OpenClaw 技术闭门：测试将比代码更值钱，Agent Computer 会是新的硬件形态

Core Insights - The OpenClaw project is evolving from a niche tool to a practical productivity tool in various businesses, with major companies in China releasing similar products or features [3] - The influx of pull requests (PRs) in OpenClaw has led to a shift in perspective, viewing code as a liability rather than an asset, as the sheer volume makes it difficult for maintainers to review contributions effectively [6][8] - The concept of "Vibe Coding" is emerging, where coding becomes a fast-consumption activity, contrasting with traditional, rigorous software development practices [12][13] Group 1 - OpenClaw receives an average of 30 to 60 PRs per hour, with peak times exceeding 100, leading to a backlog of over 2000 pending PRs [6] - The community has implemented measures to manage attention, such as limiting message submissions to one every six hours to prioritize important contributions [6][7] - The traditional open-source trust model is breaking down, necessitating a return to interpersonal trust and the exploration of automated review and testing mechanisms [9] Group 2 - The rise of AI-generated code has made testing more valuable than the code itself, as automated testing can often produce unreliable results if not properly managed [14][15] - Effective testing practices are being developed, including strict rules for mocking and validating internal services, to ensure reliability in the face of rapid development [16][17] - The importance of creating a personal benchmark for AI models is emphasized, as fluctuations in model performance can lead to inconsistencies in output [18][35] Group 3 - The transition from feature coding to platform engineering is becoming crucial, as engineers must now focus on the broader ecosystem of code management and resilience [26][28] - The concept of "Agent Computer" is emerging, where personal assistants are integrated more closely with local systems, enhancing user experience and productivity [30] - OpenClaw is seen as a long-term partner rather than a temporary tool, with mechanisms in place to maintain ongoing tasks and context [31][32] Group 4 - The challenges of using OpenClaw for SaaS applications include cost, security, and consistency issues, making it difficult to deliver reliable services [33] - The notion of "Token Tax" is introduced, suggesting that those who engage more with AI tools will better understand their operational logic and capabilities [35][38] - The evolution of AI models is leading to a new understanding of their usability, with significant advancements noted since the release of Claude 4.5 Opus [36][37]