SysArt Academy
Move from prototypes to production systems and from isolated prompts to orchestrated workflows that deliver measurable value.
Stop building demos. Start building real AI systems that operate reliably in production — from architecture to observability.
Curriculum
Understand what agents really are and when to use them over traditional automation.
Design multi-step, multi-agent systems that coordinate reliably.
Connect agents to the systems that matter — APIs, databases, and internal tools.
Build retrieval pipelines that ground agent responses in real data.
Choose the right model for each task and optimize cost-performance trade-offs.
Monitor, evaluate, and debug agent behavior in production environments.
Build efficient systems that scale without burning through your budget.
Hands-On Experience
Who Should Attend
Engineers building AI-powered features who need to move beyond prototypes into reliable, scalable production systems.
Teams responsible for data pipelines and model infrastructure who are now building agentic capabilities.
Product managers and tech leads who need to understand what production AI requires and how to plan for it.
Outcomes
Build production-grade agent systems with confidence
Design scalable architectures for multi-agent workflows
Reduce failure risk in AI projects through proven patterns
Move your team from experimentation to real, measurable delivery
Next Step
We will work with your engineering team on real use cases from your organization.
SysArt Consulting
Use these links to connect the article with relevant consulting services and practical guidance.
This programme starts where most courses stop. It covers what changes when an agent system has to run unattended — failure handling, orchestration, evaluation, cost control and the operational patterns that keep it working after launch.
Working software engineering experience. Participants should be able to read and write code and understand distributed system basics. Prior agent framework experience is helpful but not assumed.
Yes. The guided implementation is built around a use case your team brings, so the architecture decisions made during the workshop apply directly to what you go on to build.
Two days covers the architecture and orchestration material. The longer format adds evaluation, observability and the production-hardening work, which is where most teams need the most support.