Now with smart agent, memory, routing and interactive chat
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!
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.
On the analytics side, Opal 2.0 by Google Labs competes within Artificial Intelligence — topics that collectively have 466.2k followers on Product Hunt. The dashboard above tracks how Opal 2.0 by Google Labs performed against the three products that launched closest to it on the same day.
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.
For a complete overview of Opal 2.0 by Google Labs including community comment highlights and product details, visit the product overview.
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!