According to God of Prompt on Twitter, MIT researchers have introduced a novel AI safety methodology called InvThink, which trains models to proactively enumerate and analyze every possible harmful consequence before generating a response (source: God of Prompt, Twitter, Oct 23, 2025). Unlike traditional safety approaches that rely on post-response filtering or rule-based guardrails—often resulting in reduced model capability (known as the 'safety tax')—InvThink achieves a 15.7% reduction in harmful responses without any loss of reasoning ability. In fact, models show a 5% improvement in math and reasoning benchmarks, indicating that safety and intelligence can be enhanced simultaneously. The core mechanism involves teaching models to map out all potential failure modes, a process that not only strengthens constraint reasoning but also transfers to broader logic and problem-solving tasks. Notably, InvThink scales effectively with larger models, showing a 2.3x safety improvement between 7B and 32B parameters—contrasting with previous methods that degrade at scale. In high-stakes domains like medicine, finance, and law, InvThink achieved zero harmful responses, demonstrating complete safety alignment. For businesses, InvThink presents a major opportunity to deploy advanced AI systems in regulated industries without compromising intelligence or compliance, and signals a shift from reactive to proactive AI safety architectures (source: God of Prompt, Twitter, Oct 23, 2025).