Opal, no-code visual builder for AI workflows, just got a major upgrade — a new agent step that analyzes your goal, determines the best approach, and automatically calls the right tools, such as Veo for video or web search for research, to complete the task. Also, new tools to make it more capable — Memory, Dynamic Routing and Interactive Chat.
The dynamic routing piece is what catches my eye here, letting the agent decide which tool to call based on the goal rather than hardcoding the path is the right architecture for real-world workflows. Most no-code AI builders skip this and it shows.
Memory + Interactive Chat in the same loop is a meaningful combo. Does the memory layer persist across separate workflow runs, or is it session-scoped? That distinction matters a lot for use cases like client-facing automations.
Been building multi-model orchestration pipelines myself and the "smart routing" problem is genuinely hard to get right. Curious to see how Opal handles edge cases when the agent picks the wrong tool. Congrats on the launch!
The wild part is how normal it feels now. Organizing the world’s information sounds dramatic, but when you think about Search, Maps, YouTube, Drive, Gmail… they basically became the default layer of the internet. Search used to be about links. Now it’s slowly becoming about answers. That shift is massive. Curious are you thinking about this from a product perspective or just browsing Product Hunt launches?
The app is weird.
I try to check app in the library and create my own and in both cases got error.
Looks the limits is poor.
Huge upgrade to Google Opal today!
With Opal’s new agent step, workflows aren’t just linear automations anymore, they can actually analyze the goal, decide the best approach, and call the right tools (Veo for video, web search for research, etc.).
That’s a meaningful shift from “flow builder” to “decision-making system.”
The addition of Memory is huge. Persistent context is what turns demos into real products. Combine that with Dynamic Routing (@ Go to) and Interactive Chat, and you’re basically getting conditional logic + user-in-the-loop + long-term context, without code.
Example Opals you can build now:
🏠 An Interior Design Collaborator that remembers your home’s aesthetic.
📖 An Interactive Storybook creator that evolves with your choices.
💡 An Idea Generator that interviews you to refine your vision.
My take: this makes “Super Gems” on Gemini way more powerful because now your workflows can think before they act. If Google keeps tightening the loop between Gemini, Veo, and Opal, this could become one of the most underrated no-code AI builder ecosystems out there.
About Opal 2.0 by Google Labs on Product Hunt
“Now with smart agent, memory, routing and interactive chat”
Opal 2.0 by Google Labs launched on Product Hunt on February 25th, 2026 and earned 368 upvotes and 4 comments, earning #3 Product of the Day. Opal, no-code visual builder for AI workflows, just got a major upgrade — a new agent step that analyzes your goal, determines the best approach, and automatically calls the right tools, such as Veo for video or web search for research, to complete the task. Also, new tools to make it more capable — Memory, Dynamic Routing and Interactive Chat.
Opal 2.0 by Google Labs was featured in Artificial Intelligence (466.2k followers) on Product Hunt. Together, these topics include over 86.8k products, making this a competitive space to launch in.
Who hunted Opal 2.0 by Google Labs ?
Opal 2.0 by Google Labs was hunted by Rohan Chaubey. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Reviews
Opal 2.0 by Google Labs has received 69 reviews on Product Hunt with an average rating of 5.00/5. Read all reviews on Product Hunt.
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Rohan Chaubey
The dynamic routing piece is what catches my eye here, letting the agent decide which tool to call based on the goal rather than hardcoding the path is the right architecture for real-world workflows. Most no-code AI builders skip this and it shows.
Memory + Interactive Chat in the same loop is a meaningful combo. Does the memory layer persist across separate workflow runs, or is it session-scoped? That distinction matters a lot for use cases like client-facing automations.
Been building multi-model orchestration pipelines myself and the "smart routing" problem is genuinely hard to get right. Curious to see how Opal handles edge cases when the agent picks the wrong tool. Congrats on the launch!