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AI工程师应学习构建代理框架

Should you build an agent harness? I see lots of opinions about it. My thoughts: As an AI enginee...

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作为AI工程师,学习构建代理框架是保持领先并解锁独特价值的好方法。理解构建框架的知识可以用于调整任何框架,甚至应用领域专业知识构建特定领域的框架以解决可靠性问题。许多公司和初创公司已经开始这样做。虽然通用前沿模型在可验证任务上变得更好,但尚未解决在特定和动态环境中应用时的可靠性问题。依赖模型提供商构建框架可能导致供应商锁定。

作为AI工程师,学习构建代理框架是保持领先并解锁独特价值的好方法。理解构建框架的知识可以用于调整任何框架,甚至应用领域专业知识构建特定领域的框架以解决可靠性问题。许多公司和初创公司已经开始这样做。虽然通用前沿模型在可验证任务上变得更好,但尚未解决在特定和动态环境中应用时的可靠性问题。依赖模型提供商构建框架可能导致供应商锁定。

原文 · elvis

Should you build an agent harness? I see lots of opinions about it. My thoughts: As an AI enginee...

Should you build an agent harness? I see lots of opinions about it. My thoughts: As an AI engineer, learning how to build a harness is one of the best ways to stay ahead and unlock unique value from agents. If you understand how to build one, you can, at a minimum, transfer that knowledge to tune whatever harness or set of harnesses (closed or open) you use. In the best case, you apply your domain expertise to build domain-specific harnesses that unlock unique real-world value and solve reliability issues other companies just aren't willing to invest time in. If you haven't noticed, many companies and startups have already started doing this. Harnesses are enablers in that way. I don't see any drawbacks in learning to build one. The main pushback against building a custom harness is that models will get better at generating them on the fly, so why build one? Or that companies will provide harness-as-a-service, etc. Now, ask yourself: will you have the level of customization that a proper harness requires? See, you are not building a wrapper here; you are building an important part of your intelligence stack. Something you want to control completely. Like automated prompt engineering, evals, and many other areas requiring extensive domain knowledge, harness engineering isn't something models are great at (see dynamic workflows from ant as an example). We assume too much that tools will remain static, data won't change, or knowledge will not evolve. A custom harness lets you own these issues and solve them at your desired pace. You simply cannot afford to sit back and wait for model providers to solve this problem for you. The harness is too important to offload. While general frontier models get better at verifiable (math, code, and the like) tasks, I haven't seen evidence that they solve reliability issues when you apply them to domain-specific and more dynamic environments. This is why you want to understand how the harness works and potentially build your own. I see a lot of companies already doing this in bio, health, legal, and finance. My other concern about just relying on a model provider to solve the harness for you is vendor lock-in. Right now, we mostly use single models for most tasks, but it's not hard to see a world where we leverage a set of frontier models (open and closed) to address issues like cost and diversity of intelligence. Are you going to rely on some company to build that harness solution for you, or, even worse, trust a single model to do that for you? I can go on and on. Building your own harness is about working towards building your own intelligence stack. I don't think that's optional where things are headed if you really want to have a differentiated business or offering. So where do you get started? I suggest feeding this list of seminal harness engineering papers to your agent: academy.dair.ai/papers/collect… You can start with something like: "Summarize the main components of an agent harness by researching this list of papers and tools: academy.dair.ai/papers/collect… . Then put together a set of visual notes on where to get started to build my own minimal harness using <language_of_your_choice>." Your thoughts? I want to keep this as an open discussion. Please share any concerns or thoughts. I'll share more thoughts as the conversation evolves. x.com/omarsar0/statu… elvis @omarsar0 Learn to build a harness, folks. It's not surprising to me that so many YC builders want to build domain-specific harnesses. If you work long enough on a domain-specific problem, you quickly realize the opportunity. But you also realize how important that harness will be to stay competitive in the agentic era. From a product perspective, harnesses open up interesting new surface areas and experiences for the services/products you provide. From a technical perspective, harnesses are how you build and maintain a framework and set of best practices for how your users/customers interact with what you offer. Understanding how to build and design a harness means you can build much stronger intelligence stacks, given that you can customize it and understand the domain well. That's extremely valuable. It may not seem apparent yet, but a harness wave is coming. If you are getting started, give this list of harness papers to your agents and start upskilling: academy.dair.ai/papers/collect… If you are already a builder, try building one for your specific domain. It's a lot of fun, and you learn a lot of interesting things to enhance your current agentic tools. 🔗 View Quoted Tweet 💬 8 🔄 2 ❤️ 22 👀 3134 📊 12 ⚡