Google Introduces Agentic Workflows in Opal

Google Introduces Agentic Workflows in Opal Platform

Google has unveiled a new agent step in its Opal platform, marking a significant shift in no-code app development. This update allows users to create AI-driven workflows that autonomously select tools and models to achieve specified goals. The announcement was made on Google's official blog and is available to users worldwide. The integration of the Gemini 3 Flash model transforms Opal from static processes to interactive experiences (Google Blog).

Dynamic Workflow Capabilities

The new feature empowers workflow creators to define objectives using natural language. The agent then plans execution, triggers tools like Web Search or Veo for video generation, and adapts in real-time. For example, in an interior design app, the agent can interactively collaborate by uploading a room photo, querying user preferences, generating redesigns, and iterating based on feedback (TechCrunch).

Opal's Evolution

Originally launched in July 2025 as a U.S.-only experiment, Opal has rapidly expanded:

October 2025: Expanded to 15 countries, added debugging features.
November 2025: Available in over 160 countries.
December 2025: Integrated into the Gemini web app.

This evolution demonstrates Google's commitment to enhancing Opal from a prototype to a core component of its AI ecosystem (Reworked).

Key Enhancements

The agent step introduces five core enhancements:

Persistent Memory: Retains user data across sessions.
Dynamic Routing: Custom logic for multiple paths.
Interactive Chat: Solicits user input mid-process.
Tool Integration: Accesses Gemini models, Web Search, Veo.
Self-Correction: Optimizes paths automatically.

These features reduce manual setup, appealing to non-technical users and business IT teams (TechZine).

Competitive Landscape

Opal enters a competitive market with rivals like Replit and Lovable. Opal's differentiation lies in its agentic workflows and integration with Google's ecosystem (TechCrunch).

Implications and Future Outlook

Opal offers flexible automation but raises concerns about manageability due to agent unpredictability. Despite its experimental status, global expansion suggests longevity. This upgrade democratizes agentic AI, potentially accelerating adoption in SMBs and prototyping (Reworked).