What are agentic workflows and how to build them in the AI software development lifecycle
Blog post from Port
Agentic workflows are advanced processes within the AI software development lifecycle that utilize autonomous agents to perform tasks by reading platform context, deciding on actions, and altering software states under enforced guardrails. Unlike traditional scripts with predetermined steps, agentic workflows allow agents to make decisions dynamically based on real-time observations, ensuring adaptability and responsiveness. These workflows rely on a robust platform foundation, consisting of shared pillars like context lakes, reusable actions, scorecards, workflow orchestrators, access controls, and engineering intelligence, to ensure repeatability, safety, and observability. The integration of deterministic scaffolding with non-deterministic agent reasoning allows for flexible yet controlled operations, where human engineers and AI agents collaboratively enhance software development processes. By embedding governance at the platform level, agentic workflows become reliable tools that are easily adopted and scaled across organizations, providing a model for efficient, autonomous, and secure AI-driven development.
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