Fast API

Research to Reality: Bringing Frontier ML Research to Production - Vaidas Razgaitis, Higharc

Research to Reality: Bringing Frontier ML Research to Production - Vaidas Razgaitis, Higharc

Vaidas Razgaitis, Senior Research Engineer at Higharc, shares three tactical tips to accelerate the transition of novel AI/ML research into production-ready features. He emphasizes addressing the critical handoff challenge between ML researchers and software engineers through structured documentation (Research Prototype Taxonomy Document), a well-organized monorepo utilizing decoupled microservices, and a systematic approach to code decomposition and PR review. These strategies aim to improve legibility, maintainability, and delivery speed for ML-driven products.

Why You Should Care About Observability in LLM Workflows

Why You Should Care About Observability in LLM Workflows

An inside look at AlwaysCool.ai's journey from simple GPT wrappers to a production-ready agentic infrastructure. This talk covers the evolution from synchronous tools to asynchronous, multi-step flows orchestrated by LangGraph, the critical role of OpenTelemetry for compliance and observability, and the architectural patterns of using FastAPI to serve centralized AI agents.