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Fri, April 24DeepTech ArchitectureTechLead
An agent that performs well in a demo still faces a harder test in production, where real users, changing prompts, and unstable tools expose hidden weaknesses. This session focuses on turning a working agent into a system you can trust. Using a single concrete agent as the running example, the session defines what reliability means for multi step, tool using behavior, including success, partial success, and failure modes. It then shows how to design evaluations that reflect real usage by building golden datasets grounded in actual user intent and scenario based tests that cover full action paths. You will also learn how to structure evaluation runs, score outcomes to surface brittleness and silent failures, and set up regression tests that detect breakage as prompts, tools, or APIs change over time.
What You will Learn
How to define and classify reliability for multi step agents, including partial success and failure modes
How to build production relevant evaluation suites using golden datasets and scenario based action path tests
How to operationalize evaluation through scoring, regression testing, and monitoring for prompt, tool, and API drift
Who Should Attend
Developers building or maintaining AI agents
Engineers responsible for testing and reliability of AI systems
AI and ML practitioners deploying agents into production environments
Technical Leads overseeing quality and long term robustness of agent based systems
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Apurva Misra is an AI Consultant at Sentick, focusing on assisting startups with their AI strategy and building solutions. Apurva helps startups and mid-size companies start integrating AI and develop tailored solutions that align with their business goals. She is also a speaker, regularly presenting at conferences and online events about AI applications, strategy, and innovation. Passionate about democratizing education, Apurva shares her knowledge widely to make AI more accessible to everyone. Outside of work, she is learning Spanish and loves discovering hidden gem eateries, always open to new recommendations.
