Blog AI (17)
OCR + Rule + LLM
영수증 사진을 올리면 OCR이 읽고, Rule이 좁히고, LLM이 뽑아낸다 — 근거 없는 값은 절대 반환하지 않는다
Built a local-first receipt understanding pipeline that separates concerns across three explicit stages: OCR extracts text, Rules narrow candidates, and LLM performs semantic extraction — each doing only its own job.
The key principle: no hallucinated evidence. The LLM returns a value only when it …
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Claude Cowork: Automation
Cowork으로 만드는 나만의 자동화 루틴
Building My Personal Automation Routine with Cowork
I've always struggled with the same two problems. My disk fills up silently until something breaks. And my mornings start scattered — no clear picture of what's happening in AI, what I need to study, or what's on …
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Building AI Agents
AI Agent 구현해보기
Building Agentic Flows: A Hands-On Project Plan
I've been putting together a plan to build and teach a series of hands-on Agentic Flow projects. As someone who's been working across software development, AI research, and QA automation, I've always wanted to bridge the gap between …
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[AI] Generative AI Models
Choosing the Right AI Model for Generative AI Applications
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Understanding LLM & RAG
LLM과 RAG 완벽 이해 [정확도 향상의 핵심 전략]
Understanding LLM & RAG [Reliable AI]
LLM과 RAG 완벽 이해 [정확도 향상의 핵심 전략]
Take-home message: RAG strategies are essential to enhance the accuracy and trustworthiness of LLMs.
1. What is an LLM?
A Large Language Model (LLM) is …
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