Core Viewpoint - The article highlights the downfall of the AI startup Bu il d e r. a i, emphasizing the importance of verifying claims and relying on data-driven decision-making rather than intuition [1][7]. Group 1: Bu il d e r. a i Case Study - Bu il d e r. a i, founded by Sachin Dev Duggal, once valued at over $1.5 billion, was revealed to lack actual AI technology and relied on fabricated financial data [1]. - The company managed to deceive investors for eight years, with excuses for delays and poor code quality being accepted without scrutiny [1]. - The situation parallels the Theranos scandal, where Elizabeth Holmes misled high-profile investors with false promises, leading to her conviction [1]. Group 2: Investor Psychology - The article discusses why intelligent investors fall for obvious lies, attributing it to reliance on intuition rather than rational tools [2]. - A mathematical example illustrates how even highly educated individuals can be misled by their instincts, emphasizing the need for structured analysis [2]. Group 3: Cognitive Biases in Venture Capital - Three cognitive biases are identified in the venture capital space: halo effect, story dependence, and authority worship, which lead to poor decision-making [3]. - Investors often overlook due diligence due to the impressive backgrounds of founders or compelling narratives [3]. Group 4: "企查查思维" (Qichacha Thinking) - "企查查思维" is introduced as a methodology that emphasizes data-driven decision-making, risk identification, and market opportunity insights [4][5]. - The approach encourages the use of comprehensive data from platforms like Qichacha to inform business decisions rather than relying solely on intuition [5]. Group 5: Practical Applications of "企查查思维" - Examples from various regions illustrate how businesses utilize Qichacha for verifying company information, enhancing supplier risk monitoring, and improving hiring processes [6]. - The methodology aims to integrate external data into decision-making processes, enhancing competitive intelligence and data-driven decision-making [6]. Group 6: Lessons from Bu il d e r. a i - The collapse of Bu il d e r. a i serves as a cautionary tale about the vulnerabilities in human cognition and the importance of rigorous verification in the age of AI [7]. - The article concludes with a call for decision-makers to prioritize data over intuition, reinforcing the need for a systematic approach to business evaluation [8].