World Congress 2026 Europe Jul 9, 2026 Session details

Building a Multi-Agent Orchestration Engine That Actually Follows the Rules

Hussein Jundi , Torsten Stiller

Stop letting autonomous AI improvise your enterprise workflows. Discover how E.ON built a deterministic multi-agent orchestration engine that enforces strict SDLC guardrails.

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#1 about 6 min

Evolution of developer productivity and coding tools

Tracing the history of software tools reveals how past innovations paved the way for modern automated workflows.

#2 about 3 min

Shifting from prompt engineering to loop engineering

Moving beyond simple code generation towards orchestrating complex loops requires rethinking enterprise application development.

#3 about 4 min

Evolving job roles in the era of AI orchestration

How developers and domain experts are converging into modern creator roles specializing in agent operations.

#4 about 5 min

Choosing orchestrated workflows over fully autonomous agents

Restricting AI autonomy through preconfigured pipeline paths ensures state control and reliable enterprise outputs.

#5 about 3 min

Scaling enterprise automation using modular subgraphs

Breaking down massive workflows into reusable subgraphs provides modularity and saves significant computing computing costs.

#6 about 3 min

Building a minimum viable product stack for agents

Utilizing basic tooling like LangGraph and logging packages enables standardized deployments and traceable workflow telemetry.

#7 about 1 min

Designing production architectures for secure code execution

Implementing isolated execution sandboxes and fast streaming packages makes cloud-based agent workflows enterprise-ready.

#8 about 2 min

Best practices for testing and evaluating agentic workflows

Establishing golden datasets and thorough integration testing guarantees consistent performance across rapidly changing versions.

#9 about 5 min

Demonstrating an automated software development lifecycle workflow

Executing automated steps through a chat interface proves how deterministic routing mitigates unpredictable tool behavior.

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Transitioning from direct code editing to multi-agent orchestration

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Balancing developer autonomy with the adoption of coding agents

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Scaling declarative multi-agent software workflows on Kubernetes

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