recruiting · workflow
Intuit uses an AI assistant with agentic rules to generate and scale interview exercises, with mandatory human review before deployment
Traditional technical interviews at Intuit did not reflect how engineers actually work with AI tools, and manually creating diverse, high-quality interview exercises required hours of effort per exercise.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Natural language exercise request
A content creator requests a new exercise by describing it in natural language.
Tools used
AI assistant
Outcome
Intuit now generates complete interview exercises in minutes using an AI assistant constrained by agentic rules, maintaining dozens of exercises with consistent quality and a mandatory human review gate before any exercise reaches candidates.
Results
Time savedhours
Grounding & classification
Source type: technical build writeup
18 fields verified against source quotes.
agentic workflowcontent generationknowledge basefailure mode describedhuman review describednamed customerproduction runtime claimedsource backedworkflow describedsoftwareemployee productivitythroughput increasetechnical build writeuprecruitingai draft human approval