Builder.ai 破产背后：700 名工程师伪造 AI 是假，重复造轮子及财务造假是真

Core Viewpoint - The narrative that Builder.ai employed 700 engineers to impersonate AI is misleading and has been debunked by former employees, highlighting the company's actual focus on developing AI tools and custom software services [4][5][29]. Group 1: Company Background and Operations - Builder.ai has a team of approximately 15 engineers dedicated to developing a code generation platform called Natasha, which aims to streamline the software development process [22]. - The company employed around 300 engineers to build internal tools that could have been purchased instead, leading to inefficiencies and a lack of focus on core products [25]. - Builder.ai also utilized an external network of 500-1000 engineers through outsourcing firms, which contributed to the confusion regarding the number of engineers involved [25]. Group 2: Financial Issues and Bankruptcy - Builder.ai faced financial fraud allegations, leading to its bankruptcy. Reports indicated that the company's revenue forecasts for 2024 were drastically reduced from $220 million to approximately $55 million, and 2023 sales were revised from $180 million to about $45 million [26]. - The withdrawal of funding by lenders due to misleading financial statements created significant cash flow issues for the company, ultimately sealing its fate [26]. Group 3: Misleading Claims and Public Perception - The claim that Builder.ai used human engineers to simulate AI was traced back to a misleading social media post, which gained traction and was widely reported without verification [33]. - The rapid spread of this false narrative serves as a reminder of the importance of verifying sources and being skeptical of sensational claims on social media [33]. Group 4: Technology Stack and Product Development - Natasha's technology stack includes Python, Ruby, React, GPT, and Claude, with a vision to serve as a comprehensive AI tool for the entire software development lifecycle [22][23]. - The platform aims to provide features such as code generation, testing, and project management, integrating various AI capabilities to enhance development efficiency [24].