how clean code simplifies your life

February 14th, 2019. I still remember that day vividly. My wife and I were finally on our first date night in months, watching a movie we'd been planning to see together. As busy professionals, these moments were rare and precious. Then my phone started buzzing.

Our server instance had gone down. None of the standard playbooks were working. Instead of enjoying a romantic evening, I found myself in the lobby, frantically trying to restore service while our system hemorrhaged data. That was the moment I realized something had to change.

I had spent years building systems in Python, Go, and JavaScript. Each new layer of complexity fed my developer ego. But as scale increased, things started breaking in ways that weren't just technical problems – they were life problems. I was becoming someone who sacrificed playfulness and joyfulness for the sake of being successful.

I wanted to be a builder, but not at the cost of sacrificing the life I wished to live. After some soul-searching, I made two radical decisions: I left my job as an engineering lead to join a startup as a junior developer, and I decided to learn Clojure.

Building Vade Studio: A Modern NoCode Platform

Today, we're building Vade Studio with just three developers – myself and two developers who joined as interns when in college. When I tell other developers what we're building, their first reaction is usually disbelief. Here's what we've accomplished:

  • Real-time collaboration with conflict resolution
  • A drag-and-drop UI builder with live preview
  • Seamless third-party API integrations
  • Advanced database modeling
  • Complex workflow creation and management
  • A runner that converts configurations into deployable artifacts
  • Infrastructure-agnostic deployment
  • RAG (Retrieval-Augmented Generation) implementation

Building any one of these features would be challenging. Building all of them with a team of three might sound impossible. But Clojure has made it achievable.

Tackling Modern Web App Challenges

Let me walk you through how Clojure helped us solve some of the hardest challenges in building a modern web application:

Real-time Collaboration

One of our biggest challenges was building real-time collaboration. In a traditional stack, you'd need:

  1. A complex state management system
  2. Custom serialization protocols
  3. Conflict resolution frameworks
  4. Real-time pub/sub infrastructure

With Clojure, we modeled the entire collaboration system as a stream of immutable data transformations. Each user action becomes a transaction in our system. Because Clojure treats data as first-class citizens, we could build our own lightweight conflict resolution system using pure functions that operate on these transactions.

When conflicts occur, our system can merge changes intelligently because we're working with pure data structures rather than complex objects. This would have been significantly more complex in an object-oriented language.

The UI Builder Challenge

Building a drag-and-drop UI builder presented another set of challenges. We needed to:

  1. Handle complex state management
  2. Implement precise collision detection
  3. Manage a tree of UI components
  4. Provide real-time preview
  5. Support undo/redo functionality

Clojure's immutable data structures and persistent data structures made this surprisingly manageable. Every UI state is just a value, making undo/redo as simple as maintaining a history of these values. The REPL allowed us to test complex drag-and-drop scenarios by replaying actual user interactions and tweaking our algorithms in real-time.

Unified Data Modeling

One of our most powerful architectural decisions was using Pathom to create a unified data interface across our system. This approach allowed us to:

  1. Model our domain as a graph of attributes and relationships
  2. Abstract away the complexity of different data sources
  3. Compose complex queries from simple building blocks
  4. Handle data transformation and validation consistently

Starting with our domain model, we generate resolvers that expressed the relationships between different pieces of data. Pathom then allowed us to traverse these relationships seamlessly, whether the data lived in:

  • Our PostgreSQL database
  • Third-party REST APIs
  • GraphQL endpoints
  • In-memory caches

The power of this approach became evident when integrating new services. Instead of writing custom integration code, we simply:

  1. Define the shape of the data we need
  2. Generate resolvers that map between our domain model and the external service
  3. Let Pathom handle the orchestration of data fetching and transformation

Workflow Engine Evolution

Our workflow engine demonstrates the power of Clojure's simple abstractions. Instead of reaching for a comprehensive DAG implementation or workflow framework, we discovered that interceptors (a pattern I might never have encountered outside the Clojure ecosystem) provided an elegant solution.

Interceptors are simple data structures that describe a unit of processing with explicit enter and leave phases. Each interceptor is just a map containing pure functions:

{:name :validation-step
 :enter (fn [context] (validate-inputs context))
 :leave (fn [context] (validate-outputs context))
 :error (fn [context error] (handle-validation-error context error))}

This simple pattern allowed us to:

  • Compose complex workflows from small, focused pieces
  • Handle cross-cutting concerns like logging and error tracking uniformly
  • Implement bi-directional processing with the enter/leave phases
  • Add monitoring and debugging without modifying the core logic

As our requirements grew to include:

  • Parallel execution paths
  • Conditional branching
  • Error handling and recovery
  • State management

We found that interceptors scaled beautifully. Each new feature was just a matter of:

  1. Defining new interceptors for the specific capability
  2. Composing them with our existing chain
  3. Leveraging the built-in error handling and state management

The result is a powerful workflow engine built on a handful of simple functions that thread an immutable context map through a chain of interceptors. No complex frameworks, no topology management, no special runtime - just data and functions working together in a predictable way.

The REPL: Clojure's Secret Weapon

Clojure's REPL has been transformative for our development process. When building the UI builder's positioning system, instead of endless write-compile-run cycles, we could:

  1. Capture problematic states directly from the running system
  2. Experiment with different algorithms in real-time
  3. Test edge cases immediately
  4. Refine solutions iteratively
  5. Deploy fixes without restarting the system

What would have taken weeks of debugging in another language often takes hours in Clojure.

Living Life While Building Something Big

Perhaps the most remarkable aspect of building with Clojure is how it's helped us maintain balance in our lives. The robustness of Clojure systems means fewer emergencies. The REPL-driven development style means we can experiment and iterate without the mental overhead of complex debugging sessions.

We're building something incredibly ambitious with Vade Studio, but we're doing it while still maintaining time for life, for family, for joy. This isn't just about work-life balance – it's about building better systems. Clear minds write better code. When you're not constantly fighting fires or wrestling with framework complexity, you can focus on what really matters: creating value for your users.

The Road Ahead

Building Vade Studio has been an incredible journey, and we're just getting started. Clojure has given us the confidence to tackle ambitious problems with a small team while maintaining our sanity and joy in the process.

To those considering Clojure for their next project: yes, there's a learning curve. Yes, it's different from mainstream languages. But if you're looking to build robust systems while maintaining your quality of life, I can't recommend it enough.

Simple isn't easy, but with Clojure, we've found a path to building complex systems that doesn't require sacrificing our lives in the process.

Experience It Yourself

If you're curious about what a small team empowered by Clojure can build, we invite you to try it out at https://studio.vadelabs.com.

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