wuyang
82 lines
2.1 KiB
Markdown
82 lines
2.1 KiB
Markdown
# Industry: OpenAI - In-house Data Agent
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---
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type: industry
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company: OpenAI
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team: data / engineering
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title: Inside OpenAI's in-house data agent
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url: https://openai.com/index/inside-our-in-house-data-agent/
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source_name: OpenAI
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source_type: engineering-blog
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source_quality: official
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published_at:
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collected_at: 2026-07-08
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status: analyzed
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topics:
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- agent
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- data-agent
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- enterprise-ai
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implementation_signals:
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- memory
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- rag
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- mcp
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- eval
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- permissions
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product_area:
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- data-analysis
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- internal-tools
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models:
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- GPT-5.2
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- Codex
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tools:
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- Evals API
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- Embeddings API
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- MCP
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benchmarks:
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-
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related_papers:
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- 2026-memory-agent-survey
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related_jobs:
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- 2026-07-08-baidu-aidu-agent-fullstack-engineer-beijing
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related_experiments:
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-
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related_projects:
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-
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evidence_level: high
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relevance: high
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---
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## One-line Takeaway
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高价值内部 Agent 不是只接一个数据库，而是把权限、表级知识、人工注释、代码增强、组织知识、记忆和运行时上下文做成系统。
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## What They Built or Claimed
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OpenAI 构建了内部数据 Agent，用自然语言帮助员工探索和分析公司数据平台。资料描述了多层上下文、Agent API、Slack/Web/CLI/MCP 入口、记忆系统和安全边界。
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## Technical Signals
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- architecture: Agent API + internal knowledge + warehouse/platform sources + model/tool loop。
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- tool use: 查询数据、语义检索、精确文本检索、MCP 连接。
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- memory: 持续学习的记忆系统，用于提升后续查询。
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- evaluation: 使用 Evals API 作为构建工具之一。
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- safety: 内部权限和工作流是设计的一部分。
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- deployment: Slack、Web、IDE、Codex CLI、内部 ChatGPT。
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- data: 表使用、人工注释、Codex enrichment、institutional knowledge、runtime context。
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## Evidence Quality
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官方工程博客，有系统结构、上下文层和落地入口，证据强。
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## Links
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- papers: memory survey
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- jobs: Baidu Agent fullstack
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- experiments: data-agent-context-stack
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- projects:
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- docs: evaluation, memory, tool use
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## Gaps for Us
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- 需要沉淀一个“企业数据 Agent 架构”专题。
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