AI Agents Outperform Raw LLMs in Software Problem-Solving, Achieving 30% Success Rate vs 7% Without Scaffolding
SambaNova researchers discover that AI agents with structured workflows dramatically outperform raw language models in software problem-solving, with DeepSeek-R1 achieving 30.3% success versus just 7% for direct approaches, proving that intelligent scaffolding matters more than raw model capabilities.