GitHub Spark is now in public preview. The micro-app creator was first announced at GitHub Universe last fall, and is now available for Copilot Pro+ subscribers.

When GitHub Spark was announced, GitHub described it as a tool for building and sharing personalized micro apps (“sparks”). Spark is powered by natural language, and is aimed at hobbyists rather than professional developers. Spark offers live history, previews, and the ability to edit code directly.

As with Google Opal, which we reported on when it was  announced last week, the ideal Spark application is one that would otherwise not be created because it seems too short-lived, niche, or time-consuming to prioritize.

Sparks are directly usable from your desktop and mobile devices without needing to write or deploy any code. It has three tightly-integrated components: a natural language-based editor for describing your ideas; a managed runtime environment, which hosts your sparks, and provides them access to data storage, theming, and LLMs; and a progressive web apps-enabled dashboard, which lets you manage and launch your sparks from anywhere.

To use Spark, you describe your idea using natural language, and Spark builds it using Claude Sonnet 4's hybrid reasoning model.

You can then add intelligent features powered by LLMs from OpenAI, Meta, DeepSeek, and xAI. The app can then be published with a single click. You can also use visual editing controls, or code with GitHub Copilot code completions. 

Once the basics are there, users can add a repository with GitHub Actions and Dependabot incorporated, and expand the app using Copilot agents. 

The documentation for Spark suggests that if you have a specific idea for a feature or app, you can upload a mockup, sketch, screenshot, or even paste a markdown documentation into Spark and ask Spark to build out your idea.

Another suggested use is to build internal tools for yourself and your team. If you have a common workflow or process that currently sits in a document or spreadsheet, explain your workflow or process to Spark and Spark can turn it into an interactive web app.

GitHub Spark relies on four iteration methods - interactive previews, revision variants, automatic history and model selection. 

Interactive previews refers to the fact that when you type a natural language phrase into Spark, in addition to generating code it also runs and displays it via an interactive preview, meaning you quickly see what else you need. You can also optionally request a set of variants. This will generate 3-6 different versions of your request. The developers say this is aimed at cases where you might know you want a feature, but not quite know how it should look or behave.

Every revision is automatically saved and can be restored in a single click.  The idea is this encourages "curiosity-driven development", where you can have an idea, and then try it out, without any fear of negative consequences (e.g. messing up your app).

When you create or revise a spark, you can choose from one of four AI models: Claude Sonnet 3.5, GPT-4o, o1-preview, and o1-mini. This means you can see how your ideas are interpreted by different models. 

GitHub Spark and the recently announced Google Opal bring vibe coding tools more to the fore, though they are just the latest additions to options such as Tempo Labs, Bolt.new, and Lovable.dev.    

More Information

GitHub Spark

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