Saram 인사이트 (Saram Insights)
바이오텍, 인공지능, 규제 컴플라이언스의 융합에 관한 심층 전략 및 실전 아키텍처 분석.
2026년 7월 13일EN 원문
In May 2025, a federal judge ordered OpenAI to preserve every ChatGPT conversation indefinitely. ZDR customers were exempt. Here's what ZDR actually means, which providers offer it, and why it increases ROI instead of shrinking it.
글 읽기 →2026년 7월 12일EN 원문
When a single LLM call fails on a complex task, the answer is almost never a bigger prompt. It is decomposition — systematically breaking the problem into smaller, verifiable, independently solvable pieces. Here are the 5 patterns every AI architect must know, when to use each, and the anti-patterns that will sink you on the exam and in production.
글 읽기 →2026년 7월 12일EN 원문
In life sciences you cannot just show that an agent works — you have to prove it works the same way every time, trace why it answered, and have a qualified person review it. Here's how Langfuse Evaluation's four layers — Scores, Evaluators, Human Annotation, and Datasets — map directly to GxP compliance.
글 읽기 →2026년 7월 12일EN 원문
Life sciences companies spend millions on commercial MDM suites they don't need. Here's the open-source architecture that delivers the same golden records, passes FDA audit, and costs a fraction — built entirely on PostgreSQL, Kafka, and commodity hardware.
글 읽기 →2026년 7월 12일EN 원문
Multi-agent systems are the most overused and most misunderstood pattern in AI architecture. Most teams build them when a single agent with better prompting would outperform their five-agent Rube Goldberg machine. Here is how to design multi-agent systems that actually earn their 15x token cost — and how to know when you should not build one at all.
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