Copado Unveils AI Agents

Copado Unveils AI Agents to Automate Key DevOps Tasks for Salesforce Applications

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Copado has introduced a suite of generative AI agents designed to automate common tasks that DevOps teams frequently encounter when building and deploying applications on Salesforce’s software-as-a-service (SaaS) platform. This announcement comes ahead of the Dreamforce 2024 conference hosted by Salesforce.

These AI agents are the result of over a decade of data collection by Copado, according to David Brooks, Copado’s vice president of products. The initial AI agents will focus on code generation and test automation, with future agents tackling user story creation, deployment scripts, and application environment optimization. Unlike AI co-pilot tools that assist with code generation, Copado’s agents will fully automate tasks, Brooks explained.

DevOps teams will be able to orchestrate these AI agents to streamline workflows, making best DevOps practices more accessible to a wider range of development teams.

As AI continues to reshape DevOps, more tasks will be automated using agentic AI. This approach involves creating AI agents trained on a specific, narrow dataset, ensuring higher accuracy compared to general-purpose large language models (LLMs) that pull data from across the web. While it’s unclear how quickly agentic AI will transform DevOps, Brooks noted that in the future, teams will consist of both human engineers and AI agents assigned to specific tasks. DevOps engineers will still be essential for overseeing the accuracy of these tasks, but many of the repetitive tasks that often lead to burnout will be automated.

As the burden of routine work decreases, organizations can expect the pace of code writing and application deployment to significantly accelerate. This could lead to a shift in how DevOps teams approach application backlogs, enabling the deployment of more applications that might have previously been sidelined due to resource constraints.

In the interim, Brooks advises DevOps teams to begin identifying which routine tasks can be assigned to AI agents. Doing so will free up human engineers to manage workflows at a scale that was once unimaginable, positioning teams to thrive in the AI-driven future of DevOps.