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AI Agent: E2E Test
URL 하나만 주면 크롤링부터 테스트 시나리오·코드 생성·실행·리포트까지 이어지는 E2E 테스트 파이프라인
An end-to-end test pipeline that takes a single URL and automatically crawls the site, drafts natural-language test scenarios, generates runnable Jest+Playwright test code, and produces an HTML report — no site-specific hardcoding.
Key design decisions: - A general-purpose BFS crawler instead of a hardcoded page …
QA AgentRead more →
LangGraph + HITL
주제와 조건을 입력하면 여러 에이전트가 병렬로 조사하고, 쓰고, 검토한다 — 품질이 미달이면 interrupt()로 멈추고 사람의 판단을 기다린다.
Built a multi-agent pipeline that generates a lecture plan from a 6-field input (topic, audience, duration, delivery method, tools, constraints) using LangGraph + FastAPI + Gemini API + Tavily.
The pipeline runs in 3 rounds: sequential planning → parallel web research → sequential writing → …
AgentRead more →
Multi-Agent(HITL) with n8n
주제와 조건을 입력하면 AI가 조사하고, 쓰고, 세 관점으로 검토한다 — 품질이 미달이면 Slack으로 사람에게 판단을 넘긴다.
Built a multi-agent pipeline that automatically generates a lecture plan from a 6-field webhook input (topic, audience, duration, delivery method, tools, constraints). n8n orchestrates the full workflow across 20 nodes; a Flask server handles all Gemini and Tavily calls.
The pipeline runs in 3 rounds: …
AgentRead more →
Single vs Multi-Agent
에이전트를 여러 개로 쪼갠다고 항상 더 똑똑해지는 건 아니다
Before scaling an agentic workflow into a multi-agent pipeline, it's worth asking whether the added complexity actually pays off in token cost.
Single-agent overhead accumulates vertically — context grows turn by turn, but prompt caching keeps reuse efficient. Multi-agent overhead spreads horizontally — each sub-agent …
AgentRead more →
Multi-Agent with Claude Code
주제와 조건을 입력하면 9개 서브에이전트가 조사하고, 쓰고, 검토하고, 고친다 — 코드 없이
Built a multi-agent pipeline that automatically generates a lecture plan from a natural language prompt. No code — orchestrated entirely through CLAUDE.md (entry point only, 3 lines) and agent definition files (.claude/agents/*.md).
The pipeline runs in 4 rounds: sequential planning → parallel web research (up …
AIRead more →