A new educational initiative, part of the Google Developer Program, is designed to furnish developers with practical skills for constructing and deploying AI agents using the Agent Development Kit.
As businesses progress from piloting AI agents to implementing them in production environments, Google is introducing a comprehensive skills program. This program aims to assist developers in constructing, evaluating, and operationalizing AI agents utilizing Google Cloud’s toolset, specifically its Agent Development Kit (ADK).
Dubbed the Gemini Enterprise Agent Ready (GEAR) program, this initiative is housed within the Google Developer Program. It offers practical lab exercises, 35 complimentary monthly Google Skills credits, and pathways to earn badges.
Currently, the available learning tracks include “Introduction to Agents” and “Develop Agents with Agent Development Kit (ADK).” These pathways are designed to help developers grasp the fundamental structure of an agent, understand their integration with Gemini Enterprise workflows, and learn how to build an agent using the ADK.
These specialized tracks will enable developers to acquire a new set of actionable engineering competencies vital for success in commercial settings, according to Google executives in a recent blog post.
They argue that by integrating GEAR into the Google Developer Program and Google Skills, developers can experiment without financial constraints and systematically master the process of building, testing, and deploying agents at scale.
This, in turn, empowers enterprises to accelerate the shift from isolated AI trials to practical solutions that deliver tangible benefits across production workflows, they further noted.
The challenge of transitioning AI from experimentation to full deployment is widely acknowledged: Deloitte’s 2026 State of AI in the Enterprise report revealed that only approximately 25% of 3,200 survey participants indicated their organizations had advanced merely 40% of their AI pilot projects into production.
Competing hyperscale cloud providers also offer comparable educational initiatives.
While Microsoft provides structured AI learning paths and certifications through Microsoft Learn, integrated with Azure AI, AWS delivers hands-on labs and instruction via AWS Skill Builder, featuring dedicated AI/ML and generative AI tracks.
Beyond simply developing skills, these programs appear to be closely linked to broader platform strategies. Google’s introduction of GEAR can thus be interpreted as part of a wider effort to solidify Gemini Enterprise’s standing as a formidable agent development platform, particularly as hyperscalers compete fiercely for dominance in the enterprise agent market.
Microsoft’s comprehensive ecosystem—including Azure OpenAI Service, Azure AI Studio, and Copilot Studio—has been actively positioning itself as a central hub for agent orchestration and workflow automation.
Similarly, AWS is promoting Bedrock Agents as an integral component of its foundational model ecosystem.
Other key players, such as Salesforce and OpenAI, are also active in this space. Salesforce offers its Agentforce suite, integrated into CRM workflows, while OpenAI’s Assistants API is being framed as a versatile agent layer.
