A new era for software testing
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Antirez argues that LLMs open a genuinely new and uncompromised approach to software QA. Rather than replacing hand-written code with AI-generated code (which involves quality tradeoffs), AI agents can act as autonomous QA engineers executing manual testing checklists defined in markdown files. The agent inspects recent commits, identifies what could be affected, then runs integration checks like distributed inference validation, speed regression detection, and production environment simulation — tasks previously skipped due to time or logistical constraints. This methodology was applied to both DwarfStar (an LLM inference engine) and Redis Arrays. The key insight is that AI-driven QA can raise the quality bar for releases, potentially compensating for the lower structural quality of AI-generated code produced at speed.
