AI/AX 공식 소스 일일 브리프 — 2026-08-12
요약 3줄
- 대상일은 2026-08-12 KST입니다.
- 검토 건수는 13건, 보고 건수는 5건입니다.
- 자동 수집 범위는 공식 블로그/RSS만 대상으로 합니다. GitHub 릴리스, X, LinkedIn, 뉴스레터는 제외했습니다.
보고 항목
- From assistance to execution: How enterprises put AI to work
- 출처: OpenAI Blog (official)
- 시각: 2026-08-12 15:00 KST
- 링크: https://openai.com/index/how-enterprises-put-ai-to-work
- 메모: OpenAI research reveals how enterprises are adopting agentic AI, using ChatGPT and Codex, and how frontier firms are pulling ahead in AI adoption.
- Copilot memory and Ollama in GitHub Copilot for JetBrains
- 출처: GitHub Changelog (official)
- 시각: 2026-08-12 05:15 KST
- 링크: https://github.blog/changelog/2026-08-11-copilot-memory-and-ollama-in-github-copilot-for-jetbrains
- 메모: This update brings persistent memory, local model access, and more enterprise controls to GitHub Copilot for JetBrains. It also improves everyday chat workflows and resolves reliability issues across MCP servers,… The post Copilot memory an
- Upcoming deprecation of MAI-Code-1-Flash
- 출처: GitHub Changelog (official)
- 시각: 2026-08-12 03:50 KST
- 링크: https://github.blog/changelog/2026-08-11-upcoming-deprecation-of-mai-code-1-flash
- 메모: With the launch of MAI-Code-1.1-Flash, we will deprecate MAI-Code-1-Flash across all GitHub Copilot experiences on September 10, 2026: Model Deprecation date Suggested alternative MAI-Code-1-Flash 9-10-2026 MAI-Code-1.1-Flash Please update
- MAI-Code-1.1-Flash available in GitHub Copilot
- 출처: GitHub Changelog (official)
- 시각: 2026-08-12 03:13 KST
- 링크: https://github.blog/changelog/2026-08-11-mai-code-1-1-flash-available-in-github-copilot
- 메모: MAI-Code-1.1-Flash, Microsoft’s latest small-tier coding model, is now rolling out in GitHub Copilot. Building on MAI-Code-1-Flash, it adds native vision support for image understanding and delivers improvements across coding quality,… The
- What is an AI agent?
- 출처: LangChain Blog (official)
- 시각: 2026-08-12 14:47 KST
- 링크: https://www.langchain.com/blog/what-is-an-agent
- 메모: Learn what AI agents are, how they work in an LLM loop, and where workflows fit so you can build reliable, production-ready autonomous systems.