World Congress 2025 • Aug 20, 2025 • Session details

Rethinking Workflows in the Agentic Era

Eric Jadi , Rene Pajta

Single-prompt chatbots are obsolete. The future belongs to multi-step agentic workflows. Learn how to orchestrate specialized AI agents using deterministic metrics and iterative feedback loops.

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#1 about 3 min

Transitioning beyond single-task AI chat integrations

Moving from simple one-shot queries to complex multi-step workflows provides higher accuracy solutions for enterprise bottlenecks.

#2 about 4 min

Identifying complex workflows for multi-step AI automation

Iterating over problems like backend code migration and cloud infrastructure requires a strategic multi-step design mindset.

#3 about 4 min

Selecting and evaluating candidate workflows for agents

Choosing asynchronous processes where accuracy matters more than speed enables objective scoring and continuous iterative improvement.

#4 about 4 min

Mapping legacy processes to autonomous agent interactions

Decomposing human workflows into single-responsibility programmatic roles clarifies necessary tool requirements and multi-agent decision branches.

#5 about 4 min

Implementing, evaluating, and scaling multi-agent architectures

Isolating agent prompt testing prepares the overall workflow for parallel production execution and strict budget guardrails.

#6 about 8 min

Building an agentic cloud architecture and cost estimator

Specialized autonomous agents orchestrate pricing APIs and system documentation to dynamically validate infrastructure requirements with human supervisors.

#7 about 4 min

Iterating automated unit test generation with coverage metrics

Generating intermediate pseudocode before compiling automated test cases establishes deterministic feedback loops independent of subjective language models.

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Addressing the gap between coding assistants and complex workflows

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Shifting developer workloads and realistic AI productivity gains

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