Agentic AI is breaking the traditional software development rules
To scale an enterprise workforce of AI agents, organizations need to combine the principles of employee management with software development rigor.
Agentic AI is revolutionizing software development by challenging the conventional Software Development LifeCycle (SDLC) approach. Unlike traditional trustworthy software systems that follow a structured plan, build, test, and maintain phase, AI agents are autonomous probabilistic actors that work effectively in real-time, event-driven environments.
To scale AI agent workforce, organizations need to adopt an Agent Development LifeCycle (ADLC) that combines the principles of employee management with software development rigor.
The ADLC mirrors the structure of the SDLC but incorporates the development and management of AI agents. To onboard AI agents, organizations can draw from the human employee lifecycle. A new agent should be defined with a job description, assigned tools and systems, trained, and integrated into a team, much like a new human employee.
However, unlike humans, AI agents require access to real-time contextual data to perform their tasks effectively. This necessitates a structured approach to onboard and integrate AI agents into an organization, ensuring their efficiency and scalability.
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