When to use open source models vs proprietary APIs. Covers cost, control, privacy, quality, and deployment considerations.
A practical playbook for building a high-output AI engineering workflow, from morning planning and PR drafting to debugging, documentation, code reviews, and metrics that actually matter.
An in-depth analysis of a real-world RAG system failure in the legal industry, and the architectural lessons every AI engineer should learn from it.
Real infrastructure patterns for high-volume LLM applications: queue management, intelligent retries, request batching, and graceful degradation.
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Sunday 16th Aug 2026 · 8:30 PM IST · 2 hours · ₹1,499 · Full refund guarantee
2 hours of live coding. Build a real project. Walk away with a deployable app and a repeatable AI workflow.