# The new set of problems for engineers to solve
**作者**: Katelyn Lesse
**日期**: 2026-10-26T02:19:00.000Z
**来源**: [https://x.com/katelyn_lesse/status/2114542280535318557](https://x.com/katelyn_lesse/status/2114542280535318557)
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A lot of software engineers are going through what can only be described as an identity crisis. The job has changed a lot. Some are depressed, others are having the time of their lives. There's a really specific thing I see happening that makes me really excited for what engineering looks like over the next, call it a year or two - AI just isn't going to be able to create the incredible outcomes it's capable of creating unless software engineers solve problems to make it possible. This is existential, which is honestly a lot of fun, so it's a pretty incredible time to be a software engineer.
# Multiagent systems are creating these problems
Agents started out as basic, human in the loop chats. Then models got better at running for longer on harder problems, and agentic systems started moving to the cloud. While that was happening, models have started to get better at working together, and people have built basic multiagent systems. Like an orchestrator that spawns some subagents for a given task, or giving agents jobs other than executing to improve outcomes, like grading or advising or dreaming.
Now, some folks are starting to build truly amazing multiagent systems to tackle the world's hardest and most important problems, like serious research, discovery, and hardware design. Picture thousands of agents, persistently working towards these outcomes. This comes with a new set of software engineering problems that we're already seeing crop up.
Infrastructure needs to evolve to handle burstier workloads. We need proper authentication and authorization to identify agents, let them work together, enable them to take the actions they should, and prevent them from taking the actions they shouldn't. Security and proper isolation are critical for untrusted code and content. And we've gotta have monitoring and the ability to stop a system in its tracks when it's veering into the wrong territory.
Models will keep getting better, and these types of multiagent systems will become really powerful. But software engineers have to solve all these problems if we're going to actually unlock that power and enable the world to trust it to create good outcomes like cured diseases rather than bad outcomes.
# The problems
## Infrastructure needs to evolve
The software industry has been building on Kubernetes, which was designed for stateless, replicated apps or stable numbered sets of stateful pods. Agents are totally different. They're essentially isolated, stateful, single-instance workloads. They can go idle for arbitrary amounts of time between bits of work, and they spend a lot of time waiting on tools, model inference, other agents, or human input. Some workloads need fast startup times, others need to avoid wasting compute, and others need crazy scale. Amazing engineers are pushing hard on this problem space - like AI infra companies building new filesystems and sandboxing offerings, and the Google team building Agent Substrate as a new runtime. There's a ton left to figure out.
## Identity and access
There are problems to solve in agent authentication - identifying an agent that took an action. This area has the benefit of the building blocks that have been built and hardened from the microservices world, like workload identity with short-lived certs rather than static keys, and folks are beginning to apply these concepts to agents.
Agent authorization as a problem space is much more wide open - what do you allow an agent to do? Many agents work on behalf of a human, and use that human's identity and credentials to access various systems and take actions. There's already a problem in there, which is identifying that it was the agent and not the actual human who took an action. But there are deeper problems in this on-behalf-of (OBO) setup, like consent. If multiagent systems are working for weeks, how does the human meaningfully approve what their agent can do? Agentic platform features like auto approval for tool calls helps, but there's deeper permissioning needed to get this right at high scale. And then we have agents working with their own identity, which is even less solved, and how we apply that to agents working together - how does an agent trust another agent that asked it for something?
## Security and isolation
Over the past few months and especially in the past couple weeks, we've seen vulnerabilities surfacing faster than the industry can patch them, much of it in critical core software that many systems rely on. Now think about thousands of persistent agents running on top of that core software, writing untrusted code and reading untrusted content. Those unpatched vulns get a lot more dangerous in that world, and one of the most important things for software engineers to do is get creative about how to harden that software - kernels, browsers, runtimes, and common libraries.
Multiagent systems add another twist. A compromised agent could pass injected instructions to other agents it's working with, and those instructions could end up in memory for future agents to accidentally trust. Blast radius gets real - how much of the multiagent system is at risk when that first agent got compromised? Isolation becomes important in that world - agents should use strongly isolated sandboxed execution environments to take actions. I wrote a bit about that [here](https://www.katelynlesse.com/blog/secure-agents-architecture-and-sandboxing).
## Monitoring and halting
Lastly, we need the tools to make sure these multiagent systems are working in a positive direction, and that we catch them and cut them off if they're not. We need OTel tracing across agents, and to ensure that an agent can never modify its own trace or another agent's trace. We need kill switches that monitoring can trigger, that truly stop the whole system at once and cut off its creds. Really the hard part is how to know when the system is going in the wrong direction. Well-intentioned persistence to solve a problem can look a lot like maliciousness - repeated attempts to reach a domain that isn't on its allowlist, for example.
# Software engineers should be excited
This is for the engineers feeling an identity crisis because they think their knowledge and skills won't be important - you and your skills can be the difference in whether or not these problems get tackled and multiagent systems can solve the world's hardest problems. You can and should go deep in these domains, learn new things, and form opinions. So much of this problem space is wide open for new solutions. It's an incredibly exciting time to put your skills to work.
## 相关链接
- [Katelyn Lesse](https://x.com/katelyn_lesse)
- [@katelyn_lesse](https://x.com/katelyn_lesse)
- [366K](https://x.com/katelyn_lesse/status/2114542280535318557/analytics)
- [here](https://www.katelynlesse.com/blog/secure-agents-architecture-and-sandboxing)
- [Upgrade to Plus](https://x.com/i/premium_sign_up)
- [10:19 AM · Oct 26, 2026](https://x.com/katelyn_lesse/status/2114542280535318557)
- [366.6K Views](https://x.com/katelyn_lesse/status/2114542280535318557/analytics)
- [View quotes](https://x.com/katelyn_lesse/status/2114542280535318557/quotes)
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*导出时间: 2026/10/27 10:55:16*
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## 中文翻译
# 工程师亟待解决的新问题
**作者**： Katelyn Lesse
**日期**： 2026-10-26T02:19:00.000Z
**来源**： [https://x.com/katelyn_lesse/status/2114542280535318557](https://x.com/katelyn_lesse/status/2114542280535318557)
**阅读**： 366K
**点赞**： 3.1K
**转发**： 401
**回复**： 141
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很多软件工程师正在经历一场可以说是身份认同危机的时期。这份工作已经发生了巨大变化。有些人很沮丧，有些人却乐在其中。我观察到一件非常具体的事情，让我对未来一两年工程领域的样子感到非常兴奋——除非软件工程师解决那些让这一切成为可能的问题，否则 AI 根本无法创造出它有能力创造的惊人成果。这是一个关乎存亡的问题，说实话非常有趣，所以现在是成为软件工程师的绝佳时代。
# 多智能体系统正在制造这些问题
智能体最初只是基本的、需要人类在环的对话。后来模型在更长时间运行更难问题上的能力提升了，智能体系统开始迁移到云端。与此同时，模型之间的协作能力也在提升，人们构建了基础的多智能体系统。比如一个编排器为给定任务派生若干子智能体，或者给智能体分配执行之外的工作来改善结果，比如评分、建议或“畅想”。
现在，有些人开始构建真正令人惊叹的多智能体系统，来攻克世界上最难、最重要的问题，比如严肃的研究、科学发现和硬件设计。想象一下数千个智能体，持续不断地为这些目标工作。这带来了一系列新的软件工程问题，这些问题已经开始浮现。
基础设施需要演进以应对更具突发性的工作负载。我们需要完善的身份认证和授权机制来识别智能体，让它们协同工作，使它们能够执行应该执行的操作，并阻止它们执行不该执行的操作。对于不受信任的代码和内容，安全与适当的隔离至关重要。我们还需要监控能力，以及在系统走向错误方向时能够立即叫停它的能力。
模型会不断进步，这类多智能体系统会变得非常强大。但如果软件工程师不解决所有这些问题，我们就无法真正释放这种力量，也无法让世界相信它能创造治愈疾病这样的好结果而不是坏结果。
# 这些问题
## 基础设施需要演进
软件行业一直构建在 Kubernetes 之上，而 Kubernetes 是为无状态的、可复制的应用，或稳定编号的有状态 Pod 集合设计的。智能体则完全不同。它们本质上是被隔离的、有状态的、单实例的工作负载。它们可以在两段工作之间闲置任意长的时间，并且大量时间花在等待工具、模型推理、其他智能体或人类输入上。有些工作负载需要快速启动，有些需要避免浪费算力，还有些需要夸张的规模。出色的工程师们正在这个领域大力攻坚——比如 AI 基础设施公司正在构建新的文件系统和沙箱产品，Google 团队正在构建 Agent Substrate 作为新的运行时。还有很多问题有待解决。
## 身份与访问
在智能体认证方面存在需要解决的问题——识别执行了某个操作的智能体。这个领域受益于微服务世界已经构建并磨砺成熟的构建模块，比如使用短期证书而非静态密钥的工作负载身份，人们已经开始把这些概念应用到智能体上。
智能体授权作为一个问题领域则要开放得多——你允许一个智能体做什么？很多智能体代表某个人工作，并使用那个人的身份和凭证来访问各种系统并执行操作。这里面已经有一个问题，就是识别出执行操作的是智能体而非真正的人类。但在这个代行（OBO）模式中还存在更深层次的问题，比如同意授权。如果多智能体系统要工作数周，人类如何有意义地批准其智能体可以做什么？智能体平台的功能如工具调用自动批准有所帮助，但要在大规模下做对，还需要更深层次的权限控制。此外还有智能体使用自己身份工作的情况，这个问题就更没有被解决了，还有如何把这一切应用到智能体协作上——一个智能体如何信任另一个向它发起请求的智能体？
## 安全与隔离
过去几个月，尤其是最近几周，我们看到漏洞浮现的速度超过了行业打补丁的速度，其中很多出现在许多系统所依赖的关键核心软件中。现在想象一下数千个持久运行的智能体跑在这些核心软件之上，编写不受信任的代码并阅读不受信任的内容。在这个世界里，那些未修补的漏洞会危险得多，软件工程师最重要的工作之一，就是在如何加固这些软件上发挥创造力——内核、浏览器、运行时和常用类库。
多智能体系统又增加了新的变数。一个被攻陷的智能体可以向它协作的其他智能体传递注入的指令，而这些指令可能进入记忆，被未来的智能体误信。爆炸半径变得非常现实——当第一个智能体被攻陷时，多智能体系统有多大部分处于风险之中？在这种世界里，隔离变得至关重要——智能体应该使用强隔离的沙箱执行环境来执行操作。我在[这里](https://www.katelynlesse.com/blog/secure-agents-architecture-and-sandboxing)写过一些相关内容。
## 监控与叫停
最后，我们需要工具来确保这些多智能体系统在朝积极的方向工作，并且一旦偏离就能发现并切断它们。我们需要跨智能体的 OTel 追踪，并确保智能体永远无法修改自己的追踪记录或其他智能体的追踪记录。我们需要监控可以触发的终止开关，能真正立刻停止整个系统并切断其凭证。真正的难点在于如何判断系统是否在朝错误的方向前进。出于善意的坚持不懈地解决问题，看起来可能与恶意行为非常相似——比如反复尝试访问一个不在其允许清单上的域名。
# 软件工程师应该感到兴奋
这是写给那些正经历身份认同危机、认为自己的知识和技能不再重要的工程师们的——你和你的技能，可能正是这些问题能否被解决、多智能体系统能否攻克世界最难问题的关键所在。你可以也应该深入这些领域，学习新东西，形成自己的观点。这个问题领域有太多空间等待着新的解决方案。现在正是发挥你技能的无比激动人心的时代。
## 相关链接
- [Katelyn Lesse](https://x.com/katelyn_lesse)
- [@katelyn_lesse](https://x.com/katelyn_lesse)
- [366K](https://x.com/katelyn_lesse/status/2114542280535318557/analytics)
- [here](https://www.katelynlesse.com/blog/secure-agents-architecture-and-sandboxing)
- [Upgrade to Plus](https://x.com/i/premium_sign_up)
- [10:19 AM · Oct 26, 2026](https://x.com/katelyn_lesse/status/2114542280535318557)
- [366.6K Views](https://x.com/katelyn_lesse/status/2114542280535318557/analytics)
- [View quotes](https://x.com/katelyn_lesse/status/2114542280535318557/quotes)
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*导出时间： 2026/10/27 10:55:16* 
