[Full Workshop] Vibe Coding at Scale: Customizing AI Assistants for Enterprise Environments
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슬라이드 7장19:43EN
AI Engineer· 2026년 10월 26일Jack Wotherspoon on Building a Team of Managed AgentsJack Wotherspoon · Google DeepMindGoogle DeepMind’s Jack Wotherspoon introduces Gemini Managed Agents: cloud sandboxes that let teams run coding and research agents with a single API call. He explains how persistent environments, reusable skills, proxy-injected credentials, schedules, and specialized agents fit together.에이전트 엔지니어링Agent orchestrationSandboxes & isolation+2
슬라이드 5장20:55ENAI Engineer· 2026년 10월 26일Jesse Hall：语音智能体要为对话而优化，而非只看排行榜Jesse Hall · LiveKitLiveKit 的 Jesse Hall 解释了为什么语音智能体必须像实时系统一样接受评测：听清用户、允许打断、在工具调用期间继续对话，并在用户真正听到声音之前控制延迟。음성 AI에이전트 엔지니어링평가(Evals)+2 
슬라이드 8장18:27ENAI Engineer· 2026년 10월 26일Daksh Gupta on Building a Better AI Code Review AgentDaksh Gupta · GreptileGreptile co-founder Daksh Gupta explains why a webhook plus a coding agent is not enough for reliable pull-request review—and how targeted prompts, incident data, model inversion, codebase context, browser testing, and task-specific model routing can help.Code review & verification코딩 에이전트개발 워크플로와 테스트+2 
슬라이드 12장17:56ENAI Engineer· 2026년 10월 25일How Bridgewater Keeps Its AI Analyst Inside Permission BoundariesNikhil Benesch, Aaron Linsky · turbopufferAaron Linsky and Nikhil Benesch explain why search over an enterprise vault must honor document permissions without sacrificing recall or speed. Their solution combines vector indexing with native filtering to search hundreds of millions of vectors in roughly 120 milliseconds.엔터프라이즈 AIPrivacy & data governanceSearch & retrieval+2 
슬라이드 7장35:19ENAI Engineer· 2026년 10월 25일SallyAnn DeLucia: How to Write Your First AI EvalSallyAnn DeLucia · Arize AITurn an agent’s real traces into concrete pass/fail criteria, then build an LLM judge you can test, align with people, and run in production.평가와 관측 가능성평가(Evals)에이전트 엔지니어링+2 
슬라이드 9장20:58ENAI Engineer· 2026년 10월 25일Vinoo Ganesh on Making Financial AI Cite Every NumberVinoo Ganesh · KeplerKepler CEO Vinoo Ganesh explains why financial AI should retrieve and cite figures while deterministic software handles the math. His design makes traceability, retrieval quality, and tenant security part of the answer itself.금융 AI엔터프라이즈 AI검색 증강 생성(RAG)+2