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Lily Mara explains how to avoid high-risk software rewrites through incremental FFI refactoring. She shares how engineering teams can replace Python bottlenecks with Rust via PyO3, demonstrating how to achieve dramatic function-level speedups, seamless integration testing, and meaningful infrastructure cost savings without microservice overhead.
Jim Gough and Andreea Niculcea explain how Morgan Stanley uses Architecture as Code with CALM to modernize its API program. They demonstrate integrating Model Context Protocol (MCP) and Agent-to-Agent (A2A) communications, enforcing automated governance through deployment gates, and executing zero-downtime platform upgrades to safely scale enterprise AI and agentic workflows.
OpenAI’s Vinoth Govindarajan discusses why production AI agents fail beyond model hallucination. Using real-world case studies like OpenClaw, he explains the key principles of reliable agent harnesses: establishing explicit state ownership, serializing concurrent state mutations, scoping execution authority, and validating actions at the user-visible edge.
David Gudeman discusses battle-tested architectural patterns for resource-constrained engineering teams. Drawing from over a decade of startup experience, he explains how pairing GCP, Firebase, and Cloud Run accelerates product-market fit. Learn how to eliminate redundant frontend state, structure event-driven backends, and maintain lean DevOps while building for long-term scalability.
In this episode, Sahil Agarwal talks about the critical challenges of identity, authorisation, and security in the age of AI agents. Sahil introduces the DPACT framework (Delegation, Policy, Auditability, Context, and Time) as a blueprint for building responsible, guardrailed agentic systems, moving away from simple token-based access toward bounded, delegated authority.
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QCon San Francisco
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