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The hosts argue that Google’s benchmark strength has not translated into equally strong coding workflows, citing Gemini Argon’s perfect Skatebench score alongside slow product execution. They describe OpenAI Codex as incoherent and say better models can reduce the effort and fatigue of directing agents.
The hosts criticize OpenAI’s Codex experience and oversized system prompts, arguing that accumulated prompt patches can create contradictory instructions and worsen model behavior. They praise Anthropic for cutting two-thirds of its system prompt and call Codex’s persistent cache a meaningful improvement, while criticizing the 28-day release campaign for burying useful changes in frequent announcements.
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