I Made 11 AI Agents Do My Job. Here's What Happened (hackenewhome.blogspot.com)

In an eye-opening experiment reported by Jamie Dalton, eleven AI agents were tasked with performing classic venture capital workflows: deal sourcing for promising AI startups and competitor mapping. The AIMultiple AI VC Benchmark revealed that while AI can effectively assist with mechanical verification tasks like identifying potential investment opportunities, it struggles significantly with the high-judgment nature of competitor mapping, leading to a drop in accuracy. The top agent in deal sourcing achieved only a 58.5% success rate, underscoring that even the best AI models are not ready to fully replace human analysts. This benchmark is significant for the AI and machine learning community as it challenges the common narrative that AI is universally capable of outperforming humans across tasks. Demonstrating that the efficacy of AI varies significantly depending on the task, the results highlight the importance of selecting the right AI tools for specific workflows. The findings suggest that AI can augment human efforts by handling the more repetitive aspects of research, allowing analysts to focus on nuanced judgments—essentially transforming the analyst role rather than rendering it obsolete. Ultimately, this study serves as a reminder to rigorously test AI capabilities against specific tasks rather than relying on generalized performance claims.