Writing application code is no longer the big hurdle in software engineering—defining exactly what to build, how to measure it, and how to scale it safely is the challenge. A lot of artificial intelligence projects stall because of structural and architectural decisions made early in development. In this recorded workshop, MongoDB Developer Advocate Apoorva Joshi introduces a structured, repeatable framework for making critical technical decisions to ensure your applications successfully reach production.
Key Takeaways:
- Identify the underlying business problem and establish clear, quantitative success metrics.
- Learn how to choose the ideal retrieval approach and technology stack for your specific requirements.
- Use evaluation frameworks and operational guardrails to measure system performance and mitigate bad outputs.
- Practice techniques for optimizing your system architecture during deployment to handle real-world user traffic.
Watch this session now and learn how to adopt a rigorous architectural framework to take intelligent systems from initial idea to stable production deployment.
