Research-Driven Agents: What Happens When Your Agent Reads Before It Codes
Summary
The article argues that coding agents benefit from a literature- and fork-informed research phase rather than relying solely on code context. It details a case study optimizing llama.cpp CPU inference across x86 and ARM, revealing five kernel fusions that yielded measurable throughput gains. It emphasizes memory bandwidth considerations, the value of studying competing projects, and provides a replicable workflow and concrete optimization techniques for future projects.