Tag
The article argues that relying on proprietary frontier AI APIs is risky due to unpredictable cost increases, availability changes, and lack of auditability, advocating for open-weight models as a more trustworthy alternative.
A comparison of token consumption across four agent runtimes (Claude Code, OpenClaw, Hermes, and OpenClacky) on the same tasks reveals costs ranging from 0.8x to 4x relative to Claude Code, driven by differences in cache architecture and tool schema design.
The tweet points out that although some believe AI will replace programmers, data shows demand for software engineers has actually surged. This may be because the cost of using AI (like Claude) is too high, prompting companies to prefer hiring human programmers.
Microsoft and other tech firms are scaling back AI tool usage after finding that the cost of AI compute exceeds the cost of human labor, highlighting a major economic bottleneck in AI adoption.