With this expansion, Opal is shifting from a low-code orchestration tool to a platform in which an AI agent independently determines which actions, tools, and models are needed to achieve a goal. The new agent runs on the Gemini 3 Flash model and automatically selects the tools needed to complete a task.
While new models with more parameters and better reasoning are valuable, models are still limited by their lack of working memory. Context windows and improved memory will drive the most innovation in agentic AI next year, by giving agents the persistent memory they need to learn from past actions and operate autonomously on complex, long-term goals. With these improvements, agents will move beyond the limitations of single interactions and provide continuous support.
For managers, product owners, and other non-technical professionals, the growing ecosystem of vibe-coding tools - platforms that let you describe what you want and automatically generate functioning code - opens the door to a new era of participation in the development process. Instead of wrestling with syntax or learning full programming languages, managers can now use structured prompts, open source vibe coding tools, plain English instructions, and iterative refinement to create scripts, prototypes, dashboards, automations, and even full applications.
The state of AI in software engineering report from Harness, based on a Coleman Parker poll of 900 software engineers in the US, UK, France and Germany, found that almost two-thirds of the people surveyed (63%) are already using artificial intelligence (AI) tools for code generation, and just over half (51%) anticipate that AI tools will significantly impact the speed of code creation.
