Velocity by Booz Allen

management platform provides tools to monitor and manage resource consumption, ensuring that the AI agents operate within their allocated resources. • Ethics and Compliance. As AI agents take on more complex tasks, ensuring ethical use and compliance with regulations becomes crucial. The management platform provides mechanisms to enforce ethical guidelines and ensure compliance with regulations such as those related to data privacy. • Continuous Learning and Improvement. AI agents can learn and improve over time. The management platform provides a framework for continuous learning, allowing the AI agents to adapt to new tasks, improve their performance, and stay updated with the latest advancements in AI. The AI Agents Management Platform is a critical component in the successful deployment of AI agents. It provides the necessary tools and controls to manage AI agents effectively, ensuring they deliver maximum value while operating within ethical and regulatory boundaries. As AI continues to evolve, this management platform will play a pivotal role in shaping the future of AI in software development. It will not only boost developer productivity but will also fundamentally transform the way developers interact with code.

AI agents and AI agent management are already revolutionizing the way developers code and how software development teams scale their work across the entire software development lifecycle. Today, we are on the cusp of witnessing not just an exponential growth in productivity but also a fundamental shift in human- AI relationships across software Over the coming year, we anticipate AI agents to evolve from simple task executors to advanced problem solvers. With the integration of LLMs, memory solutions, and tools, AI agents will be able to plan, execute, and reprioritize tasks more effectively, thereby overcoming current bottlenecks in task execution and reprioritization. This period will also see a surge in the development of specialized tools designed to enhance the capabilities of AI agents. These tools will address the current limitations and will be instrumental in improving the quality of task execution and the ability of AI agents to adapt to changing priorities. Major cloud providers are also expected to evolve their offerings to include trained AI agents callable via an API that can be deployed for specific functions at various stages of the development lifecycle. As AI agents take on more complex development teams. The Path Forward

emergence of robust frameworks for managing AI agents, including features for monitoring ethics and bias and mechanisms for dealing with potential threats from bad actors. We are on the brink of a new era where AI agents will become an integral part of the software development process, transforming it from a labor-intensive task to a highly efficient and automated process. This transformation will redefine the role of developers, turning them into managers of AI agents, and usher in a new age of software development where code is capable of writing code. Jarid Cottrell, Michael Martoccia, and Josh Gordon manage software delivery and digital strategy projects for federal clients. They also lead strategic initiatives and solution development at the intersection of AI and software innovation. Sahil Sanghvi is a distinguished technologist and head of strategy for Booz Allen’s Technology business, with a focus on emerging technologies and their applications in government and industry.

tasks, ensuring ethical use and compliance with regulations will become crucial. We foresee the

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Rapid advancements in generative AI have impacted every stage across the entire software development lifecycle. Massive innovation has brought about a seismic shift in a short period of time: from a world where humans solely wrote code to one where AI is an indispensable partner in coding. AI agents will allow development teams to scale their productivity, with humans providing oversight. LLMs which have been trained on a massive amount of data, including code libraries and technical examples, enable AI agents to be used within development workflows and across the software development lifecycle as the new medium for interaction between developers and code. The AI Agents Management Platform is a critical component in the successful deployment of AI agents. It provides the necessary tools and controls to manage AI agents effectively, ensuring they deliver maximum value while operating within ethical and regulatory boundaries.

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