As AI agents powered by large language models (LLMs) rapidly move from experimentation to enterprise-scale adoption, organizations are facing a new reality: traditional software development lifecycles are no longer enough. Unlike static applications, AI agents are adaptive, probabilistic, and continuously evolving systems—requiring new approaches to testing, security, governance, and operations.

The Agent Development Lifecycle (ADLC) provides a structured, DevSecOps-based framework for building and managing AI agents that are safe, reliable, secure, and aligned with organizational and regulatory goals.

Read the e-book to learn about:

·       What AI agents are and why they’re transforming the enterprise, enabling autonomous multi-step workflows and redefining how work gets done

·       The Agent Development Lifecycle (ADLC) — a modern DevSecOps discipline tailored for designing, deploying, and improving enterprise agents

·       Agent observability, operations, and security best practices, ensuring performance, resilience, and protection in production

·       Governance frameworks to test, certify, and catalog agents, supporting compliance and responsible AI adoption

·       MCP server lifecycle guidance and reference architectures, enabling robust infrastructure for agentic AI platforms

·       Real-world client examples and enterprise use cases, highlighting how organizations are putting AI agents into action

Discover why adopting ADLC is essential for enterprises looking to operationalize AI agents responsibly—turning innovation into trusted, scalable outcomes.

Read the e-book to learn more!

Explore how IBM can help accelerate your agentic AI journey or connect with an expert for a live demo.