Instacart rethinks SQL interview to test AI-forward data science workflows with LLMs
Traditional SQL interviews requiring candidates to write code manually became ineffective once LLMs could solve the same questions with a simple prompt, making the format a poor test of actual on-the-job skills and unfair to candidates who do not write SQL daily.
Instacart redesigned its SQL interview to test AI-forward skills — prompt engineering for SQL, debugging and explaining LLM-generated SQL, and identifying query optimizations — better reflecting how data scientists now work.
Frequently asked questions
What did this team achieve with this AI workflow?
Instacart redesigned its SQL interview to test AI-forward skills — prompt engineering for SQL, debugging and explaining LLM-generated SQL, and identifying query optimizations — better reflecting how data scientists no…
What tools did this team use?
Ava, OpenAI, GPT-4o, Snowflake Arctic, Llama 3–70B.
What results were reported?
time and effort for SQL coding: saving significant amounts of time and effort (source-reported, not independently verified).
How is this recruiting AI workflow structured?
Schemas and questions as prompt → LLM generates SQL → SQL retrieves data insights → Candidate reviews LLM SQL.