Frontier labs chase Millennium Prize math while real production codebases stay broken
BaconShadow · reddit · 2026-10-01
The author argues Anthropic, OpenAI and other frontier labs hype every release as near-AGI because abstract math proofs and greenfield codegen make great PR, while real software engineering — tech debt, messy human context, long-horizon architectural drift — has no automated verifier.
Key points: if models were truly general, labs would deploy thousands of parallel agents to clear enterprise production backlogs, where the multi-trillion-dollar software labor market actually lives. Instead compute goes to isolated benchmarks that fuel fear-driven media cycles and investor pumps. Fixing real GitHub issues in tools like Claude Code would offer far higher product ROI. Until AI achieves recursive self-improvement and survives its own code three years later, every release is an incremental update wrapped in marketing noise.
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