AI evaluation and reasoning verification through code correctness and structured technical assessment (Solana/Rust/TypeScript).
Ebele evaluated and verified the correctness of multi-step technical reasoning within Rust and TypeScript systems, emphasizing catching silent logic errors. This work functions as AI evaluation-style assessment by scoring the soundness and quality of reasoning and outputs in a code-and-math heavy domain. The evaluation focus centered on instruction-level correctness, concurrency/state assumptions, and production safety under constraints. • Verified discriminator and instruction discriminator logic against live program IDL before committing changes. • Assessed correctness of transaction construction logic, account state transitions, and runtime behavior. • Rated reasoning quality by comparing step-by-step technical intent to actual implementation outcomes. • Conducted function-calling and structured evaluation readiness based on observed logical failures and edge cases.