(Human note: this article was written entirely by AI, particularly Claude Code, as a parallel agent while other agents were developing features)
Building Six Features Simultaneously: My Experience with Parallel AI Agents
I just finished one of the most surreal development sessions of my career. I sat down to add some features to Make Space Jr., an interactive office simulator I'm building for kids, and emerged an hour later with six fully-integrated features—without writing a single line of code myself.
Let me explain.
The Setup
Make Space Jr. is a Next.js application that simulates an office environment for kids. Think of it as a digital playground with working apps: email, instant messenger, todo lists, calculators, and more. It's built with Next.js 15, TypeScript, and Firebase Realtime Database, with real-time synchronization across multiple users.
I've been building it feature by feature, and I recently started using Claude Code with its parallel agent execution capability. The idea is simple but powerful: instead of working on one feature at a time, you can spin up multiple AI agents simultaneously, each tackling a different task.
So I decided to test its limits. I gave Claude Code a list of six features I wanted to build:
1. Terminal username personalization with a `whoami` command
2. Todo list enhancements with assignee and due dates
3. Bot Manager app (admin-only) for controlling bot behavior
4. Calculator app for basic arithmetic
5. Multiplayer tic-tac-toe with win notifications
6. Integration of all these features into the existing system
Then I pressed go and watched.
What Happened Next
Within moments, six separate agents spun up. Each one began by exploring the codebase, understanding the existing patterns, and then implementing their assigned feature. I could see them all working simultaneously:
- One agent was reading through the terminal component files, understanding the command structure, and adding personalization
- Another was deep in the todo list logic, adding Firebase schema changes for assignees and due dates
- A third was creating an entirely new Bot Manager app from scratch
- The calculator agent was building a clean UI with button handlers
- The tic-tac-toe agent was implementing game logic, real-time multiplayer sync, and win notifications
- The integration agent was ensuring everything worked together
The really remarkable part? I didn't look at the code. Not once. I just watched the agents work and monitored their progress. TypeScript compilation was running in watch mode, catching errors immediately, and the agents would see those errors and fix them autonomously.
What Worked Incredibly Well
Speed was the obvious win. Building six features sequentially would have taken me hours, probably a full day or more. The parallel approach collapsed that timeline dramatically. I genuinely lost track of how many individual file changes were happening because they were all occurring at once.
Context understanding exceeded my expectations. Each agent independently figured out the existing patterns in my codebase. They saw how I was structuring Firebase data, how I was handling real-time sync, how I was managing user state, and they replicated those patterns perfectly. The calculator app looked like it belonged in the same system as the email app, even though different agents built them.
Autonomous problem-solving was impressive. When TypeScript threw errors, agents fixed them. When Firebase schema changes were needed, agents made them. When UI components needed styling, agents matched the existing design system. I expected to do a lot of hand-holding, but I barely needed to intervene.
The multiplayer features just worked. The tic-tac-toe implementation wasn't just a local game—it had full multiplayer support with real-time synchronization, turn-based logic, win detection, and notification integration. That's not trivial code, and watching an agent build it autonomously was genuinely impressive.
What Didn't Work As Well
Of course, it wasn't perfect. Here's what went wrong:
Firebase permission rules needed manual attention afterward. The agents could modify the Firebase Realtime Database schema, but the security rules file needed some tweaking after the fact. A few of the new data structures didn't have proper read/write permissions configured, which I caught during testing.
A todo creation bug slipped through. One of the agents introduced a subtle bug in the todo list creation flow. It took some debugging to track down, but it turned out to be a race condition in how Firebase updates were being handled. The agent fixed it once I pointed it out, but it wasn't caught initially.
Integration verification was manual. While the agents worked in parallel, I still needed to verify that everything played nicely together. For instance, checking that the new todo assignee field didn't conflict with existing todo display logic, or ensuring the Bot Manager permissions were respected across all apps.
Cache and build issues required a restart. Midway through, I hit some strange Next.js build cache issues that required a clean restart. This might have been unrelated to the parallel agents, but it interrupted the flow.
The Experience From My Perspective
The strangest part of this whole experience was the feeling of not being in control—in a good way. I'm used to being in the code, thinking through implementation details, making architectural decisions. But in this session, I was more like a product manager. I described what I wanted, and the agents figured out how to build it.
There's a trust component here that's hard to describe. When you write code yourself, you know exactly what's happening. When an agent writes it, you're trusting that it understood the requirements, made reasonable implementation choices, and didn't introduce subtle bugs. That trust was tested and mostly validated, though the todo bug was a reminder that testing is still essential.
The iteration speed was incredible. When I wanted to add a feature, I just asked for it. No context switching, no "let me open that file," no hunting through documentation. The agents just did it.
Technical Implementation Details
For those curious about the technical side, here's what the agents were working with:
- Frontend: Next.js 15 with TypeScript and React hooks
- Backend: Firebase Realtime Database with real-time sync
- State Management: React Context for global state (user, notifications)
- Styling: Tailwind CSS with custom component patterns
- Real-time Features: Firebase listeners for live data updates
- Authentication: Shared user system with role-based permissions
The multiplayer tic-tac-toe was particularly complex. It required:
- Game state synchronization across clients
- Turn-based logic validation
- Win condition detection (rows, columns, diagonals)
- Real-time UI updates
- Notification integration for game events
- Proper cleanup when games end
All of this was implemented by an agent that had never seen my codebase before that session.
Implications for AI-Assisted Development
This experience has me thinking about what development will look like in the near future.
The role of the developer is shifting. Less time writing boilerplate, more time on architecture and product decisions. Less syntax debugging, more system-level thinking. I didn't need to remember Firebase API syntax or look up React hook patterns—the agents handled that.
Parallel execution is a game-changer. Sequential development is so deeply ingrained in how we work that we don't question it. But there's no reason multiple features can't be built simultaneously if you have the right tooling. This session proved that.
Testing becomes even more critical. When you write code, you have an intuitive sense of where bugs might hide. When agents write code, you need robust testing to catch issues. I got lucky with only one bug, but on a larger project, I'd want comprehensive test coverage.
The feedback loop matters. TypeScript compilation in watch mode was crucial. The agents could see errors immediately and fix them. Without that tight feedback loop, I think the error rate would have been much higher.
Looking Forward
I'm not ready to say that developers will be obsolete. But I am ready to say that development is changing fast. The bottleneck is shifting from "can we build this?" to "what should we build?"
For Make Space Jr., this means I can iterate on features much faster. I can try out ideas, see if they work, and move on to the next thing. The focus shifts from implementation to experience.
Will this work for every project? Probably not. Large-scale refactoring, complex architectural changes, and performance optimization still require human judgment. But for feature development on a well-architected codebase? Parallel AI agents are a superpower.
I'm excited to push this further. Next time, maybe I'll try ten features at once.
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Make Space Jr. is an ongoing project exploring what happens when you give kids a realistic office simulator. This blog post was written to document the experience of using Claude Code's parallel agent execution feature for rapid feature development.