π» Challenges of Local AI Workflows in Video Editing
A developer shared their experience creating a multi-agent system for automated video editing. During the process, three key problems were identified: the "Lost-in-the-Middle" effect, where LLMs ignore the central part of the context; the problem of "sycophancy," where reviewer agents simply agree with generator agents; and Whisper's inaccuracy in determining logical sentence boundaries.
π The case demonstrates the practical limitations of current LLMs in long contexts and the risks of using identical models in multi-agent systems, which leads to discussion collapse. This highlights the importance of agent heterogeneity and specialized tools (Vosk instead of Whisper) for tasks requiring high timestamp precision.
π€ If you are building AI agents, do not rely on the same type of model for both generation and verificationβthey will simply echo each other. Additionally, for editing or audio tasks, Vosk may prove more reliable than Whisper due to better handling of phrase boundaries.
Source 1: http://stefano.petrilli.xyz/building-ai-workflows/