Stop testing algorithm memorization. Start evaluating what actually matters: AI collaboration, debugging skills, and real-world problem solving.
Trusted by engineering teams at
The profession is being dramatically refactored. DSA puzzles don't predict success in an era of AI-assisted development.
"I've never felt this much behind as a programmer. There's a new programmable layer of abstraction to master involving agents, subagents, prompts, contexts, memory, modes, permissions, tools, plugins, skills, hooks, MCP, LSP... and a need to build an all-encompassing mental model for fundamentally stochastic, fallible entities suddenly intermingled with good old fashioned engineering."
— Andrej Karpathy, Former Tesla AI Director
of AI-first companies have moved away from traditional DSA interviews
productivity gap between engineers who master AI tools vs those who don't
of developers now use AI assistants in their daily workflow
See why leading engineering teams are switching to AI-age assessments.
HackerRank, LeetCode, etc.
AI-Age Assessment
Evaluate candidates on the skills that predict success in modern engineering teams.
How effectively do they prompt AI? Can they verify and improve AI outputs? Do they know when NOT to use AI?
Systematic debugging approaches, error interpretation, and ability to trace issues through complex systems.
Logging, monitoring, tracing—can they instrument code for production environments?
Coordinating multiple AI agents, tools, and services to solve complex problems efficiently.
Breaking down complex problems into manageable, AI-assistable chunks.
Strategic thinking, system design, and breaking complex projects into executable plans.
Choose from our library or create custom challenges that mirror your team's real work.
Candidates work with AI assistants. We record everything: prompts, iterations, debugging.
Our system analyzes the session across 12 dimensions of modern engineering competency.
Get comprehensive reports with session playback and comparative analytics.
Candidates code with Claude, Cursor, or their preferred AI assistant—just like on the job.
Studies show developers using AI assistants complete tasks 55% faster. Here's why traditional interviews fail to identify this new breed of engineer.
Google's randomized trial found AI-assisted developers completed tasks 21% faster. Microsoft's study across 5,000 developers showed a 26% productivity increase—effectively turning 8 hours into 10 hours of output.
LeetCode-style interviews ban AI tools—the exact tools your new hire will use daily. You're evaluating memorization skills while ignoring the collaboration abilities that actually drive productivity.
90% of developers report feeling more fulfilled when using AI tools. But 46% don't trust AI outputs blindly. The best engineers know when to accept, when to reject, and how to validate—skills no algorithm quiz measures.
"Finally, an interview platform that tests what engineers actually do. Our candidates were relieved they didn't have to study LeetCode for weeks."
"The debugging and observability metrics gave us insights we never had before. We found great engineers we would have missed with traditional interviews."
"Our new hires ramp up faster because the interview actually mirrors the job. They already know how to work with AI tools from day one."
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