一位Reddit用户正在寻求建议，如何在组织内有效地使用“composer”模型进行代码和问题分析。他们的公司已限制访问所有其他AI模型，只留下composer可用，而用户觉得它不能满足他们的需求。他们正在寻找关于技能、子代理或工作流程的技巧，以最大限度地提高composer在理解一个庞大、已有数十年历史的项目方面的效用。 AI
排序理由 用户关于特定工具局限性的查询，而非新发布或行业事件。
AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →
用户寻求使用有限的“composer”AI模型进行代码分析的技巧
本文如何被排名
- Signal score
- 0 / 100
- Composite score across the factors below. Higher = stronger signal that this story matters right now.
- Newsworthiness bucket
- Meme
- 用户关于特定工具局限性的查询，而非新发布或行业事件。
- Source corroboration
- Single-source cluster
- Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
- Topics
- product, other
- Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
- AI-industry relevance
- Standard
- On-topic for AI-industry coverage; kept in the public index.
- Story freshness
- Breaking (< 6h)
- Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.
完整方法见我们的编辑标准。
报道来源 [1]
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我的组织阻止了除composer之外的所有模型。有什么建议吗？
<!-- SC_OFF --><div class="md"><p>Our product is massive and developed over decades (including multiple generations). It seems no one person understands the project in every detail. The thinking models were very helpful for designing new features and analysing current code (acros…