Agentic vs. Vector Search: An Eval-Driven Approach to Coding Agent Performance

Official Schedule Context

Official Description

Evals let you replace gut feelings with quantifiable decisions. This talk breaks the basic concepts

of evals, including the four core components: datasets, tasks, scoring, and experiments. Then, to

solidify the concept, we’ll walk through a real eval comparing agentic search versus vector search

for coding agents. We'll also cover practical challenges like tracing Claude Code subprocess calls

and why a single eval run is never enough. You'll leave with a concrete framework for building evals

that actually inform your ship decisions.

Related YouTube Video

No related AI Engineer channel video found yet.

Transcript Status

No official session recording transcript was found by exact title match on the AI Engineer YouTube channel during this run.

People

Notes