evaluating-new-technology

Compare original and translation side by side

🇺🇸

Original

English

🇨🇳

Translation

Chinese

Evaluating New Technology

评估新兴技术

Help the user evaluate emerging technologies using frameworks from 22 product leaders who have made critical technology decisions at companies from Google to Shopify.

借助来自从谷歌到Shopify的22位产品负责人制定关键技术决策时所用的框架，帮助用户评估新兴技术。

How to Help

如何提供帮助

When the user asks for help evaluating technology:

Start with the problem - Clarify what problem they're solving before discussing tools
Assess maturity - Determine if the technology is stable enough for their use case
Consider build and buy - Help them find the right mix rather than forcing a binary choice
Plan for change - Design for modularity since the landscape will shift

当用户请求评估技术时：

从问题入手 - 在讨论工具之前，先明确他们要解决的问题
评估成熟度 - 判断该技术是否足够稳定以满足他们的使用场景
考虑自研与采购结合 - 帮助他们找到合适的组合，而非非此即彼的二元选择
为变化做规划 - 由于技术格局会不断变化，要采用模块化设计

Core Principles

核心原则

Tools solve problems, not the reverse

工具是为解决问题而生，而非反之

Austin Hay: "I have this adage I always say, which is tools are just meant to solve problems. And the problem set for marketing technologists and business technologists is you focus on the tools." Always define the problem and the people involved before selecting a system or tool.

Austin Hay：“我一直有这样一句格言：工具只是用来解决问题的。而营销技术人员和业务技术人员的问题在于，他们过于关注工具本身。”在选择系统或工具之前，一定要先明确问题和涉及的人员。

Build AND buy, not build vs buy

自研与采购结合，而非二选一

Austin Hay: "Build and buy as opposed to build versus buy. Build and buy means that both of you can win." Buy tools to handle 90% of standard functionality and build the 'cool' 10% that is unique to your business.

Austin Hay：“要选择自研加采购，而非二选一。自研加采购意味着双方都能共赢。”采购工具来处理90%的标准功能，自研那10%独特的、属于你业务核心的“亮点”功能。

Evaluate mental bandwidth, not just dollars

评估心智带宽，而非只看成本

Dhanji R. Prasanna: "The savings and costs that there might be in replacing a vendor tool by something you build in-house is probably not worth it in the mental bandwidth that you've lost." Focus technical bandwidth on core competencies, not recreating vendor tools.

Dhanji R. Prasanna：“用自研工具替代供应商工具可能带来的成本节约，远不及你因此失去的心智带宽有价值。”将技术带宽集中在核心竞争力上，而非重复开发供应商已有的工具。

Update your priors constantly

持续更新你的固有认知

Aparna Chennapragada: "The models couldn't do some things one year ago. My impression of it from trying it a few months ago - that prior needs to be updated. The baby just grew up to be a 15-year-old in a month." Re-test assumptions about what technology can do every few months.

Aparna Chennapragada：“一年前这些模型还做不到某些事。我几个月前试用后的印象——这种固有认知需要更新。就像一个婴儿在一个月内长成了15岁的少年。”每隔几个月就重新检验关于技术能力的假设。

Bet on abstraction layers

押注抽象层

Asha Sharma: "You really need to bet on a platform or some app server type layer that allows you to swap things in and out and not really be beholden to any one technology." Invest in modularity as the AI stack evolves.

Asha Sharma：“你真的需要押注一个平台或某种应用服务器层，它能让你灵活地替换组件，而不必受制于任何单一技术。”随着AI技术栈的发展，要投资于模块化设计。

AI guardrails don't work

AI防护措施并非万无一失

Sander Schulhoff: "AI guardrails do not work. If someone is determined enough to trick GPT-5, they're going to deal with that guardrail. When these guardrail providers say 'We catch everything,' that's a complete lie." Be skeptical of AI security vendor claims.

Sander Schulhoff：“AI防护措施不起作用。如果有人下定决心要绕过GPT-5的防护，他们肯定能做到。当这些防护措施供应商声称‘我们能拦截一切’时，完全是谎言。”对AI安全供应商的宣传要持怀疑态度。

Use the tools yourself

亲自试用工具

Dhanji R. Prasanna: "I would say really try and use these tools yourself. We learn a lot about how our own workflow can change." Solve a specific, personal problem with new tools to understand their true strengths.

Dhanji R. Prasanna：“我建议一定要亲自试用这些工具。我们能从中了解到自身工作流程可以如何改进。”用新工具解决一个具体的个人问题，以了解其真正的优势。

Context drives AI value

场景决定AI的价值

Jeanne Grosser: "Because this whole space is so nascent, often your own esoteric context, your content, your workflow is really key to unlocking the power of the agent." For AI agents, building internally often beats buying.

Jeanne Grosser：“由于整个领域还非常新兴，通常你自身独特的场景、内容和工作流程才是释放Agent能力的关键。”对于AI Agent来说，自研往往比采购更合适。

Questions to Help Users

可用于询问用户的问题

"What specific problem are you trying to solve with this technology?"
"Is this technology stable enough for production, or still experimental?"
"What's the mental bandwidth cost of building vs maintaining a vendor relationship?"
"When did you last test your assumptions about what this technology can do?"
"How will you swap this out if something better comes along?"
"Have you actually used this tool to solve a real problem yourself?"

“你想用这项技术解决什么具体问题？”
“这项技术是否足够稳定以用于生产环境，还是仍处于实验阶段？”
“自研相比维护供应商关系，会消耗多少心智带宽？”
“你上次检验关于这项技术能力的假设是在什么时候？”
“如果出现更优的技术，你将如何替换当前的技术？”
“你是否真的使用过这个工具来解决实际问题？”

Common Mistakes to Flag

需要指出的常见误区

Tool bias - Picking tools because you've used them before, not because they solve the problem
Binary build vs buy thinking - Missing the opportunity to buy 90% and build the strategic 10%
Outdated priors - Making decisions based on what technology couldn't do six months ago
Vendor lock-in - Betting on specific tools without an abstraction layer for future flexibility
Trusting security marketing - Believing AI guardrail vendors who claim to 'catch everything'

工具偏好 - 选择工具是因为你之前用过，而非因为它能解决问题
自研vs采购的二元思维 - 错失了采购90%标准功能、自研10%核心战略功能的机会
过时的固有认知 - 基于六个月前技术的局限性做决策
供应商锁定 - 押注特定工具，却没有为未来灵活性搭建抽象层
轻信安全营销 - 相信AI防护供应商声称“能拦截一切”的宣传

Deep Dive

深入研究

For all 27 insights from 22 guests, see

references/guest-insights.md

如需获取22位嘉宾分享的全部27条见解，请查看

references/guest-insights.md