Summary Bullets:
• Early agentic AI announcements focus on easing the app development/deployment process
• Agentic technology provides developers with greater access to advanced automation
Over the past few months vendors have made good on their promise, releasing the industry’s first AI agent solutions.
Overwhelmingly, those offerings are targeting enterprise developers, and for two good reasons. First, application platform providers have quickly transformed their AI assistants and copilots used largely for code generation into autonomous AI agents, attractive for their ability to automate more tasks and speed the application lifecycle; and second, the ease to which these agents help streamline new workflow automations provides developers with greater access to AI and data-driven technology previously out of reach due to a lack of expertise.
As a result developers are heavily sought after by vendors and service providers rolling out new AI agent tools and platforms. Examples of this trend have played out in the last few weeks.
During its Microsoft Build conference, Microsoft rolled out an upgrade of its popular Copilot AI assistant, enhanced through an autonomous coding agent which integrates with GitHub products. At the time of the announcement Microsoft reminded the industry that it is able to target an army of 15 million GitHub Copilot developers, implying that those coders just might be interested in seizing the opportunity to upskill into agentic AI. Late last year, Microsoft revealed a public preview of autonomous agents through Copilot Studio. Now developers can access new agentic capabilities, including “agent mode” and “code review”, to streamline app development, deployment, and troubleshooting. At the same time, new capabilities have been added to Azure AI Foundry Agent Service to help professional developers orchestrate multiple specialized agents.
Similarly, during its conference, Pegasystems announced agentic AI features within its flagship Pega Infinity App Studio, to ease the development process by injecting AI into learning, design, integration, user experience (UX), and testing of the application lifecycle. The idea, once again, is to speed the app development process through agentic capabilities, which include detailed instructions, best practices’ guidance, and streamlined integrations through automated third-party connections.
As part of the GenAI and agentic ecosystem, global system integrators are adopting a similar strategy releasing AI agent offerings that target developers. Deloitte stepped up its GenAI initiative by announcing an agentic network to help scale AI-driven workforce capabilities across its global markets, and provide customers’ development teams with greater access to high-productivity agentic services. The agentic network is based on a connected ecosystem of various AI business agent offerings, aimed at improving enterprises’ operations.
Ultimately, the release of these enhanced platforms open up new opportunities for developers, through greater automation of app development processes to help abstract operational complexities. This is particularly important when moving modern application architectures (e.g., microservices) quickly into production during the deployment cycle. This is the phase of app modernization which DevOps teams have struggled with for years, and the primary barrier of adoption of digital transformations. Overcoming those barriers is the promise of AI agents.
For more on these agentic AI announcements, please see Generative AI Quarterly Q2 2025: More Vendors go to Market with Agentic AI Solutions.