Google’s Opal Levels Up: AI Agents Now Turn Text Prompts Into Interactive Workflows
In a move that blurs the line between natural language and automated computing, Google has upgraded its Opal platform with a brand-new AI agent that empowers users to build agentic workflows simply by typing what they want. This isn’t your typical “run this prompt and get a response” feature — Opal now can plan, select tools, ask follow-up questions, and execute multi-step tasks on your behalf. (blog.google)
From Static Prompts to Dynamic Intelligence
First launched in mid-2025 as an experimental no-code “vibe-coding” tool, Opal lets anyone — from creators to product teams — build mini-AI apps (or “mini-apps”) through plain English prompts and visual workflows. Traditionally, Opal required users to define each logical step and tool in advance. With the new upgrade, that changes dramatically. (Yahoo! Tech)
Instead of manually picking models or sequencing steps, the upgraded Opal agent interprets your high-level goal, then…
- Plans the workflow — breaking your objective into executable steps.
- Chooses tools and models automatically (like Google Sheets, search, or other Gemini-powered services).
- Engages interactively — asking questions or offering choices when needed to refine the task.
- Maintains memory across sessions, letting your apps remember context like ongoing lists or preferences. (Dataconomy)
Whether you’re building a shopping list manager, internal briefing generator, or interactive storytelling tool, Opal’s agent steps make workflows feel less like rigid scripts and more like collaborative assistants that help refine and execute your vision. (blog.google)
Why This Matters
This upgrade reflects a growing shift in the AI world toward “agentic AI.” Instead of just responding to static prompts, these systems can reason, choose the right tools, and take action autonomously — all while maintaining conversational feedback loops with users.
In practical terms, you no longer need to be a developer to build dynamic, multi-step automations that adapt in real time. That puts Opal in direct competition with platforms like Microsoft Power Automate and Zapier, but with intelligence that can ask clarifying questions and make workflow decisions on the fly. (MLQ)
The update also underscores Google’s strategy of integrating its AI ecosystem tightly — with Gemini models powering the logic, Sheets providing memory, and Opal tying it all together in a no-code canvas. (Yahoo! Tech)
The Bigger Picture: Agents Everywhere
This isn’t just a one-off feature — it’s part of a broader industry trend. Tech companies (Google, OpenAI, Anthropic, etc.) are racing to make AI agents that don’t just answer questions but take action, plan tasks, and automate outcomes. That evolution has ripple effects for productivity tools, enterprise automation, and the future of work itself. (blog.google)
Glossary
- Agentic Workflow – An AI process where the system not only responds to inputs but plans, executes, and adapts tasks autonomously.
- No-Code / Vibe Coding – Software creation techniques that don’t require writing code; instead, users express intent via natural language or visual interfaces.
- Gemini 3 Flash Model – Google’s powerful AI model that underpins Opal’s agent logic.
- Dynamic Routing – The AI’s ability to choose different execution paths based on task requirements and real-time input.
Source
https://www.techinasia.com/news/googles-opal-introduces-agentic-workflows-via-text-prompts
