作者聊了个真实痛点：大家都在用 agentic coding 写更多代码，结果数据、权限、部署的复杂度也跟着涨，这篇给你管理思路。
随着公司用 agentic coding 提升开发效率，代码库规模持续增长，随之而来的是数据管理、访问规则、部署和监控的复杂度问题。这篇推文串分享了管理这类复杂度的方法，聚焦于 agentic coding 带来的工程实践挑战。
Building more software means managing more data, access rules, deployments, and monitoring.
Every company I talk to is using agentic coding to do more. Codebases are growing, and so are problems.
Here is the best way to manage complexity: ↓
A 65B dense model beating 500B-plus open-weight rivals on agentic coding would reshape assumptions about how much capacity agents actually need. Teams choosing self-hosted coding models should benchmark Ripple against Nemotron 3 Ultra-550B and the other named releases before committing to larger deployments. No benchmark names or independent evaluations are given yet, so treat the state-of-the-art claim as the lab's own.
YC掌门人Garry Tan说单人创业能靠AI放大400倍，想听他怎么聊vibe coding和agentic coding的可以看看。
想了解 agentic coding 对推理引擎的新要求？Together AI 的这个实操 workshop 直接带你上手，时间是6月29日上午。
