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Google launches AI-powered mini app builder Opal in IndiaThe AI-powered vibe coding platform Opal is also being made available in Japan, South Korea, Vietnam, Indonesia, Brazil, Singapore, Colombia, El Salvador, Costa Rica, Panamá, Honduras, Argentina and other regions.
Rohit KVN
Last Updated IST
<div class="paragraphs"><p>Google Opal AI coding app.</p></div>

Google Opal AI coding app.

Credit: Google

A couple of months ago, Google launched an experimental application builder platform, Opal, that allows ordinary people with technical knowledge to develop apps or software code.

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It was later launched in the US, and since then, it has received a good response from the users.

Now, the search engine giant has expanded the availability of the Opal AI coding platform to 15 global regions, including India, Canada, Japan, South Korea, Vietnam, Indonesia, Brazil, Singapore, Colombia, El Salvador, Costa Rica, Panamá, Honduras, Argentina and Pakistan.

There is a new trend in the technology spree called vibe coding, and Opal will drive it further with new features.

For the uninitiated, vibe coding is a software development method where non-tech-savvy people use large language models (LLMs) to generate code with just natural language prompts.

With the new capabilities, Opal will be able to understand more complex prompts and deliver functional software code.

Also, with the new advanced debugging feature, users will be able to run their workflow step-by-step in the visual editor or iterate on a specific step in the console panel to rectify errors faster.

The app will display errors in real time and localise them to the exact step where the failure occurred to provide immediate context and eliminate guesswork. This feature will greatly reduce the time taken to track the bug and resolve it. The saved time can be used to further improve productivity to add more features to the app project.

Also, Google has enhanced the foundational model of the Opal app to respond faster and be more efficient in delivering the functional codes.

"We’ve also enabled parallel runs, allowing complex workflows with multiple steps to execute simultaneously, helping to reduce overall wait times," said Megan Li, senior product manager, Google Labs.

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