Generated from your actual stack
We don't pull from a question bank. We read your docs, codebase, and role context - and generate a problem that could have come from your last sprint planning session.
Real engineering problems.Real collaboration.No LeetCode.
We index your codebase, docs, and stack. AI generates a problem that looks like it came from your sprint board. Your interviewer and candidate solve it together - and both walk away with something real.
See it in action
The protocol
How a depthhire session actually works.
01
Index your context
Connect your docs, codebase, or job description. depthhire reads your actual stack - not a dropdown of generic templates.
02
Generate a real problem
In under 8 seconds, AI produces a problem that looks like a task from your sprint board. A logistics company gets a different problem than a fintech startup. Every single time.
03
Solve it together
The interviewer and candidate are both in the room - shared browser IDE, real-time presence. The AI agent observes silently. No interruptions.
04
Requirements evolve mid-session
When the candidate submits, the AI layers in a new constraint - the way a PM drops one mid-sprint. This is the moment that actually reveals how an engineer thinks.
05
Both sides get a report
The company gets an observational summary of what happened - approach, tradeoffs, response to new constraints. The candidate gets their own version: what was strong, what to explore next.
Human in the loop
The interviewer is present the entire time - not watching a recording after the fact. Real-time collaboration means you're assessing communication, judgment, and instinct simultaneously.
Both sides walk away with signal
Candidates receive a real observational report about how they think - not a score. Companies get structured session data that compounds in value over time.
"The best technical interviews feel like real work. Ours do."
Not a puzzle. Not a timed test. A real engineering problem from your actual context, solved together.