How to make AI write better hardware code through iteration and learning

Verilog-Evolve treats hardware code generation as an iterative refinement problem, not a one-shot task. The system generates candidate designs, tests them against functional simulation, synthesis checks, and timing constraints, then promotes the best version and logs reusable "skills" for future tasks. On VerilogEval and GEMM benchmarks, this feedback loop improves functional correctness and downstream hardware quality compared to isolated sampling—showing that AI can learn and apply design patterns across multiple RTL generation problems.