Building Duskline: From an Idea to a Live 3D Browser Game with Kiro and Antideploy
Duskline is a browser-based 3D sniper operations game focused on tactical shooting, precision aiming, stealth, and immersive gameplay. The player takes the role of a sniper and completes missions by observing the environment, identifying targets, and executing precise long-range shots. The game combines a dark cinematic atmosphere with interactive 3D gameplay to create a compact tactical combat experience that can be played directly in a web browser without requiring installation.
Building a game from scratch is not just about writing code. It involves turning an idea into a playable experience, designing the gameplay loop, handling assets and interactions, debugging unexpected problems, and finally getting the project into the hands of real users.
For my project, I wanted to build something small enough to run directly in a browser but still feel like a complete game.
That idea became Duskline — a browser-based 3D sniper operation game focused on precision, observation, tactical gameplay, and a cinematic atmosphere.
Live project: https://duskline.antideploy.com/
Source code: https://github.com/blackshadowog/duskline
The Idea Behind Duskline
The initial concept was simple:
What if a player could open a website, enter a 3D environment, take the role of a sniper, identify a target, aim carefully, and complete an operation without installing a traditional desktop game?
Instead of trying to build a massive game with dozens of systems, I focused on creating a compact gameplay loop.
The player enters the environment, observes the scene, identifies the objective, aims through the weapon/scope system, and attempts a precise shot.
The challenge was making the experience feel interactive rather than just presenting a 3D model inside a webpage.
This meant thinking about camera movement, aiming, interactions, environment design, game states, UI feedback, and the overall atmosphere.
Why I Used Kiro IDE
One of the biggest parts of the development process was using Kiro IDE as an AI-assisted development environment.
Kiro is built around an agentic development workflow, where the developer can work with an AI agent directly inside the development environment. It also provides structured specifications, requirements, design and task planning for larger features.
For Duskline, I used Kiro as a development partner rather than treating it as a tool that simply generates random blocks of code.
I could describe a gameplay requirement in natural language and use the resulting implementation as a starting point. This was especially useful when working on features where multiple pieces of the project had to work together.
For example, instead of thinking only in terms of:
"Create a sniper scope."
I could break the feature into smaller requirements:
- Enter aiming mode.
- Change the camera or visual perspective.
- Provide appropriate aiming feedback.
- Detect interaction with the target.
- Trigger the appropriate game state.
- Return the player to the normal gameplay state.
This approach helped me think about features as systems instead of isolated pieces of code.
Using Kiro for Iteration
Game development rarely works perfectly on the first attempt.
During development, I used Kiro to help investigate problems, understand existing code, modify features and iterate on the gameplay experience.
This was particularly useful because changes in one part of a browser game can easily affect another part. For example, changing camera behavior can affect aiming, UI positioning, controls, or interactions.
Instead of rebuilding features from scratch, I could give Kiro the existing project context and work iteratively.
Kiro's spec-driven workflow is designed around turning larger requirements into structured requirements, designs and implementation tasks, which is useful when a feature becomes too complex for a single prompt.
For me, the important lesson was that AI-assisted development works better when I provide clear requirements and review the generated changes instead of blindly accepting everything.
From Development to Deployment
Once the game was playable locally, the next challenge was simple:
How do I put it online?
I wanted a live URL that I could share with other people without asking them to clone the repository, install dependencies, configure the project and run it locally.
This is where Antideploy became part of the workflow.
Using Antideploy to Ship Duskline
I used Antideploy to deploy the Duskline project and make it available as a live web application.
The interesting part of Antideploy is that deployment can be driven through an AI coding agent. Its workflow is designed around giving the agent an instruction to set up deployment, approving the connection, and then letting the deployment system build and publish the application.
For Duskline, this turned deployment from a separate, complicated process into another part of the development workflow.
Instead of thinking:
Code → figure out hosting → configure server → configure deployment → debug deployment
the workflow became closer to:
Build → test → deploy → inspect → iterate.
The final result was a publicly accessible version of Duskline:
This was particularly useful for a browser game because the final product could be experienced directly from a URL.
The Development Workflow
The overall workflow for Duskline looked roughly like this:
1. Start with the gameplay idea
I first defined the core experience: a compact 3D sniper operation playable in a browser.
2. Break the idea into systems
Instead of trying to build everything simultaneously, I separated the project into gameplay, player interaction, aiming, environment, UI and supporting logic.
3. Build with Kiro
I used Kiro to help implement and iterate on these systems, explain existing code, troubleshoot issues and refine features.
4. Test locally
The game was repeatedly tested in the browser to catch gameplay and interaction problems.
5. Iterate
When something didn't behave as expected, I investigated the issue and modified the implementation rather than treating the first version as final.
6. Deploy with Antideploy
After reaching a playable version, I used Antideploy to make the project available online.
7. Test the deployed version
The final step was checking the actual live experience instead of assuming that something working locally would automatically behave identically after deployment.
What I Learned
The biggest lesson from Duskline was that AI-assisted development does not remove the need for engineering decisions.
It changes where the developer spends their time.
Instead of spending all of my time manually writing every piece of implementation code, I could spend more time describing what the system should do, reviewing the implementation, testing it and deciding what should happen next.
Kiro helped me during the development side of that process, while Antideploy helped close the gap between having a project on my machine and having an application that other people could actually access.
The combination created a workflow where development and deployment felt much closer together.
Kiro + Antideploy: Two Different Parts of the Same Workflow
One thing I found particularly useful was that these tools solved different problems.
Kiro was primarily part of my development workflow.
It helped me work through requirements, implementation, debugging and iteration.
Antideploy was part of my shipping workflow.
It helped me take the finished project and make it accessible as a live application.
So the workflow was not about replacing the developer with AI.
It was about reducing friction between an idea and a working product.
Final Result
Duskline started as an idea for a small browser-based tactical game and became a playable 3D web experience.
The project gave me an opportunity to experiment with AI-assisted development using Kiro, while also learning how an agent-friendly deployment workflow such as Antideploy can simplify getting a project online.
The live result can be experienced here:
And the source code is available on GitHub:
For me, the most interesting part was not simply building a game.
It was experiencing the complete journey:
Idea → Development → AI-assisted iteration → Testing → Deployment → Live Product.
That is the workflow I want to continue exploring as I build more software with AI-assisted development tools.
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