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AI Engineering

Agentic AI or classic workflow automation?

Not every process needs an agent. Deterministic automation is often cheaper and easier to control; agentic AI is useful when research, interpretation, planning or flexible tool use is required.

Production-first · open standards · auditability · operations
Assess the project technically →AI engineering overview
What a production approach must deliver
  • Use classic workflows for predictable rules, stable data and defined transitions.
  • Use agentic AI for variable inputs, research, multi-step planning and context-sensitive decisions.
  • Hybrid architectures combine deterministic core flows with AI at variable decision points.
  • Tool permissions, evals, limits and human oversight constrain autonomous execution.
  • Measure cost, latency and failure risk per process step.
Related search and project terms
Agentic AI vs automationAI agent vs workflowwhen to use AI agentsAI workflow automationdeterministic automationhybrid AI automationagentic workflowAI process automation comparison
AI Engineering
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