When Solvers Guess Smarter: Teaching SMT to Think in Functions
Opening — Why this matters now Quantified SMT solving has always lived in an uncomfortable space between elegance and brute force. As models grew richer—mixing non-linear arithmetic, real-valued domains, and uninterpreted functions—the solvers stayed stubbornly syntactic. They match patterns. They enumerate. They hope. Meanwhile, large language models have quietly absorbed a century’s worth of mathematical intuition. AquaForte asks an obvious but previously taboo question: what if we let SMT solvers borrow that intuition—without surrendering formal guarantees? ...